{"id":13070,"date":"2026-05-11T19:47:20","date_gmt":"2026-05-11T17:47:20","guid":{"rendered":"https:\/\/geopard.tech\/?page_id=13070"},"modified":"2026-06-15T16:57:07","modified_gmt":"2026-06-15T14:57:07","slug":"%d3%a9%d1%80%d1%96%d1%81-%d0%b4%d0%b5%d1%80%d0%b5%d0%ba%d1%82%d0%b5%d1%80%d1%96%d0%bd-%d0%b7%d0%b5%d1%80%d1%82%d1%82%d0%b5%d1%83%d1%88%d1%96","status":"publish","type":"page","link":"https:\/\/geopard.tech\/kz\/field-data-explorer\/","title":{"rendered":"\u0422\u0435\u0433\u0456\u043d \u04e9\u0440\u0456\u0441 \u0434\u0435\u0440\u0435\u043a\u0442\u0435\u0440\u0456\u043d \u0437\u0435\u0440\u0442\u0442\u0435\u0443\u0448\u0456"},"content":{"rendered":"\n<div class=\"gp-lead\">\n<style>\n\/* Hide the WP page title heading on tool pages \u2014 the hero below carries the page name *\/\n#simple_page > .container > h1,\n.entry-header, .entry-title, .wp-block-post-title, h1.page-title,\n.post-header, .single-page .page-title { display: none !important; 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.gpx-btn{display:inline-block;background:#f76a0c;color:#fff;font-family:var(--wp--preset--font-family--poppins,\"Poppins\",sans-serif);font-weight:600;font-size:1rem;padding:14px 30px;border-radius:999px;text-decoration:none;transition:transform .15s,box-shadow .15s,background .15s;box-shadow:0 6px 18px rgba(247,106,12,0.4)}\n.gp-lead .gpx-btn:hover{transform:translateY(-1px);background:#ff7d24;color:#fff;box-shadow:0 8px 24px rgba(247,106,12,0.5)}\n.gp-lead .gpx-faq{margin:36px 0 8px}\n.gp-lead .gpx-faq h2{text-align:center;margin:0 0 20px;font-size:1.6rem}\n.gp-lead .gpx-tabs{border:1px solid #e8ebe2;border-radius:16px;overflow:hidden;background:#fff;box-shadow:0 2px 14px rgba(20,83,40,0.06)}\n.gp-lead .gpx-tablist{display:flex;gap:0;background:#f6f7f1;border-bottom:1px solid #e8ebe2;overflow-x:auto;scrollbar-width:none}\n.gp-lead .gpx-tablist::-webkit-scrollbar{display:none}\n.gp-lead .gpx-tab{flex:1 1 auto;min-width:max-content;background:transparent;border:0;padding:16px 22px;font-family:var(--wp--preset--font-family--poppins,\"Poppins\",sans-serif);font-size:.95rem;font-weight:600;color:#4c6066;cursor:pointer;border-bottom:3px solid transparent;transition:color .15s,border-color .15s,background .15s;white-space:nowrap;letter-spacing:.01em}\n.gp-lead .gpx-tab:hover{color:#145328;background:rgba(123,220,181,0.14)}\n.gp-lead .gpx-tab[aria-selected=\"true\"]{color:#145328;border-bottom-color:#15701e;background:#fff}\n.gp-lead .gpx-tab:focus{outline:2px solid #15701e;outline-offset:-2px}\n.gp-lead .gpx-panel{padding:28px 32px;display:none;animation:gpxfade .25s ease}\n.gp-lead .gpx-panel.is-active{display:block}\n@keyframes gpxfade{from{opacity:0;transform:translateY(6px)}to{opacity:1;transform:none}}\n.gp-lead .gpx-panel p{margin:0;line-height:1.7;color:#243024;font-size:1rem}\n.gp-lead .gpx-panel p+p{margin-top:10px}\n.gp-lead .gpx-panel kbd,.gp-lead .gpx-panel code{background:#f0f3ec;padding:2px 6px;border-radius:4px;font-family:var(--wp--preset--font-family--dm-mono,\"DM Mono\",ui-monospace,monospace);font-size:.88em;color:#145328}\n.gp-lead .gpx-integ{display:flex;flex-wrap:wrap;gap:8px;justify-content:center;margin:10px 0 20px}\n.gp-lead .gpx-integ-label{font-size:.86rem;color:rgba(255,255,255,0.86);margin:0 0 8px;font-weight:500;letter-spacing:.01em}\n.gp-lead .gpx-integ-chip{background:rgba(255,255,255,0.16);border:1px solid rgba(255,255,255,0.32);color:#fff;padding:6px 14px;border-radius:999px;font-size:.85rem;font-weight:600;letter-spacing:.02em}\n@media (max-width:760px){\n  .gp-lead h2{font-size:1.3rem}\n  .gp-lead .gpx-hero{padding:22px 20px;margin:4px 0 16px;border-radius:16px}\n  .gp-lead .gpx-hero-eyebrow{font-size:.68rem;letter-spacing:.12em;padding:5px 10px;margin-bottom:12px}\n  .gp-lead .gpx-hero-title{font-size:1.4rem;line-height:1.2;margin-bottom:8px}\n  .gp-lead .gpx-hero .lede{font-size:.95rem;line-height:1.5}\n  .gp-lead .gpx-hero-features{gap:6px;margin-top:14px}\n  .gp-lead .gpx-hero-feat{font-size:.78rem;padding:6px 10px}\n  .gp-lead .gpx-cta{padding:24px 22px}\n  .gp-lead .gpx-panel{padding:22px 20px}\n  .gp-lead .gpx-tab{padding:14px 16px;font-size:.9rem}\n}\n<\/style>\n<section class=\"gpx-hero\">\n  <div class=\"gpx-hero-eyebrow\">Field Data Explorer \u00b7 No signup<\/div>\n  <h1 class=\"gpx-hero-title\">Inspect any precision-ag file in seconds. See the <span class=\"accent\">variability<\/span> hiding inside.<\/h1>\n  <p class=\"lede\">Drop your yield, as-applied, soil samples, or boundaries from John Deere, Trimble, or ISO-XML. Auto-splits Coverage, replays the operation, surfaces zone-level variability worth acting on.<\/p>\n  <div class=\"gpx-hero-features\">\n    <span class=\"gpx-hero-feat\">Yield, as-applied, soil, boundaries<\/span>\n    <span class=\"gpx-hero-feat\">Operation replay<\/span>\n    <span class=\"gpx-hero-feat\">Variability heatmap<\/span>\n    <span class=\"gpx-hero-feat is-trust\">Data stays in your browser<\/span>\n  <\/div>\n<\/section>\n<\/div>\n\n\n\n\n\n<div class=\"gpy-wrap\" id=\"gpy-root\" data-theme=\"light\">\n<style>\n.gpy-wrap{all:initial;display:block;font-family:-apple-system,BlinkMacSystemFont,\"Segoe UI\",\"Helvetica Neue\",Arial,sans-serif;font-size:13px;line-height:1.45;border-radius:12px;overflow:hidden;max-width:100%}\n.gpy-wrap *,.gpy-wrap *::before,.gpy-wrap *::after{box-sizing:border-box}\n\n.gpy-wrap[data-theme=\"light\"]{\n  --bg:#fdfcf8;--panel:#ffffff;--panel2:#f7f5ef;--line:#e8e4d8;--line2:#d9d3c3;\n  --ink:#1a1a1a;--ink-dim:#6b6b6b;--ink-soft:#8a8a8a;\n  --accent:#2d6a4f;--accent-h:#346e55;--accent-soft:#86c9a8;\n  --violet:#a21caf;--violet-glow:rgba(162,28,175,.38);--grey:#6b7280;\n  --canvas-bg:#f5f2e8;--canvas-grid:rgba(0,0,0,.10);\n  --cta-bg:linear-gradient(145deg,#eefbf3 0%,#dff5e6 100%);\n  --cta-border:#b8e5c6;--cta-title:#0f5033;--cta-text:#1e5d3a;\n  --shadow:0 4px 20px rgba(30,40,50,.08);--shadow-sm:0 1px 3px rgba(30,40,50,.06);\n  color:var(--ink);background:var(--bg);border:1px solid var(--line);box-shadow:var(--shadow);\n}\n.gpy-wrap[data-theme=\"dark\"]{\n  --bg:#0b0f14;--panel:#11171f;--panel2:#161e2a;--line:#1f2a3a;--line2:#2a3548;\n  --ink:#e7edf5;--ink-dim:#93a0b3;--ink-soft:#6a7486;\n  --accent:#4ade80;--accent-h:#52e089;--accent-soft:#86efac;\n  --violet:#d946ef;--violet-glow:rgba(192,38,211,.65);--grey:#8b92a0;\n  --canvas-bg:#0b0f14;--canvas-grid:rgba(255,255,255,.08);\n  --cta-bg:linear-gradient(145deg,#0f2a1f 0%,#112e25 100%);\n  --cta-border:#1e5e3d;--cta-title:#86efac;--cta-text:#d1fae5;\n  --shadow:0 10px 40px rgba(0,0,0,.4);--shadow-sm:0 2px 6px rgba(0,0,0,.25);\n  color:var(--ink);background:var(--bg);border:1px solid var(--line);box-shadow:var(--shadow);\n}\n\n.gpy-wrap .gpy-top{display:flex;align-items:center;justify-content:space-between;padding:14px 18px;border-bottom:1px solid var(--line);background:var(--panel);gap:16px;flex-wrap:wrap}\n.gpy-wrap .gpy-brand{display:flex;align-items:center;gap:12px;min-width:0;flex:1}\n.gpy-wrap .gpy-logo{width:28px;height:28px;border-radius:7px;background:linear-gradient(135deg,#2d6a4f 0%,#4ade80 100%);display:flex;align-items:center;justify-content:center;color:#fff;font-weight:700;font-size:14px;flex:none;box-shadow:var(--shadow-sm)}\n.gpy-wrap .gpy-titles{min-width:0}\n.gpy-wrap .gpy-h1{font-size:15px;font-weight:600;color:var(--ink);letter-spacing:-.01em}\n.gpy-wrap .gpy-chip{display:inline-flex;align-items:center;gap:6px;font-family:\"SF Mono\",ui-monospace,Menlo,monospace;font-size:11px;padding:2px 8px;border-radius:10px;background:var(--panel2);color:var(--ink-dim);border:1px solid var(--line);max-width:340px;overflow:hidden;text-overflow:ellipsis;white-space:nowrap;margin-top:3px}\n.gpy-wrap .gpy-chip .gpy-dot{width:6px;height:6px;border-radius:50%;background:var(--accent);flex:none}\n.gpy-wrap .gpy-chip.is-sample .gpy-dot{background:#f59e0b}\n.gpy-wrap .gpy-actions{display:flex;align-items:center;gap:8px;flex:1 1 0;justify-content:flex-end}\n\/* Header three-zone layout: brand (left, flex:1) \u00b7 upload CTA (centered) \u00b7\n   controls (right, flex:1). 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map fills the width naturally, just needs\n     proportional height so it doesn't read as a tiny strip below the controls. *\/\n  .gpy-wrap .gpy-grid{min-height:min(78vh,820px)}\n  .gpy-wrap .gpy-main{min-height:min(78vh,820px)}\n  .gpy-wrap .gpy-side{padding:0;max-height:min(78vh,820px)}\n  .gpy-wrap .gpy-side-scroll{padding:12px;gap:10px}\n}\n.gpy-wrap .gpy-main{position:relative;overflow:hidden;min-height:640px;background:var(--canvas-bg)}\n\n.gpy-wrap .gpy-card{background:var(--panel2);border:1px solid var(--line);border-radius:8px;padding:7px 9px}\n.gpy-wrap .gpy-card h3{font-size:9.5px;text-transform:uppercase;letter-spacing:.1em;color:var(--ink-dim);margin:0 0 4px 0;font-weight:600;font-family:\"SF Mono\",ui-monospace,Menlo,monospace}\n.gpy-wrap .gpy-stats{display:grid;grid-template-columns:1fr 1fr;gap:8px 12px}\n.gpy-wrap .gpy-stat .k{font-size:9.5px;color:var(--ink-dim);text-transform:uppercase;letter-spacing:.05em;font-family:\"SF Mono\",ui-monospace,Menlo,monospace}\n.gpy-wrap .gpy-stat .v{font-size:14px;font-weight:600;font-variant-numeric:tabular-nums;font-family:\"SF Mono\",ui-monospace,Menlo,monospace;margin-top:1px;color:var(--ink)}\n.gpy-wrap .gpy-stat .v.small{font-size:12px}\n.gpy-wrap .gpy-stat.is-total .v{font-size:18px;color:var(--accent)}\n.gpy-wrap .gpy-stat .u{font-size:10px;color:var(--ink-dim);font-weight:500;margin-left:3px}\n.gpy-wrap .gpy-stats-sub{margin-top:8px;font-size:10.5px;color:var(--ink-dim);font-family:\"SF Mono\",ui-monospace,Menlo,monospace;line-height:1.5}\n.gpy-wrap select.gpy-sel{width:100%;background:var(--bg);color:var(--ink);border:1px solid var(--line);border-radius:7px;padding:8px 10px;font-family:\"SF Mono\",ui-monospace,Menlo,monospace;font-size:12px;cursor:pointer;outline:none;transition:border-color .15s}\n.gpy-wrap select.gpy-sel:focus{border-color:var(--accent-soft);box-shadow:0 0 0 3px rgba(74,222,128,.15)}\n.gpy-wrap .gpy-seg{display:flex;gap:3px;background:var(--bg);padding:3px;border-radius:7px;border:1px solid var(--line)}\n.gpy-wrap .gpy-seg button{flex:1;background:transparent;border:0;color:var(--ink-dim);padding:7px 4px;font-family:\"SF Mono\",ui-monospace,Menlo,monospace;font-size:11px;border-radius:5px;cursor:pointer;transition:all .15s;font-weight:600}\n.gpy-wrap .gpy-seg button.on{background:var(--panel);color:var(--ink);box-shadow:var(--shadow-sm)}\n\/* In-seg cross-link CTA \u2014 used to point users to a dedicated tool when a\n   data-type is better explored there (e.g. AB lines \u2192 \/guidance-lines\/). *\/\n.gpy-wrap .gpy-seg .gpy-seg-link{position:relative;flex:1;display:inline-flex;align-items:center;justify-content:center;gap:4px;background:transparent;color:var(--accent);padding:7px 4px;font-family:\"SF Mono\",ui-monospace,Menlo,monospace;font-size:11px;border-radius:5px;text-decoration:none;font-weight:600;transition:all .15s;border:1px dashed transparent}\n.gpy-wrap .gpy-seg .gpy-seg-link:hover{background:var(--panel);border-color:var(--accent-soft);color:var(--accent-h)}\n.gpy-wrap .gpy-seg .gpy-seg-link-arr{font-size:10px;opacity:.75}\n\/* Hover tooltip \u2014 small dark callout above the link explaining where the\n   cross-link goes. Pure CSS (no JS) \u2014 appears on :hover and :focus. *\/\n.gpy-wrap .gpy-seg .gpy-seg-link-tip{position:absolute;left:50%;top:calc(100% + 8px);transform:translateX(-50%) translateY(-4px);width:240px;background:#0e3a1c;color:#fafbf4;padding:9px 11px;border-radius:7px;font-family:-apple-system,BlinkMacSystemFont,\"Segoe UI\",sans-serif;font-size:11.5px;font-weight:400;line-height:1.4;letter-spacing:0;text-align:left;box-shadow:0 6px 18px rgba(20,83,40,0.28);opacity:0;pointer-events:none;transition:opacity .15s ease,transform .15s ease;z-index:20;white-space:normal}\n.gpy-wrap .gpy-seg .gpy-seg-link-tip strong{color:#86efac;font-weight:700}\n.gpy-wrap .gpy-seg .gpy-seg-link-tip::after{content:\"\";position:absolute;bottom:100%;left:50%;transform:translateX(-50%);border:5px solid transparent;border-bottom-color:#0e3a1c}\n.gpy-wrap .gpy-seg .gpy-seg-link:hover .gpy-seg-link-tip,\n.gpy-wrap .gpy-seg .gpy-seg-link:focus .gpy-seg-link-tip,\n.gpy-wrap .gpy-seg .gpy-seg-link:focus-visible .gpy-seg-link-tip{opacity:1;transform:translateX(-50%) translateY(0)}\n@media (max-width:820px){\n  \/* Mobile: tooltip is always below the link (matches desktop). Just widen for touch. *\/\n  .gpy-wrap .gpy-seg .gpy-seg-link-tip{width:min(240px,calc(100vw - 60px));font-size:12.5px}\n}\n.gpy-wrap .gpy-row{display:flex;justify-content:space-between;align-items:baseline;margin-top:9px;font-family:\"SF Mono\",ui-monospace,Menlo,monospace;font-size:11px}\n.gpy-wrap .gpy-row .l{color:var(--ink-dim);text-transform:uppercase;font-size:10px;letter-spacing:.05em}\n.gpy-wrap .gpy-row .v{font-weight:600;color:var(--ink)}\n.gpy-wrap .gpy-row .unit{color:var(--ink-dim);font-size:9px;margin-left:3px;font-weight:400}\n.gpy-wrap .gpy-mini{display:inline-block;font-family:\"SF Mono\",ui-monospace,Menlo,monospace;font-size:10px;padding:3px 7px;border-radius:4px;font-weight:600}\n.gpy-wrap[data-theme=\"light\"] .gpy-mini.mg{background:#e8eaed;color:#4b5563}\n.gpy-wrap[data-theme=\"light\"] .gpy-mini.mv{background:#fdf2fb;color:#86198f}\n.gpy-wrap[data-theme=\"dark\"] .gpy-mini.mg{background:rgba(107,114,128,.25);color:#b4bac6}\n.gpy-wrap[data-theme=\"dark\"] .gpy-mini.mv{background:rgba(192,38,211,.2);color:#e9a8f4}\n.gpy-wrap input[type=range]{width:100%;margin-top:8px;accent-color:var(--accent);height:6px}\n.gpy-wrap .gpy-toggle{display:flex;align-items:center;justify-content:space-between;cursor:pointer;user-select:none;font-size:12px;color:var(--ink);font-weight:500}\n.gpy-wrap .gpy-note{font-size:10.5px;line-height:1.45;color:var(--ink-dim);margin-top:6px;padding:7px 9px;background:var(--bg);border:1px solid var(--line);border-radius:6px}\n.gpy-wrap .gpy-note strong{color:var(--ink);font-weight:600}\n.gpy-wrap .gpy-wcfg{margin-bottom:8px}\n.gpy-wrap .gpy-wcfg label{display:block;font-size:10px;text-transform:uppercase;letter-spacing:.06em;color:var(--ink-dim);font-weight:600;font-family:\"SF Mono\",ui-monospace,Menlo,monospace;margin-bottom:4px}\n.gpy-wrap .gpy-wcfg-row{display:flex;align-items:center;gap:5px}\n.gpy-wrap .gpy-wcfg-row input[type=number]{flex:1;min-width:0;background:var(--bg);color:var(--ink);border:1px solid var(--line);border-radius:6px;padding:6px 8px;font-family:\"SF Mono\",ui-monospace,Menlo,monospace;font-size:12px;outline:none}\n.gpy-wrap .gpy-wcfg-row input[type=number]:focus{border-color:var(--accent-soft);box-shadow:0 0 0 3px rgba(74,222,128,.15)}\n.gpy-wrap .gpy-wcfg-row .gpy-wcfg-u{font-size:10.5px;color:var(--ink-dim);font-family:\"SF Mono\",ui-monospace,Menlo,monospace}\n.gpy-wrap .gpy-wcfg-row button{background:var(--panel);color:var(--ink-dim);border:1px solid var(--line);width:26px;height:26px;border-radius:6px;cursor:pointer;font-size:13px;padding:0;line-height:1;font-family:inherit}\n.gpy-wrap .gpy-wcfg-row button:hover{background:var(--panel2);color:var(--ink);border-color:var(--line2)}\n.gpy-wrap .gpy-wcfg-hint{font-size:9.5px;color:var(--ink-soft);font-family:\"SF Mono\",ui-monospace,Menlo,monospace;margin-top:4px}\n.gpy-wrap .gpy-toggle input{appearance:none;width:34px;height:19px;background:var(--line2);border-radius:10px;position:relative;cursor:pointer;transition:.15s;margin:0;flex:none}\n.gpy-wrap .gpy-toggle input::after{content:\"\";position:absolute;top:2px;left:2px;width:15px;height:15px;background:#fff;border-radius:50%;transition:.15s;box-shadow:var(--shadow-sm)}\n.gpy-wrap .gpy-toggle input:checked{background:var(--accent)}\n.gpy-wrap .gpy-toggle input:checked::after{left:17px}\n\n.gpy-wrap .gpy-legend-bar{position:relative;height:12px;border-radius:6px;margin:8px 0 6px;background:linear-gradient(90deg,#c1121f 0%,#e85d04 25%,#f9c74f 50%,#90be6d 75%,#2d6a4f 100%);cursor:pointer}\n.gpy-wrap .gpy-legend-thumb{position:absolute;top:-3px;width:8px;height:18px;border-radius:3px;background:#fff;border:2px solid var(--accent);box-shadow:0 1px 3px rgba(0,0,0,0.25);cursor:ew-resize;transform:translateX(-50%);transition:transform .12s,box-shadow .12s;touch-action:none}\n.gpy-wrap .gpy-legend-thumb:hover,.gpy-wrap .gpy-legend-thumb.is-drag{transform:translateX(-50%) scale(1.15);box-shadow:0 2px 6px rgba(0,0,0,0.35)}\n.gpy-wrap .gpy-legend-thumb.is-min{left:0%}\n.gpy-wrap .gpy-legend-thumb.is-max{left:100%}\n.gpy-wrap .gpy-legend-tickrow{display:flex;align-items:center;gap:6px;margin-top:4px;font-family:\"SF Mono\",ui-monospace,Menlo,monospace;font-size:10px;color:var(--ink-dim);font-weight:600}\n.gpy-wrap .gpy-legend-tickrow .gpy-l-lbl{font-size:9px;text-transform:uppercase;letter-spacing:.08em;color:var(--ink-dim);font-weight:700;width:54px;flex:0 0 54px}\n.gpy-wrap .gpy-legend-tickrow .gpy-l-sw{width:10px;height:10px;border-radius:3px;flex:0 0 10px;box-shadow:0 0 0 1px rgba(0,0,0,0.12)}\n.gpy-wrap .gpy-legend-tickrow .gpy-l-num{flex:1;display:flex;align-items:center;gap:3px;background:var(--bg);border:1px solid var(--line);border-radius:5px;padding:3px 6px;transition:border-color .12s,box-shadow .12s;min-width:0}\n.gpy-wrap .gpy-legend-tickrow .gpy-l-num:hover{border-color:var(--accent-soft)}\n.gpy-wrap .gpy-legend-tickrow .gpy-l-num.is-focus{border-color:var(--accent);box-shadow:0 0 0 2px rgba(74,222,128,0.15)}\n.gpy-wrap .gpy-legend-tickrow .gpy-l-num.is-override{border-color:var(--accent)}\n.gpy-wrap .gpy-legend-tickrow .gpy-l-num input{flex:1;min-width:0;width:100%;font-family:inherit;font-size:11px;background:transparent;color:var(--ink);border:0;padding:0;outline:none;-moz-appearance:textfield;font-variant-numeric:tabular-nums;text-align:left}\n.gpy-wrap .gpy-legend-tickrow .gpy-l-num input::-webkit-outer-spin-button,.gpy-wrap .gpy-legend-tickrow .gpy-l-num input::-webkit-inner-spin-button{-webkit-appearance:none;margin:0}\n.gpy-wrap .gpy-legend-tickrow .gpy-l-num.is-override input{color:var(--accent);font-weight:700}\n.gpy-wrap .gpy-legend-tickrow .gpy-l-unit{font-size:9px;color:var(--ink-dim);flex:0 0 auto;letter-spacing:.02em}\n.gpy-wrap .gpy-legend-tickrow .gpy-l-step{display:flex;flex-direction:column;gap:1px;flex:0 0 auto}\n.gpy-wrap .gpy-legend-tickrow .gpy-l-step button{font-family:inherit;background:transparent;border:0;color:var(--ink-dim);font-size:9px;line-height:1;width:14px;height:9px;padding:0;cursor:pointer;border-radius:2px}\n.gpy-wrap .gpy-legend-tickrow .gpy-l-step button:hover{background:var(--panel2);color:var(--accent)}\n.gpy-wrap .gpy-legend-mid{font-size:9px;text-align:center;color:var(--ink-dim);font-family:\"SF Mono\",ui-monospace,Menlo,monospace;margin:4px 0 0;letter-spacing:.02em}\n.gpy-wrap .gpy-legend-reset{display:none;font-size:9px;color:var(--ink-dim);cursor:pointer;margin-top:6px;background:none;border:0;padding:2px 0;font-family:\"SF Mono\",ui-monospace,Menlo,monospace;text-align:center;text-transform:uppercase;letter-spacing:.08em;font-weight:600;width:100%}\n.gpy-wrap .gpy-legend-reset:hover{color:var(--accent)}\n.gpy-wrap .gpy-legend-reset.show{display:block}\n.gpy-wrap .gpy-leg-row{display:flex;align-items:center;gap:8px;margin-top:9px;font-size:11px;color:var(--ink)}\n.gpy-wrap .gpy-sw{width:13px;height:13px;border-radius:3px;flex:none}\n.gpy-wrap .gpy-tree{display:flex;flex-direction:column;max-height:240px;overflow-y:auto;font-size:11px;border:1px solid var(--line);border-radius:6px;background:var(--bg);scrollbar-width:thin}\n.gpy-wrap .gpy-tree-empty{color:var(--ink-dim);padding:14px 12px;text-align:center;font-style:italic;font-size:11px}\n.gpy-wrap .gpy-tree-node{display:flex;align-items:center;gap:6px;padding:7px 10px 7px 8px;cursor:pointer;border:0;border-bottom:1px solid var(--line);color:var(--ink);user-select:none;transition:background .12s;min-height:30px;background:transparent;width:100%;text-align:left;font-family:inherit;font-size:inherit;outline:none}\n.gpy-wrap .gpy-tree-node:focus-visible{box-shadow:inset 0 0 0 2px var(--accent)}\n.gpy-wrap .gpy-tree-node:last-child{border-bottom:0}\n.gpy-wrap .gpy-tree-node:hover{background:var(--panel2)}\n.gpy-wrap .gpy-tree-node.is-active{background:var(--cta-bg);font-weight:600}\n.gpy-wrap .gpy-tree-node.is-boundary{background:rgba(74,222,128,0.05)}\n.gpy-wrap .gpy-tree-node.is-boundary .gpy-tree-name{color:var(--accent);font-weight:600}\n.gpy-wrap .gpy-tree-node.is-boundary.is-active{background:rgba(74,222,128,0.18)}\n.gpy-wrap .gpy-tree-glyph{flex:none;width:12px;text-align:center;color:var(--ink-dim);font-size:11px}\n.gpy-wrap .gpy-tree-node.is-active .gpy-tree-glyph,.gpy-wrap .gpy-tree-node.is-boundary .gpy-tree-glyph{color:var(--accent)}\n.gpy-wrap .gpy-tree-name{flex:1;min-width:0;overflow:hidden;text-overflow:ellipsis;white-space:nowrap;font-family:inherit}\n.gpy-wrap .gpy-tree-meta{flex:none;color:var(--ink-dim);font-family:\"SF Mono\",ui-monospace,Menlo,monospace;font-size:9px;text-transform:uppercase;letter-spacing:.05em;white-space:nowrap}\n.gpy-wrap .gpy-leg-stats{border-top:1px solid var(--line);margin-top:9px;padding-top:8px}\n.gpy-wrap .gpy-leg-stat{display:flex;justify-content:space-between;align-items:baseline;gap:10px;font-size:11px;margin-top:5px}\n.gpy-wrap .gpy-leg-stat .lbl{color:var(--ink-dim);text-transform:uppercase;letter-spacing:.06em;font-size:9px;font-family:\"SF Mono\",ui-monospace,Menlo,monospace;font-weight:600}\n.gpy-wrap .gpy-leg-stat .val{color:var(--ink);font-family:\"SF Mono\",ui-monospace,Menlo,monospace;font-weight:700;text-align:right;white-space:nowrap}\n.gpy-wrap[data-theme=\"light\"] .gpy-sw.grey{background:#6b7280}\n.gpy-wrap[data-theme=\"light\"] .gpy-sw.violet{background:#a21caf;box-shadow:0 0 8px rgba(162,28,175,.35)}\n.gpy-wrap[data-theme=\"dark\"] .gpy-sw.grey{background:#8b92a0}\n.gpy-wrap[data-theme=\"dark\"] .gpy-sw.violet{background:#d946ef;box-shadow:0 0 8px rgba(192,38,211,.5)}\n\n\/* Auto zones card \u2014 quantile-based zone highlighting + variability + ROI hint *\/\n.gpy-wrap .gpy-zones-card{display:flex;flex-direction:column;gap:5px}\n.gpy-wrap .gpy-zones-body{display:flex;flex-direction:column;gap:5px}\n.gpy-wrap .gpy-zones-seg-row{display:flex;align-items:center;justify-content:space-between;gap:8px}\n.gpy-wrap .gpy-zones-seg-l{font-size:10px;text-transform:uppercase;letter-spacing:.08em;color:var(--ink-dim);font-weight:700;font-family:\"SF Mono\",ui-monospace,Menlo,monospace}\n.gpy-wrap .gpy-zones-seg-row .gpy-seg{flex:1;max-width:200px}\n.gpy-wrap .gpy-zones-cv{display:flex;justify-content:space-between;align-items:center;gap:8px;padding:5px 9px;background:var(--bg);border:1px solid var(--line);border-radius:6px}\n.gpy-wrap .gpy-zones-cv-l{font-size:10px;text-transform:uppercase;letter-spacing:.08em;color:var(--ink-dim);font-family:\"SF Mono\",ui-monospace,Menlo,monospace}\n.gpy-wrap .gpy-zones-cv-v{font-size:13px;font-weight:700;color:var(--ink);display:flex;align-items:center;gap:6px;font-variant-numeric:tabular-nums}\n.gpy-wrap .gpy-zones-cv-tier{font-size:9.5px;font-weight:600;text-transform:uppercase;letter-spacing:.06em;padding:2px 7px;border-radius:99px;font-family:\"SF Mono\",ui-monospace,Menlo,monospace}\n.gpy-wrap .gpy-zones-cv-tier.is-low{background:rgba(144,190,109,0.22);color:#2d6a4f}\n.gpy-wrap .gpy-zones-cv-tier.is-med{background:rgba(249,199,79,0.28);color:#7a5b00}\n.gpy-wrap .gpy-zones-cv-tier.is-high{background:rgba(232,93,4,0.22);color:#c1121f}\n.gpy-wrap[data-theme=\"dark\"] .gpy-zones-cv-tier.is-med{color:#f9c74f}\n.gpy-wrap .gpy-zones-bar{display:flex;height:8px;border-radius:3px;overflow:hidden;border:1px solid var(--line);background:var(--bg)}\n.gpy-wrap .gpy-zones-bar > span{display:block;height:100%;transition:flex-basis .15s}\n.gpy-wrap .gpy-zones-list{display:flex;flex-direction:column;gap:4px}\n.gpy-wrap .gpy-zones-list .gpy-zones-row{display:grid;grid-template-columns:14px 1fr auto 62px;align-items:center;gap:8px;font-size:11px;color:var(--ink);font-family:\"SF Mono\",ui-monospace,Menlo,monospace;font-variant-numeric:tabular-nums}\n.gpy-wrap .gpy-zones-list .gpy-zones-sw{width:10px;height:10px;border-radius:2px}\n.gpy-wrap .gpy-zones-list .gpy-zones-rng{color:var(--ink-dim);overflow:hidden;white-space:nowrap;text-overflow:ellipsis;min-width:0}\n.gpy-wrap .gpy-zones-list .gpy-zones-area{color:var(--ink);font-weight:700;font-size:11px;text-align:right}\n.gpy-wrap .gpy-zones-list .gpy-zones-cnt{color:var(--ink-dim);font-size:10px}\n.gpy-wrap .gpy-zones-list .gpy-zones-row input{width:100%;padding:3px 6px;background:var(--panel);border:1px solid var(--line);color:var(--ink);border-radius:4px;font-family:inherit;font-size:11px;font-weight:600;text-align:right;outline:none;-moz-appearance:textfield}\n.gpy-wrap .gpy-zones-list .gpy-zones-row input::-webkit-outer-spin-button,\n.gpy-wrap .gpy-zones-list .gpy-zones-row input::-webkit-inner-spin-button{-webkit-appearance:none;margin:0}\n.gpy-wrap .gpy-zones-list .gpy-zones-row input:focus{border-color:var(--accent);box-shadow:0 0 0 2px rgba(74,222,128,.18)}\n\/* Per-zone rate input + total product calculator. Lets the user mock a\n   variable-rate prescription right in the panel \u2014 set rate per zone,\n   total product = \u03a3 rate \u00d7 area, plus a uniform-rate comparison. *\/\n.gpy-wrap .gpy-zones-rates{display:flex;flex-direction:column;gap:4px;padding:6px 8px;background:var(--bg);border:1px solid var(--line);border-radius:6px}\n.gpy-wrap .gpy-zones-rates-hd{display:flex;align-items:center;justify-content:space-between;gap:6px}\n.gpy-wrap .gpy-zones-rates-l{font-size:9.5px;text-transform:uppercase;letter-spacing:.08em;color:var(--ink-dim);font-weight:700;font-family:\"SF Mono\",ui-monospace,Menlo,monospace}\n.gpy-wrap .gpy-zones-unit-input{background:transparent;color:var(--ink);border:0;border-bottom:1px dashed var(--line2);padding:1px 0;font-family:\"SF Mono\",ui-monospace,Menlo,monospace;font-size:11px;font-weight:600;text-align:right;width:80px;outline:none}\n.gpy-wrap .gpy-zones-unit-input:focus{border-bottom-color:var(--accent);color:var(--accent)}\n.gpy-wrap .gpy-zones-unit-select{background:var(--panel);color:var(--ink);border:1px solid var(--line);border-radius:5px;padding:2px 6px;font-family:\"SF Mono\",ui-monospace,Menlo,monospace;font-size:11px;font-weight:600;outline:none;cursor:pointer;max-width:140px}\n.gpy-wrap .gpy-zones-unit-select:focus{border-color:var(--accent);box-shadow:0 0 0 2px rgba(74,222,128,.15)}\n.gpy-wrap .gpy-zones-unit-select:hover{border-color:var(--accent-soft)}\n.gpy-wrap .gpy-zones-rates-rows{display:flex;flex-direction:column;gap:3px}\n.gpy-wrap .gpy-zones-rates-row{display:grid;grid-template-columns:14px 1fr auto;align-items:center;gap:6px;font-size:11px;color:var(--ink);font-family:\"SF Mono\",ui-monospace,Menlo,monospace;font-variant-numeric:tabular-nums}\n.gpy-wrap .gpy-zones-rates-row .gpy-zones-sw{width:10px;height:10px;border-radius:2px}\n.gpy-wrap .gpy-zones-rates-row .gpy-zones-rate-lbl{color:var(--ink-dim)}\n.gpy-wrap .gpy-zones-rates-row input{width:62px;padding:3px 6px;background:var(--panel);border:1px solid var(--line);color:var(--ink);border-radius:4px;font-family:inherit;font-size:11px;font-weight:600;text-align:right;outline:none;-moz-appearance:textfield}\n.gpy-wrap .gpy-zones-rates-row input::-webkit-outer-spin-button,\n.gpy-wrap .gpy-zones-rates-row input::-webkit-inner-spin-button{-webkit-appearance:none;margin:0}\n.gpy-wrap .gpy-zones-rates-row input:focus{border-color:var(--accent);box-shadow:0 0 0 2px rgba(74,222,128,.18)}\n.gpy-wrap .gpy-zones-hist{position:relative;background:var(--panel);border:1px solid var(--line);border-radius:5px;padding:6px 7px 18px;margin:0 0 4px}\n.gpy-wrap .gpy-zones-hist-canvas{display:block;width:100%;height:48px;border-radius:3px}\n.gpy-wrap .gpy-zones-hist-track{position:absolute;left:7px;right:7px;bottom:14px;height:2px;background:var(--line);border-radius:1px;pointer-events:none}\n.gpy-wrap .gpy-zones-hist-thumb{position:absolute;top:6px;bottom:14px;width:10px;margin-left:-5px;background:transparent;cursor:ew-resize;touch-action:none;z-index:2}\n.gpy-wrap .gpy-zones-hist-thumb::before{content:\"\";position:absolute;left:50%;top:0;bottom:0;width:2px;margin-left:-1px;background:var(--ink);box-shadow:0 0 0 1px rgba(255,255,255,0.6);border-radius:1px}\n.gpy-wrap .gpy-zones-hist-thumb::after{content:\"\";position:absolute;left:50%;bottom:-1px;width:12px;height:12px;margin-left:-6px;background:#fff;border:2px solid var(--accent);border-radius:50%;box-shadow:0 1px 3px rgba(0,0,0,0.2)}\n.gpy-wrap .gpy-zones-hist-thumb:hover::after,.gpy-wrap .gpy-zones-hist-thumb.is-drag::after{background:var(--accent);border-color:var(--accent-h,#22c55e);transform:scale(1.15)}\n.gpy-wrap .gpy-zones-hist-scale{position:absolute;left:7px;right:7px;bottom:1px;height:12px;font-family:\"SF Mono\",ui-monospace,Menlo,monospace;font-size:9px;color:var(--ink-dim);pointer-events:none}\n.gpy-wrap .gpy-zones-hist-scale .lo{position:absolute;left:0;top:0}\n.gpy-wrap .gpy-zones-hist-scale .hi{position:absolute;right:0;top:0}\n.gpy-wrap .gpy-zones-hist-readout{position:absolute;top:-22px;background:var(--ink);color:#fff;font-family:\"SF Mono\",ui-monospace,Menlo,monospace;font-size:10px;font-weight:700;padding:2px 6px;border-radius:3px;white-space:nowrap;transform:translateX(-50%);pointer-events:none;opacity:0;transition:opacity .12s}\n.gpy-wrap .gpy-zones-hist-thumb.is-drag .gpy-zones-hist-readout,.gpy-wrap .gpy-zones-hist-thumb:hover .gpy-zones-hist-readout{opacity:1}\n\/* Compact variant on the map's legend overlay \u2014 mirrors the sidebar histogram\n   but at ~32 px tall, no scale labels, in-overlay padding. Shares zoneBreaks\n   so a drag here updates the sidebar one + the map together. *\/\n.gpy-wrap .gpy-legend-hist{position:relative;margin:6px 0 4px;padding:4px 0 8px;border-radius:4px}\n.gpy-wrap .gpy-legend-hist-canvas{display:block;width:100%;height:32px;border-radius:3px}\n.gpy-wrap .gpy-legend-hist-track{position:absolute;left:0;right:0;bottom:5px;height:2px;background:var(--line);border-radius:1px;pointer-events:none}\n.gpy-wrap .gpy-legend-hist .gpy-zones-hist-thumb{top:2px;bottom:5px}\n.gpy-wrap .gpy-legend-hist .gpy-zones-hist-thumb::after{width:10px;height:10px;margin-left:-5px;border-width:2px}\n\/* Zone-break thumb positioned DIRECTLY on the legend gradient bar. Visually\n   matches the existing 5 color-stop thumbs (.gpy-legend-thumb): white pill\n   with accent border. The bar is 12 px tall \u2014 the thumb extends \u00b13 px\n   above\/below to surface as a draggable handle. *\/\n.gpy-wrap .gpy-legend-bar-zthumb{position:absolute;top:-3px;bottom:auto;height:18px;width:10px;margin-left:-5px;background:transparent;cursor:ew-resize;z-index:3}\n.gpy-wrap .gpy-legend-bar-zthumb::before{content:\"\";position:absolute;left:50%;top:0;height:18px;width:8px;margin-left:-4px;background:#fff;border:2px solid var(--accent);border-radius:3px;box-shadow:0 1px 3px rgba(0,0,0,0.25);box-sizing:border-box;transition:transform .12s,box-shadow .12s}\n.gpy-wrap .gpy-legend-bar-zthumb::after{display:none}\n.gpy-wrap .gpy-legend-bar-zthumb:hover::before,.gpy-wrap .gpy-legend-bar-zthumb.is-drag::before{transform:scale(1.15);box-shadow:0 2px 6px rgba(0,0,0,0.35)}\n.gpy-wrap .gpy-zones-avg-row{display:flex;align-items:center;flex-wrap:wrap;gap:6px 8px;padding:5px 7px;margin:2px 0 4px;background:var(--panel);border:1px solid var(--line);border-radius:5px}\n.gpy-wrap .gpy-zones-avg-lbl{font-size:10.5px;text-transform:uppercase;letter-spacing:.06em;color:var(--ink-dim);font-weight:700;font-family:\"SF Mono\",ui-monospace,Menlo,monospace;flex:0 0 auto}\n.gpy-wrap .gpy-zones-avg-row input{width:84px;padding:3px 6px;background:var(--bg);border:1px solid var(--line);color:var(--ink);border-radius:4px;font-family:\"SF Mono\",ui-monospace,Menlo,monospace;font-size:12px;font-weight:700;text-align:right;outline:none;-moz-appearance:textfield;flex:0 0 auto;margin-left:auto}\n.gpy-wrap .gpy-zones-avg-row .gpy-zones-unit-select{flex:0 0 auto}\n.gpy-wrap .gpy-zones-avg-status{flex:1 1 100%;font-size:10.5px;color:var(--accent);font-family:\"SF Mono\",ui-monospace,Menlo,monospace;font-variant-numeric:tabular-nums;font-weight:700;line-height:1.3;text-align:right}\n.gpy-wrap .gpy-zones-avg-status:empty{display:none}\n.gpy-wrap .gpy-zones-avg-row input::-webkit-outer-spin-button,\n.gpy-wrap .gpy-zones-avg-row input::-webkit-inner-spin-button{-webkit-appearance:none;margin:0}\n.gpy-wrap .gpy-zones-avg-row input:focus{border-color:var(--accent);box-shadow:0 0 0 2px rgba(74,222,128,.18)}\n.gpy-wrap .gpy-zones-rates-total{display:flex;align-items:center;justify-content:space-between;gap:6px;border-top:1px solid var(--line);padding-top:5px;margin-top:2px}\n.gpy-wrap .gpy-zones-rates-total-l{font-size:10px;text-transform:uppercase;letter-spacing:.08em;color:var(--ink-dim);font-weight:700;font-family:\"SF Mono\",ui-monospace,Menlo,monospace}\n.gpy-wrap .gpy-zones-rates-total-v{font-size:13px;font-weight:800;color:var(--accent);font-variant-numeric:tabular-nums;font-family:\"SF Mono\",ui-monospace,Menlo,monospace}\n.gpy-wrap .gpy-zones-rates-cmp{font-size:10px;color:var(--ink-dim);font-family:\"SF Mono\",ui-monospace,Menlo,monospace;line-height:1.5}\n.gpy-wrap .gpy-zones-rates-cmp.is-save{color:#2d6a4f}\n.gpy-wrap .gpy-zones-rates-cmp.is-cost{color:#c1121f}\n.gpy-wrap[data-theme=\"dark\"] .gpy-zones-rates-cmp.is-save{color:#86efac}\n.gpy-wrap .gpy-zones-roi{padding:6px 9px;background:var(--cta-bg);border:1px solid var(--cta-border);border-radius:6px;display:flex;flex-direction:column;gap:2px}\n.gpy-wrap .gpy-zones-roi-l{font-size:9.5px;text-transform:uppercase;letter-spacing:.1em;color:var(--cta-title);font-weight:700;font-family:\"SF Mono\",ui-monospace,Menlo,monospace}\n.gpy-wrap .gpy-zones-roi-v{font-size:14px;font-weight:800;color:var(--ink);font-variant-numeric:tabular-nums;letter-spacing:-.01em}\n.gpy-wrap .gpy-zones-roi-ref{font-size:10.5px;color:var(--cta-text);font-family:\"SF Mono\",ui-monospace,Menlo,monospace;font-variant-numeric:tabular-nums;line-height:1.4;margin-top:2px}\n.gpy-wrap .gpy-zones-roi-hint{font-size:10px;color:var(--cta-text);line-height:1.4;opacity:.85}\n.gpy-wrap .gpy-zones-cta{margin-top:0}\n.gpy-wrap .gpy-zones-pitch{margin-top:4px;padding:11px 12px;background:var(--cta-bg);border:1px solid var(--cta-border);border-radius:7px;display:flex;flex-direction:column;gap:8px;position:relative;overflow:hidden}\n.gpy-wrap .gpy-zones-pitch::before{content:\"\";position:absolute;top:-24px;right:-24px;width:64px;height:64px;background:radial-gradient(circle,rgba(74,222,128,.18) 0%,transparent 70%);pointer-events:none}\n.gpy-wrap .gpy-zones-pitch-h{font-size:11px;font-weight:700;color:var(--cta-title);font-family:\"SF Mono\",ui-monospace,Menlo,monospace;letter-spacing:.04em;position:relative}\n.gpy-wrap .gpy-zones-pitch p{font-size:11.5px;line-height:1.5;color:var(--cta-text);margin:0;font-weight:500;position:relative}\n.gpy-wrap .gpy-zones-pitch-list{list-style:none;padding:0;margin:0;font-size:11.5px;line-height:1.55;color:var(--cta-text);position:relative;font-weight:500}\n.gpy-wrap .gpy-zones-pitch-list li{display:flex;align-items:flex-start;gap:6px}\n.gpy-wrap .gpy-zones-pitch-list li::before{content:\"\\2713\";color:var(--accent);font-weight:700;flex:none}\n.gpy-wrap .gpy-zones-pitch .gpy-cta-btn{margin-top:0;position:relative}\n.gpy-wrap .gpy-zones-export{background:var(--panel);color:var(--ink);border:1px solid var(--line2);margin-top:8px;font-size:12px;font-weight:600}\n.gpy-wrap[data-theme=\"light\"] .gpy-zones-export{color:var(--ink)}\n.gpy-wrap .gpy-zones-export:hover{background:var(--panel2);border-color:var(--accent-soft)}\n.gpy-wrap .gpy-zones-export svg{flex:none}\n.gpy-wrap .gpy-zones-export[disabled]{opacity:.55;cursor:default}\n\n.gpy-wrap .gpy-cta{background:var(--cta-bg);border:1px solid var(--cta-border);border-radius:10px;padding:8px 11px;position:relative;overflow:hidden}\n\/* Standalone GeoPard CTA \u2014 sits in a non-scrolling sidebar footer\n   (.gpy-side-footer), separated from .gpy-side-scroll, so it stays\n   visible regardless of how tall the zones panel grows above it. *\/\n.gpy-wrap .gpy-cta-pitch{font-size:12px;line-height:1.5;color:var(--cta-text);margin:0 0 12px 0;font-weight:500;position:relative}\n.gpy-wrap .gpy-cta-btn-pulse{box-shadow:0 0 0 0 rgba(74,222,128,0.6);animation:gpyZonesPulse 2.4s ease-out 1s 3}\n@keyframes gpyZonesPulse{\n  0%{box-shadow:0 0 0 0 rgba(74,222,128,0.55)}\n  60%{box-shadow:0 0 0 10px rgba(74,222,128,0)}\n  100%{box-shadow:0 0 0 0 rgba(74,222,128,0)}\n}\n.gpy-wrap .gpy-cta::before{content:\"\";position:absolute;top:-30px;right:-30px;width:80px;height:80px;background:radial-gradient(circle,rgba(74,222,128,.18) 0%,transparent 70%);pointer-events:none}\n.gpy-wrap .gpy-cta h4{font-size:10px;text-transform:uppercase;letter-spacing:.14em;color:var(--cta-title);margin:0 0 6px 0;font-weight:700;font-family:\"SF Mono\",ui-monospace,Menlo,monospace;position:relative}\n.gpy-wrap .gpy-cta ul{list-style:none;padding:0;margin:0 0 12px 0;font-size:12px;line-height:1.7;position:relative}\n.gpy-wrap .gpy-cta li{color:var(--cta-text);display:flex;align-items:flex-start;gap:8px;font-weight:500}\n.gpy-wrap .gpy-cta li::before{content:\"\u2713\";color:var(--accent);font-weight:700;flex:none}\n.gpy-wrap .gpy-cta-btn{display:flex;align-items:center;justify-content:center;gap:6px;background:var(--accent);color:#0b0f14;border:0;padding:10px;border-radius:7px;font-weight:700;font-size:13px;cursor:pointer;text-decoration:none;font-family:inherit;position:relative;width:100%;transition:background .15s}\n.gpy-wrap[data-theme=\"light\"] .gpy-cta-btn{color:#fff}\n.gpy-wrap .gpy-cta-btn:hover{background:var(--accent-h)}\n.gpy-wrap .gpy-cta-btn .arr{transition:transform .15s}\n.gpy-wrap .gpy-cta-btn:hover .arr{transform:translateX(3px)}\n\n\/* PLAYBACK STRIP \u2014 top of canvas, shifts legend + zoom controls down when active *\/\n.gpy-wrap .gpy-pb{position:absolute;top:14px;left:14px;right:14px;background:var(--panel);border:1px solid var(--line);border-radius:8px;padding:8px 12px;display:none;align-items:center;gap:10px;z-index:8;box-shadow:var(--shadow-sm)}\n.gpy-wrap .gpy-pb.show{display:flex}\n.gpy-wrap .gpy-pb-btn{flex:none;background:var(--accent);color:#0b0f14;border:0;width:32px;height:32px;border-radius:6px;cursor:pointer;font-size:13px;display:flex;align-items:center;justify-content:center;padding:0;font-family:inherit;transition:background .15s;line-height:1}\n.gpy-wrap[data-theme=\"light\"] .gpy-pb-btn{color:#fff}\n.gpy-wrap .gpy-pb-btn:hover{background:var(--accent-h)}\n.gpy-wrap .gpy-pb-track{flex:1;height:8px;background:var(--bg);border-radius:4px;position:relative;cursor:pointer;min-width:60px;border:1px solid var(--line)}\n.gpy-wrap .gpy-pb-fill{position:absolute;left:0;top:0;height:100%;background:var(--accent);border-radius:3px;pointer-events:none;transition:width .05s linear}\n.gpy-wrap .gpy-pb-thumb{position:absolute;top:50%;transform:translate(-50%,-50%);width:14px;height:14px;background:var(--accent);border:2px solid var(--panel);border-radius:50%;pointer-events:none;box-shadow:0 0 4px rgba(0,0,0,.3);transition:left .05s linear}\n.gpy-wrap .gpy-pb-stats{flex:none;font-family:\"SF Mono\",ui-monospace,Menlo,monospace;font-size:10px;color:var(--ink-dim);min-width:170px;text-align:right;line-height:1.35}\n.gpy-wrap .gpy-pb-stats b{color:var(--ink);font-weight:600}\n.gpy-wrap .gpy-pb-seg{flex:none;padding:2px;background:var(--bg);border:1px solid var(--line);border-radius:6px;display:flex;gap:1px}\n.gpy-wrap .gpy-pb-seg button{padding:5px 7px;font-size:10px;background:transparent;border:0;color:var(--ink-dim);cursor:pointer;border-radius:4px;font-family:\"SF Mono\",ui-monospace,Menlo,monospace;font-weight:600;min-width:28px}\n.gpy-wrap .gpy-pb-seg button.on{background:var(--accent);color:#0b0f14}\n.gpy-wrap[data-theme=\"light\"] .gpy-pb-seg button.on{color:#fff}\n.gpy-wrap .gpy-pb-price-grp{flex:none;display:flex;align-items:center;gap:2px;background:var(--bg);border:1px solid var(--line);border-radius:6px;padding:0 0 0 6px;font-family:\"SF Mono\",ui-monospace,Menlo,monospace}\n.gpy-wrap .gpy-pb-price-grp .gpy-pb-price-sym{color:var(--ink-dim);font-size:10px;font-weight:600}\n.gpy-wrap .gpy-pb-price-grp input{width:48px;background:transparent;border:0;color:var(--ink);font-family:\"SF Mono\",ui-monospace,Menlo,monospace;font-size:11px;padding:5px 2px;outline:none;-moz-appearance:textfield;text-align:right}\n.gpy-wrap .gpy-pb-price-grp input::-webkit-outer-spin-button,.gpy-wrap .gpy-pb-price-grp input::-webkit-inner-spin-button{-webkit-appearance:none;margin:0}\n.gpy-wrap .gpy-pb-price-grp .gpy-pb-price-unit{background:transparent;border:0;border-left:1px solid var(--line);color:var(--ink-dim);font-family:\"SF Mono\",ui-monospace,Menlo,monospace;font-size:10px;font-weight:600;padding:5px 8px;border-radius:0 5px 5px 0;white-space:nowrap;max-width:80px;overflow:hidden;text-overflow:ellipsis}\n.gpy-wrap .gpy-pb-collapse{display:none}\n.gpy-wrap .gpy-main.has-playback .gpy-legend-overlay{top:68px}\n.gpy-wrap .gpy-main.has-playback .gpy-ctrl{top:68px}\n\n.gpy-wrap #gpy-canvas{position:absolute;inset:0;cursor:crosshair;display:block;width:100%;height:100%;touch-action:none;-webkit-user-select:none;user-select:none;-webkit-tap-highlight-color:transparent}\n.gpy-wrap .gpy-tip{position:absolute;background:var(--panel);border:1px solid var(--line2);border-radius:7px;padding:9px 11px;font-family:\"SF Mono\",ui-monospace,Menlo,monospace;font-size:11px;pointer-events:none;opacity:0;transition:opacity .1s;z-index:10;box-shadow:var(--shadow);color:var(--ink)}\n.gpy-wrap .gpy-tip.sticky{pointer-events:auto;max-width:340px;max-height:420px;overflow-y:auto;padding-right:30px}\n.gpy-wrap .gpy-tip .gpy-tip-close{position:absolute;top:6px;right:8px;width:20px;height:20px;border:0;background:transparent;color:var(--ink-dim);font-size:16px;line-height:18px;cursor:pointer;padding:0;border-radius:4px}\n.gpy-wrap .gpy-tip .gpy-tip-close:hover{background:var(--line);color:var(--ink)}\n.gpy-wrap .gpy-tip .gpy-tip-row{display:flex;justify-content:space-between;gap:8px;padding:2px 0;font-size:11px}\n.gpy-wrap .gpy-tip .gpy-tip-row .gpy-tip-k{color:var(--ink-dim);white-space:nowrap}\n.gpy-wrap .gpy-tip .gpy-tip-row .gpy-tip-v{text-align:right;word-break:break-all}\n.gpy-wrap .gpy-tip .tv{font-size:14px;font-weight:700}\n.gpy-wrap .gpy-tip .tk{color:var(--ink-dim);text-transform:uppercase;font-size:9px;letter-spacing:.1em;margin-top:4px}\n.gpy-wrap .gpy-ctrl{position:absolute;top:14px;right:14px;display:flex;gap:6px;z-index:5}\n.gpy-wrap .gpy-ctrl button{background:var(--panel);border:1px solid var(--line);color:var(--ink);width:34px;height:34px;border-radius:7px;cursor:pointer;font-size:16px;padding:0;font-family:inherit;line-height:1;box-shadow:var(--shadow-sm);transition:all .15s;display:inline-flex;align-items:center;justify-content:center;gap:5px}\n.gpy-wrap .gpy-ctrl button:hover{background:var(--panel2);border-color:var(--line2)}\n.gpy-wrap .gpy-ctrl button.is-active{background:#f76a0c;color:#fff;border-color:#f76a0c}\n.gpy-wrap .gpy-ctrl button.is-active:hover{background:#ff7d24;border-color:#ff7d24}\n.gpy-wrap .gpy-ctrl button.gpy-btn-wide{width:auto;padding:0 10px;font-size:11px;font-weight:600;letter-spacing:.02em}\n.gpy-wrap .gpy-ctrl button.gpy-btn-wide svg{width:16px;height:16px;flex:none}\n.gpy-wrap .gpy-ctrl button svg{display:block}\n.gpy-wrap .gpy-scale{position:absolute;bottom:14px;left:14px;background:var(--panel);border:1px solid var(--line);padding:6px 10px;border-radius:7px;font-family:\"SF Mono\",ui-monospace,Menlo,monospace;font-size:10px;color:var(--ink-dim);z-index:5;box-shadow:var(--shadow-sm);font-weight:600}\n.gpy-wrap .gpy-scale .bar{display:inline-block;height:2px;background:var(--ink);vertical-align:middle;margin:0 6px}\n.gpy-wrap .gpy-foot{position:absolute;bottom:14px;right:14px;font-family:\"SF Mono\",ui-monospace,Menlo,monospace;font-size:10px;color:var(--ink-dim);background:var(--panel);padding:6px 10px;border-radius:7px;border:1px solid var(--line);z-index:5;box-shadow:var(--shadow-sm);font-weight:500;max-width:60%;text-align:right}\n.gpy-wrap .gpy-foot a{color:var(--accent);text-decoration:none;font-weight:600}\n.gpy-wrap .gpy-foot a:hover{text-decoration:underline}\n.gpy-wrap .gpy-foot .attr{opacity:.7;margin-right:6px}\n\/* Floating GeoPard CTA at canvas bottom-right. Compact pill-card with\n   bullet list + trial button. Dismissable via the \u00d7 in the corner. *\/\n.gpy-wrap .gpy-floating-cta{position:absolute;bottom:14px;right:14px;width:240px;max-width:34vw;background:var(--cta-bg);border:1px solid var(--cta-border);border-radius:10px;padding:8px 11px 9px;z-index:6;box-shadow:var(--shadow);font-family:-apple-system,BlinkMacSystemFont,\"Segoe UI\",sans-serif}\n.gpy-wrap .gpy-floating-cta.is-hidden{display:none}\n.gpy-wrap .gpy-floating-cta-h{font-size:10.5px;font-weight:700;color:var(--cta-title);text-transform:uppercase;letter-spacing:.08em;margin:0 0 5px 0;font-family:\"SF Mono\",ui-monospace,Menlo,monospace}\n.gpy-wrap .gpy-floating-cta ul{list-style:none;padding:0;margin:0 0 7px 0;font-size:10.5px;line-height:1.42;color:var(--cta-text);font-weight:500}\n.gpy-wrap .gpy-floating-cta li{display:flex;align-items:flex-start;gap:5px;padding:1px 0}\n.gpy-wrap .gpy-floating-cta li::before{content:\"\\2713\";color:var(--accent);font-weight:700;flex:none;font-size:10px;line-height:1.42}\n.gpy-wrap .gpy-floating-cta-btn{display:flex;align-items:center;justify-content:center;gap:5px;background:var(--accent);color:#0b0f14;border:0;border-radius:6px;padding:7px 8px;font-weight:700;font-size:12px;text-decoration:none;font-family:inherit;width:100%;transition:background .15s}\n.gpy-wrap[data-theme=\"light\"] .gpy-floating-cta-btn{color:#fff}\n.gpy-wrap .gpy-floating-cta-btn:hover{background:var(--accent-h);transform:translateY(-1px)}\n.gpy-wrap .gpy-floating-cta-btn .arr{transition:transform .15s}\n.gpy-wrap .gpy-floating-cta-btn:hover .arr{transform:translateX(3px)}\n@media (max-width:820px){\n  .gpy-wrap .gpy-floating-cta{display:none}\n}\n\n.gpy-wrap .gpy-legend-overlay{position:absolute;top:14px;left:14px;background:var(--panel);border:1px solid var(--line);padding:10px 12px;border-radius:8px;z-index:5;box-shadow:var(--shadow);min-width:188px;max-width:220px}\n\/* On-map attribute switcher \u2014 chip below the legend, lets the user flip\n   between numeric attributes without leaving the canvas. Hidden when the\n   dataset has only one attribute. Matches gpy-ctrl visual language. *\/\n.gpy-wrap .gpy-attr-pick{position:absolute;top:14px;left:246px;display:flex;align-items:center;gap:10px;background:linear-gradient(135deg,#145328 0%,#1b7a2a 100%);border:1px solid #1a7951;padding:7px 12px;border-radius:999px;z-index:10;box-shadow:0 4px 14px rgba(20,83,40,0.25);font-family:\"SF Mono\",ui-monospace,Menlo,monospace;color:#fff;max-width:360px}\n.gpy-wrap .gpy-attr-pick.is-hidden{display:none}\n\/* Match the legend overlay's vertical shift when the playback bar is active \u2014\n   keeps both elements on the same row, just under the playback strip. *\/\n.gpy-wrap .gpy-main.has-playback .gpy-attr-pick{top:68px}\n.gpy-wrap .gpy-attr-pick-ico{flex:none;width:16px;height:16px;color:#86efac;display:block}\n.gpy-wrap .gpy-attr-pick-lbl{font-size:10px;text-transform:uppercase;letter-spacing:.14em;color:#86efac;font-weight:800;flex:none}\n.gpy-wrap .gpy-attr-pick select{background:#fff;color:#0e3a1c;border:0;border-radius:6px;padding:6px 26px 6px 12px;font-family:inherit;font-size:13px;font-weight:700;cursor:pointer;outline:none;min-width:160px;max-width:260px;-webkit-appearance:none;-moz-appearance:none;appearance:none;background-image:url(\"data:image\/svg+xml;utf8,<svg xmlns='http:\/\/www.w3.org\/2000\/svg' viewBox='0 0 12 8' fill='none' stroke='%230e3a1c' stroke-width='2' stroke-linecap='round' stroke-linejoin='round'><path d='M2 2l4 4 4-4'\/><\/svg>\");background-repeat:no-repeat;background-position:right 8px center;background-size:10px 8px}\n.gpy-wrap .gpy-attr-pick select:hover{box-shadow:0 0 0 2px rgba(255,255,255,0.4)}\n.gpy-wrap .gpy-attr-pick select:focus{box-shadow:0 0 0 3px rgba(134,239,172,0.55)}\n.gpy-wrap .gpy-attr-pick select:disabled{cursor:default;opacity:.7}\n@media (max-width:820px){\n  \/* Pin the on-map attribute pill to the bottom-LEFT corner only \u2014 leaving\n     `right` unset lets the pill size to content (icon + select) instead of\n     stretching to fill the canvas. The duplicate selector with .has-playback\n     matches the higher-specificity rule on line ~409 so `top:68px` doesn't\n     leak back in when the playback strip is active and stretch the pill\n     vertically across the entire canvas. *\/\n  .gpy-wrap .gpy-main .gpy-attr-pick,\n  .gpy-wrap .gpy-main.has-playback .gpy-attr-pick{\n    top:auto;bottom:12px;left:12px;right:auto;\n    transform:none;max-width:calc(100% - 24px);\n    padding:6px 8px;gap:6px;border-radius:999px;\n    justify-content:flex-start;align-items:center\n  }\n  \/* \"ATTRIBUTE\" label hidden \u2014 the icon + the value in the dropdown carry\n     enough context, and on a 375 px viewport every pixel matters. *\/\n  .gpy-wrap .gpy-attr-pick-lbl{display:none}\n  .gpy-wrap .gpy-attr-pick-ico{width:14px;height:14px}\n  \/* Font \u2265 14 px stops iOS Safari from auto-zooming the page when the\n     <select> takes focus. min-width relaxed so a narrow attribute name\n     doesn't reserve a 160 px box on a 320 px viewport. *\/\n  .gpy-wrap .gpy-attr-pick select{\n    min-width:0;max-width:calc(100vw - 100px);\n    font-size:14px;padding:8px 26px 8px 10px;\n    border-radius:6px\n  }\n}\n@media (max-width:480px){\n  .gpy-wrap .gpy-main .gpy-attr-pick,\n  .gpy-wrap .gpy-main.has-playback .gpy-attr-pick{\n    bottom:8px;left:8px;padding:5px 7px;max-width:calc(100% - 16px)\n  }\n  .gpy-wrap .gpy-attr-pick select{max-width:calc(100vw - 70px)}\n}\n.gpy-wrap .gpy-legend-title{font-size:9px;text-transform:uppercase;letter-spacing:.12em;color:var(--ink-dim);font-weight:600;font-family:\"SF Mono\",ui-monospace,Menlo,monospace;margin-bottom:6px}\n.gpy-wrap .gpy-leg-out{margin-top:10px;padding-top:8px;border-top:1px solid var(--line)}\n.gpy-wrap .gpy-leg-out-hd{display:flex;align-items:center;justify-content:space-between;gap:6px;margin-bottom:6px}\n.gpy-wrap .gpy-leg-out-hd .lbl{font-size:9px;text-transform:uppercase;letter-spacing:.1em;color:var(--ink-dim);font-weight:600;font-family:\"SF Mono\",ui-monospace,Menlo,monospace;flex:1;min-width:0}\n.gpy-wrap .gpy-leg-out-hd .gpy-seg{padding:2px;gap:2px;flex:none}\n.gpy-wrap .gpy-leg-out-hd .gpy-seg button{padding:3px 5px;font-size:9.5px}\n.gpy-wrap .gpy-leg-counts{display:flex;gap:5px}\n.gpy-wrap .gpy-leg-counts .gpy-mini{flex:1;text-align:center}\n\n\/* UPLOAD MODAL *\/\n.gpy-wrap .gpy-modal{position:absolute;inset:0;background:rgba(0,0,0,.6);display:none;align-items:flex-start;justify-content:center;z-index:50;backdrop-filter:blur(4px);padding:48px 20px 20px;overflow-y:auto}\n.gpy-wrap .gpy-modal.show{display:flex}\n.gpy-wrap .gpy-modal-card{background:var(--panel);border:1px solid var(--line);border-radius:12px;padding:24px;max-width:460px;width:100%;box-shadow:0 20px 60px rgba(0,0,0,.5);position:relative;max-height:90vh;overflow-y:auto}\n.gpy-wrap .gpy-dropzone{display:flex;flex-direction:column;align-items:center;justify-content:center;gap:8px;padding:28px 16px;margin:14px 0 10px;background:var(--bg);border:2px dashed var(--line2);border-radius:10px;text-align:center;cursor:pointer;outline:none;transition:border-color .15s,background .15s}\n.gpy-wrap .gpy-dropzone:hover,.gpy-wrap .gpy-dropzone:focus{border-color:var(--accent);background:var(--cta-bg)}\n.gpy-wrap .gpy-dropzone.is-drag{border-color:var(--accent);background:var(--cta-bg);box-shadow:inset 0 0 0 2px var(--accent)}\n.gpy-wrap .gpy-dropzone-icon{width:38px;height:38px;color:var(--accent);margin-bottom:2px}\n.gpy-wrap .gpy-dropzone-title{font-size:15px;font-weight:600;color:var(--ink);letter-spacing:-.01em}\n.gpy-wrap .gpy-dropzone-btn{margin:10px auto 8px;padding:14px 44px;min-height:48px;font-size:15px;border-radius:10px;justify-content:center}\n.gpy-wrap .gpy-dz-info{position:relative;display:inline-flex;align-items:center;gap:6px;margin-top:2px;font-size:12px;color:var(--ink-dim);cursor:help;outline:none}\n.gpy-wrap .gpy-dz-i{width:16px;height:16px;flex:0 0 16px;border-radius:50%;border:1px solid var(--line2);display:inline-flex;align-items:center;justify-content:center;font-size:11px;font-weight:700;font-style:italic;line-height:1}\n.gpy-wrap .gpy-dz-info:hover .gpy-dz-i,.gpy-wrap .gpy-dz-info:focus .gpy-dz-i{border-color:var(--accent);color:var(--accent)}\n.gpy-wrap .gpy-dz-tip{position:absolute;bottom:calc(100% + 9px);left:50%;transform:translateX(-50%);width:250px;max-width:78vw;background:var(--panel);color:var(--ink);border:1px solid var(--line);border-radius:8px;padding:9px 11px;font-size:11px;line-height:1.55;text-align:left;box-shadow:var(--shadow);opacity:0;visibility:hidden;transition:opacity .12s ease;z-index:30;pointer-events:none}\n.gpy-wrap .gpy-dz-tip strong{color:var(--ink);font-weight:600}\n.gpy-wrap .gpy-dz-tip code{font-family:\"SF Mono\",ui-monospace,Menlo,monospace;color:var(--ink);font-size:10px;background:var(--bg);border:1px solid var(--line);border-radius:4px;padding:0 4px}\n.gpy-wrap .gpy-dz-tip:after{content:\"\";position:absolute;top:100%;left:50%;transform:translateX(-50%);border:6px solid transparent;border-top-color:var(--panel)}\n.gpy-wrap .gpy-dz-info:hover .gpy-dz-tip,.gpy-wrap .gpy-dz-info:focus .gpy-dz-tip,.gpy-wrap .gpy-dz-info:focus-within .gpy-dz-tip{opacity:1;visibility:visible}\n\/* Downward-opening variant \u2014 used by the header Upload hint (a tooltip above\n   the header would render off the top of the embed). *\/\n.gpy-wrap .gpy-dz-down .gpy-dz-tip{bottom:auto;top:calc(100% + 9px)}\n.gpy-wrap .gpy-dz-down .gpy-dz-tip:after{top:auto;bottom:100%;border-top-color:transparent;border-bottom-color:var(--panel)}\n.gpy-wrap .gpy-modal-close{position:absolute;top:12px;right:12px;background:transparent;border:0;color:var(--ink-dim);width:28px;height:28px;border-radius:6px;cursor:pointer;font-size:18px;line-height:1;padding:0;font-family:inherit}\n.gpy-wrap .gpy-modal-close:hover{background:var(--panel2);color:var(--ink)}\n.gpy-wrap .gpy-modal-card h3{font-size:16px;font-weight:600;color:var(--ink);margin:0 0 6px 0;letter-spacing:-.01em}\n.gpy-wrap .gpy-modal-card .gpy-modal-sub{color:var(--ink-dim);font-size:12px;margin:0 0 18px 0}\n.gpy-wrap .gpy-modal-section{margin-bottom:14px}\n.gpy-wrap .gpy-modal-section h4{font-size:10px;text-transform:uppercase;letter-spacing:.12em;color:var(--ink-dim);font-weight:600;font-family:\"SF Mono\",ui-monospace,Menlo,monospace;margin:0 0 8px 0}\n.gpy-wrap .gpy-modal-section ul{list-style:none;padding:0;margin:0 0 10px 0;font-size:13px;color:var(--ink);line-height:1.7}\n.gpy-wrap .gpy-modal-section li{display:flex;align-items:flex-start;gap:8px}\n.gpy-wrap .gpy-modal-section li::before{content:\"\u2022\";color:var(--accent);font-weight:700;flex:none}\n.gpy-wrap .gpy-modal-section li code{background:var(--bg);border:1px solid var(--line);border-radius:4px;padding:1px 6px;font-family:\"SF Mono\",ui-monospace,Menlo,monospace;font-size:11px;color:var(--ink-dim)}\n.gpy-wrap .gpy-modal-section .gpy-modal-note{font-size:11px;color:var(--ink-dim);font-family:\"SF Mono\",ui-monospace,Menlo,monospace;line-height:1.5;margin-top:4px}\n.gpy-wrap .gpy-modal-divider{height:1px;background:var(--line);margin:18px 0}\n.gpy-wrap .gpy-modal-btn{display:flex;align-items:center;justify-content:center;gap:6px;width:100%;border:0;padding:11px;border-radius:7px;font-weight:600;font-size:13px;cursor:pointer;font-family:inherit;transition:background .15s;text-decoration:none;margin-top:10px}\n.gpy-wrap .gpy-modal-btn.primary{background:var(--accent);color:#0b0f14}\n.gpy-wrap[data-theme=\"light\"] .gpy-modal-btn.primary{color:#fff}\n.gpy-wrap .gpy-modal-btn.primary:hover{background:var(--accent-h)}\n.gpy-wrap .gpy-modal-btn.outline{background:transparent;color:var(--ink);border:1px solid var(--line2)}\n.gpy-wrap .gpy-modal-btn.outline:hover{background:var(--panel2)}\n.gpy-wrap .gpy-modal-cta{background:var(--cta-bg);border:1px solid var(--cta-border);border-radius:9px;padding:14px;margin-top:6px}\n.gpy-wrap .gpy-modal-cta h4{color:var(--cta-title)}\n.gpy-wrap .gpy-modal-cta p{color:var(--cta-text);font-size:12px;line-height:1.55;margin:0 0 10px 0}\n\n.gpy-wrap .gpy-overlay{position:absolute;inset:0;background:var(--bg);display:none;align-items:center;justify-content:center;flex-direction:column;gap:12px;z-index:20;text-align:center;padding:40px}\n.gpy-wrap .gpy-overlay.show{display:flex}\n.gpy-wrap .gpy-overlay.drop{background:var(--cta-bg);box-shadow:inset 0 0 0 3px var(--accent)}\n.gpy-wrap .gpy-spinner{width:32px;height:32px;border:3px solid var(--line);border-top-color:var(--accent);border-radius:50%;animation:gpySpin .8s linear infinite}\n@keyframes gpySpin{to{transform:rotate(360deg)}}\n.gpy-wrap .gpy-overlay h3{font-size:16px;font-weight:600;margin:0;color:var(--ink)}\n.gpy-wrap .gpy-overlay p{color:var(--ink-dim);font-size:13px;margin:0;max-width:340px;line-height:1.55}\n.gpy-wrap .gpy-toast{position:absolute;top:14px;left:50%;transform:translateX(-50%);background:#dc2626;color:#fff;padding:9px 14px;border-radius:7px;font-size:12px;font-weight:500;z-index:30;box-shadow:var(--shadow);opacity:0;transition:opacity .2s;pointer-events:none}\n.gpy-wrap .gpy-toast.show{opacity:1}\n.gpy-wrap .gpy-toast.is-ok{background:#15701e}\n.gpy-wrap .gpy-toast.is-info{background:#0e3a1c}\n\n\/* ROI CALCULATOR SECTION *\/\n.gpy-wrap .gpy-tog2{display:flex;align-items:center;gap:9px;font-size:12px;color:var(--ink);padding:5px 0;cursor:pointer;user-select:none}\n.gpy-wrap .gpy-tog2 input{accent-color:var(--accent);cursor:pointer;width:14px;height:14px;margin:0;flex:none}\n.gpy-wrap[data-theme=\"light\"] .gpy-roi-cta{color:#fff}\n\n@media (max-width:820px){\n  .gpy-wrap .gpy-grid{grid-template-columns:1fr;grid-template-areas:\"main\" \"left\"}\n  .gpy-wrap .gpy-side{max-height:none;border-right:0;border-top:1px solid var(--line);padding:0;flex-direction:column;overflow:visible}\n  .gpy-wrap .gpy-side-scroll{padding:14px;gap:14px;overflow:visible}\n  .gpy-wrap .gpy-side-footer{box-shadow:none;border-top:1px solid var(--line);border-radius:0}\n  .gpy-wrap .gpy-splitter{display:none}\n  .gpy-wrap .gpy-main{min-height:62vh}\n  \/* Tighter top toolbar on mobile: smaller outer + inner gaps, less padding\n     around buttons. Tap targets stay \u2265 44 px via min-height \/ min-width,\n     only the spacing between buttons shrinks so the row reads as a single\n     control strip instead of widely-spaced standalone controls. *\/\n  .gpy-wrap .gpy-top{padding:10px 10px;gap:6px}\n  .gpy-wrap .gpy-actions{gap:5px}\n  .gpy-wrap .gpy-chip{max-width:200px}\n  .gpy-wrap .gpy-btn-primary span.lbl{display:none}\n  .gpy-wrap .gpy-btn-primary{padding:10px;min-height:44px;min-width:44px;justify-content:center}\n  \/* On mobile drop the header three-zone centering \u2014 the row packs compactly\n     (label is hidden so Upload is a 44px icon). Collapse #gpy-upload back to a\n     square and stop the side zones growing so nothing wraps oddly. *\/\n  .gpy-wrap #gpy-upload{padding:10px;min-height:44px;min-width:44px}\n  .gpy-wrap .gpy-actions{flex:0 0 auto}\n  .gpy-wrap .gpy-icon-btn{width:42px;height:42px}\n  \/* On mobile, move the ctrl strip from the canvas top-RIGHT to the top-LEFT\n     so it sits directly above the legend\/histogram block (both anchored at\n     left:14). Same horizontal alignment + vertical stacking = clear \"row\n     above row\" relationship, no horizontal competition for canvas space. *\/\n  .gpy-wrap .gpy-ctrl{gap:5px;top:14px;left:14px;right:auto}\n  .gpy-wrap .gpy-ctrl button{width:40px;height:40px;font-size:18px}\n  \/* Wide buttons in the ctrl strip (Ruler, etc.) drop the text label on\n     mobile and become icon-only \u2014 saves ~50 px of horizontal space and\n     stops the long \"Ruler\" label from overlapping with whatever sits\n     next to it. *\/\n  .gpy-wrap .gpy-ctrl button.gpy-btn-wide{width:40px;padding:0}\n  .gpy-wrap .gpy-ctrl button.gpy-btn-wide span{display:none}\n  \/* Legend overlay (with the always-on histogram) used to share the same\n     top value as the ctrl strip \u2014 they sat side-by-side on the left and\n     right of the canvas. On narrow viewports neither has room to breathe.\n     Push legend BELOW the ctrl strip so they stack vertically. *\/\n  \/* Vertical stack on mobile: playback (top, ~50 px) \u2192 ctrl strip \u2192 legend\n     overlay. Each block sits in its own row with a small gap. ctrl is 40 px\n     tall, so legend top must clear ctrl-bottom + gap. *\/\n  .gpy-wrap .gpy-legend-overlay{top:62px}\n  \/* Unit toggle (m\/km vs ft\/mi) \u2014 buttons inside a segmented control.\n     Tighten internal padding so the toggle doesn't dominate the row. *\/\n  .gpy-wrap .gpy-actions .gpy-seg{padding:2px;gap:1px}\n  .gpy-wrap .gpy-actions .gpy-seg button{padding:7px 10px;font-size:11px}\n  .gpy-wrap .gpy-foot{max-width:60%;font-size:9px;padding:5px 8px}\n  \/* Legend overlay was eating ~50 % of the canvas on mobile. Strip it down\n     to just the essentials (title + zone histogram + gradient bar + average).\n     The bulky bits \u2014 5 per-class rate-input rows, outlier \u03c3 controls,\n     coverage rows \u2014 move to the sidebar zones panel below the canvas,\n     where there's actually room for them. *\/\n  .gpy-wrap .gpy-legend-overlay{min-width:0;max-width:38%;padding:6px 8px;font-size:10px}\n  .gpy-wrap .gpy-legend-overlay .gpy-legend-stops,\n  .gpy-wrap .gpy-legend-overlay .gpy-leg-out,\n  .gpy-wrap .gpy-legend-overlay .gpy-leg-row,\n  .gpy-wrap .gpy-legend-overlay .gpy-legend-reset{display:none}\n  .gpy-wrap .gpy-legend-overlay .gpy-leg-stats{display:flex;flex-wrap:wrap;gap:4px;font-size:10px}\n  .gpy-wrap .gpy-legend-overlay .gpy-leg-stat{flex:1 1 auto;min-width:0}\n  .gpy-wrap .gpy-legend-overlay .gpy-leg-stat .lbl{font-size:9px}\n  .gpy-wrap .gpy-legend-overlay .gpy-leg-stat .val{font-size:11px}\n  .gpy-wrap .gpy-modal-card{padding:20px;max-height:88vh}\n  .gpy-wrap .gpy-modal-btn{padding:13px;min-height:46px}\n  .gpy-wrap .gpy-tip{font-size:12px;padding:8px 10px;max-width:200px}\n  .gpy-wrap .gpy-seg button{padding:9px 4px;font-size:11px;min-height:36px}\n  .gpy-wrap .gpy-tog2 input{width:18px;height:18px}\n  .gpy-wrap .gpy-tog2{padding:8px 0;font-size:13px}\n  .gpy-wrap .gpy-tree{max-height:none;font-size:13px}\n  .gpy-wrap .gpy-tree-node{padding:11px 12px 11px 8px;min-height:44px;font-size:13px;gap:8px}\n  .gpy-wrap .gpy-tree-meta{font-size:10px}\n  .gpy-wrap .gpy-tree-glyph{width:14px;font-size:13px}\n  .gpy-wrap .gpy-tree-empty{padding:18px 12px;font-size:13px}\n  .gpy-wrap .gpy-pb{flex-wrap:wrap;padding:10px;gap:10px;top:10px;left:10px;right:10px}\n  \/* Collapse toggle visible only on mobile. Tap target \u2265 36 \u00d7 36 px (chevron\n     icon, no labels \u2014 just play\/pause-style minimal). Collapsed state shows:\n     play + pause + scrubber + chevron. Expanded state adds: speed buttons,\n     stats line, price input. The track stays inline (no width:100%) when\n     collapsed so the row stays compact. *\/\n  .gpy-wrap .gpy-pb-collapse{\n    display:flex;align-items:center;justify-content:center;flex:none;\n    background:var(--bg);border:1px solid var(--line);color:var(--ink-dim);\n    width:36px;height:36px;border-radius:6px;cursor:pointer;\n    font-size:14px;line-height:1;padding:0;font-family:inherit;\n    transition:transform .15s,color .15s;margin-left:auto;-webkit-appearance:none\n  }\n  .gpy-wrap .gpy-pb-collapse:hover{color:var(--accent);border-color:var(--accent-soft)}\n  .gpy-wrap .gpy-pb.is-expanded .gpy-pb-collapse{transform:rotate(180deg);color:var(--accent)}\n  .gpy-wrap .gpy-pb:not(.is-expanded) .gpy-pb-seg,\n  .gpy-wrap .gpy-pb:not(.is-expanded) .gpy-pb-stats,\n  .gpy-wrap .gpy-pb:not(.is-expanded) .gpy-pb-price-grp{display:none}\n  .gpy-wrap .gpy-pb:not(.is-expanded) .gpy-pb-track{order:0;width:auto;flex:1 1 60px}\n  \/* With playback bar (collapsed ~50 px on mobile by default):\n       playback: top:10 \u2192 60\n       ctrl    : top:68 \u2192 108 (8 px gap above)\n       legend  : top:116      (8 px gap above ctrl)\n     Each row is clearly above the next; no overlap with the legend\n     overlay below. *\/\n  .gpy-wrap .gpy-main.has-playback .gpy-ctrl{top:68px}\n  .gpy-wrap .gpy-main.has-playback .gpy-legend-overlay{top:116px}\n  .gpy-wrap .gpy-pb-btn{width:44px;height:44px;font-size:16px}\n  .gpy-wrap .gpy-pb-track{order:99;width:100%;flex-basis:100%;height:10px}\n  .gpy-wrap .gpy-pb-thumb{width:18px;height:18px}\n  .gpy-wrap .gpy-pb-stats{flex:1;text-align:left;font-size:11px;min-width:auto}\n  .gpy-wrap .gpy-pb-seg button{padding:9px 6px;min-height:36px;min-width:32px;font-size:10px}\n  .gpy-wrap .gpy-pb-price-grp{padding:0 0 0 8px;min-height:44px}\n  .gpy-wrap .gpy-pb-price-grp input{width:64px;font-size:14px;padding:11px 4px;min-height:44px}\n  .gpy-wrap .gpy-pb-price-grp .gpy-pb-price-unit{padding:11px 12px;min-height:44px;font-size:12px;max-width:110px}\n  .gpy-wrap .gpy-pb-stats{flex:1;order:50;width:100%;flex-basis:100%;text-align:left;font-size:11px;min-width:auto;padding:4px 0}\n}\n@media (max-width:480px){\n  .gpy-wrap{font-size:14px;border-radius:0}\n  .gpy-wrap .gpy-top{padding:10px 12px}\n  .gpy-wrap .gpy-chip{max-width:150px;font-size:10px}\n  .gpy-wrap .gpy-main{min-height:58vh}\n  .gpy-wrap .gpy-legend-overlay{max-width:42%;font-size:10px;padding:5px 7px;top:54px}\n  .gpy-wrap .gpy-main.has-playback .gpy-ctrl{top:64px}\n  .gpy-wrap .gpy-main.has-playback .gpy-legend-overlay{top:112px}\n  .gpy-wrap .gpy-legend-title{font-size:8px}\n  .gpy-wrap .gpy-foot{display:none}\n  .gpy-wrap .gpy-stats{grid-template-columns:1fr 1fr;gap:8px}\n  .gpy-wrap .gpy-side h4{font-size:12px}\n  .gpy-wrap .gpy-pb{padding:8px;gap:6px;top:8px;left:8px;right:8px}\n  .gpy-wrap .gpy-pb-seg{flex-wrap:wrap;gap:1px}\n  .gpy-wrap .gpy-pb-seg button{padding:8px 5px;min-width:30px;font-size:10px}\n  .gpy-wrap .gpy-pb-price-grp{order:60;flex-basis:auto}\n  .gpy-wrap .gpy-pb-price-grp input{width:52px}\n  \/* Duplicate has-playback rules removed \u2014 see consolidated values in the\n     @media 480 block above (ctrl:64, legend:112). The old 148-px legacy\n     positions assumed a 110-px-tall uncollapsed playback bar; with the\n     default collapsed bar at ~50 px those values left a 60-px gap of\n     wasted canvas above the ctrl + caused legend\/ctrl overlap. *\/\n}\n<\/style>\n\n<div class=\"gpy-top\">\n  <div class=\"gpy-brand\">\n    <div class=\"gpy-logo\">G<\/div>\n    <div class=\"gpy-titles\">\n      <div class=\"gpy-h1\">Field Data Explorer<\/div>\n      <div class=\"gpy-chip is-sample\" id=\"gpy-chip\">\n        <span class=\"gpy-dot\"><\/span>\n        <span id=\"gpy-chip-label\">Sample \u00b7 2017 soybean<\/span>\n      <\/div>\n    <\/div>\n  <\/div>\n  <div class=\"gpy-upload-wrap\">\n    <button class=\"gpy-btn-primary\" id=\"gpy-upload\" title=\"Upload field data\">\n      <svg viewBox=\"0 0 24 24\"><path d=\"M9 16V8H5l7-7 7 7h-4v8H9zm-4 2h14v2H5v-2z\"\/><\/svg>\n      <span class=\"lbl\">Upload your file<\/span>\n    <\/button>\n    <div class=\"gpy-dz-info gpy-dz-down\" tabindex=\"0\" role=\"note\" aria-label=\"Supported file types: GeoJSON, Shapefile zip, CSV or TSV, Excel xlsx and xls, ISOXML, whole folder, multiple files at once\">\n      <span class=\"gpy-dz-i\" aria-hidden=\"true\">i<\/span>\n      <div class=\"gpy-dz-tip\" role=\"tooltip\">\n        <strong>Supported file types<\/strong><br>\n        GeoJSON <code>.json<\/code> \/ <code>.geojson<\/code> \u00b7 Shapefile <code>.zip<\/code> \u00b7 CSV \/ TSV <code>.csv<\/code> \/ <code>.tsv<\/code> \u00b7 Excel <code>.xlsx<\/code> \/ <code>.xls<\/code> \u00b7 KML \/ KMZ <code>.kml<\/code> \/ <code>.kmz<\/code> \u00b7 ISO-XML <code>.xml<\/code> \u00b7 whole folder \u00b7 multiple files at once\n      <\/div>\n    <\/div>\n  <\/div>\n  <div class=\"gpy-actions\">\n    <div class=\"gpy-seg\" id=\"gpy-samples\">\n      <a class=\"gpy-seg-link\" href=\"\/guidance-lines\/\" target=\"_blank\" rel=\"noopener\" aria-describedby=\"gpy-seg-link-tip\">AB lines<span class=\"gpy-seg-link-arr\" aria-hidden=\"true\">\u2197<\/span><span class=\"gpy-seg-link-tip\" id=\"gpy-seg-link-tip\" role=\"tooltip\">Line planning lives in the dedicated <strong>Guidance Lines Simulator<\/strong> \u2014 AB-line layout, headland strategy, U-turn shape, coverage %. Opens in a new tab.<\/span><\/a>\n    <\/div>\n    <div class=\"gpy-seg\" id=\"gpy-units\" role=\"group\" aria-label=\"Distance units\">\n      <button data-u=\"metric\" class=\"on\" title=\"Metric (m \/ km \/ ha)\">m \/ km<\/button>\n      <button data-u=\"imperial\" title=\"Imperial (ft \/ mi \/ ac)\">ft \/ mi<\/button>\n    <\/div>\n    <button class=\"gpy-icon-btn\" id=\"gpy-theme\" title=\"Toggle theme\">\n      <svg class=\"gpy-sun\" viewBox=\"0 0 24 24\"><path d=\"M12 18a6 6 0 100-12 6 6 0 000 12zM11 1h2v3h-2V1zm0 19h2v3h-2v-3zM3.5 4.9l1.4-1.4 2.1 2.1-1.4 1.4-2.1-2.1zm13.1 13.1l1.4-1.4 2.1 2.1-1.4 1.4-2.1-2.1zM20 11h3v2h-3v-2zM1 11h3v2H1v-2zm5.3 5.6l2.1 2.1-1.4 1.4-2.1-2.1 1.4-1.4zm12.4-12.4l2.1 2.1-1.4 1.4-2.1-2.1 1.4-1.4z\"\/><\/svg>\n      <svg class=\"gpy-moon\" viewBox=\"0 0 24 24\"><path d=\"M21.4 13.7A9 9 0 1110.3 2.6a1 1 0 011.1 1.3A7 7 0 0020 13.5a1 1 0 011.4.2z\"\/><\/svg>\n    <\/button>\n  <\/div>\n<\/div>\n\n<input type=\"file\" id=\"gpy-input\" accept=\".json,.geojson,.zip,.shp,.csv,.tsv,.txt,.xlsx,.xlsm,.xls,.kml,.kmz,application\/json,application\/zip,text\/csv,application\/vnd.google-earth.kml+xml,application\/vnd.google-earth.kmz,application\/vnd.openxmlformats-officedocument.spreadsheetml.sheet,application\/vnd.ms-excel\" multiple style=\"display:none\">\n\n<div class=\"gpy-grid\">\n  <aside class=\"gpy-side\">\n    <div class=\"gpy-side-scroll\">\n    <div class=\"gpy-card\">\n      <h3>Datasets<\/h3>\n      <div class=\"gpy-tree\" id=\"gpy-tree\"><\/div>\n    <\/div>\n\n    <!-- Sidebar Attribute card removed \u2014 the on-map chip (#gpy-attr-pick)\n         is the single source of truth now. #gpy-col still exists hidden\n         below so the existing setColumn \u2194 select wiring keeps working\n         (used as a programmatic hook for the on-map picker). -->\n    <select id=\"gpy-col\" style=\"display:none\"><\/select>\n\n    <div class=\"gpy-card gpy-zones-card\" id=\"gpy-zones-card\">\n      <h3>Auto zones<\/h3>\n      <div class=\"gpy-zones-cv\" id=\"gpy-zones-cv\">\n        <div class=\"gpy-zones-cv-l\">Variability (CV)<\/div>\n        <div class=\"gpy-zones-cv-v\"><span id=\"gpy-zones-cv-num\">\u2014<\/span> <span class=\"gpy-zones-cv-tier\" id=\"gpy-zones-cv-tier\">\u2014<\/span><\/div>\n      <\/div>\n      <div class=\"gpy-zones-seg-row\">\n        <div class=\"gpy-zones-seg-l\">Show zones<\/div>\n        <div class=\"gpy-seg\" id=\"gpy-zones-seg\" role=\"group\" aria-label=\"Number of management zones to highlight\">\n          <button data-z=\"0\" class=\"on\">Off<\/button>\n          <button data-z=\"3\">3<\/button>\n          <button data-z=\"4\">4<\/button>\n          <button data-z=\"5\">5<\/button>\n        <\/div>\n      <\/div>\n      <div class=\"gpy-zones-body\" id=\"gpy-zones-body\" hidden>\n        <div class=\"gpy-zones-bar\" id=\"gpy-zones-bar\" title=\"Zone proportions\"><\/div>\n        <div class=\"gpy-zones-rates\" id=\"gpy-zones-rates\">\n          <!-- Value-distribution histogram with K-1 draggable break thumbs.\n               Each thumb sits at one of zoneBreaks[i]; dragging it shifts\n               the break point between adjacent zones, points reclassify,\n               the map + per-zone rows update in real time. -->\n          <div class=\"gpy-zones-hist\" id=\"gpy-zones-hist\" title=\"Drag a thumb to move the break between adjacent zones. Histogram shows the value distribution of the active attribute.\">\n            <canvas class=\"gpy-zones-hist-canvas\" id=\"gpy-zones-hist-canvas\" width=\"600\" height=\"48\"><\/canvas>\n            <div class=\"gpy-zones-hist-track\" id=\"gpy-zones-hist-track\"><\/div>\n            <div class=\"gpy-zones-hist-scale\" id=\"gpy-zones-hist-scale\"><\/div>\n          <\/div>\n          <!-- Target-average rate + unit picker on a single row. User types\n               one number; per-zone rates redistribute via a \u00b115% gradient\n               (lower-value zones get less, higher-value zones get more)\n               area-weighted so the field-wide average lands on the typed\n               target. The unit picker drives BOTH the avg and per-zone\n               rate columns; picking a \/ac unit flips the total to acres. -->\n          <div class=\"gpy-zones-avg-row\">\n            <span class=\"gpy-zones-avg-lbl\">Target avg rate<\/span>\n            <input type=\"number\" inputmode=\"decimal\" id=\"gpy-zones-avg-input\" min=\"0\" step=\"any\" placeholder=\"auto\" aria-label=\"Target average rate\" title=\"Type one target average rate. Higher-value zones get more product (+15%), lower-value zones get less (-15%); the gradient is then area-weighted so the field-wide weighted average matches your target.\">\n            <select class=\"gpy-zones-unit-select\" id=\"gpy-zones-unit\" title=\"Pick a rate unit. Imperial choices (per acre) flip the per-zone total to acres automatically.\">\n              <optgroup label=\"Fertilizer (dry)\">\n                <option value=\"kg\/ha\">kg\/ha<\/option>\n                <option value=\"t\/ha\">t\/ha<\/option>\n                <option value=\"lb\/ac\">lb\/ac<\/option>\n                <option value=\"ton\/ac\">ton\/ac<\/option>\n              <\/optgroup>\n              <optgroup label=\"Liquid\">\n                <option value=\"L\/ha\">L\/ha<\/option>\n                <option value=\"mL\/ha\">mL\/ha<\/option>\n                <option value=\"gal\/ac\">gal\/ac<\/option>\n                <option value=\"fl oz\/ac\">fl oz\/ac<\/option>\n              <\/optgroup>\n              <optgroup label=\"Seeding\">\n                <option value=\"seeds\/ha\">seeds\/ha<\/option>\n                <option value=\"seeds\/ac\">seeds\/ac<\/option>\n                <option value=\"k seeds\/ha\">k seeds\/ha<\/option>\n                <option value=\"k seeds\/ac\">k seeds\/ac<\/option>\n                <option value=\"units\/ac\">units\/ac<\/option>\n                <option value=\"bags\/ac\">bags\/ac<\/option>\n              <\/optgroup>\n              <optgroup label=\"Lime \/ amendments\">\n                <option value=\"t\/ac\">t\/ac<\/option>\n                <option value=\"cwt\/ac\">cwt\/ac<\/option>\n              <\/optgroup>\n            <\/select>\n            <span class=\"gpy-zones-avg-status\" id=\"gpy-zones-avg-status\" title=\"Achieved weighted average and resulting total product after smart distribution.\"><\/span>\n          <\/div>\n          <div class=\"gpy-zones-list\" id=\"gpy-zones-list\"><\/div>\n          <div class=\"gpy-zones-rates-total\">\n            <span class=\"gpy-zones-rates-total-l\">Total product<\/span>\n            <span class=\"gpy-zones-rates-total-v\" id=\"gpy-zones-rates-total-v\">\u2014<\/span>\n          <\/div>\n          <div class=\"gpy-zones-rates-cmp\" id=\"gpy-zones-rates-cmp\"><\/div>\n        <\/div>\n        <div class=\"gpy-zones-roi\">\n          <div class=\"gpy-zones-roi-l\">Estimated VRA upside<\/div>\n          <div class=\"gpy-zones-roi-v\" id=\"gpy-zones-roi-v\">\u2014<\/div>\n          <div class=\"gpy-zones-roi-ref\" id=\"gpy-zones-roi-ref\"><\/div>\n          <div class=\"gpy-zones-roi-hint\">Calibrated from published variable-rate trial midpoints. Conservative.<\/div>\n        <\/div>\n        <button class=\"gpy-cta-btn gpy-zones-export\" id=\"gpy-zones-export\" type=\"button\" title=\"Download a zipped shapefile with one polygon per management zone\">\n          <svg viewBox=\"0 0 24 24\" width=\"14\" height=\"14\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\" aria-hidden=\"true\"><path d=\"M21 15v4a2 2 0 0 1-2 2H5a2 2 0 0 1-2-2v-4\"\/><polyline points=\"7 10 12 15 17 10\"\/><line x1=\"12\" y1=\"15\" x2=\"12\" y2=\"3\"\/><\/svg>\n          Download zone polygons .shp\n        <\/button>\n        <!-- Inline \"Smarter zones in GeoPard\" pitch removed \u2014 the standalone\n             sidebar card below is the single CTA. -->\n\n      <\/div>\n    <\/div>\n    <\/div> <!-- \/.gpy-side-scroll -->\n\n    <!-- GeoPard CTA moved to a floating chip at canvas bottom-right (#gpy-floating-cta). -->\n\n  <\/aside>\n\n  <div class=\"gpy-splitter\" id=\"gpy-splitter\" role=\"separator\" aria-orientation=\"vertical\" aria-label=\"Resize datasets panel\" title=\"Drag to resize\"><\/div>\n\n  <main class=\"gpy-main\">\n    <canvas id=\"gpy-canvas\"><\/canvas>\n    <div class=\"gpy-tip\" id=\"gpy-tip\"><\/div>\n    <div class=\"gpy-ctrl\">\n      <button id=\"gpy-ruler\" class=\"gpy-btn-wide\" title=\"Measure distance \u2014 click points on the map, double-click to finish, ESC to clear\"><svg viewBox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><rect x=\"2\" y=\"9\" width=\"20\" height=\"6\" rx=\"1\"\/><line x1=\"6\" y1=\"9\" x2=\"6\" y2=\"13\"\/><line x1=\"10\" y1=\"9\" x2=\"10\" y2=\"13\"\/><line x1=\"14\" y1=\"9\" x2=\"14\" y2=\"13\"\/><line x1=\"18\" y1=\"9\" x2=\"18\" y2=\"13\"\/><\/svg><span>Ruler<\/span><\/button>\n      <button id=\"gpy-export\" class=\"gpy-btn-wide\" title=\"Download the current layer as a zipped shapefile \u2014 geometry + all attributes, EPSG:4326. Works for any uploaded file.\"><svg viewBox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M21 15v4a2 2 0 0 1-2 2H5a2 2 0 0 1-2-2v-4\"\/><polyline points=\"7 10 12 15 17 10\"\/><line x1=\"12\" y1=\"15\" x2=\"12\" y2=\"3\"\/><\/svg><span>Export<\/span><\/button>\n      <button id=\"gpy-zin\" title=\"Zoom in\">+<\/button>\n      <button id=\"gpy-zout\" title=\"Zoom out\">\u2212<\/button>\n      <button id=\"gpy-reset\" title=\"Reset view\">\u27f2<\/button>\n    <\/div>\n    <div class=\"gpy-scale\"><span class=\"bar\" id=\"gpy-sc-b\" style=\"width:60px\"><\/span><span id=\"gpy-sc-t\">\u2014 m<\/span><\/div>\n\n    <div class=\"gpy-attr-pick\" id=\"gpy-attr-pick\" title=\"Switch which numeric attribute the colour scale represents\">\n      <svg class=\"gpy-attr-pick-ico\" viewBox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\" aria-hidden=\"true\"><path d=\"M3 7h6M3 12h12M3 17h18\"\/><\/svg>\n      <span class=\"gpy-attr-pick-lbl\">Attribute<\/span>\n      <select class=\"gpy-sel\" id=\"gpy-col-overlay\"><\/select>\n    <\/div>\n\n    <div class=\"gpy-legend-overlay\" id=\"gpy-legend\">\n      <div class=\"gpy-legend-title\" id=\"gpy-legend-title\">Scale<\/div>\n      <!-- Compact value-distribution histogram + draggable zone-break thumbs.\n           Mirrors the sidebar histogram (#gpy-zones-hist); both share\n           zoneBreaks, so a drag on either updates both + the map. Hidden\n           until zones are turned on (zonesK > 0) via the same display\n           gate as renderHistogram() uses. -->\n      <div class=\"gpy-legend-hist\" id=\"gpy-legend-hist\" title=\"Value-distribution histogram. With zones on, K-1 draggable break thumbs sit above the bars \u2014 drag to move the boundary between adjacent zones.\">\n        <canvas class=\"gpy-legend-hist-canvas\" id=\"gpy-legend-hist-canvas\"><\/canvas>\n        <div class=\"gpy-legend-hist-track\" id=\"gpy-legend-hist-track\"><\/div>\n      <\/div>\n      <div class=\"gpy-legend-bar\" id=\"gpy-legend-bar\">\n        <div class=\"gpy-legend-thumb\" id=\"gpy-l-thumb-0\" data-stop=\"0\" title=\"Drag the Low threshold\"><\/div>\n        <div class=\"gpy-legend-thumb\" id=\"gpy-l-thumb-1\" data-stop=\"1\" title=\"Drag the Low-mid threshold\"><\/div>\n        <div class=\"gpy-legend-thumb\" id=\"gpy-l-thumb-2\" data-stop=\"2\" title=\"Drag the Mid threshold\"><\/div>\n        <div class=\"gpy-legend-thumb\" id=\"gpy-l-thumb-3\" data-stop=\"3\" title=\"Drag the High-mid threshold\"><\/div>\n        <div class=\"gpy-legend-thumb\" id=\"gpy-l-thumb-4\" data-stop=\"4\" title=\"Drag the High threshold\"><\/div>\n      <\/div>\n      <div class=\"gpy-legend-stops\" id=\"gpy-legend-stops\"><\/div>\n      <button class=\"gpy-legend-reset\" id=\"gpy-l-reset\" title=\"Reset all thresholds to auto-detected values\">\u21ba Auto<\/button>\n      <div class=\"gpy-leg-stats\" id=\"gpy-leg-stats\" style=\"display:none\">\n        <div class=\"gpy-leg-stat\"><span class=\"lbl\">Avg<\/span><span class=\"val\" id=\"gpy-l-avg\">\u2014<\/span><\/div>\n        <div class=\"gpy-leg-stat\" id=\"gpy-l-area-row\" style=\"display:none\"><span class=\"lbl\">Coverage<\/span><span class=\"val\" id=\"gpy-l-area\">\u2014<\/span><\/div>\n        <div class=\"gpy-leg-stat\" id=\"gpy-l-tot-row\" style=\"display:none\"><span class=\"lbl\">Total<\/span><span class=\"val\" id=\"gpy-l-tot\">\u2014<\/span><\/div>\n      <\/div>\n      <div class=\"gpy-leg-row\"><span class=\"gpy-sw grey\"><\/span><span>Low<\/span><\/div>\n      <div class=\"gpy-leg-row\"><span class=\"gpy-sw violet\"><\/span><span>High outlier<\/span><\/div>\n      <div class=\"gpy-leg-out\">\n        <div class=\"gpy-leg-out-hd\">\n          <span class=\"lbl\" title=\"Sigma cutoff \u2014 tighter cutoff flags more points as outliers\">Outliers<\/span>\n          <div class=\"gpy-seg\" id=\"gpy-sig\" aria-label=\"\u03c3 sensitivity for the high cutoff\">\n            <button data-k=\"1\">1\u03c3<\/button>\n            <button data-k=\"2\">2\u03c3<\/button>\n            <button data-k=\"3\" class=\"on\">3\u03c3<\/button>\n          <\/div>\n        <\/div>\n        <div class=\"gpy-leg-counts\" title=\"Polygons flagged on each side\">\n          <span class=\"gpy-mini mg\" id=\"gpy-loc\">\u2014<\/span>\n          <span class=\"gpy-mini mv\" id=\"gpy-hic\">\u2014<\/span>\n        <\/div>\n        <span hidden id=\"gpy-lo\">\u2014<\/span><span hidden id=\"gpy-lo-u\"><\/span>\n        <span hidden id=\"gpy-hi\">\u2014<\/span><span hidden id=\"gpy-hi-u\"><\/span>\n        <input type=\"range\" hidden id=\"gpy-lo-r\" min=\"0\" max=\"2000\" step=\"50\" value=\"500\">\n        <input type=\"range\" hidden id=\"gpy-hi-r\" min=\"0\" max=\"2000\" step=\"50\" value=\"0\">\n      <\/div>\n    <\/div>\n\n    <aside class=\"gpy-floating-cta\" id=\"gpy-floating-cta\">\n      <div class=\"gpy-floating-cta-h\">Smarter zones in GeoPard<\/div>\n      <ul>\n        <li>More accurate zoning algorithms<\/li>\n        <li>Formula-based prescriptions<\/li>\n        <li>AI assistant \u2014 knows what you know<\/li>\n        <li>Reads binary monitor files<\/li>\n        <li>2-way sync: JD Ops, CNH FieldOps, AGCO PTx + API<\/li>\n        <li>Rates + product + ROI<\/li>\n        <li>Automated product distribution<\/li>\n      <\/ul>\n      <a class=\"gpy-floating-cta-btn\" href=\"https:\/\/app.geopard.tech\/signup?utm_source=field-data-explorer&amp;utm_medium=wp-embed&amp;utm_campaign=floating-cta\" target=\"_blank\" rel=\"noopener\">\n        Start free trial<span class=\"arr\">\u2192<\/span>\n      <\/a>\n    <\/aside>\n\n    <div class=\"gpy-overlay\" id=\"gpy-overlay\">\n      <div class=\"gpy-spinner\" id=\"gpy-spinner\"><\/div>\n      <h3 id=\"gpy-overlay-h\">Loading\u2026<\/h3>\n      <p id=\"gpy-overlay-p\">Parsing your file.<\/p>\n    <\/div>\n    <div class=\"gpy-toast\" id=\"gpy-toast\"><\/div>\n\n    <div class=\"gpy-pb\" id=\"gpy-pb\" role=\"region\" aria-label=\"Playback controls\">\n      <button class=\"gpy-pb-btn\" id=\"gpy-pb-play\" title=\"Play (Space)\" aria-label=\"Play\">\u25b6<\/button>\n      <button class=\"gpy-pb-btn\" id=\"gpy-pb-pause\" title=\"Pause\" aria-label=\"Pause\" disabled>\u23f8<\/button>\n      <div class=\"gpy-pb-track\" id=\"gpy-pb-track\" title=\"Scrub through the operation\">\n        <div class=\"gpy-pb-fill\" id=\"gpy-pb-fill\"><\/div>\n        <div class=\"gpy-pb-thumb\" id=\"gpy-pb-thumb\"><\/div>\n      <\/div>\n      <div class=\"gpy-pb-stats\" id=\"gpy-pb-stats\">\u2014<\/div>\n      <div class=\"gpy-seg gpy-pb-seg\" id=\"gpy-pb-speed\" role=\"group\" aria-label=\"Playback speed\">\n        <button data-s=\"1\">1\u00d7<\/button>\n        <button data-s=\"5\">5\u00d7<\/button>\n        <button data-s=\"20\" class=\"on\">20\u00d7<\/button>\n        <button data-s=\"100\">100\u00d7<\/button>\n        <button data-s=\"500\">500\u00d7<\/button>\n        <button data-s=\"2000\">2000\u00d7<\/button>\n      <\/div>\n      <label class=\"gpy-pb-price-grp\" id=\"gpy-pb-price-lbl\" title=\"Price per unit of the selected attribute. For yield data, enter your revenue per unit. For as-applied data, enter your product cost per unit.\">\n        <span class=\"gpy-pb-price-sym\">$<\/span>\n        <input type=\"number\" id=\"gpy-pb-price\" step=\"0.01\" min=\"0\" max=\"100000\" inputmode=\"decimal\" aria-label=\"Price per unit\">\n        <span class=\"gpy-pb-price-unit\" id=\"gpy-pb-price-unit\">\/unit<\/span>\n      <\/label>\n      <!-- Mobile-only collapse toggle. Hidden on desktop. Collapsed = compact\n           row with just play \/ pause \/ scrubber; tap the chevron to reveal\n           speed buttons + stats + price input. Default state on mobile is\n           collapsed so the playback bar starts at ~50 px tall, not ~250 px. -->\n      <button class=\"gpy-pb-collapse\" id=\"gpy-pb-collapse\" type=\"button\" title=\"Show \/ hide playback details\" aria-label=\"Show or hide playback details\" aria-expanded=\"false\">\u25be<\/button>\n    <\/div>\n  <\/main>\n<\/div>\n\n<div class=\"gpy-modal\" id=\"gpy-upload-modal\">\n  <div class=\"gpy-modal-card\">\n    <button class=\"gpy-modal-close\" id=\"gpy-modal-x\" title=\"Close\">\u00d7<\/button>\n    <h3>Upload field data<\/h3>\n    <p class=\"gpy-modal-sub\">Yield, as-applied, soil samples, boundaries \u2014 drag in or pick from your computer.<\/p>\n\n    <div class=\"gpy-dropzone\" id=\"gpy-dropzone\" tabindex=\"0\" role=\"button\" aria-label=\"Drop files here or click to choose\">\n      <svg viewBox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.8\" stroke-linecap=\"round\" stroke-linejoin=\"round\" class=\"gpy-dropzone-icon\" aria-hidden=\"true\">\n        <path d=\"M21 15v4a2 2 0 0 1-2 2H5a2 2 0 0 1-2-2v-4\"\/>\n        <polyline points=\"17 8 12 3 7 8\"\/>\n        <line x1=\"12\" y1=\"3\" x2=\"12\" y2=\"15\"\/>\n      <\/svg>\n      <div class=\"gpy-dropzone-title\">Drop files here<\/div>\n      <span class=\"gpy-btn-primary gpy-dropzone-btn\" aria-hidden=\"true\">Upload your file<\/span>\n      <div class=\"gpy-dz-info\" tabindex=\"0\" role=\"note\" aria-label=\"Supported file types: GeoJSON, Shapefile zip, CSV or TSV, Excel xlsx and xls, ISOXML, whole folder, multiple files at once\">\n        <span class=\"gpy-dz-i\" aria-hidden=\"true\">i<\/span><span>Which file types?<\/span>\n        <div class=\"gpy-dz-tip\" role=\"tooltip\">\n          <strong>Supported file types<\/strong><br>\n          GeoJSON <code>.json<\/code> \/ <code>.geojson<\/code> \u00b7 Shapefile <code>.zip<\/code> \u00b7 CSV \/ TSV <code>.csv<\/code> \/ <code>.tsv<\/code> \u00b7 Excel <code>.xlsx<\/code> \/ <code>.xls<\/code> \u00b7 KML \/ KMZ <code>.kml<\/code> \/ <code>.kmz<\/code> \u00b7 ISO-XML <code>.xml<\/code> \u00b7 whole folder \u00b7 multiple files at once\n        <\/div>\n      <\/div>\n    <\/div>\n\n    <div class=\"gpy-modal-note\">Files stay in your browser \u2014 nothing is uploaded. <strong>EPSG:4326<\/strong> shapefiles only (other CRS open in the full GeoPard app).<\/div>\n\n    <div class=\"gpy-modal-divider\"><\/div>\n\n    <div class=\"gpy-modal-cta\">\n      <h4 id=\"gpy-modal-cta-title\" style=\"font-size:10px;text-transform:uppercase;letter-spacing:.12em;font-weight:700;font-family:'SF Mono',ui-monospace,Menlo,monospace;margin:0 0 6px 0\">More formats?<\/h4>\n      <p id=\"gpy-modal-cta-body\">GeoPard imports <strong>ISOXML<\/strong>, <strong>John Deere Ops Center<\/strong>, <strong>CNH<\/strong>, <strong>AGCO<\/strong>, raw monitor exports, and projected shapefiles (any CRS). Auto-cleans yield, generates Rx files, runs zoning and correlation.<\/p>\n      <a class=\"gpy-modal-btn primary\" href=\"https:\/\/app.geopard.tech\/signup?utm_source=yield-explorer&amp;utm_medium=wp-embed&amp;utm_campaign=upload-modal\" target=\"_blank\" rel=\"noopener\" style=\"margin-top:0\">Open GeoPard \u2192<\/a>\n    <\/div>\n  <\/div>\n<\/div>\n\n<script type=\"application\/json\" id=\"gpy-soilscan-data\" nowprocket data-no-optimize=\"1\" data-no-defer=\"1\" 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5,3.3,3.6,3.9,2.9,3.9,3.7,2.4,3.6,3.9,3.4,2.2,3.1,4.1,2.2,4.0,2.9,2.2,3.0,3.9,2.9,3.9,3.1,3.6,3.3,3.8,3.9,3.5,3.5,4.1,3.8,3.4,3.4,4.3,3.3,4.1,4.1,4.5,3.1,4.1,3.1,4.4,4.3,4.1,3.1,4.4,3.2,3.6,4.3,3.3,3.5,4.1,3.9,2.9,4.1,2.7,4.1,4.3,4.4,2.5,4.2,2.5,3.5,4.3,3.4,3.4,2.6,2.8,4.3,3.1,3.7,4.4,3.9,3.4,4.5,4.0,4.1,4.7,4.3,4.3,4.6,4.5,4.6,4.5,4.8,4.4,4.4,3.9,4.6,4.2,4.2,3.6,3.9,3.6,4.2,3.7,4.2,3.6,3.7,3.8,3.7,4.1,4.1,4.0,4.1,3.7,4.1,3.8,3.8,3.8,4.0,3.6,3.9,3.5,3.2,3.3,3.1,3.7,2.8,3.9,2.3,3.9,2.9,2.2,3.1,3.9,2.2,3.7,3.2,3.4,2.5,3.6,3.6,3.1,3.6,4.2,3.6,4.3,3.6,3.4,3.9,3.2,4.5,4.2,4.3,3.1,4.0,3.0,3.8,4.0,3.5,3.1,3.1,4.6,2.8,3.3,4.5,3.7,2.7,4.5,2.6,3.9,4.2,3.8,2.6,4.1,2.9,3.7,4.2,3.5,3.1,4.1,3.3,3.7,3.5,3.8,4.1,3.9,4.2,4.1,4.5,4.2,4.2,4.6,4.3,4.2,4.2,4.9,4.3,5.1,4.1,4.4,4.0,4.8,3.7,4.4,3.9,4.5,4.3,4.3,3.9,4.2,4.0,4.1,4.1,4.0,3.9,4.3,3.2,4.4,3.9,3.2,3.8,3.9,4.0,3.3,4.0,3.6,3.5,3.4,3.9,3.7,3.9,3.3,3.9,3.1,3.8,3.8,3.6,3.1,3.6,3.3,3.7,3.3,3.8,3.7,3.0,3.9,4.2,3.8,2.5,3.6,4.3,2.2,4.4,3.6,3.6,2.2,3.6,4.4,2.3,4.0,3.4,2.8,3.3,3.7,3.2,3.3,3.2,3.1,3.8,2.9,3.3,4.2,3.6,2.7,4.1,2.6,4.0,4.0,4.3,2.9,3.9,3.1,4.6,3.8,4.6,3.2,3.7,4.1,4.5,4.2,3.6,4.1,4.2,4.3,3.7,4.6,4.0,3.9,4.0,4.2,3.9,4.7,4.5,4.5,5.0,4.2,4.0,5.2,4.0,3.9,3.9,4.0,5.2,4.0,3.7,4.8,3.9,4.1,4.6,4.1,4.0,4.2,4.1,3.8,2.2,3.6,4.1,2.2,4.1,3.6,2.3,3.4,4.1,4.0,2.8,3.4,3.2,3.2,3.2,3.4,3.7,3.5,3.3,3.9,3.3,3.5,3.9,3.4,3.3,3.9,3.5,3.6,3.5,3.8,3.8,3.6,3.6,3.5,4.0,4.1,3.6,4.3,3.2,3.6,2.9,4.3,3.6,4.3,2.6,3.6,2.2,4.0,3.5,3.8,2.9,3.4,2.7,3.5,3.7,3.3,3.0,3.8,3.1,3.2,5.0,3.8,5.2,3.2,3.5,3.9,3.8,5.1,4.0,4.8,4.1,4.0,4.5,4.5,4.0,4.2,4.4,3.9,4.5,4.2,3.9,4.3,4.2,3.8,3.9,4.6,3.7,4.9,3.9,3.6,3.7,4.8,3.6,4.6,3.6,3.8,3.7,4.2,4.0,4.0,3.9,4.0,4.3,4.1,3.9,4.3,4.7,4.2,3.9,3.6,3.3,4.2,3.6,4.1,3.3,3.5,3.0,4.0,3.4,3.9,2.8,3.3,2.6,3.8,3.1,3.8,2.3,3.2,2.2,3.6,3.4,3.5,2.2,3.5,2.2,3.4,3.5,3.3,2.4,3.5,2.9,3.3,3.2,3.6,3.7,3.4,4.0,3.5,4.1,4.2,4.0,4.4,4.2,4.1,4.0,4.3,3.7,3.8,4.3,3.6,3.7,3.5,3.6,3.6,3.6,3.5,3.5,3.2,3.8,3.0,3.4,4.1,3.4,4.3,3.4,3.6,4.6,3.6,3.8,4.9,3.9,4.9,3.9,4.9,3.9,4.6,3.9,3.1,4.5,3.8,3.2,4.2,3.3,3.6,4.3,3.6,3.3,4.5,3.5,3.4,4.5,4.5,4.3,3.9,4.6,4.1,4.0,4.6,3.8,4.2,4.3,3.9,4.0,3.9,4.0,3.7,4.0,2.4,3.7,3.0,4.1,3.6,4.1,3.4,3.5,3.8,4.3,3.4,4.3,4.0,3.3,4.2,4.3,3.2,4.3,4.1,4.0,3.9,3.1,3.7,4.0,2.9,4.0,3.5,2.7,3.3,3.9,2.6,3.6,3.2,2.8,3.5,2.5,3.9,2.9,2.3,3.2,4.2,2.2,4.3,3.4,2.2,3.6,4.3,2.2,4.3,3.3,3.8,3.2,4.4,4.0,4.2,3.4,3.9,3.5,3.9,3.9,3.7,3.8,3.7,3.9,3.7,3.6,3.6,4.0,3.5,3.8,3.3,3.6,3.2,3.5,3.3,3.2,3.6,2.9,3.8,3.1,3.9,3.1,4.1,3.3,4.4,3.4,3.6,4.5,4.6,4.6,4.5,4.1,4.3,4.2,4.2,4.3,4.2,4.4,4.2,4.3,4.2,4.3,4.3,4.2,4.3,4.1,4.3,4.0,4.1,3.9,3.8,3.9,3.7,3.4,3.8,3.2,3.8,3.8,4.0,3.2,3.9,3.2,4.2,3.8,4.1,3.1,3.6,2.9,3.6,3.4,3.4,3.2,2.8,4.4,2.7,3.1,4.1,2.7,2.8,2.6,3.8,2.5,2.6,3.6,2.8,2.3,3.7,2.2,3.1,3.6,3.3,2.2,3.5,2.2,3.5,3.5,3.5,2.7,3.8,3.3,4.1,3.1,3.4,3.3,4.2,3.4,4.3,3.5,3.9,3.3,4.0,4.4,3.3,4.5,3.8,3.4,3.1,3.5,3.7,3.4,3.0,3.8,3.4,3.1,3.6,2.8,3.5,4.0,3.5,3.7,2.7,2.9,4.0,3.9,3.0,3.6,3.2,4.0,3.5,4.3,3.4,3.6,3.7,4.2,3.9,4.3,3.9,4.1,4.0,4.1,4.1,4.3,3.9,4.0,4.4,3.8,3.9,4.0,3.8,3.5,4.1,3.4,3.2,3.9,4.2,4.0,4.1,4.3,2.6,4.4,2.4,4.0,3.8,4.4,3.8,2.2,4.3,2.3,3.8,4.1,3.9,2.5,2.8,2.5,3.0,4.0,2.8,4.1,3.2,3.0,3.4,4.0,3.3,3.7,3.7,3.4,3.7,3.1,3.7,2.7,3.5,3.9,3.4,2.7,3.2,4.2,3.1,2.7,2.8,4.3,2.8,2.8,4.4,2.5,2.7,4.6,3.0,3.6,4.4,3.5,3.1,4.2,3.3,3.5,3.9,3.5,3.5,3.6,3.8,3.4,3.6,3.3,3.2,3.9,3.7,4.0,3.2,3.5,3.4,3.9,3.6,3.7,3.6,3.8,3.5,3.6,3.8,3.4,3.1,3.3,3.9,3.3,3.0,4.0,3.3,3.3,4.0,3.0,2.8,3.3,3.7,3.4,2.8,3.7,3.6,3.5,3.6,3.7,3.8,3.6,4.1,3.8,3.7,3.9,4.2,3.6,4.3,4.1,3.6,4.3,4.4,3.4,3.9,4.3,3.3,3.9,4.0,4.0,3.2,4.1,3.5,3.1,2.4,2.8,4.2,2.4,4.2,2.8,2.6,2.8,4.2,2.7,4.1,2.9,4.0,2.8,4.0,2.9,3.0,3.0,3.8,3.3,3.1,2.9,2.7,3.5,3.7,3.3,3.5,3.5,3.8,3.5,3.4,3.4,4.1,3.3,4.3,3.2,3.2,3.0,4.4,2.9,4.6,4.5,3.1,2.7,3.3,4.3,2.5,4.1,3.4,2.6,3.3,3.7,2.8,3.5,3.4,3.5,3.4,3.6,3.6,3.8,3.2,3.7,3.1,2.9,3.6,3.9,3.6,3.1,3.9,3.3,3.5,3.6,3.7,3.8,3.4,3.7,3.9,3.8,3.6,3.7,4.1,3.4,4.3,3.7,3.2,3.6,4.3,3.2,4.4,3.6,3.3,3.6,3.6,3.4,3.4,3.3,3.7,3.5,3.7,3.1,3.4,3.0,3.7,3.7,3.4,3.9,2.9,3.5,3.2,3.9,3.7,3.9,3.5,3.7,3.9,2.8,3.9,4.1,3.9,2.7,4.3,2.7,3.8,4.4,3.7,2.7,4.1,2.7,3.2,3.7,3.4,2.9,3.2,3.3,3.6,3.1,4.0,4.3,3.4,2.9,3.4,4.5,3.0,4.6,3.4,3.0,3.3,3.2,4.5,2.9,4.4,2.9,3.1,2.7,4.2,3.4,3.9,2.6,3.3,2.8,3.6,3.0,3.7,2.9,3.5,3.7,3.9,3.6,3.7,3.5,3.7,3.7,3.8,3.2,3.7,3.0,3.6,3.7,3.6,2.9,3.0,3.7,3.2,3.7,3.7,3.7,3.3,3.6,3.5,3.6,3.5,3.6,3.5,3.4,3.5,3.6,3.3,3.6,3.4,3.4,3.2,3.3,3.4,3.2,3.3,3.4,3.4,3.6,3.0,2.9,3.5,2.7,3.7,3.5,3.9,2.9,3.5,3.2,4.0,3.9,4.1,3.4,3.8,3.6,4.2,3.9,4.3,4.4,3.5,4.0,3.2,3.0,3.1,4.1,3.3,4.3,3.2,2.8,2.8,4.2,2.8,3.2,4.0,3.2,2.8,3.5,3.2,3.4,3.3,3.5,3.7,3.3,3.2,3.3,3.9,3.1,3.9,3.4,3.1,3.3,3.9,3.0,3.0,3.2,3.3,3.0,3.2,3.6,3.3,2.9,3.7,2.8,3.5,2.8,3.8,3.9,3.9,3.6,4.2,3.8,3.6,3.6,4.4,4.5,3.6,4.5,3.4,3.7,3.0,4.4,3.6,4.5,2.8,3.6,2.8,4.2,3.7,3.8,3.1,3.7,3.2,3.9,4.0,3.6,3.8,3.6,3.6,3.7,3.9,3.7,3.3,3.6,3.5,3.3,3.6,3.4,3.4,3.5,3.7,3.4,3.6,3.5,3.4,3.7,3.6,3.6,3.5,3.6,3.3,3.8,3.4,3.7,3.9,3.6,3.7,4.0,3.9,3.5,4.0,3.2,4.0,4.0,4.2,3.0,4.0,2.9,4.3,4.1,4.4,2.6,4.2,2.7,2.7,4.2,2.8,2.8,3.1,3.2,4.1,3.8,2.6,3.9,2.7,3.9,3.6,3.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3,3.9,3.7,3.9,4.3,3.6,4.2,3.4,3.6,3.3,3.8,4.2,3.9,3.1,3.8,3.7,3.1,3.7,3.6,3.2,3.5,3.9,2.9,3.8,3.4,2.9,3.2,3.8,3.1,3.8,3.4,3.3,3.1,3.9,4.0,3.1,3.7,3.3,4.0,3.9,3.3,4.1,4.0,4.0,3.5,4.2,3.4,4.0,4.4,3.7,3.4,4.0,3.5,3.5,3.9,3.4,4.1,3.5,4.0,3.5,3.3,3.6,3.9,4.1,4.1,3.6,4.0,3.7,4.1,4.0,4.1,3.8,4.1,4.1,4.0,4.2,4.0,4.1,4.1,4.1,4.2,4.0,3.8,4.3,3.7,4.2,4.5,4.3,3.6,4.7,3.7,4.1,4.8,4.2,3.6,4.9,3.8,4.0,4.8,3.8,3.8,4.2,4.0,3.7,4.0,3.4,3.7,3.6,3.7,3.6,3.4,3.8,3.3,3.6,4.1,3.7,3.2,3.1,3.2,3.9,3.3,4.0,3.3,3.5,3.5,4.2,3.7,4.2,3.6,3.8,3.6,4.2,3.9,4.1,3.7,4.1,3.5,3.9,3.7,4.1,3.6,3.3,4.0,3.3,3.3,3.4,3.9,3.2,3.1,4.0,3.1,4.0,3.6,3.1,3.2,4.1,3.4,4.3,3.3,3.3,4.3,3.5,3.3,4.3,3.3,3.8,3.2,4.0,4.0,4.1,3.3,4.2,3.2,4.3,4.3,3.3,4.3,3.3,4.1,3.3,4.3,3.3,4.2,3.3,4.2,3.4,3.5,4.2,3.8,4.0,4.0,3.9,4.1,3.6,4.0,3.5,4.1,3.6,4.2,4.3,3.6,4.0,4.2,3.8,4.1,3.9,3.8,4.4,4.2,4.0,4.3,4.4,3.7,4.3,4.3,4.6,3.8,4.8,4.2,5.0,3.7,5.0,4.2,3.8,4.1,4.7,3.9,4.6,3.8,4.0,3.5,4.2,4.0,4.1,3.5,4.1,3.4,4.3,4.1,3.1,3.2,4.3,3.2,3.3,4.0,3.3,3.2,3.4,3.8,3.5,3.7,3.8,3.5,4.0,3.6,3.2,3.7,4.2,3.1,4.3,3.9,2.9,3.5,4.3,4.1,4.1,4.0,3.3,4.0,3.4,4.0,3.7,4.0,3.3,3.5,3.2,4.2,3.4,4.3,3.2,3.3,3.2,4.3,3.3,4.2,3.4,3.3,3.6,4.1,3.2,4.2,3.7,3.2,3.9,4.3,3.2,4.3,4.1,3.1,4.3,4.2,2.9,4.2,3.1,4.3,4.4,3.2,4.3,4.2,4.4,3.6,4.4,3.6,3.9,3.7,4.4,5.0,4.3,3.8,4.8,3.9,4.4,4.2,4.6,4.0,4.0,4.5,3.8,4.0,4.0,4.5,4.2,3.6,4.6,3.7,4.2,4.5,4.2,3.2,4.4,3.3,4.2,4.4,4.3,3.5,4.5,3.6,4.7,4.4,4.9,3.7,4.1,3.9,5.1,5.2,4.0,3.7,4.0,5.0,3.6,3.3,4.1,3.4,4.3,3.1,3.3,3.1,4.1,3.2,4.1,2.8,4.0,3.0,4.0,4.1,4.1,3.2,3.4,4.1,3.4,3.9,4.0,3.6,3.7,3.9,3.9,3.4,3.6,4.2,4.4,4.3,3.2,4.5,4.5,4.6,3.3,4.5,4.3,3.2,4.0,4.3,3.4,4.3,3.9,3.3,3.9,4.1,3.4,4.0,2.9,3.5,3.0,3.7,3.6,3.4,3.3,3.7,3.8,3.4,3.9,3.5,4.0,4.1,4.1,4.2,3.3,4.3,3.3,4.3,4.1,4.2,3.3,3.9,3.1,4.4,2.8,3.7,4.7,4.4,3.8,4.5,4.9,3.7,5.2,4.5,3.6,4.5,5.3,3.7,5.1,4.5,3.9,4.4,5.2,4.4,4.0,3.9,5.2,3.9,5.0,3.7,3.9,3.5,4.8,4.1,4.9,3.3,4.2,3.3,4.9,4.2,4.5,4.5,3.2,4.3,3.3,3.4,4.4,4.4,4.6,3.5,4.0,3.7,4.5,4.0,4.2,3.9,3.9,4.2,4.7,3.6,4.4,4.2,3.4,4.4,4.5,4.1,3.3,4.0,4.3,3.0,4.1,3.8,3.0,3.8,3.5,3.0,3.6,3.9,3.9,3.1,3.9,3.7,3.2,3.8,3.8,3.4,3.6,4.1,3.4,4.1,4.4,3.2,3.8,3.1,4.7,4.0,4.7,3.1,4.3,3.2,4.6,3.4,4.6,4.5,3.5,4.7,4.5,3.6,4.7,3.6,4.3,4.7,3.5,4.6,3.2,4.1,4.6,2.8,3.8,4.5,3.7,2.8,4.3,2.9,3.8,4.0,4.0,3.1,3.8,3.6,4.2,3.7,4.2,3.8,4.0,3.7,4.1,3.6,4.2,3.6,4.2,4.5,4.5,3.8,5.0,3.9,4.7,4.6,3.8,4.8,5.1,4.7,3.9,4.5,5.3,4.4,5.1,4.4,4.6,4.4,5.2,4.6,5.3,4.5,4.5,4.2,4.0,5.2,4.3,5.1,3.8,4.1,3.7,5.1,4.0,5.1,3.4,3.8,3.3,4.7,3.6,3.4,3.3,3.5,3.3,3.8,3.3,4.0,4.3,3.3,3.1,3.5,3.5,4.6,3.0,4.8,3.8,3.0,4.1,4.5,3.1,4.3,3.1,3.2,3.0,3.4,3.0,4.1,4.5,3.9,3.1,3.3,4.4,3.5,3.7,4.2,3.7,3.7,4.1,3.7,3.6,4.0,3.7,3.7,4.1,3.9,3.6,3.9,3.5,4.1,3.9,4.2,3.3,3.6,4.0,4.5,3.1,4.7,4.1,2.9,5.6,4.7,4.7,3.0,4.6,5.5,2.9,5.3,3.5,3.3,3.6,5.3,3.6,5.3,3.7,3.8,3.7,5.1,3.9,5.0,3.7,5.3,3.9,4.8,5.2,4.6,4.0,5.1,4.1,4.5,5.2,4.2,4.4,4.8,4.5,3.9,3.7,4.6,3.7,4.6,4.3,4.7,3.5,4.3,3.3,4.9,4.3,5.0,3.4,4.1,3.4,5.0,3.8,5.1,3.6,3.7,4.0,5.3,3.7,3.1,4.4,3.6,4.7,3.0,3.5,3.0,4.8,3.4,4.7,4.4,3.1,3.3,3.4,3.6,4.2,3.5,4.0,3.9,4.2,3.5,4.3,3.8,3.6,3.7,4.7,3.5,3.6,4.8,3.4,4.6,3.4,3.2,3.2,4.3,3.0,4.2,4.3,3.0,4.4,4.0,3.0,3.8,4.5,3.1,4.6,4.6,3.6,3.1,3.4,4.5,3.7,4.5,3.1,3.3,3.8,3.6,4.4,3.8,4.3,3.7,3.8,3.9,4.2,4.3,3.9,4.3,3.9,4.1,5.6,4.2,4.3,3.9,5.6,4.0,5.6,3.7,3.8,3.3,5.5,3.8,5.4,3.0,5.3,3.5,5.1,4.6,3.3,4.8,4.7,4.8,3.4,4.6,3.4,4.6,4.9,3.5,5.1,3.5,3.6,3.5,5.1,3.7,5.2,3.5,5.2,3.9,5.1,3.6,4.1,3.5,3.4,4.8,4.2,4.7,3.3,4.4,3.3,4.4,4.2,4.4,4.0,3.5,4.5,3.8,3.9,3.9,3.6,4.3,3.8,4.6,3.5,3.6,4.4,4.8,4.8,3.6,4.6,4.2,3.5,4.1,4.4,3.2,4.1,3.9,3.2,3.8,3.8,3.2,3.8,3.6,3.1,3.5,3.9,3.2,3.9,3.6,3.6,3.5,3.7,4.0,3.9,4.1,3.4,4.2,3.2,4.1,4.4,4.2,3.1,4.7,3.0,4.3,4.4,4.8,4.2,3.1,4.6,3.2,4.3,4.3,4.4,3.6,5.6,4.3,5.4,4.4,4.0,4.2,4.5,5.3,3.7,4.8,4.4,3.4,3.8,4.5,3.2,4.6,3.9,3.2,4.1,4.5,3.3,4.3,4.0,4.2,3.5,4.2,3.9,3.7,3.7,4.2,3.7,4.4,3.4,3.9,3.2,4.6,5.6,4.6,3.2,5.6,3.3,4.7,5.0,5.6,3.5,5.0,5.6,3.6,5.6,4.5,5.0,5.1,4.5,5.0,4.3,4.6,4.0,4.8,4.7,4.7,3.7,4.8,3.3,4.1,4.5,4.4,3.2,4.2,3.2,3.3,4.6,4.0,4.7,3.4,3.8,3.6,4.6,4.4,3.7,3.6,3.6,3.5,3.5,4.3,4.2,3.6,4.1,3.4,3.3,3.6,4.0,3.4,3.9,3.8,3.4,4.1,3.7,3.2,3.6,3.4,3.3,3.3,3.7,3.5,3.9,3.1,3.8,3.2,3.7,4.3,3.5,3.4,5.6,4.3,5.6,3.5,4.1,3.7,3.8,5.6,4.4,5.6,3.9,4.5,4.0,5.6,4.4,5.6,4.1,4.3,3.9,5.5,4.2,5.3,4.0,4.9,4.0,4.0,3.7,4.0,4.5,4.5,3.5,4.4,3.6,4.3,4.1,4.1,3.5,3.3,4.2,3.5,4.1,3.2,3.7,3.2,3.9,3.7,3.5,3.2,3.7,3.4,4.8,3.6,5.0,4.9,3.7,3.6,3.8,4.9,3.7,3.9,4.8,3.8,4.7,4.2,4.0,4.2,4.5,4.3,4.1,4.1,4.4,4.2,3.7,4.6,3.4,4.3,4.4,4.7,4.6,3.1,4.6,2.9,4.8,4.4,4.9,3.1,3.3,4.1,3.5,3.5,3.8,3.5,3.6,3.7,3.6,3.4,3.5,3.4,3.7,3.5,3.7,3.6,3.7,3.4,4.0,3.7,3.8,3.9,3.8,4.1,4.4,3.8,4.5,3.6,3.7,3.6,4.5,3.8,4.3,3.5,3.9,3.4,4.2,4.0,4.2,3.3,4.1,3.4,4.2,4.1,4.1,3.5,3.5,4.1,4.0,3.9,4.2,3.7,3.7,3.9,4.3,4.0,3.6,4.3,3.7,4.2,4.2,4.2,3.8,4.2,3.8,4.2,4.2,4.2,5.6,5.6,4.0,5.6,4.2,3.8,4.0,5.6,4.2,5.6,3.7,4.3,3.5,5.6,4.3,5.5,3.2,4.4,3.1,5.2,4.6,4.8,3.1,3.2,4.4,4.7,4.4,3.5,4.6,3.7,3.0,4.8,3.0,3.8,4.9,4.1,3.2,4.9,3.4,4.2,4.9,4.2,3.6,4.9,3.7,4.2,4.7,3.9,3.7,3.8,4.4,3.8,3.6,4.0,3.3,3.8,3.5,3.9,3.3,3.3,3.3,3.5,4.2,4.1,4.2,3.6,4.0,3.5,4.4,4.5,4.1,4.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5,3.4,3.7,3.2,3.6,3.1,3.9,3.8,3.2,3.9,3.4,3.9,3.9,4.0,4.1,3.7,4.0,3.9,4.2,4.0,3.6,3.2,3.8,3.2,3.2,3.6,3.8,3.5,3.4,3.8,3.5,3.4,4.1,3.3,3.5,4.3,3.2,4.2,3.0,3.6,3.9,3.7,2.2,3.6,2.2,3.5,2.3,3.5,3.5,3.3,2.8,3.3,3.5,3.2,3.1,3.5,3.3,3.3,3.5,3.2,3.1,3.2,3.1,3.2,3.6,3.3,3.2,3.4,3.7,3.6,3.3,3.7,3.6,3.7,3.6,3.5,3.4,3.7,3.3,3.5,3.7,3.6,3.3,3.4,3.6,3.5,3.8,3.9,3.8,3.5,4.1,3.4,3.6,4.1,3.5,3.4,3.3,4.2,3.2,3.1,4.1,3.1,3.3,3.3,4.3,3.5,3.3,4.2,3.3,3.7,4.1,3.7,3.6,4.0,3.7,3.8,3.7,3.6,3.8,3.5,4.0,3.8,4.0,3.6,3.5,3.6,3.8,3.6,3.2,3.9,3.8,4.2,3.1,3.8,2.2,4.2,4.1,2.2,3.7,2.6,3.8,3.6,3.8,2.8,3.4,3.1,3.6,3.7,3.4,3.6,3.5,3.2,3.5,3.7,3.2,3.6,3.4,3.5,3.3,3.5,3.3,3.4,3.3,3.6,3.4,3.7,3.3,3.4,3.4,3.6,3.5,3.7,3.8,3.6,3.4,3.8,3.8,3.4,3.7,4.0,4.2,3.3,4.4,3.5,3.3,3.4,4.3,3.4,4.4,3.3,3.1,3.3,4.4,3.1,4.4,3.1,3.2,3.2,4.3,3.5,3.1,3.6,4.2,3.2,4.1,3.4,3.8,3.4,3.7,3.3,3.6,3.2,3.5,3.8,3.2,3.2,3.2,3.9,3.3,3.2,3.7,3.4,3.6,3.6,3.3,3.5,3.8,3.4,3.8,3.5,3.5,3.6,3.7,3.8,3.8,4.0,3.9,3.4,4.0,3.4,3.7,3.2,3.6,3.3,3.2,3.6,3.2,3.4,3.3,3.6,3.2,3.1,3.7,3.3,3.4,3.8,3.5,3.4,3.7,3.3,3.7,3.6,3.6,3.4,3.3,3.7,3.3,3.8,3.7,4.0,3.1,3.7,2.2,4.0,3.9,3.8,2.2,4.6,3.9,2.5,4.0,2.7,4.6,4.1,4.5,3.0,4.5,3.2,4.4,3.3,4.2,4.5,4.0,3.2,4.6,3.1,3.8,4.5,3.7,3.0,3.0,3.1,3.4,3.1,3.1,3.1,3.4,3.0,3.4,3.6,3.5,2.9,3.1,3.7,3.7,3.7,3.2,3.7,3.3,3.5,3.5,3.5,3.2,3.4,3.1,3.5,3.1,3.1,3.4,3.1,3.8,3.5,3.5,3.0,3.5,3.0,3.4,3.7,3.3,3.2,3.6,3.3,3.2,3.7,3.3,3.3,3.7,3.3,3.5,3.5,3.8,3.7,3.3,3.9,3.2,4.0,3.9,3.2,2.5,2.7,3.7,3.1,3.8,3.3,4.0,3.6,4.0,3.6,4.2,3.6,4.2,3.7,3.4,4.5,3.5,4.5,3.7,4.1,4.5,4.1,3.5,4.7,3.5,3.8,4.8,3.7,3.7,4.7,3.8,3.8,3.6,3.5,4.7,3.2,3.7,4.6,3.6,3.1,4.5,2.9,3.6,4.2,3.3,2.8,3.9,2.9,3.1,3.8,3.0,3.0,3.3,3.1,3.1,3.1,3.4,3.0,3.1,3.2,3.1,3.1,3.0,3.3,3.1,3.1,3.3,3.1,3.1,3.4,3.4,3.0,3.5,3.0,3.8,3.7,4.0,4.0,3.3,4.0,3.6,3.9,4.0,3.8,3.6,3.8,3.6,3.7,3.7,3.7,3.6,3.6,3.4,2.9,3.4,3.4,3.1,3.0,3.2,3.2,3.4,3.1,3.1,3.2,3.5,3.2,3.5,3.3,3.2,3.3,3.6,4.8,3.5,3.2,4.8,3.2,3.2,3.5,3.6,4.7,3.7,3.3,4.6,2.9,4.0,4.0,4.5,4.2,2.9,4.3,2.9,3.0,4.3,4.1,4.4,3.1,3.9,3.2,4.4,3.8,4.6,3.3,3.7,3.1,4.7,3.8,3.1,2.9,3.0,3.8,3.3,2.9,3.9,2.9,3.0,3.6,4.0,3.7,3.0,4.0,3.1,3.6,3.9,3.6,3.0,3.8,3.0,3.5,3.4,3.6,3.4,3.0,4.0,3.0,3.9,3.2,3.0,3.2,3.7,3.2,3.5,3.2,3.2,3.2,3.4,3.2,3.1,3.4,3.2,3.6,2.9,3.2,2.9,4.0,3.2,4.1,2.9,3.4,3.4,4.2,3.4,4.3,4.3,3.8,3.4,3.9,4.4,3.4,4.6,3.9,3.8,3.3,3.7,4.9,3.5,4.9,3.7,3.7,3.5,4.8,3.7,4.7,3.9,4.5,3.3,4.3,4.0,4.1,4.2,4.2,3.0,4.3,4.0,3.2,3.9,4.0,3.1,3.9,4.0,2.9,3.9,3.6,2.9,3.2,3.9,3.0,4.0,3.0,3.0,2.9,3.2,3.3,3.2,3.5,3.0,3.3,3.5,3.4,3.8,3.7,4.0,3.5,3.7,3.3,4.1,3.7,4.1,3.2,3.6,3.1,4.0,3.6,3.9,3.0,3.6,3.0,3.7,3.6,3.2,3.5,2.8,3.8,3.3,3.8,2.7,3.2,2.5,3.6,3.4,3.4,2.8,3.4,3.2,3.1,3.7,2.8,3.7,3.9,3.7,2.9,4.1,3.0,3.9,4.0,4.2,4.0,3.1,4.2,3.1,3.2,4.1,4.5,4.3,3.2,4.7,3.3,4.4,4.9,4.3,3.3,4.8,3.2,4.1,4.7,3.9,3.3,3.6,4.5,3.5,4.4,3.4,4.3,3.2,4.0,3.1,4.0,3.1,4.0,3.2,3.7,3.2,3.6,2.9,2.8,3.3,2.8,3.4,2.8,3.4,3.1,3.5,3.4,3.7,3.6,3.9,3.8,4.0,3.8,4.1,3.8,4.2,3.8,4.2,3.9,4.0,2.8,3.5,3.2,3.0,3.4,2.8,3.6,2.4,3.7,2.5,3.8,3.2,3.6,3.5,3.3,3.3,3.2,2.7,3.3,2.7,3.7,2.8,3.9,2.9,4.1,3.0,3.1,4.3,3.1,4.3,3.2,4.4,3.1,4.7,4.0,4.7,3.9,4.6,3.9,4.4,3.9,4.3,3.9,4.4,4.0,3.2,4.2,3.1,4.3,4.3,4.1,4.3,3.1,3.4,3.6,3.5,4.2,3.6,3.9,3.6,3.4,3.5,3.5,3.1,3.2,3.5,3.1,4.0,3.2,3.5,3.0,3.6,3.8,3.0,3.7,2.7,3.4,3.6,2.7,3.6,3.4,2.6,3.4,3.5,2.4,2.6,2.6,2.8,3.7,2.9,3.8,3.1,3.2,3.3,3.9,3.5,4.1,3.5,3.8,3.7,4.2,3.9,4.3,4.3,3.6,3.5,4.1,3.4,3.8,4.0,3.5,2.8,3.2,2.6,3.1,3.4,2.7,2.5,3.7,2.6,2.8,3.9,3.8,4.0,3.8,3.0,4.0,3.0,3.8,4.3,4.0,3.2,4.3,3.6,4.2,4.3,4.2,3.2,4.4,3.0,2.8,4.2,4.2,4.6,4.0,2.8,4.4,2.5,3.6,4.4,3.3,2.4,4.2,2.4,3.4,4.2,3.6,2.4,4.3,2.7,3.7,4.3,3.6,3.0,3.2,3.6,4.2,3.7,3.7,4.0,3.9,3.7,2.7,3.4,4.1,2.8,4.2,3.4,2.9,3.4,4.1,3.1,3.9,3.4,3.3,3.7,4.1,3.4,4.5,4.4,3.8,3.8,3.5,4.1,4.3,3.4,4.3,4.4,4.2,4.4,3.1,4.3,4.3,2.7,4.2,4.1,2.5,3.7,4.0,2.5,4.1,3.4,2.6,3.1,4.2,2.7,4.3,2.7,2.8,2.6,4.2,3.5,3.9,3.7,4.0,3.8,3.7,3.7,4.1,4.0,4.0,3.7,2.4,3.7,4.0,2.3,4.0,3.4,2.3,3.6,3.9,2.3,3.7,3.8,2.3,3.9,3.4,2.5,3.4,4.0,2.8,4.2,3.6,3.0,3.5,3.5,4.2,3.4,4.3,4.1,3.5,3.7,3.6,3.9,4.0,3.7,3.2,4.1,2.9,3.4,4.1,3.0,2.5,3.8,2.9,3.2,2.8,2.8,3.6,2.7,3.4,3.4,2.6,3.3,2.8,3.5,3.2,3.2,4.4,3.9,4.2,2.9,2.6,4.0,2.5,4.0,3.9,3.9,2.4,3.6,2.5,4.0,4.2,3.4,4.2,2.7,3.4,3.9,4.1,3.4,3.9,4.0,3.2,4.0,4.3,3.7,3.2,3.7,3.6,4.7,3.3,4.4,3.5,3.2,3.5,4.3,2.3,2.9,2.7,3.6,3.7,2.5,3.7,2.9,2.2,3.1,3.8,2.2,4.1,3.3,2.2,3.8,4.1,2.3,4.1,4.0,4.1,2.3,3.9,3.9,3.0,3.8,3.6,2.6,3.4,3.7,2.5,3.6,3.4,2.5,3.2,3.3,2.4,3.1,3.3,2.5,3.6,3.8,3.0,4.0,2.8,2.6,4.0,4.2,4.1,2.5,4.3,2.6,3.9,4.5,4.0,2.9,4.7,3.2,3.9,4.5,3.6,3.2,4.6,3.2,3.6,4.2,3.6,3.3,4.1,3.1,3.6,4.0,3.5,2.9,2.9,3.3,3.8,3.2,3.0,3.9,2.9,3.4,3.8,3.5,2.4,4.1,2.2,3.6,3.9,4.0,2.2,3.6,2.2,2.4,4.0,3.5,3.8,2.4,3.4,2.4,3.6,3.4,3.3,3.6,2.6,3.3,2.8,3.5,3.5,3.1,3.3,3.6,3.2,3.4,3.5,4.0,2.4,3.0,4.2,2.7,4.3,4.2,4.4,2.5,4.2,2.6,4.4,4.1,4.5,2.7,2.9,3.9,2.9,4.6,3.7,4.8,3.1,3.6,3.0,4.5,3.4,4.3,2.7,3.4,2.6,2.5,4.2,4.0,3.5,3.8,2.5,3.3,2.7,3.6,3.0,3.7,2.8,2.9,2.4,3.7,3.0,3.5,2.2,3.4,2.2,3.4,3.6,3.7,3.5,2.3,4.0,2.5,3.5,3.8,3.4,2.5,2.5,3.6,2.6,3.3,3.4,3.4,2.9,3.2,3.1,3.6,2.9,3.9,3.4,2.7,3.6,4.1,2.5,4.3,3.7,3.4,4.0,4.2,3.4,4.1,3.8,3.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5,2.8,2.8,2.6,2.9,2.8,2.7,2.6,3.1,2.7,3.3,2.7,2.8,2.8,2.7,2.8,2.9,2.6,2.6,2.5,2.9,2.2,2.4,2.9,2.1,2.0,2.7,2.0,2.0,2.6,2.1,2.0,2.7,1.9,2.0,2.0,2.6,2.2,3.2,3.4,3.2,2.2,3.3,2.3,3.1,3.1,3.1,2.4,2.9,2.4,2.9,3.1,2.7,2.3,3.1,2.4,2.6,3.0,2.6,2.7,3.0,2.9,2.6,2.9,2.6,2.6,3.1,3.1,2.8,3.6,2.9,2.8,3.1,3.3,2.8,3.1,3.2,2.9,3.2,2.9,3.3,2.7,3.3,3.6,3.4,2.6,3.6,2.4,2.5,2.9,3.6,2.9,2.6,2.8,2.8,2.8,2.7,2.9,2.9,2.9,3.0,2.9,2.9,2.8,2.9,3.0,2.9,2.7,3.0,2.9,2.9,2.6,2.9,2.9,2.7,2.9,3.0,2.7,2.9,2.0,2.0,2.7,2.1,2.6,2.9,2.7,2.1,3.2,2.1,2.6,3.0,2.8,2.4,2.9,2.4,2.8,2.9,2.8,2.4,2.4,2.6,2.6,2.9,2.4,2.8,2.6,2.2,2.7,2.5,2.8,2.4,2.8,2.9,3.0,2.3,3.0,2.2,3.0,3.2,2.9,2.1,2.1,2.7,3.3,2.8,2.3,3.2,2.3,2.8,3.2,3.1,2.3,3.1,2.4,3.2,2.9,3.2,2.3,2.7,2.2,3.0,2.7,2.7,2.9,2.4,2.8,2.6,3.1,2.7,3.1,3.3,2.5,3.5,3.5,3.0,2.4,3.0,3.6,2.6,3.4,2.8,2.7,2.7,3.2,2.7,2.9,2.7,2.8,2.7,2.7,2.9,3.0,2.7,2.5,2.8,2.5,2.7,2.8,2.8,2.4,2.8,2.4,2.9,2.9,2.9,2.6,2.9,2.6,3.1,2.9,3.1,2.7,2.6,3.0,2.5,3.0,3.1,2.9,3.0,3.0,2.9,2.9,2.8,3.0,2.6,2.7,3.1,2.6,2.7,2.9,2.9,2.5,2.6,2.5,2.9,2.6,3.0,2.3,2.9,2.2,3.2,3.0,2.2,2.4,2.8,2.4,2.3,2.9,2.4,2.5,2.4,3.0,2.4,2.6,2.4,3.0,2.5,2.7,2.8,2.9,2.6,2.8,2.7,3.0,2.7,3.1,2.8,2.5,2.8,3.1,2.5,3.1,3.1,2.4,2.3,2.2,2.9,2.3,2.8,2.2,2.3,2.3,2.8,2.3,3.2,2.4,2.4,2.7,3.0,2.3,2.8,2.8,2.4,3.0,2.9,2.7,2.4,2.6,2.7,2.7,2.3,2.8,3.0,2.2,3.2,3.0,2.3,3.0,3.3,2.6,3.4,3.0,2.7,3.1,3.4,2.6,3.1,2.9,2.7,3.3,3.0,2.7,2.7,3.2,2.7,2.8,2.4,2.8,2.4,2.6,2.7,2.6,2.4,2.3,2.9,2.5,2.6,3.1,2.7,2.8,3.3,2.7,2.9,3.0,3.2,3.2,2.8,2.3,3.1,3.3,2.4,3.4,3.2,2.5,3.2,3.3,2.6,3.2,3.2,2.7,3.1,3.1,3.0,2.8,2.9,2.8,2.7,2.7,2.7,2.8,2.5,2.4,3.0,2.4,2.6,2.4,3.0,2.3,2.6,3.0,2.5,2.5,2.3,2.9,2.5,2.9,2.9,2.3,2.9,2.3,2.3,2.8,2.7,2.8,2.3,2.6,2.3,3.5,2.4,3.4,2.5,3.0,2.6,3.1,2.8,3.0,2.2,2.8,3.1,2.9,2.1,3.2,2.0,2.8,3.1,2.9,2.0,3.0,2.3,3.0,2.9,2.5,2.5,2.8,2.7,2.4,2.7,2.4,2.9,2.8,2.8,2.4,2.8,2.9,2.6,2.5,3.1,2.5,2.7,3.2,2.9,2.4,2.4,3.2,2.1,3.2,3.1,3.3,2.1,2.9,2.3,3.4,2.8,3.4,2.5,3.4,2.4,3.1,3.4,2.8,2.4,3.2,2.5,2.7,3.0,2.6,2.6,2.7,2.9,2.8,2.5,2.6,2.8,3.0,2.6,3.2,2.7,2.9,2.7,3.4,3.1,3.6,2.6,2.3,3.1,2.3,3.6,3.3,3.0,2.3,3.4,2.8,2.7,3.1,2.6,2.4,3.0,2.5,2.6,3.0,2.5,2.5,2.8,2.4,2.5,2.5,2.9,2.7,2.5,2.8,2.5,2.8,2.5,2.7,2.4,2.8,2.7,2.9,2.3,2.9,2.2,2.9,2.8,2.6,2.1,2.8,2.2,2.8,2.7,2.9,2.4,3.7,2.6,2.9,3.6,3.1,3.0,3.4,3.0,3.1,3.0,3.2,3.4,2.8,2.6,2.5,2.5,2.4,3.3,2.1,3.1,2.4,2.0,2.4,3.1,2.0,3.0,2.5,2.1,2.5,2.5,2.8,2.7,2.4,2.8,2.4,2.2,2.2,2.9,2.3,3.0,2.1,2.3,2.2,2.3,2.8,2.9,2.4,3.2,2.2,2.5,3.2,3.6,2.5,3.7,2.9,2.6,3.0,3.6,2.9,3.6,2.9,3.2,2.9,3.6,2.9,3.4,2.8,3.3,3.5,3.1,2.8,3.2,2.8,2.7,2.5,2.9,2.7,2.5,2.8,2.4,2.8,2.3,2.7,2.3,2.8,2.7,3.0,2.2,2.7,2.2,3.3,2.1,2.5,2.6,2.3,2.3,2.1,2.4,2.7,2.2,2.8,2.0,2.3,2.9,2.5,2.9,2.6,2.8,2.6,2.8,2.6,2.7,2.7,2.7,2.7,2.7,2.6,2.8,2.0,3.6,2.1,2.7,3.6,2.7,2.7,2.4,3.6,2.7,3.2,3.1,2.5,2.3,2.6,2.7,3.1,2.1,3.2,2.7,2.0,2.7,3.2,2.3,3.4,3.5,2.8,2.3,2.9,3.5,2.2,3.3,2.8,2.7,3.3,2.2,3.1,2.6,2.2,2.4,3.0,2.3,2.7,2.5,2.2,2.5,2.8,2.2,2.7,2.4,2.4,2.4,2.6,2.4,2.7,2.5,2.5,2.5,2.8,2.7,3.0,2.3,3.2,2.3,3.2,2.5,3.3,2.9,3.5,3.5,3.1,3.6,2.9,3.0,2.7,3.7,3.0,3.5,3.3,2.8,2.2,2.8,2.8,2.8,2.2,2.6,2.8,2.1,2.7,2.4,2.2,2.5,2.7,2.3,2.8,2.4,2.3,3.1,2.8,2.4,2.6,2.9,2.5,2.7,2.5,2.4,2.7,2.2,2.4,2.8,2.2,2.2,2.8,2.1,2.1,2.7,2.8,2.3,2.3,2.8,2.4,2.8,2.4,2.0,2.9,1.9,2.4,2.9,2.5,2.5,2.0,1.9,3.1,2.3,2.5,3.3,3.5,3.4,3.2,2.6,2.9,3.3,3.4,2.5,3.1,2.5,3.5,2.8,3.5,2.4,2.8,2.4,3.7,2.7,3.6,2.4,2.6,2.3,3.4,2.6,3.4,2.3,2.8,2.3,3.0,2.9,3.0,2.2,2.8,2.2,3.2,2.7,2.9,2.1,2.6,2.2,2.2,2.8,2.7,2.6,2.6,2.3,2.6,2.3,2.7,2.4,2.8,2.7,2.4,3.1,3.0,2.4,3.2,2.7,2.7,2.4,3.3,2.6,3.3,2.3,2.4,2.3,3.6,2.2,3.5,2.3,2.5,2.2,2.6,3.3,2.2,3.0,2.9,2.6,2.1,2.6,2.9,2.1,3.0,2.6,2.6,2.2,2.6,3.2,2.2,3.3,2.6,2.2,2.5,3.3,2.3,3.1,2.6,2.4,2.9,2.8,2.6,2.5,2.9,2.7,2.5,2.4,2.6,2.2,2.5,2.7,3.3,2.2,2.3,3.2,3.7,3.0,2.4,3.7,2.3,2.9,3.7,2.5,2.3,3.4,2.4,2.3,3.4,1.9,2.7,3.3,2.7,1.9,3.3,1.9,2.3,2.2,3.0,2.4,2.3,2.9,2.3,2.8,2.8,3.2,2.3,2.6,2.5,2.5,3.4,2.7,3.6,2.4,2.7,2.5,2.2,2.8,2.2,2.6,2.8,2.4,2.3,2.8,2.3,2.3,2.7,2.3,2.7,3.2,2.8,2.8,2.3,3.3,2.2,3.2,3.2,3.1,2.2,3.1,2.3,2.9,2.3,2.9,2.4,2.8,2.7,2.6,2.7,2.5,3.0,2.7,2.8,2.3,2.9,2.9,2.3,2.8,2.2,2.6,3.0,2.2,3.1,2.3,2.4,2.6,2.3,2.4,2.5,2.4,2.4,2.6,2.4,2.1,2.6,2.1,2.6,2.5,2.8,2.1,2.1,2.3,2.1,2.8,2.2,3.1,2.1,2.3,2.1,3.3,2.2,3.4,3.4,2.6,2.3,3.0,3.2,2.4,2.9,3.4,2.4,3.6,2.7,3.3,2.4,3.8,3.2,3.8,2.2,3.0,2.2,3.7,2.7,3.5,2.8,2.5,2.8,3.4,2.4,3.3,2.8,2.2,2.7,3.2,2.0,3.0,2.7,2.7,3.0,1.9,2.9,2.4,2.1,2.2,2.8,2.3,2.8,2.1,2.3,2.1,2.8,2.3,2.8,2.3,2.3,2.4,2.8,2.2,3.0,2.3,2.2,2.4,2.6,3.1,2.2,3.1,2.6,2.2,2.4,3.0,2.2,2.9,2.6,2.8,2.4,2.7,2.5,2.5,2.3,2.2,2.6,2.6,2.4,2.2,2.9,2.2,2.4,3.1,2.4,2.4,3.1,2.8,2.3,2.9,2.2,3.0,2.7,3.0,2.8,2.3,2.5,2.8,2.1,2.6,2.7,2.6,2.1,2.7,2.0,2.7,2.4,2.6,2.0,2.2,2.0,2.5,2.1,2.1,2.1,2.2,2.1,2.2,2.3,2.3,2.1,2.3,2.2,2.6,2.3,2.9,2.4,2.4,2.6,3.3,3.5,3.4,3.7,2.8,3.3,3.0,3.7,3.0,3.7,3.3,2.7,3.5,3.4,3.5,2.4,3.4,3.2,2.4,3.0,3.3,2.4,3.2,3.1,2.2,2.9,2.1,3.0,2.9,3.1,2.6,3.1,2.9,2.9,2.5,2.9,2.8,2.3,2.8,2.7,2.3,2.7,2.8,2.3,2.9,2.7,2.3,2.5,2.8,2.2,2.8,2.3,2.2,2.2,2.9,2.2,3.0,2.1,2.2,2.2,2.9,2.9,2.4,2.8,2.3,2.4,2.2,2.3,2.7,2.5,2.7,2.5,2.6,2.7,2.4,2.6,2.9,2.5,2.4,3.0,2.5,2.4,3.0,2.8,2.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5,2.5,3.2,2.6,2.9,2.7,2.6,2.9,2.7,2.8,2.6,2.6,2.9,2.5,3.2,2.6,2.4,2.8,3.4,2.6,3.4,3.0,2.6,3.1,3.1,3.4,3.4,2.6,3.5,3.0,2.9,3.1,3.3,2.9,3.7,3.0,3.0,2.9,3.8,3.0,2.9,2.9,2.8,3.8,2.9,3.9,2.9,3.7,2.9,3.6,2.7,2.7,3.0,2.8,3.3,3.0,3.1,2.9,2.9,2.8,3.0,3.0,2.9,2.6,3.2,2.7,3.0,3.3,3.1,2.7,3.4,2.7,3.3,3.4,3.1,2.6,3.4,2.5,3.0,3.6,2.9,2.9,2.7,2.9,2.7,2.6,2.7,3.0,2.6,2.6,2.8,2.5,2.7,2.7,2.9,2.4,2.5,2.3,3.0,2.2,3.1,2.3,2.1,2.4,3.1,2.1,3.1,2.4,2.1,2.5,3.0,2.3,2.9,2.8,2.3,3.3,2.8,2.4,2.8,2.8,3.2,3.3,2.4,3.1,2.4,3.0,2.5,2.5,3.2,3.1,3.3,2.5,3.4,2.7,3.5,3.4,2.7,3.5,3.4,2.7,3.4,3.4,2.7,3.3,3.0,2.9,2.8,3.0,2.8,2.9,2.7,2.9,3.2,2.8,2.7,3.2,2.6,3.2,2.6,2.8,3.3,2.9,3.3,3.4,3.4,3.0,3.3,3.0,3.6,3.1,3.7,2.9,3.0,2.9,3.9,3.0,3.9,3.0,2.9,2.9,4.1,2.8,4.0,2.9,3.2,2.8,3.8,3.5,3.1,3.3,2.9,3.1,3.0,3.1,3.1,3.0,3.0,2.4,2.8,2.5,3.0,2.6,3.1,2.4,2.6,2.5,3.3,2.6,3.4,2.7,2.6,2.8,2.6,2.3,2.6,3.1,2.5,3.1,2.6,2.6,2.5,2.9,2.7,2.7,2.4,2.7,2.4,2.3,2.6,2.7,2.6,2.2,2.7,2.2,2.7,2.5,2.9,2.2,3.1,2.3,2.5,3.0,3.3,3.1,2.6,3.4,2.8,3.1,3.4,3.0,2.6,3.3,2.7,3.0,3.4,3.0,2.7,3.3,2.6,3.0,3.1,3.5,3.3,2.7,3.1,2.8,3.1,3.0,3.1,2.7,2.6,3.0,3.1,3.0,3.0,2.6,3.2,2.7,3.1,3.3,3.0,3.0,3.2,3.3,3.0,3.3,2.9,3.2,3.0,3.5,2.9,2.8,3.0,3.7,2.7,3.7,3.0,3.1,3.1,2.8,3.0,3.0,2.8,3.1,3.0,3.0,3.0,3.3,3.1,3.3,2.7,2.7,3.2,2.9,3.3,3.5,3.2,2.9,3.7,2.8,3.1,3.9,3.0,2.7,3.9,2.6,3.0,4.0,2.7,2.5,2.5,4.0,2.5,2.5,2.4,3.9,2.4,2.7,3.7,3.1,2.3,3.4,2.4,3.2,3.2,3.1,2.5,3.0,2.3,2.3,2.9,3.1,2.5,2.5,3.1,2.6,2.5,3.1,3.0,2.8,3.2,2.7,3.1,3.2,3.1,2.7,3.1,3.4,3.0,2.7,2.6,3.4,2.5,2.9,3.3,2.7,2.5,3.3,2.5,2.8,3.4,2.7,2.4,3.3,2.4,2.7,3.2,2.7,2.5,3.1,2.7,2.9,3.0,2.7,2.9,3.0,3.0,2.5,3.0,2.5,2.4,3.1,3.3,3.5,2.7,3.2,3.9,3.8,3.1,3.9,3.8,3.8,3.2,3.7,3.6,3.2,3.5,3.5,3.3,3.0,3.1,3.2,2.8,3.2,3.1,2.7,3.0,3.3,2.7,3.3,3.1,2.8,3.2,3.3,2.9,3.2,3.2,3.0,3.3,3.2,3.1,3.3,3.2,3.2,3.5,3.2,2.4,3.8,2.3,3.2,3.8,2.8,2.6,2.3,3.8,2.4,3.2,2.3,3.1,2.5,2.3,2.6,3.1,2.3,2.7,2.7,2.4,2.9,2.6,2.6,2.6,3.0,2.9,2.9,2.8,2.4,2.4,3.0,2.6,2.7,3.2,2.6,2.8,3.3,2.8,2.5,3.3,2.5,2.8,3.2,2.9,2.6,3.3,2.9,2.8,3.4,2.6,3.2,2.6,3.4,2.5,3.3,3.4,3.2,2.7,3.3,2.5,3.0,3.3,2.9,3.0,2.4,3.5,2.4,2.9,3.4,2.9,2.4,3.4,2.7,2.9,3.3,2.9,2.8,3.1,3.4,2.8,3.5,2.7,2.8,2.8,2.8,2.8,2.9,3.4,3.5,3.6,3.9,3.9,3.7,3.7,3.3,3.4,3.5,3.5,3.2,3.6,3.4,3.5,3.3,3.4,3.0,3.6,3.4,3.6,2.7,3.2,2.4,3.5,3.0,3.4,2.3,3.0,2.3,3.3,2.8,3.1,3.1,2.3,2.4,2.8,2.6,2.8,2.7,3.0,2.9,2.9,2.9,3.1,3.0,3.0,3.0,3.0,2.5,3.1,3.0,2.6,2.9,3.1,2.6,2.9,2.7,2.7,3.5,2.8,3.0,2.7,3.5,3.1,3.4,2.7,3.1,2.4,2.3,3.3,2.8,3.3,2.1,2.8,2.2,3.3,3.4,2.8,3.2,2.4,2.7,2.7,2.9,3.0,2.4,3.0,3.1,2.4,3.3,2.8,2.6,2.8,3.3,2.7,3.3,2.8,2.9,2.9,3.4,3.0,3.4,2.8,2.7,2.8,3.7,3.0,2.9,3.4,3.1,2.9,3.5,2.9,3.0,3.6,2.9,2.7,3.7,2.6,2.9,3.6,3.0,2.4,3.7,2.4,3.2,3.7,3.3,2.3,3.6,2.3,3.3,3.6,3.3,2.4,3.6,2.7,3.3,3.7,3.3,3.1,3.5,3.5,3.7,3.3,3.5,3.3,3.6,3.4,3.7,3.2,3.3,3.1,3.0,2.9,3.3,2.8,2.9,2.4,3.1,2.8,2.5,2.8,3.0,2.8,3.0,2.9,3.0,3.0,2.9,3.0,2.7,3.2,2.9,3.0,2.7,2.9,2.7,2.7,2.8,2.5,2.7,2.6,2.8,2.2,2.3,2.2,3.0,3.0,2.2,2.8,2.3,2.4,2.0,2.5,2.9,2.1,2.9,2.7,2.4,2.8,2.7,2.6,2.9,2.9,3.1,2.4,3.3,3.1,3.4,3.3,3.4,2.7,3.4,2.8,3.6,2.9,3.4,3.7,3.4,2.9,3.0,3.5,3.3,3.3,3.0,3.4,2.9,3.3,3.6,3.3,2.6,3.7,2.4,3.4,3.8,3.3,2.3,3.7,2.3,3.2,3.8,3.1,2.3,3.1,3.8,2.2,3.7,2.4,2.9,3.8,2.9,2.8,3.8,3.2,3.0,3.7,2.8,3.4,3.3,3.1,3.6,3.0,3.4,3.5,3.3,2.9,2.6,2.7,3.2,2.8,3.1,2.7,3.0,2.6,3.1,3.0,3.1,2.6,3.0,2.7,3.1,3.0,3.3,2.8,3.0,2.9,3.3,2.8,3.2,2.7,2.7,2.6,3.2,2.8,3.3,3.2,2.4,2.4,2.6,3.1,2.4,2.5,2.5,3.1,2.7,3.0,2.5,2.8,2.6,2.9,2.9,2.7,2.8,2.9,3.0,2.4,3.0,2.2,2.4,3.1,3.1,3.2,3.4,2.7,3.2,2.9,3.3,3.1,3.3,2.9,2.9,3.1,2.9,3.3,2.9,3.3,2.9,2.7,2.7,3.3,2.8,3.3,2.4,2.8,2.2,3.2,2.8,3.3,2.1,2.9,2.0,3.3,3.1,3.1,2.2,3.1,2.2,3.2,2.9,3.8,2.2,2.6,2.7,3.7,3.6,2.9,2.3,3.2,3.5,2.2,3.5,3.3,2.2,3.4,3.5,3.3,3.5,3.6,3.1,3.2,3.3,3.0,3.3,3.4,3.0,3.6,3.4,3.7,3.0,3.7,3.3,3.1,3.3,3.9,3.1,3.9,3.3,3.3,2.8,3.2,3.9,2.7,3.9,3.2,2.5,3.3,2.4,2.4,2.5,2.6,2.4,2.7,2.6,2.6,2.5,2.6,2.8,2.7,3.0,2.7,2.6,2.9,3.0,2.6,2.8,3.0,2.5,3.0,2.6,2.4,2.3,2.4,3.0,2.2,3.0,2.8,2.6,2.0,2.8,2.8,2.0,2.8,2.9,2.3,2.9,2.6,2.5,2.5,2.9,2.8,2.9,2.5,2.9,3.0,2.7,3.1,2.5,2.9,2.9,3.2,2.6,2.9,3.0,3.3,3.1,2.4,3.2,2.2,3.2,3.1,3.3,2.1,3.1,2.2,3.3,3.1,2.6,3.0,2.9,3.0,3.1,3.8,3.3,3.1,3.9,2.8,2.8,3.4,3.9,3.5,2.8,3.8,2.8,3.1,3.7,3.2,2.9,3.3,3.7,3.5,3.0,3.6,3.1,3.6,3.5,3.4,3.4,3.3,3.3,3.2,3.5,3.4,3.4,3.5,3.4,3.3,3.1,3.4,2.4,3.2,3.5,3.0,2.4,3.5,2.5,3.1,3.4,3.2,2.5,2.8,2.5,3.2,2.7,3.0,2.6,2.5,2.6,2.9,2.4,2.5,2.6,2.4,2.5,2.6,2.3,2.6,2.7,2.3,2.8,2.8,2.9,2.9,2.9,2.9,2.9,2.8,2.9,2.8,2.8,2.6,2.5,2.9,2.5,2.9,2.3,2.5,2.0,2.7,2.6,2.8,1.9,2.7,2.1,2.9,2.9,2.8,2.7,2.3,2.6,2.8,2.8,2.8,3.0,2.7,2.5,3.0,3.1,3.1,3.2,3.3,2.4,3.1,2.8,3.1,3.0,2.9,3.0,2.7,3.2,3.1,2.5,3.2,3.4,2.4,3.5,3.4,3.3,2.3,3.7,2.6,3.8,3.8,3.0,2.8,2.9,3.6,2.9,3.0,2.8,3.6,3.2,3.5,2.9,3.4,3.6,3.4,3.5,3.4,3.5,2.9,3.4,3.3,3.1,3.2,3.4,2.3,3.3,3.3,2.2,3.4,3.5,2.1,3.5,3.4,2.2,3.5,3.5,2.2,3.5,3.2,2.6,2.6,2.3,2.6,3.2,2.5,3.4,2.7,2.6,2.5,3.3,2.7,3.3,2.4,2.8,2.4,3.0,2.7,2.7,2.5,2.7,2.6,2.5,2.9,2.8,2.7,2.9,2.8,2.8,2.9,2.8,2.8,2.9,2.9,2.8,2.8,2.8,2.7,2.8,2.8,3.2,2.6,2.8,3.0,2.8,2.5,2.7,2.2,3.1,2.6,2.9,2.0,2.5,2.0,2.9,2.5,3.0,2.1,2.4,2.4,3.1,2.3,3.1,2.6,2.1,2.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 var SAMPLE_META = { name:'2017 soybean yield', col:'Yld_Mass_D', unit:'kg\/ha', cols:[\n    { key:'Yld_Mass_D', unit:'kg\/ha' },\n    { key:'Elevation_', unit:'m' },\n    { key:'Speed_mph_', unit:'mph' },\n    { key:'Crop_Flw_M', unit:'kg\/s' }\n  ] };\n  var SAMPLE_APPLIED_RAW = 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 var SAMPLE_APPLIED_META = { name:'2024 N fertilizer application', col:'AppldRate', unit:'kg\/ha' };\n  \/\/ \u2500\u2500 grid display \u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\n  var showGrid = true;\n  \/\/ \u2500\u2500 theme \u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\n  try { var t = localStorage.getItem('gpy-theme'); if(t==='dark'||t==='light') root.setAttribute('data-theme', t); } catch(e){}\n  var themeColors = {};\n  function readThemeColors(){\n    var cs = getComputedStyle(root);\n    themeColors.canvasBg = cs.getPropertyValue('--canvas-bg').trim();\n    themeColors.grid = cs.getPropertyValue('--canvas-grid').trim();\n    themeColors.grey = cs.getPropertyValue('--grey').trim();\n    themeColors.violet = cs.getPropertyValue('--violet').trim();\n    themeColors.violetGlow = cs.getPropertyValue('--violet-glow').trim();\n  }\n  readThemeColors();\n  $('#gpy-theme').onclick = function(){\n    var cur = root.getAttribute('data-theme');\n    var next = cur==='dark' ? 'light' : 'dark';\n    root.setAttribute('data-theme', next);\n    try { localStorage.setItem('gpy-theme', next); } catch(e){}\n    readThemeColors();\n    draw();\n  };\n  \/\/ \u2500\u2500 state \u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\n  var canvas = $('#gpy-canvas'), ctx = canvas.getContext('2d');\n  var tip = $('#gpy-tip'), overlay = $('#gpy-overlay'), toast = $('#gpy-toast');\n  var fileInput = $('#gpy-input');\n  var features = [], numericCols = [], currentCol = null, currentUnit = '';\n  var mode = 'point'; \/\/ 'point' or 'polygon'\n  var values = [], coords = [], sorted = [], mean = 0, std = 0, median = 0;\n  var sigmaK = 3, loCutoff = 500, showOutliers = true;\n  \/\/ Master toggle for the playback simulation (trail + swath band + tractor sprite + control bar).\n  \/\/ Hardcoded OFF. The synthetic-path overlay (trail \/ sprite \/ swath \/ U-turn arcs) is hidden;\n  \/\/ playback reveals polygons in file order, matching the released live page. The path-rendering\n  \/\/ IIFE in draw() still gates on this flag so the entire overlay block returns early. Toggle UI\n  \/\/ and event handler removed \u2014 re-enable by flipping this to true and re-adding the gpy-path-t\n  \/\/ button + handler if the simulation needs to come back.\n  var showMachinePath = false;\n  var currentIsBoundary = false;\n  \/\/ Sibling metadata lookup: dirPath \u2192 parsed metadata json (Trimble-style {Product, DataAttributes, ...})\n  var metadataByDir = {};\n  \/\/ Playback state \u2014 replays polygon-mode operations as if traveling through the field over time.\n  \/\/ `order` maps playback index \u2192 feature index (sorted by timestamp if available, else nearest-neighbor from top-left).\n  \/\/ `cumM` is cumulative distance in real meters along the playback order (so distance-traveled stat is cheap to look up).\n  \/\/ Timer uses requestAnimationFrame (not setTimeout) so it stays smooth and respects the browser frame budget.\n  var playback = { active:false, idx:0, idxFloat:0, speed:20, raf:null, lastT:0, dieselLPerHa:10, opLabel:'operation', turnarounds:0, order:null, cumM:null, smoothedHeading:null, smoothedX:null, smoothedY:null, turnAct:false, turnFrac:0, turnEnd:0, turnDurMs:0, turnBezier:null };\n  \/\/ Ruler tool: user-drawn polyline measuring real-world distance across the map.\n  \/\/ `points` array holds waypoints in mercator coords (relative to wmCx\/wmCy).\n  \/\/ `hover` is the live mouse position for previewing the next segment before clicking.\n  var ruler = { active:false, points:[], hover:null };\n  \/\/ Imperial vs metric locale heuristic. Used by `distanceUnit` default below.\n  function isImperialLocale(){\n    try {\n      var lang = (navigator.language || '').toLowerCase();\n      if(lang === 'en-us' || lang === 'en-ca' || lang.indexOf('en-us-') === 0 || lang.indexOf('en-ca-') === 0) return true;\n    } catch(_){}\n    return false;\n  }\n  \/\/ Product price (revenue for yield data, product cost for as-applied data).\n  \/\/ Per unit of the active attribute. Persisted in localStorage so it sticks across sessions.\n  \/\/ 0 means \"not set\" \u2014 no $ figure rendered in the playback stats until the user enters a price.\n  var productPrice = (function(){\n    try {\n      var v = +localStorage.getItem('gpy-product-price');\n      if(isFinite(v) ? v >= 0 : false) return v;\n    } catch(_){}\n    return 0;\n  })();\n  \/\/ Distance \/ area unit system. Defaults to imperial in US\/CA, metric elsewhere.\n  var distanceUnit = (function(){\n    try {\n      var u = localStorage.getItem('gpy-distance-unit');\n      if(u === 'metric' || u === 'imperial') return u;\n    } catch(_){}\n    return isImperialLocale() ? 'imperial' : 'metric';\n  })();\n  \/\/ User-overridable high cutoff. Null = auto-compute. Set by slider or by \u03c3 buttons.\n  var hiCutoff = null;\n  var outClass = null, colorMin = 0, colorMax = 1;\n  \/\/ tArr[i] = inlier rank fraction in [0,1] for feature i. Used for quantile-based coloring\n  \/\/ (every inlier gets a distinct color along the gradient regardless of distribution shape \u2014 shows\n  \/\/ maximum variability even when most values are clustered tightly).\n  var tArr = null;\n  \/\/ Per-class threshold overrides \u2014 one slot per gradient stop (5). null entry = auto (linearly\n  \/\/ distributed between inlierMin and inlierMax). Setting any non-null switches colorFor() into\n  \/\/ VALUE-based interpolation between effStops so the user's exact breakpoints are honored.\n  var STOP_COLORS = [[193,18,31],[232,93,4],[249,199,79],[144,190,109],[45,106,79]];\n  var STOP_LABELS = ['Low','Low-mid','Mid','High-mid','High'];\n  var stopValueOverrides = [null, null, null, null, null];\n  var effStops = [0, 0.25, 0.5, 0.75, 1];  \/\/ computed each recompute()\n  \/\/ points\n  var mx = null, my = null, sxArr = null, syArr = null;\n  \/\/ polygons: per-feature {rings: [{mx,my}], cx, cy, minX, maxX, minY, maxY}\n  var polyData = null;\n  var wmCx = 0, wmCy = 0, latC = 0;\n  var mxMin, mxMax, myMin, myMax, fW, fH;\n  var W = 0, H = 0, DPR = window.devicePixelRatio || 1;\n  var view = { scale:1, tx:0, ty:0 };\n  var R = 6378137, DEG = Math.PI\/180;\n  function lngToWmX(lng){ return lng * DEG * R; }\n  function latToWmY(lat){ return Math.log(Math.tan((90+lat)*Math.PI\/360)) * R; }\n  \/\/ Polygon ring area in hectares from lon\/lat coords (equirectangular approx, fine for ag-scale fields)\n  function ringAreaHa(ring){\n    if(ring.length < 3) return 0;\n    var lat0 = 0;\n    for(var i=0;i<ring.length;i++) lat0 += ring[i][1];\n    lat0 \/= ring.length;\n    var cosLat = Math.cos(lat0 * Math.PI \/ 180);\n    var degMeters = Math.PI * R \/ 180;\n    var sl = 0;\n    for(var i=0;i<ring.length;i++){\n      var j = (i+1) % ring.length;\n      sl += ring[i][0] * ring[j][1] - ring[j][0] * ring[i][1];\n    }\n    return Math.abs(sl) * 0.5 * cosLat * degMeters * degMeters \/ 10000;\n  }\n  \/\/ Andrew's monotone-chain convex hull on [lon, lat] points. Returns the hull as a closed ring.\n  \/\/ Used to estimate \"field area\" for Point and Line datasets \u2014 there's no native area to multiply\n  \/\/ average \u00d7 area against otherwise, and bbox overestimates significantly for irregular fields.\n  function convexHull(points){\n    if(points.length < 3) return points.slice();\n    var pts = points.slice().sort(function(a,b){ return a[0]-b[0] || a[1]-b[1]; });\n    function cross(o, a, b){ return (a[0]-o[0])*(b[1]-o[1]) - (a[1]-o[1])*(b[0]-o[0]); }\n    var lower = [];\n    for(var i=0;i<pts.length;i++){\n      var p = pts[i];\n      while(lower.length >= 2 ? cross(lower[lower.length-2], lower[lower.length-1], p) <= 0 : false) lower.pop();\n      lower.push(p);\n    }\n    var upper = [];\n    for(var i2=pts.length-1; i2>=0; i2--){\n      var p2 = pts[i2];\n      while(upper.length >= 2 ? cross(upper[upper.length-2], upper[upper.length-1], p2) <= 0 : false) upper.pop();\n      upper.push(p2);\n    }\n    return lower.concat(upper.slice(1));\n  }\n  var fmt = function(x){\n    if(!isFinite(x)) return '\u2014';\n    var a = Math.abs(x);\n    if(a >= 100) return Math.round(x).toLocaleString('en-US');\n    if(a >= 10) return (Math.round(x*10)\/10).toLocaleString('en-US');\n    return (Math.round(x*100)\/100).toLocaleString('en-US');\n  };\n  function showToast(msg, kind){\n    toast.textContent = msg;\n    toast.classList.remove('is-ok'); toast.classList.remove('is-info');\n    if(kind === 'ok') toast.classList.add('is-ok');\n    else if(kind === 'info') toast.classList.add('is-info');\n    toast.classList.add('show');\n    setTimeout(function(){ toast.classList.remove('show'); }, 4000);\n  }\n  \/\/ Called when the user drops a proprietary monitor format (.agdata, .cn1, .jdl, ...). Opens the\n  \/\/ upload modal with a customized banner highlighting the GeoPard signup CTA \u2014 the actual answer,\n  \/\/ since these formats need vendor SDKs that the GeoPard backend already wraps.\n  function showProprietaryFormatModal(formatName){\n    hideOverlay();\n    var modal = $('#gpy-upload-modal');\n    var ctaTitle = $('#gpy-modal-cta-title');\n    var ctaBody  = $('#gpy-modal-cta-body');\n    if(ctaTitle) ctaTitle.textContent = formatName + ' \u2014 advanced parsing required';\n    if(ctaBody) ctaBody.innerHTML =\n      'This file type needs the vendor SDK to read. GeoPard handles it for you: drop the same file ' +\n      'after a free signup and it parses on the backend, with auto yield cleaning, Rx generation, ' +\n      'and zoning + correlation analysis on top.';\n    if(modal) modal.classList.add('show');\n  }\n  function showOverlay(title, body, spinner){\n    $('#gpy-overlay-h').textContent = title;\n    $('#gpy-overlay-p').textContent = body;\n    $('#gpy-spinner').style.display = spinner ? 'block' : 'none';\n    overlay.classList.add('show');\n  }\n  function hideOverlay(){ overlay.classList.remove('show'); overlay.classList.remove('drop'); }\n  \/\/ \u2500\u2500 file handling \u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\n  var shpjsPromise = null;\n  function loadShpjs(){\n    if(window.shp) return Promise.resolve();\n    if(shpjsPromise) return shpjsPromise;\n    shpjsPromise = new Promise(function(resolve, reject){\n      var s = document.createElement('script');\n      s.src = 'https:\/\/cdn.jsdelivr.net\/npm\/shpjs@4.0.4\/dist\/shp.min.js';\n      s.onload = function(){ resolve(); };\n      s.onerror = function(){ shpjsPromise = null; reject(new Error('Could not load shapefile parser')); };\n      document.head.appendChild(s);\n    });\n    return shpjsPromise;\n  }\n  \/\/ Lazy load shp-write for the Export button. Depends on JSZip (loaded\n  \/\/ separately below). See rule 4 \u2014 runtime exception for an on-demand\n  \/\/ user-triggered download flow.\n  var shpwritePromise = null;\n  function loadShpWrite(){\n    if(window.shpwrite) return Promise.resolve();\n    if(shpwritePromise) return shpwritePromise;\n    shpwritePromise = new Promise(function(resolve, reject){\n      var s = document.createElement('script');\n      s.src = 'https:\/\/cdn.jsdelivr.net\/npm\/@mapbox\/shp-write@0.4.3\/shpwrite.js';\n      s.onload = function(){ resolve(); };\n      s.onerror = function(){ shpwritePromise = null; reject(new Error('Could not load shapefile writer')); };\n      document.head.appendChild(s);\n    });\n    return shpwritePromise;\n  }\n  var jszipPromise = null;\n  function loadJSZip(){\n    if(window.JSZip) return Promise.resolve();\n    if(jszipPromise) return jszipPromise;\n    jszipPromise = new Promise(function(resolve, reject){\n      var s = document.createElement('script');\n      s.src = 'https:\/\/cdn.jsdelivr.net\/npm\/jszip@3.10.1\/dist\/jszip.min.js';\n      s.onload = function(){ resolve(); };\n      s.onerror = function(){ jszipPromise = null; reject(new Error('Could not load zip parser')); };\n      document.head.appendChild(s);\n    });\n    return jszipPromise;\n  }\n  \/\/ \u2500\u2500 Shapefile writer \u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\n  \/\/ Pure-JS shapefile output: builds .shp (geometry), .shx (record index),\n  \/\/ .dbf (attribute table), .prj (WGS84 WKT) as ArrayBuffers \/ strings.\n  \/\/ Supports Polygon (type 5) and Point (type 1). Attributes are character or\n  \/\/ numeric, field names auto-normalized to 10-char uppercase ASCII per DBF.\n  \/\/ Sanitize an attribute name to DBF spec: \u2264 10 chars, uppercase ASCII\n  \/\/ letters \/ digits \/ underscore, must start with a letter.\n  function sanitizeDbfFieldName(raw){\n    var s = (raw === null ? '' : raw === undefined ? '' : String(raw)).toUpperCase();\n    var out = '';\n    for(var i=0; (i<s.length ? out.length<10 : false); i++){\n      var c = s.charCodeAt(i);\n      var ok = (c >= 65 ? c <= 90 : false) ? true : ((c >= 48 ? c <= 57 : false) ? true : (c === 95));\n      if(ok) out += s.charAt(i);\n    }\n    if(out.length === 0) return 'FIELD';\n    var first = out.charCodeAt(0);\n    if(first >= 48 ? first <= 57 : false) out = 'F' + out.substring(0, 9);\n    return out;\n  }\n  \/\/ Build a single ASCII-only string from a JS value for DBF storage.\n  function dbfStringifyValue(v){\n    if(v === null ? true : v === undefined) return '';\n    if(typeof v === 'number'){\n      if(!isFinite(v)) return '';\n      return Number.isInteger(v) ? String(v) : v.toString();\n    }\n    return String(v);\n  }\n  \/\/ Format a value into a fixed-width DBF field (right-aligned for N, left-\n  \/\/ aligned for C, truncated to length).\n  function formatDbfField(val, type, length, decimal){\n    var s = dbfStringifyValue(val);\n    if(type === 'N'){\n      var n = Number(s);\n      if(!isFinite(n)){\n        var blank = '';\n        for(var i=0; i<length; i++) blank += ' ';\n        return blank;\n      }\n      var formatted;\n      if(decimal > 0){\n        formatted = n.toFixed(decimal);\n      } else {\n        formatted = String(Math.round(n));\n      }\n      if(formatted.length > length) formatted = formatted.substring(0, length);\n      while(formatted.length < length) formatted = ' ' + formatted;\n      return formatted;\n    }\n    \/\/ Character \u2014 truncate or pad with spaces (latin-1 only)\n    var ascii = '';\n    for(var ci=0; (ci<s.length ? ascii.length < length : false); ci++){\n      var cc = s.charCodeAt(ci);\n      ascii += cc < 256 ? s.charAt(ci) : '?';\n    }\n    while(ascii.length < length) ascii += ' ';\n    return ascii;\n  }\n  \/\/ Build SHP \/ SHX \/ DBF \/ PRJ buffers for a dataset.\n  \/\/   features: array of GeoJSON-style features (only Polygon\/MultiPolygon and\n  \/\/             Point are supported here)\n  \/\/   geomType: 'polygon' or 'point'\n  \/\/   attrSpecs: array of attribute specs { name, type ('N'|'C'), length,\n  \/\/              decimal (for N), get(feature) -> value }\n  function buildShapefile(features, geomType, attrSpecs){\n    var shapeTypeCode = geomType === 'point' ? 1 : 5;\n    \/\/ Pass 1: compute global bbox and per-record sizes.\n    var records = [];\n    var globalBbox = { xmin: Infinity, ymin: Infinity, xmax: -Infinity, ymax: -Infinity };\n    var hasGeom = new Array(features.length);\n    for(var fi=0; fi<features.length; fi++){\n      hasGeom[fi] = false;\n      var g = features[fi].geometry;\n      if(!g) continue;\n      if(geomType === 'point' ? g.type === 'Point' : false){\n        var xy = g.coordinates;\n        if(!xy ? true : xy.length < 2) continue;\n        var x = +xy[0], y = +xy[1];\n        if(!isFinite(x) ? true : !isFinite(y)) continue;\n        if(x < globalBbox.xmin) globalBbox.xmin = x;\n        if(x > globalBbox.xmax) globalBbox.xmax = x;\n        if(y < globalBbox.ymin) globalBbox.ymin = y;\n        if(y > globalBbox.ymax) globalBbox.ymax = y;\n        records.push({ type:'point', x:x, y:y, contentBytes:20 });\n        hasGeom[fi] = true;\n      } else if(geomType === 'polygon' ? (g.type === 'Polygon' ? true : g.type === 'MultiPolygon') : false){\n        var polys = g.type === 'Polygon' ? [g.coordinates] : g.coordinates;\n        var parts = [];\n        var points = [];\n        var localBbox = { xmin: Infinity, ymin: Infinity, xmax: -Infinity, ymax: -Infinity };\n        for(var pi=0; pi<polys.length; pi++){\n          var rings = polys[pi];\n          if(!rings) continue;\n          for(var ri=0; ri<rings.length; ri++){\n            var ring = rings[ri];\n            if(!ring ? true : ring.length < 4) continue;\n            parts.push(points.length \/ 2);\n            for(var vi=0; vi<ring.length; vi++){\n              var px = +ring[vi][0], py = +ring[vi][1];\n              if(!isFinite(px) ? true : !isFinite(py)) continue;\n              points.push(px, py);\n              if(px < globalBbox.xmin) globalBbox.xmin = px;\n              if(px > globalBbox.xmax) globalBbox.xmax = px;\n              if(py < globalBbox.ymin) globalBbox.ymin = py;\n              if(py > globalBbox.ymax) globalBbox.ymax = py;\n              if(px < localBbox.xmin) localBbox.xmin = px;\n              if(px > localBbox.xmax) localBbox.xmax = px;\n              if(py < localBbox.ymin) localBbox.ymin = py;\n              if(py > localBbox.ymax) localBbox.ymax = py;\n            }\n          }\n        }\n        if(parts.length === 0 ? true : points.length === 0) continue;\n        var nPts = points.length \/ 2;\n        var contentBytes = 4 + 32 + 4 + 4 + 4 * parts.length + 16 * nPts;\n        records.push({ type:'polygon', bbox:localBbox, parts:parts, points:points, nPts:nPts, contentBytes:contentBytes });\n        hasGeom[fi] = true;\n      }\n    }\n    if(records.length === 0) throw new Error('No exportable geometry in dataset');\n    if(!isFinite(globalBbox.xmin)){\n      globalBbox.xmin = 0; globalBbox.ymin = 0; globalBbox.xmax = 0; globalBbox.ymax = 0;\n    }\n    \/\/ SHP file\n    var shpBytes = 100;\n    for(var r=0; r<records.length; r++) shpBytes += 8 + records[r].contentBytes;\n    var shp = new ArrayBuffer(shpBytes);\n    var shpV = new DataView(shp);\n    shpV.setInt32(0, 9994, false);\n    shpV.setInt32(24, shpBytes \/ 2, false);\n    shpV.setInt32(28, 1000, true);\n    shpV.setInt32(32, shapeTypeCode, true);\n    shpV.setFloat64(36, globalBbox.xmin, true);\n    shpV.setFloat64(44, globalBbox.ymin, true);\n    shpV.setFloat64(52, globalBbox.xmax, true);\n    shpV.setFloat64(60, globalBbox.ymax, true);\n    \/\/ zMin\/zMax\/mMin\/mMax stay 0 (2D shapefile)\n    \/\/ SHX index\n    var shxBytes = 100 + records.length * 8;\n    var shx = new ArrayBuffer(shxBytes);\n    var shxV = new DataView(shx);\n    shxV.setInt32(0, 9994, false);\n    shxV.setInt32(24, shxBytes \/ 2, false);\n    shxV.setInt32(28, 1000, true);\n    shxV.setInt32(32, shapeTypeCode, true);\n    shxV.setFloat64(36, globalBbox.xmin, true);\n    shxV.setFloat64(44, globalBbox.ymin, true);\n    shxV.setFloat64(52, globalBbox.xmax, true);\n    shxV.setFloat64(60, globalBbox.ymax, true);\n    \/\/ Records\n    var off = 100;\n    for(var ri2=0; ri2<records.length; ri2++){\n      var rec = records[ri2];\n      var contentWords = rec.contentBytes \/ 2;\n      shpV.setInt32(off, ri2 + 1, false);\n      shpV.setInt32(off + 4, contentWords, false);\n      var pOff = off + 8;\n      shpV.setInt32(pOff, shapeTypeCode, true);\n      if(rec.type === 'point'){\n        shpV.setFloat64(pOff + 4, rec.x, true);\n        shpV.setFloat64(pOff + 12, rec.y, true);\n      } else {\n        shpV.setFloat64(pOff + 4, rec.bbox.xmin, true);\n        shpV.setFloat64(pOff + 12, rec.bbox.ymin, true);\n        shpV.setFloat64(pOff + 20, rec.bbox.xmax, true);\n        shpV.setFloat64(pOff + 28, rec.bbox.ymax, true);\n        shpV.setInt32(pOff + 36, rec.parts.length, true);\n        shpV.setInt32(pOff + 40, rec.nPts, true);\n        for(var partI=0; partI<rec.parts.length; partI++){\n          shpV.setInt32(pOff + 44 + partI * 4, rec.parts[partI], true);\n        }\n        var ptStart = pOff + 44 + rec.parts.length * 4;\n        for(var pp=0; pp<rec.nPts; pp++){\n          shpV.setFloat64(ptStart + pp * 16, rec.points[pp * 2], true);\n          shpV.setFloat64(ptStart + pp * 16 + 8, rec.points[pp * 2 + 1], true);\n        }\n      }\n      var shxOff = 100 + ri2 * 8;\n      shxV.setInt32(shxOff, off \/ 2, false);\n      shxV.setInt32(shxOff + 4, contentWords, false);\n      off += 8 + rec.contentBytes;\n    }\n    \/\/ DBF \u2014 one record per record in shp, in same order. Map original feature\n    \/\/ index to record index for attribute pulls.\n    var recordFeatureIdx = [];\n    for(var fi2=0; fi2<features.length; fi2++) if(hasGeom[fi2]) recordFeatureIdx.push(fi2);\n    var recordLen = 1;\n    for(var ai=0; ai<attrSpecs.length; ai++) recordLen += attrSpecs[ai].length;\n    var dbfHeaderLen = 32 + 32 * attrSpecs.length + 1;\n    var dbfBytes = dbfHeaderLen + records.length * recordLen + 1;\n    var dbf = new ArrayBuffer(dbfBytes);\n    var dbfV = new DataView(dbf);\n    var dbf8 = new Uint8Array(dbf);\n    dbf8[0] = 0x03;\n    var d = new Date();\n    dbf8[1] = d.getFullYear() - 1900;\n    dbf8[2] = d.getMonth() + 1;\n    dbf8[3] = d.getDate();\n    dbfV.setUint32(4, records.length, true);\n    dbfV.setUint16(8, dbfHeaderLen, true);\n    dbfV.setUint16(10, recordLen, true);\n    for(var aj=0; aj<attrSpecs.length; aj++){\n      var aSpec = attrSpecs[aj];\n      var fdStart = 32 + 32 * aj;\n      var nm = aSpec.name;\n      for(var c=0; (c<nm.length ? c<11 : false); c++) dbf8[fdStart + c] = nm.charCodeAt(c);\n      dbf8[fdStart + 11] = aSpec.type.charCodeAt(0);\n      dbf8[fdStart + 16] = aSpec.length;\n      dbf8[fdStart + 17] = aSpec.decimal ? aSpec.decimal : 0;\n    }\n    dbf8[32 + 32 * attrSpecs.length] = 0x0D;\n    var recOff = dbfHeaderLen;\n    for(var rIdx=0; rIdx<records.length; rIdx++){\n      dbf8[recOff] = 0x20;\n      var fieldOff = recOff + 1;\n      var origFeat = features[recordFeatureIdx[rIdx]];\n      for(var ak=0; ak<attrSpecs.length; ak++){\n        var aS = attrSpecs[ak];\n        var val = aS.get(origFeat);\n        var str = formatDbfField(val, aS.type, aS.length, aS.decimal ? aS.decimal : 0);\n        for(var sc=0; sc<str.length; sc++) dbf8[fieldOff + sc] = str.charCodeAt(sc) % 256;\n        fieldOff += aS.length;\n      }\n      recOff += recordLen;\n    }\n    dbf8[dbfBytes - 1] = 0x1A;\n    var prj = 'GEOGCS[\"GCS_WGS_1984\",DATUM[\"D_WGS_1984\",SPHEROID[\"WGS_1984\",6378137.0,298.257223563]],PRIMEM[\"Greenwich\",0.0],UNIT[\"Degree\",0.0174532925199433]]';\n    return { shp: shp, shx: shx, dbf: dbf, prj: prj };\n  }\n  \/\/ Inspect a dataset's properties to build default attribute specs. Detects\n  \/\/ numeric vs character per attribute by checking the first non-null value.\n  function buildAttrSpecsFromDataset(ds){\n    var specs = [];\n    if(!ds.features ? true : ds.features.length === 0) return specs;\n    var seen = {};\n    var rawNames = [];\n    for(var i=0; (i<ds.features.length ? i<200 : false); i++){\n      var p = ds.features[i].properties;\n      if(!p) continue;\n      for(var k in p){\n        if(!Object.prototype.hasOwnProperty.call(p, k)) continue;\n        if(!seen[k]){ seen[k] = 1; rawNames.push(k); }\n      }\n    }\n    var usedNames = {};\n    for(var ni=0; ni<rawNames.length; ni++){\n      var rawName = rawNames[ni];\n      var name = sanitizeDbfFieldName(rawName);\n      var suffix = 1;\n      var baseName = name;\n      while(usedNames[name]){\n        var sfx = String(suffix++);\n        name = baseName.substring(0, 10 - sfx.length) + sfx;\n      }\n      usedNames[name] = 1;\n      \/\/ Detect type from sample values\n      var isNumeric = true;\n      var samplesSeen = 0;\n      for(var si=0; (si<ds.features.length ? samplesSeen<20 : false); si++){\n        var v = ds.features[si].properties ? ds.features[si].properties[rawName] : null;\n        if(v === null ? true : v === undefined) continue;\n        samplesSeen++;\n        if(typeof v === 'number'){ continue; }\n        if(typeof v === 'string' ? isFinite(Number(v)) : false){ continue; }\n        isNumeric = false;\n        break;\n      }\n      var spec;\n      if(isNumeric){\n        spec = { name: name, rawName: rawName, type: 'N', length: 19, decimal: 6, get: (function(rn){\n          return function(f){ var p = f.properties; return p ? p[rn] : null; };\n        })(rawName) };\n      } else {\n        spec = { name: name, rawName: rawName, type: 'C', length: 64, decimal: 0, get: (function(rn){\n          return function(f){ var p = f.properties; return p ? p[rn] : null; };\n        })(rawName) };\n      }\n      specs.push(spec);\n    }\n    return specs;\n  }\n  \/\/ Trigger a browser download for a Blob.\n  function downloadBlob(blob, filename){\n    var url = URL.createObjectURL(blob);\n    var a = document.createElement('a');\n    a.href = url;\n    a.download = filename;\n    document.body.appendChild(a);\n    a.click();\n    document.body.removeChild(a);\n    setTimeout(function(){ URL.revokeObjectURL(url); }, 1000);\n  }\n  \/\/ \u2500\u2500\u2500 MULTI-FILE DATASET \/ TREE PIPELINE \u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\n  var datasets = [];            \/\/ [{ id, name, source, geomType, features, bbox, areaHa, parentId, isBoundary }]\n  var activeDatasetId = null;\n  var datasetCounter = 0;\n  \/\/ Recursively walk a zip (incl. nested zips); resolves to [{path, entry}]\n  function walkArchive(zip, prefix){\n    prefix = prefix || '';\n    var out = [];\n    var promises = [];\n    zip.forEach(function(p, e){\n      if(e.dir) return;\n      var fullPath = prefix + p;\n      var lc = p.toLowerCase();\n      if(\/\\.zip$\/i.test(lc)){\n        promises.push(e.async('arraybuffer').then(function(buf){\n          return window.JSZip.loadAsync(buf).then(function(inner){\n            return walkArchive(inner, fullPath + '\/');\n          });\n        }).then(function(nested){\n          for(var i=0;i<nested.length;i++) out.push(nested[i]);\n        }).catch(function(err){\n          try { console.warn('[GPY] nested zip failed:', fullPath, err); } catch(_){}\n        }));\n      } else {\n        out.push({ path: fullPath, entry: e });\n      }\n    });\n    return Promise.all(promises).then(function(){ return out; });\n  }\n  \/\/ Group shapefile parts by base name + directory\n  function groupShapefiles(entries){\n    var groups = {};\n    for(var i=0;i<entries.length;i++){\n      var e = entries[i];\n      var m = e.path.match(\/^(.*\\\/)?([^\\\/]+)\\.(shp|shx|dbf|prj)$\/i);\n      if(!m) continue;\n      var dir = m[1] || '';\n      var base = m[2];\n      var ext = m[3].toLowerCase();\n      var key = (dir + base).toLowerCase();\n      if(!groups[key]) groups[key] = { dir: dir, base: base, parts: {} };\n      groups[key].parts[ext] = e;\n    }\n    var out = [];\n    for(var k in groups){\n      var g = groups[k];\n      if(g.parts.shp ? g.parts.dbf : false){ out.push(g); }\n    }\n    return out;\n  }\n  function parseShapefileGroup(group){\n    return Promise.all([\n      group.parts.shp.entry.async('arraybuffer'),\n      group.parts.dbf.entry.async('arraybuffer'),\n      group.parts.prj ? group.parts.prj.entry.async('string') : Promise.resolve(null)\n    ]).then(function(arr){\n      try {\n        var shpResult = window.shp.parseShp(arr[0], arr[2]);\n        var dbfResult = window.shp.parseDbf(arr[1]);\n        var fc = window.shp.combine([shpResult, dbfResult]);\n        return { ok: true, fc: fc, name: group.base, dir: group.dir };\n      } catch(err){\n        try { console.warn('[GPY] shapefile parse failed:', group.dir+group.base, err); } catch(_){}\n        return { ok: false };\n      }\n    });\n  }\n  \/\/ CSV \/ TSV parser. Detects delimiter automatically (comma, semicolon, or tab \u2014 whichever appears\n  \/\/ most consistently across the first 5 non-empty lines). Handles quoted fields with embedded\n  \/\/ delimiters. Returns { header: [colNames], rows: [[v1, v2, ...], ...] }.\n  function parseCsv(text){\n    if(text.charCodeAt(0) === 0xFEFF) text = text.slice(1);  \/\/ strip BOM\n    \/\/ Pick delimiter by counting occurrences in the first non-empty line (header is the truth)\n    var firstLine = '';\n    for(var p=0; p<text.length; p++){\n      if(text[p] === '\\n' ? true : text[p] === '\\r'){\n        if(firstLine.length) break;\n        continue;\n      }\n      firstLine += text[p];\n    }\n    var commaC = (firstLine.match(\/,\/g) || []).length;\n    var semiC  = (firstLine.match(\/;\/g) || []).length;\n    var tabC   = (firstLine.match(\/\\t\/g) || []).length;\n    var delim = ',';\n    if(semiC > commaC ? semiC > tabC : false) delim = ';';\n    else if(tabC > commaC) delim = '\\t';\n    \/\/ Stateful parser handling quoted strings + escaped quotes (\"foo,bar\" \u2192 foo,bar)\n    var rows = [];\n    var cur = [];\n    var field = '';\n    var inQuote = false;\n    var i = 0;\n    while(i < text.length){\n      var ch = text[i];\n      if(inQuote){\n        if(ch === '\"'){\n          if(text[i+1] === '\"'){ field += '\"'; i += 2; continue; }\n          inQuote = false; i++; continue;\n        }\n        field += ch; i++; continue;\n      }\n      if(ch === '\"'){ inQuote = true; i++; continue; }\n      if(ch === delim){ cur.push(field); field = ''; i++; continue; }\n      if(ch === '\\r'){ i++; continue; }\n      if(ch === '\\n'){\n        cur.push(field); field = '';\n        if(cur.length > 1 ? true : cur[0] !== '') rows.push(cur);\n        cur = []; i++; continue;\n      }\n      field += ch; i++;\n    }\n    if(field.length ? true : cur.length){\n      cur.push(field);\n      if(cur.length > 1 ? true : cur[0] !== '') rows.push(cur);\n    }\n    if(!rows.length) return null;\n    var header = rows[0].map(function(h){ return String(h).trim(); });\n    return { header: header, rows: rows.slice(1), delim: delim };\n  }\n  \/\/ Detect lat\/lon column indices in a parsed header. Two strategies:\n  \/\/  1) Fuzzy NAME match \u2014 handles prefixed \/ multilingual conventions across\n  \/\/     vendors (Lat, Latitude, Centr_Lat, GPS_Lat, Y, Northing, \u0448\u0438\u0440\u043e\u0442\u0430; and the\n  \/\/     longitude equivalents). This is the reliable signal and is tried first.\n  \/\/  2) BY-VALUE fallback for cryptic names (X \/ Y \/ field1): coordinate columns\n  \/\/     are the numeric columns carrying the HIGHEST decimal precision whose\n  \/\/     values sit in plausible ranges \u2014 depths \/ counts \/ yields are integers or\n  \/\/     1-2 decimals, GPS coordinates carry 5-8. We pick the two highest-precision\n  \/\/     in-range columns and assign lat = the one bounded to \u00b190.\n  \/\/ Validates the chosen pair by magnitude before returning { latIdx, lonIdx }.\n  function detectLatLonCols(header, rows){\n    var latName = function(h){\n      return \/lat$|^lat|latitude|\u0448\u0438\u0440\u043e\u0442|breite\/.test(h) ? true\n           : (h === 'y' ? true : \/northing|^north$|ycoord|^ycrd|^y[0-9]\/.test(h));\n    };\n    var lonName = function(h){\n      return \/lng$|lon$|long$|^lon|^lng|longitude|\u0434\u043e\u0432\u0433\u043e\u0442|\u0434\u043e\u043b\u0433\u043e\u0442|dlugo\/.test(h) ? true\n           : (h === 'x' ? true : \/easting|^east$|xcoord|^xcrd|^x[0-9]\/.test(h));\n    };\n    var latCand = -1, lonCand = -1;\n    for(var i=0; i<header.length; i++){\n      var h = String(header[i] || '').replace(\/[\\s_\\-.,()\u00b0]\/g, '').toLowerCase();\n      if(!h) continue;\n      if(latCand < 0 ? latName(h) : false) latCand = i;\n      if(lonCand < 0 ? lonName(h) : false) lonCand = i;\n    }\n    \/\/ By-value fallback \u2014 only when NEITHER coordinate was named.\n    if(latCand < 0 ? lonCand < 0 : false){\n      var sample = Math.min(rows.length, 60);\n      var cand = [];\n      for(var c=0; c<header.length; c++){\n        var finite = 0, prec = 0, mn = Infinity, mx = -Infinity, nonconst = false, first = null;\n        for(var r=0; r<sample; r++){\n          var raw = rows[r] ? rows[r][c] : undefined;\n          var v = parseFloat(raw);\n          if(!isFinite(v)) continue;\n          finite++;\n          if(first === null) first = v; else if(v !== first) nonconst = true;\n          if(v < mn) mn = v; if(v > mx) mx = v;\n          var sv = String(raw);\n          var dot = sv.indexOf('.');\n          if(dot >= 0) prec += (sv.length - dot - 1);\n        }\n        if(finite < Math.max(3, sample * 0.6)) continue;   \/\/ mostly-numeric columns only\n        if(!nonconst) continue;                            \/\/ a constant column is not a coordinate\n        if(mn < -180 ? true : mx > 180) continue;          \/\/ out of lon range \u2192 projected \/ other\n        cand.push({ idx: c, prec: prec \/ finite, inLat: (mn >= -90 ? mx <= 90 : false) });\n      }\n      cand.sort(function(a, b){ return b.prec - a.prec; });\n      var coordCand = cand.filter(function(o){ return o.prec >= 3; });   \/\/ \u22653 decimals \u21d2 coordinate-like\n      if(coordCand.length >= 2){\n        var ca = coordCand[0], cb = coordCand[1];\n        if(ca.inLat ? !cb.inLat : false){ latCand = ca.idx; lonCand = cb.idx; }\n        else if(cb.inLat ? !ca.inLat : false){ latCand = cb.idx; lonCand = ca.idx; }\n        else { latCand = Math.min(ca.idx, cb.idx); lonCand = Math.max(ca.idx, cb.idx); }  \/\/ both \u00b190 \u2192 file order\n        try { console.warn('[GPY] coords detected by value (cols ' + latCand + '\/' + lonCand + ') \u2014 no name match'); } catch(_){}\n      }\n    }\n    if(latCand < 0 ? true : lonCand < 0) return null;\n    \/\/ Validate the actual values in the rows fall in range\n    var checkN = Math.min(rows.length, 50);\n    var latOk = 0, lonOk = 0, tot = 0;\n    for(var k=0; k<checkN; k++){\n      if(!rows[k]) continue;\n      tot++;\n      var la = parseFloat(rows[k][latCand]);\n      var lo = parseFloat(rows[k][lonCand]);\n      if(isFinite(la) ? Math.abs(la) <= 90 : false) latOk++;\n      if(isFinite(lo) ? Math.abs(lo) <= 180 : false) lonOk++;\n    }\n    if(!tot) return null;\n    if(latOk < tot * 0.7 ? true : lonOk < tot * 0.7) return null;\n    return { latIdx: latCand, lonIdx: lonCand };\n  }\n  function csvToFeatureCollection(parsed){\n    var lonlat = detectLatLonCols(parsed.header, parsed.rows);\n    if(!lonlat) return null;\n    var feats = [];\n    var header = parsed.header;\n    for(var r=0; r<parsed.rows.length; r++){\n      var row = parsed.rows[r];\n      var lat = parseFloat(row[lonlat.latIdx]);\n      var lon = parseFloat(row[lonlat.lonIdx]);\n      if(!isFinite(lat) ? true : !isFinite(lon)) continue;\n      if(Math.abs(lat) > 90 ? true : Math.abs(lon) > 180) continue;\n      var props = {};\n      for(var c=0; c<header.length; c++){\n        if(c === lonlat.latIdx ? true : c === lonlat.lonIdx) continue;\n        var raw = row[c];\n        var num = parseFloat(raw);\n        \/\/ Keep numeric where possible (downstream numeric-column detector needs typeof === 'number')\n        props[header[c]] = isFinite(num) ? num : raw;\n      }\n      feats.push({ type:'Feature', geometry:{ type:'Point', coordinates:[lon, lat] }, properties: props });\n    }\n    var fc = { type:'FeatureCollection', features: feats };\n    \/\/ Auto-detect units from the header labels so the legend reads correctly for\n    \/\/ any CSV \/ Excel (soil, yield, as-applied, compaction \u2026). makeDataset seeds\n    \/\/ ds.unitMap from this, and it wins over magnitude-based guessUnit().\n    fc.__unitMap = detectUnitsFromHeaders(header, parsed.rows);\n    return fc;\n  }\n  function handleCsvFile(file){\n    var rd = new FileReader();\n    rd.onload = function(e){\n      try {\n        var parsed = parseCsv(e.target.result);\n        if(!parsed ? true : !parsed.rows.length){ showToast('CSV is empty or unparseable.'); return; }\n        var fc = csvToFeatureCollection(parsed);\n        if(!fc ? true : !fc.features.length){\n          showToast('CSV has no recognizable lat\/lon columns. Add a latitude and longitude column (decimal degrees) and re-export.');\n          return;\n        }\n        var name = file.name.replace(\/\\.(csv|tsv|txt)$\/i, '');\n        var ds = makeDataset(fc, name, file.name);\n        if(!ds){ showToast('No usable rows in CSV.'); return; }\n        addDatasets([ds]);\n        activateDataset(ds.id);\n        try { console.warn('[GPY] CSV imported:', fc.features.length, 'points (delim \"' + parsed.delim + '\")'); } catch(_){}\n      } catch(ex){ showToast('CSV parse error: ' + ex.message); }\n    };\n    rd.onerror = function(){ showToast('Could not read file.'); };\n    rd.readAsText(file);\n  }\n  \/\/ Auto-detect a unit for each column from its HEADER LABEL (not magnitude \u2014 see\n  \/\/ CLAUDE.md rule 19). Only emits HIGH-CONFIDENCE units: explicit unit tokens\n  \/\/ embedded in the header (\"Yield, t\/ha\", \"P (mg\/kg)\", \"\u0413\u043b\u0438\u0431\u0438\u043d\u0430, \u0441\u043c\"), coordinate\n  \/\/ names, and the penetrometer depth-profile signature. Columns with no explicit\n  \/\/ unit are left out so the magnitude-aware guessUnit() can fill them in. Works\n  \/\/ generically across soil \/ yield \/ as-applied \/ compaction CSV + Excel files.\n  function detectUnitsFromHeaders(header, rows){\n    var map = {};\n    if(!header) return map;\n    \/\/ Known explicit unit tokens \u2192 canonical unit. Longer \/ more-specific first so\n    \/\/ \"kg\/ha\" wins over a bare \"kg\", \"cmol\/kg\" over \"cm\", etc.\n    var TOKENS = [\n      ['1000seeds\/ha','1000seeds\/ha'],['seeds\/ha','seeds\/ha'],['seeds\/m2','seeds\/m\u00b2'],['seeds\/m\u00b2','seeds\/m\u00b2'],\n      ['cmol\/kg','cmol\/kg'],['meq\/100g','meq\/100g'],['mg\/kg','mg\/kg'],['mg\/dm3','mg\/kg'],['mg\/dm\u00b3','mg\/kg'],\n      ['t\/ha','t\/ha'],['kg\/ha','kg\/ha'],['g\/ha','g\/ha'],['l\/ha','L\/ha'],['lb\/ac','lb\/ac'],['bu\/ac','bu\/ac'],\n      ['gal\/ac','gal\/ac'],['c\/ha','c\/ha'],['\u0446\/\u0433\u0430','c\/ha'],['\u0442\/\u0433\u0430','t\/ha'],['\u043a\u0433\/\u0433\u0430','kg\/ha'],['\u043b\/\u0433\u0430','L\/ha'],\n      ['ppm','mg\/kg'],['ds\/m','dS\/m'],['mmho\/cm','dS\/m'],['kpa','kPa'],['mpa','MPa'],['psi','psi'],['bar','bar'],\n      ['km\/h','km\/h'],['mph','mph'],['m\/s','m\/s'],['\u00b0c','C'],['\u00b0f','F'],\n      ['mm','mm'],['cm','cm'],['\u0441\u043c','cm'],['\u043c\u043c','mm'],['ft','ft'],['%','%'],['\u2030','\u2030'],['\u00b0','deg']\n    ];\n    for(var i=0; i<header.length; i++){\n      var name = String(header[i] || '');\n      var lc = name.toLowerCase();\n      var norm = lc.replace(\/[\\s_\\-.,()]\/g, '');\n      var unit = '';\n      \/\/ 1) Explicit unit token. Alphabetic tokens must be delimited (so the \"m\" in\n      \/\/    \"magnesium\" or \"cm\" in \"cmol\" can't false-match); symbol tokens (%, \u00b0) match anywhere.\n      for(var t=0; t<TOKENS.length; t++){\n        var tok = TOKENS[t][0];\n        var hit;\n        if(\/[a-z\u0430-\u044f\u0451]\/.test(tok)){\n          hit = false;\n          var idx = lc.indexOf(tok);\n          while(idx >= 0){\n            var before = idx === 0 ? '' : lc.charAt(idx - 1);\n            var after = lc.charAt(idx + tok.length);\n            var bOk = before === '' ? true : !\/[a-z\u0430-\u044f\u04510-9]\/.test(before);\n            var aOk = after === '' ? true : !\/[a-z\u0430-\u044f\u04510-9]\/.test(after);\n            if(bOk ? aOk : false){ hit = true; break; }\n            idx = lc.indexOf(tok, idx + 1);\n          }\n        } else {\n          hit = lc.indexOf(tok) >= 0;\n        }\n        if(hit){ unit = TOKENS[t][1]; break; }\n      }\n      \/\/ 2) Bare metres token after a delimiter (\"Elev, m\" \/ \"\u0412\u0438\u0441\u043e\u0442\u0430 (\u043c)\").\n      if(!unit ? (\/(^|[\\s,(\\[\\\/])m($|[\\s,)\\]\\\/])\/.test(lc) ? true : \/,\\s*\u043c$|\\(\u043c\\)\/.test(lc)) : false) unit = 'm';\n      \/\/ 3) Coordinate names \u2192 degrees.\n      if(!unit ? \/lat$|^lat|latitude|\u0448\u0438\u0440\u043e\u0442|lng$|lon$|long$|^lon|^lng|longitude|\u0434\u043e\u0432\u0433\u043e\u0442|\u0434\u043e\u043b\u0433\u043e\u0442\/.test(norm) : false) unit = 'deg';\n      \/\/ 4) Penetration \/ compaction RESISTANCE \/ soil density (no explicit unit, not a depth column) \u2192 kPa.\n      if(!unit ? (\/penetr|resist|\u0449\u0456\u043b\u044c\u043d|\u0443\u0449\u0456\u043b\u044c\u043d|density|\u0442\u0432\u0451\u0440\u0434|\u0442\u0432\u0435\u0440\u0434\/.test(lc) ? !\/\u0441\u043c|cm|\u0433\u043b\u0438\u0431|\u0433\u043b\u0443\u0431|depth|\u0434\u0456\u0430\u043f\u0430\u0437\u043e\u043d|range\/.test(lc) : false) : false) unit = 'kPa';\n      if(unit) map[name] = unit;\n    }\n    \/\/ 5) Penetrometer depth-profile signature: a RUN of \u22655 purely-numeric headers\n    \/\/    (0, 2.5, 5 \u2026 60 cm) holds resistance-at-depth readings \u2192 kPa.\n    var run = [];\n    var flush = function(){\n      if(run.length >= 5){ for(var j=0; j<run.length; j++){ if(!map[run[j]]) map[run[j]] = 'kPa'; } }\n      run = [];\n    };\n    for(var hh=0; hh<header.length; hh++){\n      var hn = String(header[hh] || '').trim();\n      if(\/^\\d+(\\.\\d+)?$\/.test(hn)) run.push(header[hh]);\n      else flush();\n    }\n    flush();\n    return map;\n  }\n  \/\/ \u2500\u2500 XLSX import \u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\n  \/\/ .xlsx is a zip of XML, so we reuse the JSZip already lazy-loaded for shapefiles\n  \/\/ rather than pulling a heavyweight spreadsheet library \u2014 keeps the CDN footprint\n  \/\/ identical (CLAUDE.md rule 4). Reads the FIRST worksheet only; strings + numbers.\n  \/\/ Returns the SAME { header, rows, delim } shape parseCsv returns so it flows\n  \/\/ through csvToFeatureCollection unchanged. Old binary .xls (BIFF) is NOT a zip\n  \/\/ and is unsupported \u2014 those users are told to re-save as .xlsx \/ CSV.\n  var XAMP = String.fromCharCode(38);   \/\/ the ampersand char \u2014 built via charcode so no literal sits in the script body (rule 1)\n  function xmlDecode(t){\n    if(!t) return '';\n    if(t.indexOf(XAMP) < 0) return t;\n    return t.replace(new RegExp(XAMP + '#x([0-9a-fA-F]+);', 'g'), function(_, h){ return String.fromCharCode(parseInt(h, 16)); })\n            .replace(new RegExp(XAMP + '#(\\\\d+);', 'g'), function(_, d){ return String.fromCharCode(parseInt(d, 10)); })\n            .split(XAMP + 'lt;').join('<')\n            .split(XAMP + 'gt;').join('>')\n            .split(XAMP + 'quot;').join('\"')\n            .split(XAMP + 'apos;').join(\"'\")\n            .split(XAMP + 'amp;').join(XAMP);\n  }\n  function xlsxColToIdx(ref){\n    var m = ref.match(\/^([A-Z]+)\/);\n    if(!m) return -1;\n    var s = m[1], n = 0;\n    for(var i=0; i<s.length; i++){ n = n * 26 + (s.charCodeAt(i) - 64); }\n    return n - 1;\n  }\n  function xlsxSharedStrings(xml){\n    var out = [];\n    if(!xml) return out;\n    var siRe = \/<si>([\\s\\S]*?)<\\\/si>\/g, m;\n    while((m = siRe.exec(xml))){\n      var inner = m[1];\n      var tRe = \/<t[^>]*>([\\s\\S]*?)<\\\/t>\/g, tm, txt = '';   \/\/ concat rich-text runs split across <r><t>\n      while((tm = tRe.exec(inner))){ txt += tm[1]; }\n      out.push(xmlDecode(txt));\n    }\n    return out;\n  }\n  function parseXlsxSheet(xml, shared){\n    var grid = {}, maxRow = -1, maxCol = -1;\n    var cRe = \/<c\\s+([^>]*?)(?:\\\/>|>([\\s\\S]*?)<\\\/c>)\/g, cm;\n    while((cm = cRe.exec(xml))){\n      var attrs = cm[1];\n      var body = cm[2] || '';\n      var refM = attrs.match(\/r=\"([A-Z]+)(\\d+)\"\/);\n      if(!refM) continue;\n      var col = xlsxColToIdx(refM[1]);\n      var row = parseInt(refM[2], 10) - 1;\n      if(col < 0 ? true : row < 0) continue;\n      var typeM = attrs.match(\/t=\"([^\"]+)\"\/);\n      var type = typeM ? typeM[1] : 'n';\n      var val;\n      if(type === 'inlineStr'){\n        var isM = body.match(\/<t[^>]*>([\\s\\S]*?)<\\\/t>\/);\n        val = isM ? xmlDecode(isM[1]) : '';\n      } else {\n        var vM = body.match(\/<v>([\\s\\S]*?)<\\\/v>\/);\n        var raw = vM ? vM[1] : '';\n        if(type === 's'){\n          var si = parseInt(raw, 10);\n          val = (isFinite(si) ? shared[si] : '') || '';\n        } else if(type === 'str' ? true : type === 'e'){\n          val = xmlDecode(raw);\n        } else if(type === 'b'){\n          val = (raw === '1' ? 'TRUE' : 'FALSE');\n        } else {\n          var num = parseFloat(raw);\n          val = isFinite(num) ? num : (raw === '' ? '' : xmlDecode(raw));\n        }\n      }\n      if(!grid[row]) grid[row] = {};\n      grid[row][col] = val;\n      if(row > maxRow) maxRow = row;\n      if(col > maxCol) maxCol = col;\n    }\n    if(maxRow < 0) return null;\n    var rowKeys = Object.keys(grid).map(function(k){ return parseInt(k, 10); }).sort(function(a, b){ return a - b; });\n    var headerObj = grid[rowKeys[0]] || {};\n    var header = [];\n    for(var c2=0; c2<=maxCol; c2++){\n      var hv = headerObj[c2];\n      header.push(hv === undefined ? '' : String(hv));\n    }\n    var rows = [];\n    for(var rk=1; rk<rowKeys.length; rk++){\n      var ro = grid[rowKeys[rk]] || {};\n      var arr = [], any = false;\n      for(var cc=0; cc<=maxCol; cc++){\n        var cv = ro[cc];\n        if(cv === undefined){ arr.push(''); } else { arr.push(cv); any = true; }\n      }\n      if(any) rows.push(arr);\n    }\n    return { header: header, rows: rows, delim: 'xlsx' };\n  }\n  function parseXlsx(buf){\n    return loadJSZip().then(function(){\n      return window.JSZip.loadAsync(buf);\n    }).then(function(zip){\n      var ssFile = zip.file('xl\/sharedStrings.xml');\n      var sheetFiles = zip.file(\/^xl\\\/worksheets\\\/sheet\\d+\\.xml$\/);\n      if(!sheetFiles ? true : !sheetFiles.length){ throw new Error('No worksheet found in the .xlsx file.'); }\n      sheetFiles.sort(function(a, b){\n        var na = parseInt((a.name.match(\/sheet(\\d+)\\.xml\/) || [])[1] || '0', 10);\n        var nb = parseInt((b.name.match(\/sheet(\\d+)\\.xml\/) || [])[1] || '0', 10);\n        return na - nb;\n      });\n      return Promise.all([ sheetFiles[0].async('string'), ssFile ? ssFile.async('string') : Promise.resolve('') ]);\n    }).then(function(parts){\n      var shared = xlsxSharedStrings(parts[1]);\n      var parsed = parseXlsxSheet(parts[0], shared);\n      if(!parsed ? true : !parsed.header.length){ throw new Error('Could not read rows from the .xlsx sheet.'); }\n      return parsed;\n    });\n  }\n  function handleXlsxFile(file){\n    showOverlay('Reading Excel\u2026', 'Parsing the first worksheet and detecting coordinates + units.', true);\n    var rd = new FileReader();\n    rd.onload = function(e){\n      parseXlsx(e.target.result).then(function(parsed){\n        hideOverlay();\n        if(!parsed.rows.length){ showToast('Excel sheet has no data rows.'); return; }\n        var fc = csvToFeatureCollection(parsed);\n        if(!fc ? true : !fc.features.length){\n          showToast('No latitude \/ longitude columns found in the Excel sheet. Add coordinate columns (decimal degrees, EPSG:4326) and try again.');\n          return;\n        }\n        var name = file.name.replace(\/\\.(xlsx|xlsm)$\/i, '');\n        var ds = makeDataset(fc, name, file.name);\n        if(!ds){ showToast('No usable rows in the Excel sheet.'); return; }\n        addDatasets([ds]);\n        activateDataset(ds.id);\n        try { console.warn('[GPY] XLSX imported:', fc.features.length, 'points,', parsed.header.length, 'columns'); } catch(_){}\n      }).catch(function(err){\n        hideOverlay();\n        showToast('Excel parse error: ' + (err ? err.message : 'unknown') + '. If this is an old .xls, re-save as .xlsx or CSV.');\n      });\n    };\n    rd.onerror = function(){ hideOverlay(); showToast('Could not read file.'); };\n    rd.readAsArrayBuffer(file);\n  }\n  \/\/ \u2500\u2500 KML import \u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\n  \/\/ KML is XML; we parse it with the browser's DOMParser (no CDN dep). Placemarks\n  \/\/ carry Point \/ LineString \/ Polygon \/ MultiGeometry; attributes usually live in\n  \/\/ an HTML <table> inside <description> (GeoPard \/ Google Earth exports have no\n  \/\/ ExtendedData). Mixed-geometry KMLs are split into one dataset per geometry\n  \/\/ family (zones \/ lines \/ points) because makeDataset keeps a single type.\n  \/\/ .kmz (zipped KML) is unzipped via the lazy-loaded JSZip. EPSG:4326 only \u2014 KML\n  \/\/ is WGS84 by spec, so coordinates drop straight in.\n  function kmlTags(root, tag){\n    \/\/ Namespace-agnostic lookup \u2014 KML may use a default ns or a kml: prefix.\n    if(root.getElementsByTagNameNS){\n      var ns = root.getElementsByTagNameNS('*', tag);\n      if(ns ? ns.length : false) return ns;\n    }\n    return root.getElementsByTagName(tag);\n  }\n  function kmlText(el, tag){\n    var n = kmlTags(el, tag);\n    return (n ? n.length : false) ? (n[0].textContent || '') : '';\n  }\n  function parseKmlCoordStr(s){\n    \/\/ \"lon,lat[,alt] lon,lat[,alt] \u2026\" \u2192 [[lon,lat], \u2026]; altitude dropped.\n    var out = [];\n    var toks = String(s || '').replace(\/\\s+\/g, ' ').trim().split(' ');\n    for(var i=0; i<toks.length; i++){\n      if(!toks[i]) continue;\n      var c = toks[i].split(',');\n      var lon = parseFloat(c[0]), lat = parseFloat(c[1]);\n      if(isFinite(lon) ? isFinite(lat) : false) out.push([lon, lat]);\n    }\n    return out;\n  }\n  function kmlCloseRing(c){\n    if(c.length < 3) return c;\n    var a = c[0], b = c[c.length-1];\n    if(a[0] !== b[0] ? true : a[1] !== b[1]) c.push([a[0], a[1]]);\n    return c;\n  }\n  \/\/ Build a GeoJSON geometry from a Placemark (or MultiGeometry). Polygon wins over\n  \/\/ line over point when a placemark mixes them; multiple of one kind become Multi*.\n  function kmlGeometryFrom(el){\n    var polys = kmlTags(el, 'Polygon');\n    if(polys.length){\n      var pcoords = [];\n      for(var p=0; p<polys.length; p++){\n        var rings = [];\n        var ob = kmlTags(polys[p], 'outerBoundaryIs');\n        var oring = (ob.length ? kmlTags(ob[0], 'LinearRing') : kmlTags(polys[p], 'LinearRing'));\n        if(oring.length){ var oc = parseKmlCoordStr(kmlText(oring[0], 'coordinates')); if(oc.length >= 3) rings.push(kmlCloseRing(oc)); }\n        var inners = kmlTags(polys[p], 'innerBoundaryIs');\n        for(var ii=0; ii<inners.length; ii++){ var ir = kmlTags(inners[ii], 'LinearRing'); if(ir.length){ var ic = parseKmlCoordStr(kmlText(ir[0], 'coordinates')); if(ic.length >= 3) rings.push(kmlCloseRing(ic)); } }\n        if(rings.length) pcoords.push(rings);\n      }\n      if(!pcoords.length) return null;\n      return pcoords.length === 1 ? { type:'Polygon', coordinates: pcoords[0] } : { type:'MultiPolygon', coordinates: pcoords };\n    }\n    var lines = kmlTags(el, 'LineString');\n    if(lines.length){\n      var lc = [];\n      for(var l=0; l<lines.length; l++){ var arr = parseKmlCoordStr(kmlText(lines[l], 'coordinates')); if(arr.length >= 2) lc.push(arr); }\n      if(!lc.length) return null;\n      return lc.length === 1 ? { type:'LineString', coordinates: lc[0] } : { type:'MultiLineString', coordinates: lc };\n    }\n    var points = kmlTags(el, 'Point');\n    if(points.length){\n      var pc = [];\n      for(var pt=0; pt<points.length; pt++){ var a2 = parseKmlCoordStr(kmlText(points[pt], 'coordinates')); if(a2.length) pc.push(a2[0]); }\n      if(!pc.length) return null;\n      return pc.length === 1 ? { type:'Point', coordinates: pc[0] } : { type:'MultiPoint', coordinates: pc };\n    }\n    return null;\n  }\n  function kmlCoerce(v){\n    \/\/ \"10.38 HA\" \u2192 10.38, \"1.782\" \u2192 1.782, \"EVI2\" \u2192 \"EVI2\". Keeps the number when\n    \/\/ the cell is numeric (optionally trailed by a unit) so it stays colourable.\n    var str = String(v).trim();\n    var m = str.match(\/^-?\\d+(\\.\\d+)?\/);\n    if(m){\n      var rest = str.slice(m[0].length).trim();\n      if(rest === '' ? true : \/^(ha|ac|t\\\/ha|kg\\\/ha|l\\\/ha|mg\\\/kg|ppm|%|m|cm|mm|ds\\\/m|kpa|deg)$\/i.test(rest)){\n        var num = parseFloat(m[0]);\n        if(isFinite(num)) return num;\n      }\n    }\n    return str;\n  }\n  function parseKmlDescription(descHtml, props){\n    if(!descHtml) return;\n    \/\/ The XML parser already entity-decoded the description, so descHtml is real\n    \/\/ HTML (\"<table>\u2026\"). Parse it as HTML and pull key\/value rows. <br> \u2192 newline\n    \/\/ first so \"<b>Zone 1<\/b><br\/>Area: 10.38 HA\" splits into readable lines.\n    var html = String(descHtml).replace(\/<br\\s*\\\/?>\/gi, '\\n');\n    var doc;\n    try { doc = new DOMParser().parseFromString(html, 'text\/html'); } catch(_){ doc = null; }\n    if(!doc) return;\n    var rows = doc.getElementsByTagName('tr');\n    if(rows.length){\n      for(var r=0; r<rows.length; r++){\n        var cells = rows[r].children;\n        if(cells ? cells.length >= 2 : false){\n          var k = (cells[0].textContent || '').replace(\/\\s+\/g, ' ').trim();\n          var val = (cells[cells.length-1].textContent || '').replace(\/\\s+\/g, ' ').trim();\n          if(k ? k.length <= 40 : false) props[k] = kmlCoerce(val);\n        }\n      }\n      return;\n    }\n    \/\/ No table \u2014 fall back to \"Key: Value\" text lines.\n    var txt = (doc.body ? doc.body.textContent : html) || '';\n    var ln = txt.split(\/[\\n\\r]+\/);\n    for(var li=0; li<ln.length; li++){\n      var idx = ln[li].indexOf(':');\n      if(idx > 0){\n        var kk = ln[li].slice(0, idx).replace(\/\\s+\/g, ' ').trim();\n        var vv = ln[li].slice(idx + 1).replace(\/\\s+\/g, ' ').trim();\n        if(kk ? (kk.length <= 40 ? vv : false) : false) props[kk] = kmlCoerce(vv);\n      }\n    }\n  }\n  function parseKml(text){\n    var xml = new DOMParser().parseFromString(text, 'application\/xml');\n    var perr = xml.getElementsByTagName('parsererror');\n    if(perr ? perr.length : false) throw new Error('KML is not valid XML.');\n    var pms = kmlTags(xml, 'Placemark');\n    var feats = [];\n    for(var i=0; i<pms.length; i++){\n      var geom = kmlGeometryFrom(pms[i]);\n      if(!geom) continue;\n      var props = {};\n      var nameTxt = kmlText(pms[i], 'name').replace(\/\\s+\/g, ' ').trim();\n      if(nameTxt) props.name = nameTxt;\n      parseKmlDescription(kmlText(pms[i], 'description'), props);\n      feats.push({ type:'Feature', geometry: geom, properties: props });\n    }\n    return feats;\n  }\n  \/\/ Split mixed-geometry KML features into per-family datasets and register them.\n  function kmlFeaturesToDatasets(feats, baseName, source){\n    var groups = { polygon: [], line: [], point: [] };\n    for(var i=0; i<feats.length; i++){\n      var t = feats[i].geometry ? feats[i].geometry.type : '';\n      if(\/Polygon\/.test(t)) groups.polygon.push(feats[i]);\n      else if(\/LineString\/.test(t)) groups.line.push(feats[i]);\n      else if(\/Point\/.test(t)) groups.point.push(feats[i]);\n    }\n    var present = 0, order = ['polygon', 'line', 'point'], suffix = { polygon:' \u2014 zones', line:' \u2014 lines', point:' \u2014 points' };\n    for(var k0=0; k0<order.length; k0++){ if(groups[order[k0]].length) present++; }\n    var made = [];\n    for(var g=0; g<order.length; g++){\n      var arr = groups[order[g]];\n      if(!arr.length) continue;\n      var label = baseName + (present > 1 ? suffix[order[g]] : '');\n      var ds = makeDataset({ type:'FeatureCollection', features: arr }, label, source);\n      if(ds) made.push(ds);\n    }\n    return made;\n  }\n  function handleKmlFile(file){\n    showOverlay('Reading KML\u2026', 'Parsing placemarks and grouping by geometry type.', true);\n    var rd = new FileReader();\n    rd.onload = function(e){\n      hideOverlay();\n      try {\n        var feats = parseKml(e.target.result);\n        if(!feats.length){ showToast('No placemarks with geometry found in the KML.'); return; }\n        var made = kmlFeaturesToDatasets(feats, file.name.replace(\/\\.kml$\/i, ''), file.name);\n        if(!made.length){ showToast('No usable geometry in the KML.'); return; }\n        addDatasets(made);\n        activateDataset(made[0].id);\n        try { console.warn('[GPY] KML imported:', feats.length, 'placemarks \u2192', made.length, 'layer(s)'); } catch(_){}\n      } catch(ex){ showToast('KML parse error: ' + (ex ? (ex.message ? ex.message : ex) : 'unknown')); }\n    };\n    rd.onerror = function(){ hideOverlay(); showToast('Could not read file.'); };\n    rd.readAsText(file);\n  }\n  function handleKmzFile(file){\n    showOverlay('Reading KMZ\u2026', 'Unzipping and parsing the KML inside.', true);\n    loadJSZip().then(function(){\n      return new Promise(function(res, rej){\n        var rd = new FileReader();\n        rd.onload = function(e){ res(e.target.result); };\n        rd.onerror = function(){ rej(new Error('read failed')); };\n        rd.readAsArrayBuffer(file);\n      });\n    }).then(function(buf){\n      return window.JSZip.loadAsync(buf);\n    }).then(function(zip){\n      \/\/ Prefer doc.kml; otherwise the first .kml entry in the archive.\n      var kmlFiles = zip.file(\/\\.kml$\/i);\n      if(!kmlFiles ? true : !kmlFiles.length) throw new Error('No .kml inside the .kmz.');\n      var pick = kmlFiles[0];\n      for(var i=0; i<kmlFiles.length; i++){ if(\/(^|\\\/)doc\\.kml$\/i.test(kmlFiles[i].name)){ pick = kmlFiles[i]; break; } }\n      return pick.async('string');\n    }).then(function(kmlText2){\n      hideOverlay();\n      var feats = parseKml(kmlText2);\n      if(!feats.length){ showToast('No placemarks with geometry found in the KMZ.'); return; }\n      var made = kmlFeaturesToDatasets(feats, file.name.replace(\/\\.kmz$\/i, ''), file.name);\n      if(!made.length){ showToast('No usable geometry in the KMZ.'); return; }\n      addDatasets(made);\n      activateDataset(made[0].id);\n      try { console.warn('[GPY] KMZ imported:', feats.length, 'placemarks \u2192', made.length, 'layer(s)'); } catch(_){}\n    }).catch(function(err){\n      hideOverlay();\n      showToast('KMZ error: ' + (err ? (err.message ? err.message : err) : 'unknown'));\n    });\n  }\n  \/\/ Folder \/ zip pipeline: parse a .kml entry into grouped datasets.\n  function readKmlEntry(entry, path){\n    return entry.async('string').then(function(s){\n      try {\n        var feats = parseKml(s);\n        if(!feats.length) return { ok:false };\n        var base = path.split('\/').pop().replace(\/\\.kml$\/i, '');\n        var made = kmlFeaturesToDatasets(feats, base, path);\n        if(!made.length) return { ok:false };\n        return { ok:true, kmlDatasets: made };\n      } catch(err){ return { ok:false }; }\n    });\n  }\n  function readCsvEntry(entry, path){\n    return entry.async('string').then(function(s){\n      try {\n        var parsed = parseCsv(s);\n        if(!parsed ? true : !parsed.rows.length) return { ok:false };\n        var fc = csvToFeatureCollection(parsed);\n        if(!fc ? true : !fc.features.length) return { ok:false };\n        var name = path.split('\/').pop().replace(\/\\.(csv|tsv)$\/i,'');\n        var dir = path.substring(0, path.lastIndexOf('\/') + 1);\n        return { ok:true, json: fc, name: name, dir: dir };\n      } catch(err){ return { ok:false }; }\n    });\n  }\n  function readJsonEntry(entry, path){\n    return entry.async('string').then(function(s){\n      try {\n        var json = JSON.parse(s);\n        var name = path.split('\/').pop().replace(\/\\.(geo)?json$\/i,'');\n        var dir = path.substring(0, path.lastIndexOf('\/') + 1);\n        \/\/ Trimble-style sidecar metadata (e.g., Coverage_Metadata.json) \u2014 not a FeatureCollection,\n        \/\/ but has DataAttributes \/ Product \/ FieldName. Stash by dir for later lookup.\n        var isMeta = (!json.features) ? ((!Array.isArray(json)) ? (json.DataAttributes || json.Product || json.Vendor) : false) : false;\n        if(isMeta){ metadataByDir[dir] = json; return { ok: true, isMeta: true }; }\n        return { ok: true, json: json, name: name, dir: dir };\n      } catch(err){ return { ok: false }; }\n    });\n  }\n  \/\/ ISO 11783-10 (ISOXML) TASKDATA.XML import. Pulls field boundaries from PFD\/PLN\/LSG\/PNT.\n  \/\/ ALSO scans sibling TLGxxxxx.bin files for per-record GPS positions and groups them by TSK,\n  \/\/ emitting one Point dataset per task (the operation's path on the field). Rate \/ dose decoding\n  \/\/ is not standardized across producers \u2014 we surface positions only, which is robust and immediately\n  \/\/ useful (visualize where the tractor drove).\n  \/\/ PLN.A=1 \u2192 polygon exterior; LSG.A=2 \u2192 hole. PNT.C = latitude, D = longitude (decimal degrees).\n  \/\/ PFD.D = field area in m^2. TLG bin: variable-length records, lat at offset 6, lon at offset 10\n  \/\/ within each record. Validation: time uint32 < 86_400_000 (one day), lat\/lon inside field bbox.\n  function readIsoxmlEntry(entry, path, allEntries){\n    return entry.async('string').then(function(s){\n      try {\n        if(s.charCodeAt(0) === 0xFEFF) s = s.slice(1);\n        var doc = new DOMParser().parseFromString(s, 'application\/xml');\n        var perr = doc.getElementsByTagName('parsererror');\n        if(perr.length) throw new Error('XML parse error');\n        var dir = path.substring(0, path.lastIndexOf('\/') + 1);\n        \/\/ ISOXML can be monolithic (everything inline in TASKDATA.XML) OR split via <XFR>\n        \/\/ (External File Reference) \u2014 TASKDATA only lists references, each referenced .XML file\n        \/\/ is wrapped in <XFC>. Topcon Agriculture, John Deere export, and several producers use\n        \/\/ the split format. Resolve XFRs first so the rest of the pipeline reads a single doc.\n        return resolveXfrReferences(doc, dir, allEntries).then(function(){\n          return finishIsoxmlImport(doc, dir, path, allEntries);\n        });\n      } catch(err){\n        try { console.warn('[GPY] ISOXML parse failed:', path, err); } catch(_){}\n        return { ok:false };\n      }\n    });\n  }\n  \/\/ For each <XFR A=\"REFNAME\" B=\"1\"\/> in TASKDATA.XML, fetch the sibling REFNAME.XML, parse it,\n  \/\/ and import its <XFC> children directly into the main TASKDATA document. After this returns,\n  \/\/ doc.getElementsByTagName('PFD'|'TSK'|'TLG'|...) sees everything inline as if the file was\n  \/\/ monolithic. Tolerant of case (.XML\/.xml) and of files anywhere in the archive (the producer\n  \/\/ sometimes puts them in a different folder than TASKDATA.XML).\n  function resolveXfrReferences(doc, dir, allEntries){\n    var xfrs = doc.getElementsByTagName('XFR');\n    if(!xfrs.length) return Promise.resolve();\n    var mainRoot = doc.documentElement;\n    var jobs = [];\n    for(var i=0; i<xfrs.length; i++){\n      (function(refName){\n        if(!refName) return;\n        \/\/ Look for refName.XML (case-insensitive) \u2014 prefer the same dir, fall back to any path\n        var refEntry = null;\n        var preferredPath = (dir + refName + '.XML').toLowerCase();\n        for(var j=0; j<allEntries.length; j++){\n          if(allEntries[j].path.toLowerCase() === preferredPath){ refEntry = allEntries[j].entry; break; }\n        }\n        if(!refEntry){\n          var re = new RegExp('(^|\/)' + refName + '\\\\.XML$', 'i');\n          for(var j2=0; j2<allEntries.length; j2++){\n            \/\/ Skip macOS resource-fork files (paths like __MACOSX\/._FOO.XML)\n            if(\/(^|\\\/)__MACOSX\\\/\/.test(allEntries[j2].path)) continue;\n            if(\/\\\/\\._\/.test(allEntries[j2].path) ? true : \/^\\._\/.test(allEntries[j2].path)) continue;\n            if(re.test(allEntries[j2].path)){ refEntry = allEntries[j2].entry; break; }\n          }\n        }\n        if(!refEntry) return;\n        jobs.push(refEntry.async('string').then(function(sub){\n          if(sub.charCodeAt(0) === 0xFEFF) sub = sub.slice(1);\n          var subDoc = new DOMParser().parseFromString(sub, 'application\/xml');\n          if(subDoc.getElementsByTagName('parsererror').length) return;\n          var subRoot = subDoc.documentElement;\n          if(!subRoot) return;\n          \/\/ Move XFC's children into the main TASKDATA root. For non-XFC roots we still import\n          \/\/ their children (some producers wrap the content in a different element name).\n          var kids = subRoot.children;\n          for(var ci=0; ci<kids.length; ci++){\n            mainRoot.appendChild(doc.importNode(kids[ci], true));\n          }\n        }).catch(function(e){ try { console.warn('[GPY] XFR load failed:', refName, e); } catch(_){} }));\n      })(xfrs[i].getAttribute('A'));\n    }\n    return Promise.all(jobs);\n  }\n  function finishIsoxmlImport(doc, dir, path, allEntries){\n    var boundaryDs = extractIsoxmlBoundaries(doc, dir);\n    var bbox = computeIsoxmlFieldBbox(doc);\n    \/\/ Index TLG bin AND xml entries by their TLG-name (case-insensitive on filename + extension)\n    var tlgBin = {}, tlgXml = {};\n    for(var i=0; i<allEntries.length; i++){\n      var pth = allEntries[i].path;\n      \/\/ Skip macOS resource-fork files\n      if(\/(^|\\\/)__MACOSX\\\/\/.test(pth)) continue;\n      if(\/\\\/\\._\/.test(pth) ? true : \/^\\._\/.test(pth)) continue;\n      var mb = pth.match(\/(?:^|\\\/)(TLG\\d+)\\.bin$\/i);\n      if(mb){ tlgBin[mb[1].toUpperCase()] = allEntries[i].entry; continue; }\n      var mx = pth.match(\/(?:^|\\\/)(TLG\\d+)\\.xml$\/i);\n      if(mx){ tlgXml[mx[1].toUpperCase()] = allEntries[i].entry; }\n    }\n    var tasks = doc.getElementsByTagName('TSK');\n    var taskJobs = [];\n    for(var t=0; t<tasks.length; t++){\n      (function(tsk){\n        var tskId = tsk.getAttribute('A') || 'TSK?';\n        var tskName = tsk.getAttribute('B') || tskId;\n        var tlgs = tsk.getElementsByTagName('TLG');\n        var binJobs = [];\n        for(var u=0; u<tlgs.length; u++){\n          var ref = (tlgs[u].getAttribute('A') || '').toUpperCase();\n          var be = tlgBin[ref];\n          var xe = tlgXml[ref];\n          if(be){\n            \/\/ Load XML (DLV layout) and BIN together. Layout may be null if the sidecar XML is missing\n            \/\/ \u2014 in that case scanTlgPositions still emits position-only points.\n            var layoutJob = xe ? readTlgXml(xe) : Promise.resolve(null);\n            binJobs.push(Promise.all([layoutJob, be.async('arraybuffer')]).then(function(arr){\n              return scanTlgPositions(arr[1], bbox, arr[0]);\n            }).catch(function(){ return []; }));\n          }\n        }\n        taskJobs.push(Promise.all(binJobs).then(function(arr){\n          var pts = [];\n          for(var ai=0; ai<arr.length; ai++){\n            if(arr[ai] ? arr[ai].length : false){\n              for(var pj=0; pj<arr[ai].length; pj++) pts.push(arr[ai][pj]);\n            }\n          }\n          if(!pts.length) return null;\n          \/\/ Union of property keys across all points (delta-encoding means some points have a key\n          \/\/ and others don't \u2014 the dataset pipeline detects numeric columns from sampled features).\n          var feats = new Array(pts.length);\n          for(var pk=0; pk<pts.length; pk++){\n            var p = pts[pk];\n            var props = { _index: pk, time_ms: p.time };\n            for(var k in p){\n              if(k === 'time' ? true : k === 'lat' ? true : k === 'lon') continue;\n              props[k] = p[k];\n            }\n            feats[pk] = {\n              type: 'Feature',\n              geometry: { type:'Point', coordinates: [p.lon, p.lat] },\n              properties: props\n            };\n          }\n          try { console.warn('[GPY] ISOXML task track:', tskName, pts.length, 'points'); } catch(_){}\n          return {\n            fc: { type:'FeatureCollection', features: feats },\n            name: tskName + ' (' + pts.length + ' pts)',\n            dir: dir,\n            _isTrack: true\n          };\n        }));\n      })(tasks[t]);\n    }\n    return Promise.all(taskJobs).then(function(trackDs){\n      var datasets = boundaryDs.slice();\n      for(var d=0; d<trackDs.length; d++){\n        if(trackDs[d]) datasets.push(trackDs[d]);\n      }\n      try { console.warn('[GPY] ISOXML import done:', boundaryDs.length, 'boundary +', trackDs.filter(function(x){return x;}).length, 'task datasets'); } catch(_){}\n      return { ok:true, isoxmlDatasets: datasets, path: path };\n    });\n  }\n  \/\/ Build a degree-bounded bbox from PNT coordinates with a 0.1\u00b0 pad. Used to validate TLG GPS hits.\n  function computeIsoxmlFieldBbox(doc){\n    var minLat = Infinity, maxLat = -Infinity, minLon = Infinity, maxLon = -Infinity;\n    var pnts = doc.getElementsByTagName('PNT');\n    for(var i=0; i<pnts.length; i++){\n      var lat = parseFloat(pnts[i].getAttribute('C'));\n      var lon = parseFloat(pnts[i].getAttribute('D'));\n      if(isFinite(lat) ? isFinite(lon) : false){\n        if(lat < minLat) minLat = lat;\n        if(lat > maxLat) maxLat = lat;\n        if(lon < minLon) minLon = lon;\n        if(lon > maxLon) maxLon = lon;\n      }\n    }\n    if(!isFinite(minLat)) return null;\n    return {\n      latMinE7: Math.round((minLat - 0.1) * 1e7),\n      latMaxE7: Math.round((maxLat + 0.1) * 1e7),\n      lonMinE7: Math.round((minLon - 0.1) * 1e7),\n      lonMaxE7: Math.round((maxLon + 0.1) * 1e7)\n    };\n  }\n  \/\/ ISO 11783-10 DDI (Data Dictionary Identifier) \u2014 the most common identifiers seen in real ag\n  \/\/ exports. Each entry: human label, raw\u2192real scale factor, and unit suffix for the legend.\n  \/\/ Unknown DDIs fall back to \"DDI_xxxx\" with no scale; users can still pick them.\n  var DDI_KNOWN = {\n    '0006':{label:'Target Rate',           scale:0.01,   unit:'kg\/ha'},\n    '0007':{label:'Applied Rate',          scale:0.01,   unit:'kg\/ha'},\n    '0043':{label:'Working Width',         scale:0.001,  unit:'m'},\n    '0046':{label:'Setpoint Width',        scale:0.001,  unit:'m'},\n    '005A':{label:'Yield Total',           scale:1,      unit:'kg'},\n    '0074':{label:'Total Area',            scale:0.0001, unit:'ha'},\n    '0075':{label:'Effective Distance',    scale:0.001,  unit:'m'},\n    '0076':{label:'Ineffective Distance',  scale:0.001,  unit:'m'},\n    '0077':{label:'Effective Time',        scale:0.001,  unit:'s'},\n    '0078':{label:'Ineffective Time',      scale:0.001,  unit:'s'},\n    '0086':{label:'Offset X',              scale:0.001,  unit:'m'},\n    '0087':{label:'Offset Y',              scale:0.001,  unit:'m'},\n    '008D':{label:'Work State',            scale:1,      unit:''},\n    '0090':{label:'GNSS Type',             scale:1,      unit:''},\n    '0091':{label:'GNSS UTC Date',         scale:1,      unit:'d'},\n    '0092':{label:'GNSS UTC Time',         scale:1,      unit:'ms'},\n    '00A0':{label:'Workstate 1-8',         scale:1,      unit:''},\n    '00A1':{label:'Workstate 9-16',        scale:1,      unit:''},\n    '00A2':{label:'Workstate 17-24',       scale:1,      unit:''},\n    '00B7':{label:'Yield Mass Wet',        scale:1,      unit:'kg'},\n    '00B8':{label:'Header Width',          scale:0.001,  unit:'m'},\n    '0105':{label:'Wet Mass Yield',        scale:0.001,  unit:'t'},\n    '0106':{label:'Dry Mass Yield',        scale:0.001,  unit:'t'},\n    '0107':{label:'Wet Yield per Area',    scale:0.01,   unit:'t\/ha'},\n    '0166':{label:'Yield Volume',          scale:0.001,  unit:'L'},\n    '0167':{label:'Yield Volume per Area', scale:0.001,  unit:'L\/ha'},\n    '018D':{label:'Driving Speed',         scale:0.001,  unit:'m\/s'},\n    '0198':{label:'Crop Type',             scale:1,      unit:''},\n    '01D2':{label:'Crop Moisture',         scale:0.001,  unit:'%'}\n  };\n  function ddiInfo(ddi){\n    if(!ddi) return null;\n    var key = String(ddi).toUpperCase();\n    while(key.length < 4) key = '0' + key;\n    return DDI_KNOWN[key] || null;\n  }\n  \/\/ Read a TLG sidecar XML (e.g. TLG00013.XML next to TLG00013.BIN). Returns the ordered DLV list\n  \/\/ PLUS the per-record binary layout. ISO 11783-10:2015 \u00a78.6.3 + Table 3:\n  \/\/   - Empty attributes in the XML are recorded in the bin, in the order TIM.A (time, date),\n  \/\/     then PTN.A-I (lat, lon, up, status, pdop, hdop, nsat, gpsutc-time, gpsutc-date).\n  \/\/   - Non-empty XML values are constants applied to every record (NOT in bin).\n  \/\/   - Then 1 byte #DLV count, then count \u00d7 (idx_byte + int32_value) DLV records.\n  \/\/\n  \/\/ PTN.A field meanings (NOT time! \u2014 TIM.A is time, PTN.A is PositionNorth):\n  \/\/   A=PositionNorth  B=PositionEast  C=PositionUp  D=PositionStatus\n  \/\/   E=PDOP           F=HDOP          G=NSats       H=GpsUtcTime  I=GpsUtcDate\n  function readTlgXml(entry){\n    return entry.async('string').then(function(s){\n      if(s.charCodeAt(0) === 0xFEFF) s = s.slice(1);\n      var doc = new DOMParser().parseFromString(s, 'application\/xml');\n      if(doc.getElementsByTagName('parsererror').length) return null;\n      var layout = computeTlgBinLayout(doc);\n      var dlvs = doc.getElementsByTagName('DLV');\n      var ddiCount = {};\n      var list = [];\n      for(var i=0; i<dlvs.length; i++){\n        var ddi = (dlvs[i].getAttribute('A') || '').toUpperCase();\n        while(ddi.length < 4) ddi = '0' + ddi;\n        var det = dlvs[i].getAttribute('C') || '';\n        list.push({ ddi: ddi, det: det });\n        ddiCount[ddi] = (ddiCount[ddi] || 0) + 1;\n      }\n      for(var j=0; j<list.length; j++){\n        var info = DDI_KNOWN[list[j].ddi];\n        var base = info ? info.label : ('DDI_' + list[j].ddi);\n        if(ddiCount[list[j].ddi] > 1 ? list[j].det : false) base += ' (' + list[j].det + ')';\n        list[j].propName = base;\n        list[j].scale = info ? info.scale : 1;\n        list[j].unit = info ? info.unit : '';\n      }\n      layout.dlvList = list;\n      return layout;\n    }).catch(function(){ return null; });\n  }\n  function computeTlgBinLayout(doc){\n    var L = {\n      timeOff:-1, dateOff:-1, latOff:-1, lonOff:-1, upOff:-1,\n      statusOff:-1, pdopOff:-1, hdopOff:-1, nsatOff:-1,\n      utcTimeOff:-1, utcDateOff:-1,\n      countOff:-1, headerSize:0,\n      dlvList:null\n    };\n    var off = 0;\n    var tim = doc.getElementsByTagName('TIM')[0];\n    \/\/ TIM.A empty \u2192 time-of-day (uint32, 4) + date (uint16, 2) are both recorded\n    if(tim ? tim.getAttribute('A') === '' : false){\n      L.timeOff = off; off += 4;\n      L.dateOff = off; off += 2;\n    }\n    var ptn = doc.getElementsByTagName('PTN')[0];\n    if(ptn){\n      \/\/ Map ISO 11783-10 Table 3 (in order): attr name \u2192 field, byte width\n      var attrs = [\n        ['A', 4, 'latOff'],     \/\/ PositionNorth\n        ['B', 4, 'lonOff'],     \/\/ PositionEast\n        ['C', 4, 'upOff'],      \/\/ PositionUp\n        ['D', 1, 'statusOff'],  \/\/ PositionStatus\n        ['E', 2, 'pdopOff'],    \/\/ PDOP \u00d7 10\n        ['F', 2, 'hdopOff'],    \/\/ HDOP \u00d7 10\n        ['G', 1, 'nsatOff'],    \/\/ NumberOfSatellites\n        ['H', 4, 'utcTimeOff'], \/\/ GpsUtcTime (UTC ms since midnight)\n        ['I', 2, 'utcDateOff']  \/\/ GpsUtcDate (UTC days since 1980-01-01)\n      ];\n      for(var a=0; a<attrs.length; a++){\n        if(ptn.getAttribute(attrs[a][0]) === ''){\n          L[attrs[a][2]] = off;\n          off += attrs[a][1];\n        }\n      }\n    }\n    L.countOff = off;\n    L.headerSize = off + 1;\n    return L;\n  }\n  \/\/ Walks a TLG bin file emitting Point records with per-record DLV (Data Log Value) properties.\n  \/\/ Spec-compliant: uses the layout computed from the TLG sidecar XML (see computeTlgBinLayout)\n  \/\/ for header field offsets \u2014 different ISOXML producers record different PTN attributes, so\n  \/\/ record sizes vary. ISO 11783-10:2015 \u00a78.6.3 + Table 3.\n  \/\/\n  \/\/ Records are delta-encoded \u2014 most records carry 0 DLVs (just position). The parser maintains a\n  \/\/ running DLV state and snapshots it into every emitted point so the feature collection has a\n  \/\/ consistent property set across all records (required for the numeric-column detector).\n  function scanTlgPositions(arrayBuf, bbox, layout){\n    if(!bbox) return [];\n    var dv = new DataView(arrayBuf);\n    var len = arrayBuf.byteLength;\n    var pts = [];\n    var state = {};   \/\/ running DLV state: idx \u2192 raw int32 value\n    var lastLat = 0, lastLon = 0;\n    \/\/ If we have an XML-derived layout, use it. Otherwise fall back to the heuristic (lat at offset 6).\n    var hasLayout = layout ? layout.latOff >= 0 ? layout.lonOff >= 0 : false : false;\n    var latOff = hasLayout ? layout.latOff : 6;\n    var lonOff = hasLayout ? layout.lonOff : 10;\n    var timeOff = hasLayout ? layout.timeOff : 0;\n    var countOff = hasLayout ? layout.countOff : 30;\n    var headerSize = hasLayout ? layout.headerSize : 31;\n    var dlvList = (hasLayout ? layout.dlvList : null) || [];\n    var dlvN = dlvList.length;\n    function isValidPos(off){\n      if(off + headerSize > len) return false;\n      if(timeOff >= 0){\n        var t = dv.getUint32(off + timeOff, true);\n        if(t > 86400000) return false;\n      }\n      var la = dv.getInt32(off + latOff, true);\n      if(la < bbox.latMinE7 ? true : la > bbox.latMaxE7) return false;\n      var lo = dv.getInt32(off + lonOff, true);\n      if(lo < bbox.lonMinE7 ? true : lo > bbox.lonMaxE7) return false;\n      return true;\n    }\n    var i = 0;\n    while(i + headerSize <= len){\n      if(!isValidPos(i)){ i++; continue; }\n      var t = timeOff >= 0 ? dv.getUint32(i + timeOff, true) : 0;\n      var lat = dv.getInt32(i + latOff, true);\n      var lon = dv.getInt32(i + lonOff, true);\n      \/\/ Read DLV count + records (validate by next-record alignment)\n      var advancedBy = 1;\n      var validatedDlvs = null;\n      if(hasLayout ? dlvN > 0 : false){\n        var cnt = dv.getUint8(i + countOff);\n        if(cnt < 40 ? i + headerSize + cnt * 5 <= len : false){\n          var allIdxOk = true;\n          for(var dj=0; dj<cnt; dj++){\n            var idx = dv.getUint8(i + headerSize + dj * 5);\n            if(idx >= dlvN){ allIdxOk = false; break; }\n          }\n          if(allIdxOk){\n            var nextOff = i + headerSize + cnt * 5;\n            \/\/ Validate: next record should be at expected offset (or EOF)\n            if(nextOff + headerSize > len ? true : isValidPos(nextOff)){\n              validatedDlvs = [];\n              for(var dk=0; dk<cnt; dk++){\n                var iidx = dv.getUint8(i + headerSize + dk * 5);\n                var ival = dv.getInt32(i + headerSize + dk * 5 + 1, true);\n                validatedDlvs.push({ idx: iidx, val: ival });\n              }\n              advancedBy = headerSize + cnt * 5;\n            }\n          }\n        }\n      }\n      \/\/ Apply DLV updates to running state (delta encoding)\n      if(validatedDlvs){\n        for(var dl=0; dl<validatedDlvs.length; dl++){\n          state[validatedDlvs[dl].idx] = validatedDlvs[dl].val;\n        }\n      }\n      \/\/ De-dup consecutive same-position records ONLY when they carry no new DLV data \u2014 otherwise\n      \/\/ we'd drop the records where a stationary harvester is still accumulating yield totals.\n      var hasNewData = validatedDlvs ? validatedDlvs.length > 0 : false;\n      if(lat === lastLat ? lon === lastLon : false){\n        if(!hasNewData){ i += advancedBy; continue; }\n      }\n      var props = { time: t, lat: lat \/ 1e7, lon: lon \/ 1e7 };\n      for(var pi=0; pi<dlvN; pi++){\n        if(state[pi] !== undefined){\n          var ent = dlvList[pi];\n          props[ent.propName] = state[pi] * ent.scale;\n        }\n      }\n      pts.push(props);\n      lastLat = lat; lastLon = lon;\n      i += advancedBy;\n    }\n    return pts;\n  }\n  function extractIsoxmlBoundaries(doc, dir){\n    var out = [];\n    var pfds = doc.getElementsByTagName('PFD');\n    for(var i=0; i<pfds.length; i++){\n      var pfd = pfds[i];\n      var fieldId = pfd.getAttribute('A') || ('PFD'+(i+1));\n      var fieldName = pfd.getAttribute('C') || fieldId;\n      var fieldAreaM2 = parseFloat(pfd.getAttribute('D') || '0');\n      var feats = [];\n      \/\/ Group LSGs by parent PLN to build Polygons with holes (interior rings).\n      var plns = pfd.getElementsByTagName('PLN');\n      for(var p=0; p<plns.length; p++){\n        var pln = plns[p];\n        \/\/ PLN.A: 1=Boundary, 2=TreatmentZone, 3=WaterSurface, ... \u2014 only render boundary-type for now\n        var plnType = pln.getAttribute('A') || '1';\n        if(plnType !== '1') continue;\n        var plnName = pln.getAttribute('B') || ('PLN'+(p+1));\n        var plnArea = parseFloat(pln.getAttribute('C') || '0');\n        var exterior = null;\n        var holes = [];\n        var lsgs = pln.getElementsByTagName('LSG');\n        for(var l=0; l<lsgs.length; l++){\n          var lsg = lsgs[l];\n          \/\/ LSG.A: 1=PolygonExterior, 2=PolygonInterior, 5\/6=LineStrings (skipped here)\n          var lsgType = lsg.getAttribute('A');\n          var isExt = lsgType === '1';\n          var isInt = lsgType === '2';\n          if(!isExt ? !isInt : false) continue;\n          var pts = lsg.getElementsByTagName('PNT');\n          var coords = [];\n          for(var nn=0; nn<pts.length; nn++){\n            var pnt = pts[nn];\n            var lat = parseFloat(pnt.getAttribute('C'));\n            var lon = parseFloat(pnt.getAttribute('D'));\n            if(isFinite(lat) ? isFinite(lon) : false){\n              coords.push([lon, lat]);\n            }\n          }\n          if(coords.length < 3) continue;\n          \/\/ Close ring if needed\n          var f0 = coords[0], fL = coords[coords.length-1];\n          if(f0[0] !== fL[0] ? true : f0[1] !== fL[1]) coords.push([f0[0], f0[1]]);\n          if(isExt) exterior = coords;\n          else holes.push(coords);\n        }\n        if(!exterior) continue;\n        var rings = [exterior];\n        for(var hi=0; hi<holes.length; hi++) rings.push(holes[hi]);\n        feats.push({\n          type: 'Feature',\n          properties: {\n            PartfieldDesignator: fieldName,\n            PartfieldId: fieldId,\n            PLNName: plnName,\n            PLNType: plnType,\n            AreaHa: plnArea > 0 ? plnArea \/ 10000 : 0\n          },\n          geometry: { type: 'Polygon', coordinates: rings }\n        });\n      }\n      if(!feats.length) continue;\n      out.push({\n        fc: { type:'FeatureCollection', features: feats },\n        name: fieldName + ' \u2014 Field Boundary',\n        dir: dir,\n        fieldName: fieldName,\n        fieldId: fieldId,\n        fieldAreaHa: fieldAreaM2 > 0 ? fieldAreaM2 \/ 10000 : 0\n      });\n    }\n    return out;\n  }\n  function isBoundaryByName(name){\n    \/\/ Files with zone-like keywords are categorical classifications, NOT boundaries \u2014\n    \/\/ even if the filename starts with \"Field_\" (e.g. \"Field_Potential_GP\",\n    \/\/ \"Field_Productivity_2024.shp\"). These need fills, not just outlines.\n    if(\/zone|potential|productivity|management|prescription|vra|prod[_\\- ]?zone|class|cluster|grade\/i.test(name)) return false;\n    return \/(^|[\\\/_\\- ])boundary(\\.|$|[_\\- ])|^field(\\.|\\s|$)|^field[_\\- ]?(boundary|outline|edge|border|area|aoi)|field[_\\- ]?boundary|partfield\/i.test(name);\n  }\n  \/\/ Geometry-based detection was creating false positives (e.g., AgGPS \"AreaFeature\" with 1\u20133 polygons).\n  \/\/ Filename rules: explicit \"boundary\" wins; \"Field\" prefix only matches the bare word or with\n  \/\/ explicit boundary suffixes; zone-like keywords (see above) block boundary classification.\n  function computeBbox(features){\n    var minX = Infinity, minY = Infinity, maxX = -Infinity, maxY = -Infinity;\n    function visit(coords){\n      if(!coords) return;\n      if(typeof coords[0] === 'number'){\n        if(coords[0]<minX) minX=coords[0]; if(coords[0]>maxX) maxX=coords[0];\n        if(coords[1]<minY) minY=coords[1]; if(coords[1]>maxY) maxY=coords[1];\n      } else {\n        for(var i=0;i<coords.length;i++) visit(coords[i]);\n      }\n    }\n    for(var j=0;j<features.length;j++){\n      if(features[j] ? features[j].geometry : false) visit(features[j].geometry.coordinates);\n    }\n    if(!isFinite(minX)) return null;\n    return [minX, minY, maxX, maxY];\n  }\n  function bboxOverlapFrac(a, b){\n    \/\/ returns overlap_area(a\u2229b) \/ area(a) in [0,1]\n    if(!a || !b) return 0;\n    if(a[0] >= b[2] || a[2] <= b[0]) return 0;\n    if(a[1] >= b[3] || a[3] <= b[1]) return 0;\n    var ix = Math.max(a[0], b[0]), iy = Math.max(a[1], b[1]);\n    var ax = Math.min(a[2], b[2]), ay = Math.min(a[3], b[3]);\n    var inter = Math.max(0, ax-ix) * Math.max(0, ay-iy);\n    var aArea = Math.max(1e-12, (a[2]-a[0]) * (a[3]-a[1]));\n    return inter \/ aArea;\n  }\n  function totalPolygonAreaHa(features){\n    var total = 0;\n    for(var i=0;i<features.length;i++){\n      var g = features[i].geometry;\n      if(!g) continue;\n      if(g.type === 'Polygon'){\n        for(var ri=0;ri<g.coordinates.length;ri++){\n          total += (ri === 0 ? 1 : -1) * ringAreaHa(g.coordinates[ri]);\n        }\n      } else if(g.type === 'MultiPolygon'){\n        for(var pi=0;pi<g.coordinates.length;pi++){\n          for(var rj=0;rj<g.coordinates[pi].length;rj++){\n            total += (rj === 0 ? 1 : -1) * ringAreaHa(g.coordinates[pi][rj]);\n          }\n        }\n      }\n    }\n    return Math.max(0, total);\n  }\n  \/\/ Convert ISO 11783-10 \/ Trimble unit codes like \"kg1ha-1\" to display strings (\"kg\/ha\")\n  function decodeUnit(u){\n    if(!u) return '';\n    var direct = { 'prcnt':'%', 'C':'\u00b0C', 'm':'m', 'm2':'m\u00b2', 'ha':'ha' };\n    if(direct[u]) return direct[u];\n    var parts = String(u).match(\/[A-Za-z]+|-?\\d+\/g);\n    if(!parts || !parts.length) return String(u);\n    var num = [], den = [];\n    for(var i=0;i<parts.length;){\n      var unit = parts[i++];\n      var exp = 1;\n      if(i < parts.length ? \/^-?\\d+$\/.test(parts[i]) : false){ exp = parseInt(parts[i++], 10); }\n      if(exp > 0) num.push(unit + (exp === 1 ? '' : '^' + exp));\n      else if(exp < 0) den.push(unit + (exp === -1 ? '' : '^' + (-exp)));\n    }\n    var s = num.length ? num.join('\u00b7') : '1';\n    if(den.length) s += '\/' + den.join('\u00b7');\n    return s;\n  }\n  \/\/ Derive a field\/farm name from a directory path. Skip generic + operation\/crop dir names.\n  function deriveFieldName(dir){\n    if(!dir) return null;\n    var parts = String(dir).split('\/').filter(function(s){ return s; });\n    if(!parts.length) return null;\n    \/\/ Generic structural folders + common operation\/crop type names (EN + UK)\n    var skip = \/^(data|aggps|tasks?|files?|samples?|root|task|taskdata|prescriptions?|coverage|cover|harvest|planting|seeding|sowing|spraying|application|applied|\u043f\u043e\u0441\u0430\u0434\u043a\u0430|\u0441\u0456\u0432\u0431\u0430|\u0437\u0431\u0456\u0440|\u0437\u0431\u0438\u0440\u0430\u043d\u043d\u044f|\u043e\u0431\u043f\u0440\u0438\u0441\u043a\u0443\u0432\u0430\u043d\u043d\u044f|\u043f\u0440\u0438\u043c\u0435\u043d\u0435\u043d\u0438\u0435|\u043e\u0431\u0440\u0430\u0431\u043e\u0442\u043a\u0430)$\/i;\n    var zipExt = \/\\.zip$\/i;\n    for(var i=parts.length-1; i>=0; i--){\n      var p = parts[i];\n      if(zipExt.test(p)) continue;\n      if(skip.test(p)) continue;\n      return p;\n    }\n    return null;\n  }\n  \/\/ Scan dataset properties for product\/operation hints. Returns ALL distinct product values found\n  \/\/ (so mixed-material Coverage shapefiles surface as \"\u043a\u0443\u043a\u0443\u0440\u0443\u0434\u0437\u0430 + \u041a\u0430\u0440\u0431\u0430\u043c\u0456\u0434\" \u2014 a signal that the data\n  \/\/ contains two operations and statistical outlier detection will be unreliable on the combined set).\n  function inferProduct(features){\n    if(!features || !features.length) return null;\n    var prodKeys = ['Material', 'Product', 'ProductName', 'Product_Name', 'MATERIAL', 'PRODUCT'];\n    var seen = {};\n    var limit = Math.min(features.length, 1000);\n    for(var i=0;i<limit;i++){\n      var p = features[i].properties || {};\n      for(var k=0;k<prodKeys.length;k++){\n        var v = p[prodKeys[k]];\n        if(typeof v === 'string' ? v.length > 0 : false){\n          if(v !== '---') seen[v] = true;\n        }\n      }\n    }\n    var list = Object.keys(seen);\n    if(!list.length) return null;\n    if(list.length === 1) return list[0];\n    return list.join(' + ');\n  }\n  function makeDataset(fc, name, source, dir){\n    var feats = fc.features || (Array.isArray(fc) ? fc : []);\n    var pts = [], geomType = null;\n    for(var i=0;i<feats.length;i++){\n      var f = feats[i];\n      if(!f || !f.geometry) continue;\n      var t = f.geometry.type;\n      if(t === 'Point'){\n        var c = f.geometry.coordinates;\n        if(!c || typeof c[0] !== 'number' || typeof c[1] !== 'number') continue;\n        if(geomType === null) geomType = 'point';\n        if(geomType === 'point') pts.push(f);\n      } else if(t === 'Polygon' || t === 'MultiPolygon'){\n        if(geomType === null) geomType = 'polygon';\n        if(geomType === 'polygon') pts.push(f);\n      } else if(t === 'LineString' || t === 'MultiLineString'){\n        \/\/ Trimble exports often include Swath \/ AB Line shapefiles (guidance + applied-path lines)\n        if(geomType === null) geomType = 'line';\n        if(geomType === 'line') pts.push(f);\n      }\n    }\n    if(!pts.length) return null;\n    var ds = {\n      id: 'ds-' + (++datasetCounter),\n      name: String(name || 'Layer'),\n      source: String(source || name || ''),\n      dir: String(dir || ''),\n      geomType: geomType,\n      features: pts,\n      bbox: computeBbox(pts),\n      areaHa: geomType === 'polygon' ? totalPolygonAreaHa(pts) : 0,\n      parentId: null,\n      isBoundary: false,\n      fieldName: deriveFieldName(dir),\n      product: null,\n      unitMap: {}\n    };\n    ds.isBoundary = isBoundaryByName(ds.name);\n    \/\/ Seed units auto-detected from CSV \/ Excel header labels (csvToFeatureCollection\n    \/\/ attaches fc.__unitMap). Sibling metadata below can still override per-column.\n    if(fc ? fc.__unitMap : false){\n      for(var uk in fc.__unitMap){ if(fc.__unitMap.hasOwnProperty(uk)) ds.unitMap[uk] = fc.__unitMap[uk]; }\n    }\n    \/\/ For coverage \/ application \/ swath layers, try to guess the product\n    if(\/coverage|appl|seed|plant|swath\/i.test(ds.name)){\n      ds.product = inferProduct(pts);\n    }\n    \/\/ Pull units from sibling metadata json (e.g., Trimble Coverage_Metadata.json)\n    var meta = metadataByDir[ds.dir];\n    if(meta){\n      if(meta.DataAttributes ? meta.DataAttributes.length : false){\n        for(var ai=0;ai<meta.DataAttributes.length;ai++){\n          var att = meta.DataAttributes[ai];\n          if(att.Name ? att.Unit : false) ds.unitMap[att.Name] = decodeUnit(att.Unit);\n        }\n      }\n      if(meta.Product ? meta.Product.ProductName : false){\n        var pn = meta.Product.ProductName;\n        if(pn ? pn !== '---' : false) ds.product = pn;\n      }\n      if(meta.FieldName ? !ds.fieldName : false) ds.fieldName = meta.FieldName;\n    }\n    return ds;\n  }\n  \/\/ Split a single dataset into multiple if its Material\/Product column has more than one\n  \/\/ distinct non-empty value. Each split inherits the parent's boundary \/ field attachment.\n  \/\/ This handles the Trimble case where one Coverage.shp aggregates planting + fertilizing in\n  \/\/ the same file \u2014 the user wants to see them as separate layers, each with its own range.\n  function splitByMaterial(ds){\n    if(!ds) return [];\n    if(!ds.features.length) return [ds];\n    var matKey = null;\n    var probeKeys = ['Material','Product','ProductName','MATERIAL','PRODUCT'];\n    var p0 = ds.features[0].properties || {};\n    for(var k=0;k<probeKeys.length;k++){\n      if(p0[probeKeys[k]] !== undefined){ matKey = probeKeys[k]; break; }\n    }\n    if(!matKey) return [ds];\n    var groups = {};\n    for(var i=0;i<ds.features.length;i++){\n      var v = ds.features[i].properties[matKey];\n      var key = (typeof v === 'string' ? v : '') || '(no material)';\n      if(key === '---' || key === '') key = '(no material)';\n      if(!groups[key]) groups[key] = [];\n      groups[key].push(ds.features[i]);\n    }\n    var matNames = Object.keys(groups);\n    if(matNames.length <= 1) return [ds]; \/\/ single material \u2014 no split needed\n    var out = [];\n    for(var mi=0; mi<matNames.length; mi++){\n      var mname = matNames[mi];\n      var feats = groups[mname];\n      \/\/ Drop tiny stray groups (likely sensor glitches recording one wrong material)\n      if(feats.length < 3) continue;\n      var subName = ds.name + ' \u2014 ' + mname;\n      var sub = makeDataset({ type:'FeatureCollection', features: feats }, subName, ds.source, ds.dir);\n      if(sub){\n        sub.parentId = ds.parentId;\n        sub.fieldName = ds.fieldName;\n        sub.product = mname === '(no material)' ? null : mname;\n        sub.isBoundary = ds.isBoundary;\n        out.push(sub);\n      }\n    }\n    if(!out.length) return [ds];\n    try { console.warn('[GPY] auto-split \"'+ds.name+'\" by '+matKey+' into '+out.length+' layers: '+matNames.join(', ')); } catch(_){}\n    return out;\n  }\n  function attachToBoundaries(newDatasets){\n    var boundaries = [];\n    var others = [];\n    for(var i=0;i<newDatasets.length;i++){\n      (newDatasets[i].isBoundary ? boundaries : others).push(newDatasets[i]);\n    }\n    if(!boundaries.length) return;\n    for(var j=0;j<others.length;j++){\n      var ds = others[j];\n      var best = null, bestOv = 0;\n      for(var k=0;k<boundaries.length;k++){\n        var b = boundaries[k];\n        var ov = bboxOverlapFrac(ds.bbox, b.bbox);\n        if(ov > bestOv){ bestOv = ov; best = b; }\n      }\n      if(best ? bestOv >= 0.5 : false){\n        ds.parentId = best.id;\n        \/\/ Inherit the boundary's field name (often more accurate than the child's own path-derived guess)\n        if(best.fieldName) ds.fieldName = best.fieldName;\n      }\n    }\n  }\n  function addDatasets(newDatasets){\n    if(!newDatasets || !newDatasets.length) return;\n    attachToBoundaries(newDatasets);\n    for(var i=0;i<newDatasets.length;i++) datasets.push(newDatasets[i]);\n    renderTree();\n  }\n  function escHTML(s){\n    \/\/ Avoid the literal ampersand char anywhere in this function (WP convert_chars encodes it to numeric entity inside scripts).\n    return String(s)\n      .replace(\/[\\u0026]\/g, '\\u0026amp;')\n      .replace(\/<\/g, '\\u0026lt;')\n      .replace(\/>\/g, '\\u0026gt;')\n      .replace(\/\"\/g, '\\u0026quot;');\n  }\n  function renderTree(){\n    var root = $('#gpy-tree');\n    if(!root) return;\n    if(!datasets.length){\n      root.innerHTML = '<div class=\"gpy-tree-empty\">Drop a file or pick a sample.<\/div>';\n      return;\n    }\n    var children = {};\n    var roots = [];\n    for(var i=0;i<datasets.length;i++){\n      var d = datasets[i];\n      if(d.parentId){\n        if(!children[d.parentId]) children[d.parentId] = [];\n        children[d.parentId].push(d);\n      } else {\n        roots.push(d);\n      }\n    }\n    function nodeHTML(d, depth){\n      var on = d.id === activeDatasetId ? ' is-active' : '';\n      var isB = d.isBoundary ? ' is-boundary' : '';\n      var glyph = d.geomType === 'polygon' ? '\u25a5' : (d.geomType === 'line' ? '\u223f' : '\u2022');\n      var unitLbl = d.geomType === 'polygon' ? ' poly' : (d.geomType === 'line' ? ' lines' : ' pts');\n      var meta = d.features.length + unitLbl;\n      if(d.geomType === 'polygon' ? d.areaHa > 0 : false){\n        meta += ' \u00b7 ' + (d.areaHa < 10 ? d.areaHa.toFixed(2) : Math.round(d.areaHa)) + ' ha';\n      }\n      \/\/ Label: for boundaries use the parent field name when we have one;\n      \/\/ for non-boundaries with a product hint, append it to the layer name.\n      var label = d.name;\n      if(d.isBoundary ? d.fieldName : false) label = d.fieldName;\n      else if(d.product) label = d.name + ' \u2014 ' + d.product;\n      \/\/ Tooltip: full source path + dir + extras\n      var title = d.source;\n      if(d.dir) title += '\\n' + d.dir;\n      if(d.fieldName ? d.fieldName !== label : false) title += '\\nField: ' + d.fieldName;\n      if(d.product ? d.product !== label : false) title += '\\nProduct: ' + d.product;\n      var pad = 8 + depth*14;\n      \/\/ <button> instead of <div> so single-click fires reliably across browsers \/ inside Gutenberg blocks\n      \/\/ (divs can swallow the first click for focus when nested in WP block editors).\n      var s = '<button type=\"button\" class=\"gpy-tree-node'+on+isB+'\" data-id=\"'+d.id+'\" style=\"padding-left:'+pad+'px\" title=\"'+escHTML(title)+'\">';\n      s +=    '<span class=\"gpy-tree-glyph\">'+glyph+'<\/span>';\n      s +=    '<span class=\"gpy-tree-name\">'+escHTML(label)+'<\/span>';\n      s +=    '<span class=\"gpy-tree-meta\">'+meta+'<\/span>';\n      s +=    '<\/button>';\n      var kids = children[d.id] || [];\n      for(var ci=0;ci<kids.length;ci++) s += nodeHTML(kids[ci], depth+1);\n      return s;\n    }\n    var html = '';\n    for(var i2=0;i2<roots.length;i2++) html += nodeHTML(roots[i2], 0);\n    root.innerHTML = html;\n    var nodes = root.querySelectorAll('.gpy-tree-node');\n    for(var n=0;n<nodes.length;n++){\n      (function(el){\n        el.addEventListener('click', function(){ activateDataset(el.getAttribute('data-id')); });\n      })(nodes[n]);\n    }\n  }\n  function activateDataset(id){\n    var ds = null;\n    for(var i=0;i<datasets.length;i++){ if(datasets[i].id === id){ ds = datasets[i]; break; } }\n    if(!ds) return;\n    \/\/ UX redirect: when the user clicks a boundary\/parent dataset (the field name in\n    \/\/ the tree), automatically activate the first as-applied \/ as-planted polygon\n    \/\/ child so the playback simulation has real coverage data to work with. A bare\n    \/\/ boundary outline isn't useful for playback. Match by name pattern \u2014 Trimble\n    \/\/ and most ag tools name these \"Coverage \u2014 <product>\" or \"As-applied \u2026\" etc.\n    if(ds.isBoundary){\n      var preferRe = \/coverage|as[\\s-]?applied|as[\\s-]?planted|application|seeding|spraying|harvest|yield|tillage\/i;\n      var pick = null;\n      for(var cI=0; cI<datasets.length; cI++){\n        var ch = datasets[cI];\n        if(ch.parentId !== ds.id) continue;\n        if(ch.isBoundary) continue;\n        if(ch.geomType !== 'polygon') continue;\n        if(preferRe.test(ch.name)){ pick = ch; break; }\n      }\n      \/\/ Fallback: any non-boundary polygon child wins over the bare boundary.\n      if(!pick){\n        for(var cI2=0; cI2<datasets.length; cI2++){\n          var ch2 = datasets[cI2];\n          if(ch2.parentId !== ds.id) continue;\n          if(ch2.isBoundary) continue;\n          if(ch2.geomType !== 'polygon') continue;\n          pick = ch2;\n          break;\n        }\n      }\n      if(pick){\n        ds = pick;\n        id = pick.id;\n      }\n    }\n    activeDatasetId = id;\n    currentIsBoundary = !!ds.isBoundary;\n    \/\/ Reset user overrides on each dataset switch so the new layer auto-fits its own range.\n    for(var so=0; so<stopValueOverrides.length; so++) stopValueOverrides[so] = null;\n    var resetBtn0 = $('#gpy-l-reset');\n    if(resetBtn0) resetBtn0.classList.remove('show');\n    \/\/ Default sigmaK: 3 across the board (conservative outlier flagging by\n    \/\/ default \u2014 users can tighten to 1\u03c3 \/ 2\u03c3 for noisy datasets).\n    if(!ds.isBoundary){\n      sigmaK = 3;\n      var sigBtns2 = root.querySelectorAll('#gpy-sig button');\n      for(var b=0;b<sigBtns2.length;b++){\n        var sb = sigBtns2[b];\n        sb.classList.toggle('on', +sb.dataset.k === sigmaK);\n      }\n    }\n    if(ds._isSample){\n      loadGeoJSON({ type:'FeatureCollection', features: ds.features }, ds.name, true, ds.name);\n    } else {\n      loadGeoJSON({ type:'FeatureCollection', features: ds.features }, ds.name, false);\n    }\n    \/\/ After loadGeoJSON has picked currentCol: override currentUnit from sibling metadata if known\n    if(ds.unitMap ? ds.unitMap[currentCol] : false){\n      currentUnit = ds.unitMap[currentCol];\n      \/\/ Re-render legend title with the new unit\n      var legendTitle = $('#gpy-legend-title');\n      if(legendTitle) legendTitle.textContent = (currentCol || 'Value') + (currentUnit ? ' \u00b7 ' + currentUnit : '');\n    }\n    \/\/ Enrich the chip label with product info when available\n    if(ds.product){\n      var chipLabel = $('#gpy-chip-label');\n      if(chipLabel ? chipLabel.textContent : false){\n        if(chipLabel.textContent.indexOf(ds.product) < 0){\n          chipLabel.textContent = chipLabel.textContent + ' \u00b7 ' + ds.product;\n        }\n      }\n    }\n    renderTree();\n    \/\/ Show \/ hide playback strip based on whether this dataset can be replayed (polygon, not boundary)\n    setupPlayback(ds);\n    \/\/ setupPlayback computes playback.keptMask (item 3+4): re-run recompute so the legend total volume\n    \/\/ + area reflect the kept\/dropped polygons (seeders dedup duplicates, fertilizer sums all passes).\n    recompute();\n    \/\/ Re-evaluate zones for the new dataset (column changed \u2192 outClass changed).\n    if(zonesK > 0){ computeZones(); }\n    updateZonesPanel();\n    \/\/ After the playback strip has been shown\/hidden and overlays re-positioned, force a fresh fit-all.\n    \/\/ This guarantees the user sees the entire layer when they click a tree node \u2014 no stale zoom\/pan\n    \/\/ from the previous dataset, no clipping from the playback strip's appearance.\n    if(window.requestAnimationFrame){\n      window.requestAnimationFrame(function(){\n        resize(); fitView(); draw();\n      });\n    } else {\n      setTimeout(function(){ resize(); fitView(); draw(); }, 16);\n    }\n  }\n  function pickInitialActive(newDatasets){\n    \/\/ Prefer the first non-boundary dataset (boundaries are usually outlines, not the data of interest)\n    for(var i=0;i<newDatasets.length;i++){ if(!newDatasets[i].isBoundary) return newDatasets[i]; }\n    return newDatasets[0];\n  }\n  function processArchive(file){\n    showOverlay('Parsing archive\u2026', 'Unpacking nested zips and finding shapefiles + GeoJSON + ISOXML.', true);\n    return Promise.all([loadShpjs(), loadJSZip()]).then(function(){\n      return new Promise(function(r,j){\n        var rd = new FileReader();\n        rd.onload = function(e){ r(e.target.result); };\n        rd.onerror = function(){ j(new Error('Could not read file')); };\n        rd.readAsArrayBuffer(file);\n      });\n    }).then(function(buf){\n      return window.JSZip.loadAsync(buf);\n    }).then(function(zip){\n      return walkArchive(zip);\n    }).then(function(entries){\n      return processEntries(entries, file.name);\n    }).catch(function(err){\n      hideOverlay();\n      try { console.error('[GPY] archive parse error:', err); } catch(_){}\n      showToast('Archive error: ' + (err.message ? err.message : err));\n    });\n  }\n  \/\/ Folder import (already-unpacked TASKDATA\/, etc.). Uses webkitdirectory upload to get a FileList\n  \/\/ with webkitRelativePath set on each File. Wraps each File in a JSZip-shaped entry so the rest\n  \/\/ of the pipeline (groupShapefiles, ISOXML, JSON detection) doesn't need to change.\n  function makeVirtualEntry(file, relativePath){\n    return {\n      path: relativePath,\n      entry: {\n        async: function(type){\n          return new Promise(function(resolve, reject){\n            var rd = new FileReader();\n            rd.onload = function(e){ resolve(e.target.result); };\n            rd.onerror = function(){ reject(new Error('read failed: ' + file.name)); };\n            if(type === 'string') rd.readAsText(file);\n            else rd.readAsArrayBuffer(file);\n          });\n        }\n      }\n    };\n  }\n  function processFolder(fileList){\n    if(!fileList ? true : !fileList.length){ showToast('No files in folder.'); return; }\n    \/\/ Detect proprietary monitor formats by sentinel file names \u2014 surface the GeoPard CTA modal\n    \/\/ instead of silently failing. Trimble .cn1 has index.vy1 + NAV_Vehicle\/; Ag Leader SMS dumps\n    \/\/ .agdata; John Deere Ops Center exports contain .jdl files. None of these can be parsed\n    \/\/ without the vendor SDK that GeoPard's backend already wraps.\n    var sawVy1 = false, sawAgdata = false, sawJdl = false;\n    for(var fi=0; fi<fileList.length; fi++){\n      var n = (fileList[fi].name || '').toLowerCase();\n      var rp = (fileList[fi].webkitRelativePath || n).toLowerCase();\n      if(\/\\.vy1$\/.test(n) ? true : \/\\.cn1\\\/\/.test(rp)) sawVy1 = true;\n      if(\/\\.agdata$\/.test(n)) sawAgdata = true;\n      if(\/\\.jdl$\/.test(n)) sawJdl = true;\n    }\n    if(sawVy1){ showProprietaryFormatModal('Trimble AgGPS .cn1'); return; }\n    if(sawAgdata){ showProprietaryFormatModal('Ag Leader .agdata'); return; }\n    if(sawJdl){ showProprietaryFormatModal('John Deere .jdl'); return; }\n    showOverlay('Parsing folder\u2026', 'Finding shapefiles, GeoJSON and ISOXML.', true);\n    \/\/ Need shp.js for any .shp groups + JSZip only if folder contains nested .zip files (unlikely)\n    var hasZip = false;\n    for(var i=0;i<fileList.length;i++){ if(\/\\.zip$\/i.test(fileList[i].name)){ hasZip = true; break; } }\n    var loaders = [loadShpjs()];\n    if(hasZip) loaders.push(loadJSZip());\n    var rootName = fileList[0] ? (fileList[0].webkitRelativePath || fileList[0].name) : 'folder';\n    rootName = rootName.split('\/')[0] || 'folder';\n    return Promise.all(loaders).then(function(){\n      var entries = [];\n      var zipPromises = [];\n      for(var i=0; i<fileList.length; i++){\n        var f = fileList[i];\n        var rp = f.webkitRelativePath || f.name;\n        if(\/\\.zip$\/i.test(rp) ? window.JSZip : false){\n          \/\/ Nested zip inside folder \u2014 unpack it just like processArchive does for top-level zips\n          (function(file, basePath){\n            zipPromises.push(new Promise(function(r,j){\n              var rd = new FileReader();\n              rd.onload = function(e){ r(e.target.result); };\n              rd.onerror = function(){ j(new Error('read failed: ' + file.name)); };\n              rd.readAsArrayBuffer(file);\n            }).then(function(buf){\n              return window.JSZip.loadAsync(buf);\n            }).then(function(zip){\n              return walkArchive(zip, basePath + '\/');\n            }).then(function(nested){\n              for(var k=0;k<nested.length;k++) entries.push(nested[k]);\n            }).catch(function(err){\n              try { console.warn('[GPY] nested zip in folder failed:', file.name, err); } catch(_){}\n            }));\n          })(f, rp);\n          continue;\n        }\n        entries.push(makeVirtualEntry(f, rp));\n      }\n      return Promise.all(zipPromises).then(function(){ return entries; });\n    }).then(function(entries){\n      return processEntries(entries, rootName + '\/');\n    }).catch(function(err){\n      hideOverlay();\n      try { console.error('[GPY] folder parse error:', err); } catch(_){}\n      showToast('Folder error: ' + (err.message ? err.message : err));\n    });\n  }\n  \/\/ Shared post-walk pipeline: takes a flat entry list (from archive or folder) and turns it into\n  \/\/ datasets registered in the tree. Used by both processArchive and processFolder.\n  function processEntries(entries, sourceName){\n    try { console.warn('[GPY] entries:', entries.length, 'files (source='+sourceName+')'); } catch(_){}\n    var shapefileGroups = groupShapefiles(entries);\n    var jsonEntries = [];\n    var csvEntries = [];\n    var isoxmlEntries = [];\n    var kmlEntries = [];\n    for(var i=0;i<entries.length;i++){\n      var pth = entries[i].path;\n      \/\/ Skip macOS resource-fork files\n      if(\/(^|\\\/)__MACOSX\\\/\/.test(pth)) continue;\n      if(\/\\\/\\._\/.test(pth) ? true : \/^\\._\/.test(pth)) continue;\n      if(\/\\.(geo)?json$\/i.test(pth)) jsonEntries.push(entries[i]);\n      else if(\/(^|\\\/)TASKDATA\\.XML$\/i.test(pth)) isoxmlEntries.push(entries[i]);\n      else if(\/\\.(csv|tsv)$\/i.test(pth)) csvEntries.push(entries[i]);\n      else if(\/\\.kml$\/i.test(pth)) kmlEntries.push(entries[i]);\n    }\n    var jobs = [];\n    for(var j=0;j<shapefileGroups.length;j++){\n      jobs.push(parseShapefileGroup(shapefileGroups[j]));\n    }\n    for(var k=0;k<jsonEntries.length;k++){\n      jobs.push(readJsonEntry(jsonEntries[k].entry, jsonEntries[k].path));\n    }\n    for(var ix=0; ix<isoxmlEntries.length; ix++){\n      jobs.push(readIsoxmlEntry(isoxmlEntries[ix].entry, isoxmlEntries[ix].path, entries));\n    }\n    for(var ci=0; ci<csvEntries.length; ci++){\n      jobs.push(readCsvEntry(csvEntries[ci].entry, csvEntries[ci].path));\n    }\n    for(var km=0; km<kmlEntries.length; km++){\n      jobs.push(readKmlEntry(kmlEntries[km].entry, kmlEntries[km].path));\n    }\n    return Promise.all(jobs).then(function(results){\n      var newDatasets = [];\n      for(var i=0;i<results.length;i++){\n        var r = results[i];\n        if(!r || !r.ok || r.isMeta) continue;\n        if(r.kmlDatasets ? r.kmlDatasets.length : false){\n          \/\/ KML entry already produced per-geometry datasets \u2014 register them as-is.\n          for(var kd=0; kd<r.kmlDatasets.length; kd++) newDatasets.push(r.kmlDatasets[kd]);\n          continue;\n        }\n        if(r.isoxmlDatasets ? r.isoxmlDatasets.length : false){\n          for(var ix2=0; ix2<r.isoxmlDatasets.length; ix2++){\n            var ixd = r.isoxmlDatasets[ix2];\n            var dsi = makeDataset(ixd.fc, ixd.name, sourceName, ixd.dir);\n            if(!dsi) continue;\n            if(ixd._isTrack){\n              \/\/ ISOXML TLG GPS-position dataset \u2014 render as a Point cloud (path); not a boundary.\n              dsi.product = ixd.taskName || dsi.product;\n            } else {\n              dsi.isBoundary = true;  \/\/ PFD\/PLN polygon\n              dsi.fieldName = ixd.fieldName || dsi.fieldName;\n              if(ixd.fieldAreaHa > 0) dsi.areaHa = ixd.fieldAreaHa;\n            }\n            newDatasets.push(dsi);\n          }\n          continue;\n        }\n        var fc = r.fc ? r.fc : r.json;\n        if(!fc) continue;\n        var ds = makeDataset(fc, r.name, sourceName, r.dir);\n        if(!ds) continue;\n        var splits = splitByMaterial(ds);\n        for(var s=0;s<splits.length;s++) newDatasets.push(splits[s]);\n      }\n      if(!newDatasets.length){\n        hideOverlay();\n        \/\/ Look for proprietary-format sentinels in the unpacked entries \u2014 common when the user\n        \/\/ dropped a JD Operations Center export (nested zips full of .jdl), a Trimble .cn1 folder,\n        \/\/ or an Ag Leader .agdata file. Surface the GeoPard signup CTA instead of a dead end.\n        var sawJdlE = false, sawAgE = false, sawCn1E = false;\n        for(var ee=0; ee<entries.length; ee++){\n          var ep = entries[ee].path;\n          if(\/(^|\\\/)__MACOSX\\\/\/.test(ep)) continue;\n          if(\/\\.jdl$\/i.test(ep)) sawJdlE = true;\n          else if(\/\\.agdata$\/i.test(ep)) sawAgE = true;\n          else if(\/\\.vy1$\/i.test(ep) ? true : \/\\.cn1\\\/\/i.test(ep)) sawCn1E = true;\n        }\n        if(sawJdlE){ showProprietaryFormatModal('John Deere .jdl'); return; }\n        if(sawAgE){ showProprietaryFormatModal('Ag Leader .agdata'); return; }\n        if(sawCn1E){ showProprietaryFormatModal('Trimble AgGPS .cn1'); return; }\n        showToast('No usable layers found.');\n        return;\n      }\n      addDatasets(newDatasets);\n      var initial = pickInitialActive(newDatasets);\n      if(initial) activateDataset(initial.id);\n      hideOverlay();\n      var n = newDatasets.length;\n      showToast(n + ' layer' + (n===1 ? '' : 's') + ' loaded.');\n    });\n  }\n  function handleFile(file){\n    if(!file) return;\n    var name = (file.name || '').toLowerCase();\n    if(\/\\.zip$\/i.test(name)){\n      processArchive(file);\n      return;\n    }\n    if(\/\\.shp$\/i.test(name)){\n      showToast('Drop the zip containing the .shp + .shx + .dbf files together.');\n      return;\n    }\n    \/\/ Proprietary monitor formats \u2014 surface a CTA modal directing the user to GeoPard signup,\n    \/\/ which has the SDKs to parse these formats directly. Simple \".shp \/ ISOXML\" conversion advice\n    \/\/ didn't help most users; pointing at the full GeoPard pipeline is the actual answer.\n    if(\/\\.agdata$\/i.test(name)){ showProprietaryFormatModal('Ag Leader .agdata'); return; }\n    if(\/\\.cn1$\/i.test(name) ? true : \/\\.vy1$\/i.test(name)){ showProprietaryFormatModal('Trimble AgGPS .cn1'); return; }\n    if(\/\\.jdl$\/i.test(name)){ showProprietaryFormatModal('John Deere .jdl'); return; }\n    \/\/ Drone imagery \/ GeoTIFFs \/ orthomosaics require raster rendering (geotiff.js) plus advanced\n    \/\/ sensor metadata \u2014 outside the lightweight tool's scope. Route to the GeoPard CTA.\n    if(\/\\.(tif|tiff|geotiff)$\/i.test(name)){ showProprietaryFormatModal('Drone GeoTIFF \/ orthomosaic'); return; }\n    if(\/\\.(jpg|jpeg|png)$\/i.test(name)){ showProprietaryFormatModal('Drone image (raster)'); return; }\n    \/\/ CSV \/ TSV \u2014 parse text, detect lat\/lon columns, build a GeoJSON Point dataset\n    if(\/\\.(csv|tsv|txt)$\/i.test(name)){\n      handleCsvFile(file);\n      return;\n    }\n    \/\/ Excel \u2014 .xlsx \/ .xlsm are zip-of-XML, parsed locally via the lazy-loaded JSZip.\n    if(\/\\.(xlsx|xlsm)$\/i.test(name)){\n      handleXlsxFile(file);\n      return;\n    }\n    \/\/ Old binary .xls (BIFF) is not a zip \u2014 can't parse with JSZip; route to CSV \/ .xlsx.\n    if(\/\\.xls$\/i.test(name)){\n      showToast('Old .xls detected \u2014 re-save as .xlsx (\"File \u2192 Save As \u2192 Excel Workbook\") or CSV and drop again. Keep latitude \/ longitude columns.');\n      return;\n    }\n    \/\/ KML \u2014 XML parsed locally via DOMParser; .kmz is a zipped KML (JSZip).\n    if(\/\\.kml$\/i.test(name)){ handleKmlFile(file); return; }\n    if(\/\\.kmz$\/i.test(name)){ handleKmzFile(file); return; }\n    \/\/ GeoJSON path \u2014 read text, parse, register as a dataset\n    var reader = new FileReader();\n    reader.onload = function(e){\n      try {\n        var json = JSON.parse(e.target.result);\n        var ds = makeDataset(json, file.name.replace(\/\\.(geo)?json$\/i,''), file.name);\n        if(!ds){ showToast('No usable geometry in JSON.'); return; }\n        addDatasets([ds]);\n        activateDataset(ds.id);\n      } catch(ex){ showToast('Invalid JSON: ' + ex.message); }\n    };\n    reader.onerror = function(){ showToast('Could not read file.'); };\n    reader.readAsText(file);\n  }\n  function loadGeoJSON(json, name, isSample, sampleLabel){\n    var feats = json.features || (Array.isArray(json) ? json : null);\n    if(!feats || !feats.length){ hideOverlay(); showToast('No features found.'); return; }\n    \/\/ Reset overlay state BEFORE we recompute wmCx\/wmCy\/polyData for the new dataset.\n    \/\/ loadGeoJSON ends with a draw() call (line ~2925) that fires before setupPlayback\n    \/\/ runs \u2014 without this reset, the previous field's hulls \/ AB lines (stored in OLD-\n    \/\/ wmCx-relative mercator coords) would project as ghosts onto the new field. Most\n    \/\/ visible when switching across continents (US \u2192 Ukraine) where the geographic\n    \/\/ distance is huge but the relative coords still land inside the new view.\n    playback.fieldHulls = [];\n    playback.fieldAxes = [];\n    playback.fieldClusters = [];\n    playback.abSiblingLines = [];\n    playback.abLines = { perCluster: [], flat: [], rowSpacingMerc: 0 };\n    playback.polygonRowSpacingM = 0;\n    playback.headlandMask = null;\n    playback.machineXY = null;\n    playback.boundaries = null;\n    playback.spritePathX = null;\n    playback.spritePathY = null;\n    playback.smoothPathX = null;\n    playback.smoothPathY = null;\n    playback.passKeptMask = null;\n    playback.wideSkipN = null;\n    playback.turnBezier = null;\n    var pts = [], geomType = null;\n    for(var i=0;i<feats.length;i++){\n      var f = feats[i];\n      if(!f || !f.geometry) continue;\n      var t = f.geometry.type;\n      if(t === 'Point'){\n        var c = f.geometry.coordinates;\n        if(!c || typeof c[0] !== 'number' || typeof c[1] !== 'number') continue;\n        if(geomType === null) geomType = 'point';\n        if(geomType === 'point') pts.push(f);\n      } else if(t === 'Polygon' || t === 'MultiPolygon'){\n        if(geomType === null) geomType = 'polygon';\n        if(geomType === 'polygon') pts.push(f);\n      } else if(t === 'LineString' || t === 'MultiLineString'){\n        if(geomType === null) geomType = 'line';\n        if(geomType === 'line') pts.push(f);\n      }\n    }\n    if(!pts.length){ hideOverlay(); showToast('No supported geometries (Point\/Line\/Polygon) found.'); return; }\n    var sample = Math.min(pts.length, 200), propTally = {};\n    for(var j=0;j<sample;j++){\n      var p = pts[j].properties || {};\n      for(var k in p){ var v = p[k]; if(typeof v === 'number' ? isFinite(v) : false) propTally[k] = (propTally[k]||0) + 1; }\n    }\n    var cols = Object.keys(propTally).filter(function(k){ return propTally[k] > sample*0.8; });\n    if(!cols.length){\n      if(geomType === 'line'){\n        \/\/ Lines (guidance \/ Swath) may carry no numeric attributes \u2014 inject a synthetic Index col\n        \/\/ so the renderer can still draw them as a visible reference path.\n        for(var fi2=0; fi2<pts.length; fi2++){\n          if(!pts[fi2].properties) pts[fi2].properties = {};\n          pts[fi2].properties._index = fi2;\n        }\n        cols = ['_index'];\n      } else {\n        hideOverlay(); showToast('No numeric columns found.'); return;\n      }\n    }\n    \/\/ Attribute auto-pick \u2014 defaults to the MEANINGFUL agronomic value, not the FID\/index.\n    \/\/ Ranks from 0 (best) to 99 (worst). Identifiers and shape geometry meta fall to the\n    \/\/ bottom so they're never auto-selected when a real value exists. See README.\n    cols.sort(function(a,b){\n      var rank = function(c){\n        var s = c.toLowerCase();\n        \/\/ \u2500\u2500 soil-report files: Soil_* prefix takes priority over Tgt_Rate_ \u2500\u2500\n        \/\/ (agronomists' soil shapefiles ship lab results + recommended\n        \/\/ application rates; users want the lab values first, not the rate.)\n        if(\/^soil[_\\s]\/.test(s)){\n          if(\/ph\/.test(s)) return 3;\n          if(\/_om|organic\/.test(s)) return 4;\n          if(\/_p\\d?_|_p_|phosph\/.test(s)) return 5;\n          if(\/_k_pp|_k__|potass\/.test(s)) return 6;\n          if(\/cec|cation\/.test(s)) return 7;\n          if(\/_mg|magnesium\/.test(s)) return 8;\n          if(\/_ca|calcium\/.test(s)) return 9;\n          if(\/_s_p|sulfur|sulphur\/.test(s)) return 10;\n          if(\/_zn|_cu|_fe|_mn|_b_|zinc|copper|iron|mangan|boron\/.test(s)) return 11;\n          if(\/_na|sodium\/.test(s)) return 12;\n          if(\/_temp|temperature\/.test(s)) return 30;\n          return 15;\n        }\n        \/\/ \u2500\u2500 primary agronomic outputs \u2500\u2500\n        \/\/ As-applied \/ prescription rate (highest \u2014 what the operator actually applied).\n        \/\/ Patterns are case-insensitive (s is .toLowerCase()'d above) and fuzzy\n        \/\/ enough to catch Trimble \/ JD \/ CNH naming variations.\n        if(\/^appldrate$|applied_rate|appld_rt|^aprate$|^rate$|^actual$|^act_rate|^fact$|^fact_\/.test(s)) return 0;\n        if(\/tgt.*rate|target.*rate|prescr\/.test(s)) return 1;\n        \/\/ Seeding \/ planting rate (treat as primary rate signal \u2014 operator's actual sown rate).\n        if(\/seeding[_\\s]?rate|^seed_rate$|^seedr(ate|t)?$|^sowing_rate$|^seeding$\/.test(s)) return 1;\n        if(\/rate|sown|planted\/.test(s)) return 2;\n        \/\/ Yield (dry preferred \u2014 water-corrected). \"vol\" catches grain-flow\n        \/\/ volume columns and \"fresh\" \/ \"wet\" catches non-dry yield streams.\n        if(\/yld_mass_d|yield_dry|dry_yield|yld_dry|_dry_\/.test(s)) return 3;\n        if(\/yld.*mass|yield.*mass\/.test(s)) return 4;\n        if(\/yld|yield|crop_flw|crop_flow|harvest|grain_flow|_vol$|^vol_|^volume$|^fresh|^wet_\/.test(s)) return 5;\n        if(\/prod_ac|productivity\/.test(s)) return 6;\n        \/\/ Soil compaction \u2014 penetrometer depth \/ resistance (the headline value for\n        \/\/ compaction files; beats the raw per-depth resistance profile columns, which\n        \/\/ are bare numeric names ranked 50). Depth column (\"\u0413\u043b\u0438\u0431\u0438\u043d\u0430 \u0443\u0449\u0456\u043b\u044c\u043d\u0435\u043d\u043d\u044f, \u0441\u043c\")\n        \/\/ is the intuitive default; resistance\/penetration columns rank just after.\n        if(\/compact|penetr|\u0443\u0449\u0456\u043b\u044c\u043d|\u0449\u0456\u043b\u044c\u043d\/.test(s) ? \/\u0433\u043b\u0438\u0431|\u0433\u043b\u0443\u0431|depth|\u0433\u043b\u0438\u0431\u0438\u043d\u0430\/.test(s) : false) return 3;\n        if(\/compact|penetr|\u0443\u0449\u0456\u043b\u044c\u043d|\u0449\u0456\u043b\u044c\u043d|\u0442\u0432\u0451\u0440\u0434|\u0442\u0432\u0435\u0440\u0434|soil.*density\/.test(s)) return 6;\n        \/\/ Zone \/ management classifications (categorical fills)\n        if(\/^zone$|^zones?_|_zones?$|^class$|cluster|^potential$|management.*zone\/.test(s)) return 7;\n        \/\/ \u2500\u2500 soil chemistry (lab results \u2014 pH first, then macros, then micros) \u2500\u2500\n        if(\/^ph$|^ph_|_ph$|soil.*ph\/.test(s)) return 10;\n        if(\/^om$|organic.*matter|^omp$|^som$\/.test(s)) return 11;\n        if(\/^p$|^p_|_p$|^p2o5$|phosphor\/.test(s)) return 12;\n        if(\/^k$|^k_|_k$|^k2o$|potash|potassi\/.test(s)) return 13;\n        if(\/^n$|^n_|_n$|nitrog|^no3|^nh4\/.test(s)) return 14;\n        if(\/^cec$|cation\/.test(s)) return 15;\n        if(\/^mg$|magnesium\/.test(s)) return 16;\n        if(\/^ca$|calcium\/.test(s)) return 17;\n        if(\/^s$|^s_|^so4|sulfur|sulphur\/.test(s)) return 18;\n        if(\/^ec$|conductiv|salin\/.test(s)) return 19;\n        if(\/^zn$|^cu$|^fe$|^mn$|^b$|zinc|copper|iron|mangan|boron\/.test(s)) return 20;\n        \/\/ \u2500\u2500 other useful signals \u2500\u2500\n        if(\/moisture|moist|water\/.test(s)) return 25;\n        if(\/elev|altitude|slope|aspect|terrain\/.test(s)) return 26;\n        if(\/ndvi|ndre|evi|imagery|biomass\/.test(s)) return 27;\n        if(\/speed|distance\/.test(s)) return 28;\n        \/\/ \u2500\u2500 identifiers \/ shape \/ housekeeping (NEVER auto-selected when something else exists) \u2500\u2500\n        if(\/^fid$|^objectid$|^oid$|^id$|^uid$|^row.?id|^poly.?id|^obj.?id\/.test(s)) return 95;\n        if(\/^shape_|shape_area|shape_leng|shape_len\/.test(s)) return 96;\n        if(\/^_index$|^index$\/.test(s)) return 97;\n        return 50;\n      };\n      var ra = rank(a), rb = rank(b);\n      return ra!==rb ? ra-rb : a.localeCompare(b);\n    });\n    features = pts; numericCols = cols; currentCol = cols[0]; mode = geomType;\n    var sel = $('#gpy-col'); sel.innerHTML = '';\n    var selOv = $('#gpy-col-overlay'); if(selOv) selOv.innerHTML = '';\n    for(var c=0;c<cols.length;c++){\n      var opt = document.createElement('option');\n      opt.value = cols[c]; opt.textContent = cols[c];\n      sel.appendChild(opt);\n      if(selOv){\n        var optOv = document.createElement('option');\n        optOv.value = cols[c]; optOv.textContent = cols[c];\n        selOv.appendChild(optOv);\n      }\n    }\n    sel.value = currentCol;\n    if(selOv) selOv.value = currentCol;\n    \/\/ Show the on-map attribute picker only when there's a meaningful choice.\n    \/\/ Single-attribute datasets (e.g. synthetic _index line layers) don't need it.\n    var attrPick = $('#gpy-attr-pick');\n    if(attrPick){\n      \/\/ Always show the on-map picker once a dataset is loaded \u2014 it's the\n      \/\/ only way to switch attributes now (sidebar Attribute card was\n      \/\/ removed). Disable the select itself when there's only one column.\n      attrPick.classList.remove('is-hidden');\n      if(selOv) selOv.disabled = !(cols.length > 1);\n    }\n    var isAsApplied = mode === 'polygon' || \/rate\/i.test(currentCol);\n    var chipLabel = $('#gpy-chip-label'), chip = $('#gpy-chip');\n    if(isSample){\n      chip.classList.add('is-sample');\n      chipLabel.textContent = sampleLabel || ('Sample \u00b7 ' + (name || 'data'));\n      currentUnit = 'kg\/ha';\n    } else {\n      chip.classList.remove('is-sample');\n      var prefix = isAsApplied ? 'As-applied \u00b7 ' : 'Yield \u00b7 ';\n      chipLabel.textContent = prefix + (name || 'loaded');\n      currentUnit = '';\n      \/\/ user uploaded their own \u2014 deselect sample buttons\n      syncSampleButtons(null);\n    }\n    hideOverlay();\n    setColumn(currentCol);\n  }\n  function syncSampleButtons(active){\n    var btns = root.querySelectorAll('#gpy-samples button');\n    for(var i=0;i<btns.length;i++){\n      btns[i].classList.toggle('on', active ? (btns[i].dataset.s === active) : false);\n    }\n  }\n  \/\/ Find an existing dataset by exact name (used to refresh samples without dupes)\n  function findDatasetByName(name){\n    for(var i=0;i<datasets.length;i++){ if(datasets[i].name === name) return datasets[i]; }\n    return null;\n  }\n  function loadSample(){\n    var label = 'Sample \u00b7 2017 soybean yield';\n    var existing = findDatasetByName(label);\n    if(existing){ activateDataset(existing.id); syncSampleButtons('yield'); return; }\n    var feats = new Array(SAMPLE_PTS.length);\n    var sampleCols = SAMPLE_META.cols ? SAMPLE_META.cols : [{ key: SAMPLE_META.col, unit: SAMPLE_META.unit }];\n    for(var i=0;i<SAMPLE_PTS.length;i++){\n      var p = SAMPLE_PTS[i];\n      feats[i] = { type:'Feature', geometry:{ type:'Point', coordinates:[p[0], p[1]] }, properties:{} };\n      \/\/ Positional values: p[0]=lng, p[1]=lat, p[2..]=column values in SAMPLE_META.cols order.\n      for(var c=0; c<sampleCols.length; c++){\n        var val = p[2 + c];\n        if(val === null ? false : val !== undefined){\n          feats[i].properties[sampleCols[c].key] = val;\n        }\n      }\n    }\n    var ds = makeDataset({ type:'FeatureCollection', features: feats }, label, 'embedded sample');\n    if(!ds) return;\n    ds._isSample = true; ds._sampleUnit = 'kg\/ha';\n    \/\/ Seed unitMap so column-switcher shows the right unit for each attribute (otherwise\n    \/\/ guessUnit's magnitude heuristic might mis-classify e.g. Speed as elevation).\n    ds.unitMap = ds.unitMap ? ds.unitMap : {};\n    for(var u=0; u<sampleCols.length; u++){\n      ds.unitMap[sampleCols[u].key] = sampleCols[u].unit;\n    }\n    addDatasets([ds]);\n    activateDataset(ds.id);\n    syncSampleButtons('yield');\n  }\n  function loadSampleApplied(){\n    var label = 'Sample \u00b7 2024 N fertilizer application';\n    var existing = findDatasetByName(label);\n    if(existing){ activateDataset(existing.id); syncSampleButtons('applied'); return; }\n    var raw = SAMPLE_APPLIED_RAW;\n    var feats = new Array(raw.length);\n    for(var i=0;i<raw.length;i++){\n      var r = raw[i];\n      var ring = [\n        [r[0], r[1]],\n        [r[2], r[1]],\n        [r[2], r[3]],\n        [r[0], r[3]],\n        [r[0], r[1]]\n      ];\n      feats[i] = {\n        type:'Feature',\n        geometry:{ type:'Polygon', coordinates:[ring] },\n        properties:{ AppldRate: r[4] }\n      };\n    }\n    var ds = makeDataset({ type:'FeatureCollection', features: feats }, label, 'embedded sample');\n    if(!ds) return;\n    ds._isSample = true; ds._sampleUnit = 'kg\/ha';\n    addDatasets([ds]);\n    activateDataset(ds.id);\n    syncSampleButtons('applied');\n  }\n  \/\/ Guidance lines: 6 parallel passes at 18 m swath spacing, 300 m long, joined by\n  \/\/ half-circle U-turns at the headlands. Mirrors the user-facing reference at\n  \/\/ samples\/lines\/boustrophedon-uturn-reference.geojson \u2014 a canonical AB-line layout.\n  \/\/ Real-world soil sampling lab results \u2014 80 Points carrying full agronomic\n  \/\/ panel: pH, OM, CEC, P1, K (ppm and %), Mg, Ca, S, Fe, Mn, Zn, Cu, Na, B\n  \/\/ and a lime target rate. Field \/ farm \/ customer names stripped (rule 16).\n  \/\/ Attribute names use the DBF-truncated form (\"Soil_pH__1\", \"Soil_OM___\",\n  \/\/ \"Soil_P1_pp\", etc.) because that's how a typical agronomist's soil-report\n  \/\/ shapefile exports. The rank function below recognises the \"Soil_\" prefix\n  \/\/ and picks pH as the default render attribute.\n  function loadSampleSoil(){\n    var label = 'Sample \u00b7 soil sampling (lab results)';\n    var existing = findDatasetByName(label);\n    if(existing){ activateDataset(existing.id); syncSampleButtons('soil'); return; }\n    var json = 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":156.0,\"Soil___MG_\":5.84,\"Tgt_Rate_l\":5500.0}},{\"type\":\"Feature\",\"geometry\":{\"type\":\"Point\",\"coordinates\":[-88.522808,36.681685]},\"properties\":{\"Soil_CU_pp\":0.91,\"Soil_CA_pp\":1103.0,\"Soil_ZN_pp\":2.0,\"Soil_Temp_\":32.0,\"Soil_MN_pp\":202.0,\"Soil_CEC_m\":13.47,\"Soil_P1_pp\":114.0,\"Soil_FE_pp\":217.0,\"Soil___K__\":4.35,\"Soil_BpH__\":6.64,\"Soil_NA_pp\":27.0,\"Soil_S_ppm\":20.0,\"Soil___H__\":50.31,\"Soil_OM___\":2.93,\"Soil_MG_pp\":65.0,\"Soil___NA_\":0.86,\"Soil_pH__1\":5.6,\"Soil_K_ppm\":229.0,\"Soil___MG_\":3.99,\"Tgt_Rate_l\":5000.0}},{\"type\":\"Feature\",\"geometry\":{\"type\":\"Point\",\"coordinates\":[-88.521206,36.684404]},\"properties\":{\"Soil_CU_pp\":1.58,\"Soil_CA_pp\":1030.0,\"Soil_ZN_pp\":2.0,\"Soil_Temp_\":32.0,\"Soil_MN_pp\":193.0,\"Soil_CEC_m\":12.26,\"Soil_P1_pp\":24.0,\"Soil_FE_pp\":167.0,\"Soil___K__\":1.45,\"Soil_BpH__\":6.69,\"Soil_NA_pp\":32.0,\"Soil_S_ppm\":12.0,\"Soil___H__\":50.49,\"Soil_OM___\":2.86,\"Soil_MG_pp\":81.0,\"Soil___NA_\":1.12,\"Soil_pH__1\":5.7,\"Soil_K_ppm\":70.0,\"Soil___MG_\":5.51,\"Tgt_Rate_l\":4500.0}},{\"type\":\"Feature\",\"geometry\":{\"type\":\"Point\",\"coordinates\":[-88.523357,36.681382]},\"properties\":{\"Soil_CU_pp\":1.18,\"Soil_CA_pp\":1132.0,\"Soil_ZN_pp\":4.0,\"Soil_Temp_\":32.0,\"Soil_MN_pp\":189.0,\"Soil_CEC_m\":12.94,\"Soil_P1_pp\":164.0,\"Soil_FE_pp\":248.0,\"Soil___K__\":4.77,\"Soil_BpH__\":6.72,\"Soil_NA_pp\":29.0,\"Soil_S_ppm\":14.0,\"Soil___H__\":44.96,\"Soil_OM___\":3.52,\"Soil_MG_pp\":93.0,\"Soil___NA_\":0.97,\"Soil_pH__1\":5.8,\"Soil_K_ppm\":241.0,\"Soil___MG_\":5.99,\"Tgt_Rate_l\":4500.0}}]}');\n    var ds = makeDataset(json, label, 'embedded sample');\n    if(!ds) return;\n    ds._isSample = true;\n    \/\/ Friendly units for the legend \/ footer readout. Maps DBF-truncated\n    \/\/ column names to the right unit so the legend reads correctly.\n    ds.unitMap = {\n      Soil_pH__1:'pH', Soil_BpH__:'pH',\n      Soil_OM___:'%',\n      Soil_P1_pp:'ppm', Soil_K_ppm:'ppm', Soil_CA_pp:'ppm', Soil_MG_pp:'ppm',\n      Soil_NA_pp:'ppm', Soil_S_ppm:'ppm', Soil_FE_pp:'ppm', Soil_MN_pp:'ppm',\n      Soil_ZN_pp:'ppm', Soil_CU_pp:'ppm',\n      Soil_CEC_m:'meq\/100g', 'Soil___K__':'%', 'Soil___MG_':'%',\n      'Soil___H__':'%', 'Soil___NA_':'%',\n      Tgt_Rate_l:'lb\/ac', Soil_Temp_:'\u00b0F'\n    };\n    addDatasets([ds]);\n    activateDataset(ds.id);\n    syncSampleButtons('soil');\n  }\n  \/\/ Soil scan: dense multi-attribute soil-scanner output (Veris MSP3 \/ SoilOptix\n  \/\/ style \u2014 pH, OM, CEC, P, K, Mg, Ca + texture + plant-available water) covering\n  \/\/ a ~40 ha field. Source: anonymised real-world scan, FULL resolution (17,181\n  \/\/ points at ~5 m spacing) embedded as a columnar JSON blob in #gpy-soilscan-data\n  \/\/ so the user sees every reading the scanner produced \u2014 not a downsampled subset.\n  \/\/ Units are pre-set per attribute via ds.unitMap so the legend always reads\n  \/\/ correctly regardless of value magnitude.\n  function loadSampleEC(){\n    var label = 'Sample \u00b7 soil scan (multi-attribute)';\n    var existing = findDatasetByName(label);\n    if(existing){ activateDataset(existing.id); syncSampleButtons('ec'); return; }\n    var dataEl = document.getElementById('gpy-soilscan-data');\n    if(!dataEl ? true : !dataEl.textContent){ return; }\n    var blob;\n    try { blob = JSON.parse(dataEl.textContent); } catch(_){ return; }\n    var lon = blob.lon, lat = blob.lat, props = blob.props, keys = blob.keys;\n    if(!lon ? true : !lat ? true : !props ? true : !keys) return;\n    var n = lon.length;\n    var feats = new Array(n);\n    for(var i=0;i<n;i++){\n      var p = {};\n      for(var ki=0; ki<keys.length; ki++){\n        var k = keys[ki];\n        var col = props[k];\n        if(col) p[k] = col[i];\n      }\n      feats[i] = { type:'Feature', geometry:{ type:'Point', coordinates:[lon[i], lat[i]] }, properties:p };\n    }\n    var ds = makeDataset({ type:'FeatureCollection', features: feats }, label, 'embedded sample');\n    if(!ds) return;\n    ds._isSample = true;\n    \/\/ Pre-set device-defined units for each attribute. activateDataset reads ds.unitMap\n    \/\/ first (highest priority) so the legend shows the right unit on every column without\n    \/\/ guessing from magnitude.\n    ds.unitMap = blob.units || {};\n    addDatasets([ds]);\n    activateDataset(ds.id);\n    syncSampleButtons('ec');\n  }\n  \/\/ Smart unit detection. Priority:\n  \/\/   1. Sidecar \/ device-defined unit (set by activateDataset from ds.unitMap)\n  \/\/   2. Column-name keyword match (moisture\/speed\/yield\/rate\/...)\n  \/\/   3. Product-aware heuristic (urea\u2192kg\/ha, glyphosate\u2192L\/ha, corn seed\u21921000seeds\/ha or seeds\/ha)\n  \/\/   4. Magnitude-based fallback (med>30 \u2192 bu\/ac for yield, etc.)\n  \/\/ The result is what shows in legend ticks, slider unit labels, and totals\/average displays.\n  function guessUnit(col, vals, product){\n    if(!col) return '';\n    var s = String(col).toLowerCase();\n    var p = String(product || '').toLowerCase();\n    if(!vals) return '';\n    var n = vals.length;\n    if(!n) return '';\n    \/\/ Magnitude probe \u2014 median of finite, positive values (rates \/ yields are non-negative)\n    var fin = [];\n    for(var i=0;i<n;i++){ if(isFinite(vals[i]) ? vals[i] > 0 : false) fin.push(vals[i]); }\n    if(!fin.length) return '';\n    fin.sort(function(a,b){return a-b;});\n    var med = fin[Math.floor(fin.length*0.5)];\n    \/\/ Direct name hints \u2014 these win regardless of magnitude\n    \/\/ pH (incl. pH_KCl \/ pH_H2O \/ pH_CaCl2 suffixes) is ALWAYS unitless and MUST\n    \/\/ be caught before the moisture rule below \u2014 otherwise \"pH_H2O\" matches its\n    \/\/ h2o token and gets mislabeled \"%\". Prefix\/suffix tolerant (underscore is a\n    \/\/ \\w char, so the old ^ph$ anchors silently missed pH_KCl \/ Soil_pH).\n    if(\/(^|[_\\s])ph([_\\s\\d]|$)|water[_ ]?ph|salt[_ ]?ph|\u043a\u0438\u0441\u043b\u043e\u0442\u043d\/.test(s)) return '';\n    if(\/moist|moisture|h2o|water[_ ]?pct|\u0432\u043e\u043b\u043e\u0433\u0456\u0441\u0442\u044c|\u0432\u043b\u0430\u0436\/.test(s)) return '%';\n    if(\/speed|velocity|\u0448\u0432\u0438\u0434\u043a|\u0441\u043a\u043e\u0440\u043e\u0441\u0442\/.test(s)) return 'km\/h';\n    if(\/elev|altitude|\u0432\u0438\u0441\u043e\u0442|\u0432\u044b\u0441\u043e\u0442\/.test(s)) return 'm';\n    if(\/heading|bearing|\u043a\u0443\u0440\u0441|\u0430\u0437\u0438\u043c\u0443\u0442\/.test(s)) return 'deg';\n    if(\/temp\\b|temperature|\u0442\u0435\u043c\u043f\u0435\u0440\u0430\u0442\/.test(s)) return 'C';\n    if(\/cell.?width|swath|track.?width|width\/.test(s)) return 'm';\n    if(\/^lat\\b|latitude\/.test(s)) return 'deg';\n    if(\/^lon\\b|^lng\\b|longitude\/.test(s)) return 'deg';\n    \/\/ Soil sampling \u2014 lab results. Returned units follow the most common ag-lab conventions\n    \/\/ (mg\/kg for macro+secondary nutrients, ppm interchangeable, % for OM\/OC\/texture, dS\/m for EC).\n    \/\/ Single-letter columns are matched with word-boundaries to avoid false positives on yield names.\n    \/\/ Element \/ analyte symbols are matched PREFIX-TOLERANT: \"(^|[_\\s])ca([_\\s\\d]|$)\"\n    \/\/ catches bare \"Ca\" AND \"Soil_Ca\" \/ \"BS_Ca\". The old \"^ca$\" anchors missed\n    \/\/ every underscore-prefixed lab column (\"Soil_Ca\", \"Soil_Mg\", \"Soil_CEC\",\n    \/\/ \"Soil_OM\", \"Soil_S\", \"Soil_Al\") \u2014 verified 2026-06-09 on a Ukrainian\n    \/\/ soil-sampling file. `_rateY` keeps single-letter symbols (S \/ N \/ P \/ K \/ B)\n    \/\/ from hijacking application-rate \/ yield columns (\"N_rate\", \"S_yield\").\n    var _rateY = \/rate|norm|target|tgt|appl|prescr|yield|yld|prod_|sown|planted|harvest\/.test(s);\n    \/\/ Base saturation (BS_Ca \/ BS_Mg \/ BS_K \/ BS_Na \u2026) is a PERCENT of CEC \u2014\n    \/\/ checked BEFORE the element rules so \"BS_Mg\" reads % not mg\/kg.\n    if(\/(^|[_\\s])bs([_\\s]|$)|base[_ ]?sat|\u043d\u0430\u0441\u0438\u0447\/.test(s)) return '%';\n    if(\/p2o5|phosph|\u0444\u043e\u0441\u0444\u043e\u0440\/.test(s) ? !_rateY : false) return 'mg\/kg';                         \/\/ Phosphorus (P2O5)\n    if(\/(^|[_\\s])p([_\\s\\d]|$)\/.test(s) ? !_rateY : false) return 'mg\/kg';                       \/\/ P\n    if(\/k2o|potass|\u043a\u0430\u043b\u0456\u0439|\u043a\u0430\u043b\u0438\u0439\/.test(s) ? !_rateY : false) return 'mg\/kg';                      \/\/ Potassium (K2O)\n    if(\/(^|[_\\s])k([_\\s\\d]|$)\/.test(s) ? !_rateY : false) return 'mg\/kg';                       \/\/ K\n    if(\/(^|[_\\s])ca([_\\s\\d]|$)|calci|\u043a\u0430\u043b\u044c\u0446\/.test(s) ? !_rateY : false) return 'mg\/kg';          \/\/ Calcium\n    if(\/(^|[_\\s])mg([_\\s\\d]|$)|magnes|\u043c\u0430\u0433\u043d\/.test(s) ? !_rateY : false) return 'mg\/kg';          \/\/ Magnesium\n    if(\/(^|[_\\s])s([_\\s\\d]|$)|sulfur|sulph|\u0441\u0443\u043b\u044c\u0444|\u0441\u0435\u0440\u0430\/.test(s) ? !_rateY : false) return 'mg\/kg'; \/\/ Sulfur\n    if(\/(^|[_\\s])n([_\\s\\d]|$)|nitrog|\u0430\u0437\u043e\u0442|nh4|no3\/.test(s) ? !_rateY : false) return 'mg\/kg';   \/\/ Nitrogen\n    if(\/(^|[_\\s])al([_\\s\\d]|$)|alumin|\u0430\u043b\u044e\u043c\u0456\u043d|\u0430\u043b\u044e\u043c\u0438\u043d\/.test(s) ? !_rateY : false) return 'mg\/kg'; \/\/ Aluminium\n    if(\/(^|[_\\s])na([_\\s\\d]|$)|sodium|\u043d\u0430\u0442\u0440\u0456|\u043d\u0430\u0442\u0440\u0438\/.test(s) ? !_rateY : false) return 'mg\/kg';   \/\/ Sodium\n    if(\/(^|[_\\s])om([_\\s]|$)|organic[_ ]?matter|humus|\u0433\u0443\u043c\u0443\u0441\/.test(s)) return '%';               \/\/ Organic Matter\n    if(\/(^|[_\\s])oc([_\\s]|$)|organic[_ ]?carb|\u0443\u0433\u043b\u0435\u0440\u043e\u0434\/.test(s)) return '%';                      \/\/ Organic Carbon\n    if(\/(^|[_\\s])ec([_\\s]|$)|conductivity|salin\/.test(s)) return 'dS\/m';                         \/\/ EC\n    if(\/(^|[_\\s])cec([_\\s]|$)|cation\/.test(s)) return 'cmol\/kg';                                 \/\/ CEC\n    if(\/(^|[_\\s])zn([_\\s\\d]|$)|zinc|\u0446\u0438\u043d\u043a\/.test(s)) return 'mg\/kg';\n    if(\/(^|[_\\s])fe([_\\s\\d]|$)|iron|\u0436\u0435\u043b\u0435\u0437|\u0437\u0430\u043b\u0456\u0437\u043e\/.test(s)) return 'mg\/kg';\n    if(\/(^|[_\\s])mn([_\\s\\d]|$)|mangan\/.test(s)) return 'mg\/kg';\n    if(\/(^|[_\\s])cu([_\\s\\d]|$)|copper|\u043c\u0435\u0434\u044c|\u043c\u0456\u0434\u044c\/.test(s)) return 'mg\/kg';\n    if(\/(^|[_\\s])b([_\\s\\d]|$)|boron|\u0431\u043e\u0440\/.test(s)) return 'mg\/kg';\n    if(\/(^|[_\\s])mo([_\\s\\d]|$)|molybd\/.test(s)) return 'mg\/kg';\n    if(\/sand|\u043f\u0435\u0441\u043e\u043a|\u043f\u0456\u0441\u043e\u043a\/.test(s) ? !\/sandy\/.test(s) : false) return '%';\n    if(\/clay|\u0433\u043b\u0438\u043d\u0430\/.test(s)) return '%';\n    if(\/silt|\u043f\u044b\u043b\u044c|\u043c\u0443\u043b\/.test(s)) return '%';\n    \/\/ Yield-like columns: name says yield\/yld\/prod_\/harvest\n    if(\/yld|yield|prod_|harvest|\u0443\u0440\u043e\u0436|\u0443\u0440\u043e\u0436_\/.test(s)){\n      \/\/ bu\/ac is the dominant NA unit for grain (corn 100-300, soy 30-80, wheat 30-80)\n      \/\/ t\/ha is the dominant EU\/CIS unit (corn 4-14, soy 1-4, wheat 3-8)\n      \/\/ centners\/ha = \u0446\/\u0433\u0430 (CIS) \u2014 10x t\/ha (corn 40-140, wheat 30-80) \u2014 overlaps bu\/ac range\n      \/\/ Strategy: name hint first, then magnitude.\n      if(\/centner|\u0446\u0435\u043d\u0442\u043d\u0435\u0440|\u0446.?\\\/.?\u0433\u0430|c.?\\\/.?ha\/.test(s)) return 'c\/ha';\n      if(\/_d$|dry|d_mass|d_yld\/.test(s)){\n        if(med > 30 ? med < 400 : false) return 'bu\/ac';\n        if(med > 0.3 ? med < 30 : false) return 't\/ha';\n        if(med >= 400) return 'kg\/ha';\n        return 't\/ha';\n      }\n      if(\/_w$|wet|w_mass|w_yld\/.test(s)){\n        if(med > 30 ? med < 400 : false) return 'bu\/ac';\n        if(med > 0.3 ? med < 30 : false) return 't\/ha';\n        return 't\/ha';\n      }\n      if(\/_vol|volume\/.test(s)) return 'L\/ha';\n      \/\/ Generic yield \u2014 magnitude-based\n      if(med >= 400) return 'kg\/ha';\n      if(med > 30) return 'bu\/ac';\n      if(med > 0.3) return 't\/ha';\n      return 't\/ha';\n    }\n    \/\/ Rate columns (applied \/ target \/ prescription)\n    if(\/rate|appldrate|appl_rate|app_rate|target|tgt|prescr|prescript|norm|\u043d\u043e\u0440\u043c\u0430\/.test(s)){\n      \/\/ Liquid (sprayed) products \u2192 L\/ha or gal\/ac\n      if(\/glyphos|\u0440\u043e\u0443\u043d\u0434|\u0440\u0430\u0443\u043d\u0434|round.?up|herbic|fungic|pestic|atraz|spray|\u043e\u0431\u043f\u0440\u0438\u0441\u043a|liquid|\u041a\u0410\u0421|UAN\/.test(p)){\n        if(med >= 100) return 'L\/ha';   \/\/ bulk liquid fertilizer\n        return 'L\/ha';\n      }\n      \/\/ Dry fertilizer \u2192 kg\/ha (or lb\/ac in NA)\n      if(\/urea|\u043a\u0430\u0440\u0431\u0430\u043c\u0456\u0434|\u043a\u0430\u0440\u0431\u0430\u043c\u0438\u0434|nitr|amm|\u0441\u0435\u043b\u0456\u0442\u0440\u0430|\u0441\u0435\u043b\u0438\u0442\u0440\u0430|sulph|\u0441\u0443\u043b\u044c\u0444|phos|\u0444\u043e\u0441\u0444\u043e|potash|\u043a\u0430\u043b\u0456\u0439|\u043a\u0430\u043b\u0438\u0439|NPK|DAP|MAP|lime|\u0432\u0430\u043f\u043d\u043e|\u0438\u0437\u0432\u0435\u0441\u0442\u044c|gypsum|\u0433\u0456\u043f\u0441\/.test(p)){\n        return 'kg\/ha';\n      }\n      \/\/ Seeds \u2014 depends on crop and unit convention\n      if(\/corn|maize|\u043a\u0443\u043a\u0443\u0440\u0443\u0434\u0437\u0430|sunflower|\u0441\u043e\u043d\u044f\u0448\u043d\u0438\u043a|\u043f\u043e\u0434\u0441\u043e\u043b\u043d|soy|\u0441\u043e\u044f|wheat|\u043f\u0448\u0435\u043d\u0438\u0446|barley|\u044f\u0447\u043c\u0456\u043d\u044c|\u044f\u0447\u043c\u0435\u043d\u044c|rye|\u0436\u0438\u0442\u043e|oats|\u043e\u0432\u0435\u0441|cotton|\u0431\u0430\u0432\u043e\u0432\u043d\u0430|rape|\u0440\u0456\u043f\u0430\u043a|sorghum|\u0441\u043e\u0440\u0433\u043e|millet|\u043f\u0440\u043e\u0441\u043e|seed\/.test(p)){\n        \/\/ Corn\/sunflower seed rate ranges:\n        \/\/   raw seeds\/ha:   60,000-90,000 (corn), 50,000-70,000 (sunflower)\n        \/\/   thousands\/ha:   60-90 (corn), 50-70 (sunflower)\n        \/\/   thousands\/ac:   24-36 (corn)\n        \/\/   kg\/ha:          20-30 (corn ~80k seeds \u00d7 0.3g)\n        \/\/ Wheat\/cereal:\n        \/\/   kg\/ha:          150-250\n        \/\/   seeds\/m\u00b2:       300-500\n        if(med >= 10000) return 'seeds\/ha';\n        if(med >= 1000) return 'seeds\/ha';\n        if(med >= 30 ? med < 200 : false) return '1000seeds\/ha';\n        if(med >= 100 ? med < 400 : false) return 'kg\/ha';  \/\/ cereal seed rate\n        if(med < 30) return '1000seeds\/ha';\n        return 'kg\/ha';\n      }\n      \/\/ No product hint \u2014 magnitude only\n      if(med >= 10000) return 'seeds\/ha';\n      if(med >= 100) return 'kg\/ha';\n      if(med >= 30) return 'kg\/ha';\n      if(med >= 0.5) return 'L\/ha';\n      return 'kg\/ha';\n    }\n    \/\/ Standalone mass \/ volume columns\n    if(\/^mass\\b|total.?mass|weight\/.test(s)) return 'kg';\n    if(\/^vol\\b|liter|liquid\/.test(s)) return 'L';\n    if(\/^area\\b|square|hectare\/.test(s)) return 'ha';\n    return '';\n  }\n  function setColumn(col){\n    currentCol = col;\n    \/\/ Force IDW cache invalidation \u2014 the new column has fresh values and\n    \/\/ potentially fresh outClass, so the cached bitmap is stale even if a\n    \/\/ digest happened to collide.\n    interpCache.canvas = null;\n    interpCache.col = null;\n    \/\/ Recompute zones lazily on the next draw \u2014 values + outClass change here.\n    zoneClass = null;\n    zoneBreaks = null;\n    zoneStats = null;\n    \/\/ Rates are tied to the active attribute; reset so the next render seeds\n    \/\/ fresh defaults based on the new column's zone means.\n    zoneRates = [];\n    \/\/ Keep both attribute pickers (sidebar + on-map overlay) in sync regardless\n    \/\/ of which one (or neither) was the caller.\n    var sidebarSel = $('#gpy-col'); if(sidebarSel ? sidebarSel.value !== col : false) sidebarSel.value = col;\n    var overlaySel = $('#gpy-col-overlay'); if(overlaySel ? overlaySel.value !== col : false) overlaySel.value = col;\n    \/\/ Reset playback state up-front so the FIRST draw (from inside setColumn) doesn't read a stale\n    \/\/ playback.order from the previous dataset. Without this, after switching from a 15k-polygon\n    \/\/ Coverage layer to a 7-polygon ISOXML boundary the order array points at indices that no longer\n    \/\/ exist in polyData, crashing drawPolygons with \"Cannot read properties of undefined (minX)\".\n    playback.order = null;\n    playback.idx = features.length;\n    playback.keptMask = null;\n    values = new Array(features.length);\n    for(var i=0;i<features.length;i++){\n      values[i] = +features[i].properties[col];\n    }\n    \/\/ keep features whose value is finite (must preserve indexing with geometry)\n    if(mode === 'point'){\n      coords = new Array(features.length);\n      for(var i=0;i<features.length;i++) coords[i] = features[i].geometry.coordinates;\n      var keep = [];\n      for(var i=0;i<values.length;i++){ if(isFinite(values[i])) keep.push(i); }\n      if(keep.length < values.length){\n        var v2 = [], c2 = [];\n        for(var k=0;k<keep.length;k++){ v2.push(values[keep[k]]); c2.push(coords[keep[k]]); }\n        values = v2; coords = c2;\n        \/\/ also filter features so polyData\/values stay in sync\n        var f2 = [];\n        for(var k=0;k<keep.length;k++) f2.push(features[keep[k]]);\n        features = f2;\n      }\n    } else {\n      \/\/ polygon: filter features with non-finite value\n      var keepIdx = [];\n      for(var i=0;i<values.length;i++){ if(isFinite(values[i])) keepIdx.push(i); }\n      if(keepIdx.length < values.length){\n        var v2 = [], f2 = [];\n        for(var k=0;k<keepIdx.length;k++){ v2.push(values[keepIdx[k]]); f2.push(features[keepIdx[k]]); }\n        values = v2; features = f2;\n      }\n    }\n    var n = values.length;\n    sorted = values.slice().sort(function(a,b){ return a-b; });\n    var sum = 0; for(var i=0;i<n;i++) sum += values[i];\n    mean = sum\/n;\n    var ss = 0; for(var i=0;i<n;i++){ var d = values[i]-mean; ss += d*d; }\n    std = Math.sqrt(ss\/n);\n    median = quantile(0.5);\n    \/\/ Resolve a unit for this column. Order: dataset's device-defined unitMap \u2192 magnitude-aware\n    \/\/ guessUnit (yield \u2192 bu\/ac vs t\/ha, rate \u2192 kg\/ha vs L\/ha vs seeds\/ha). The user can later swap\n    \/\/ sample-yield via the chip; this keeps that flow but adds smart defaults for uploaded data.\n    var _activeDs = null;\n    for(var _di=0; _di<datasets.length; _di++){\n      if(datasets[_di].id === activeDatasetId){ _activeDs = datasets[_di]; break; }\n    }\n    var _hasMapEntry = _activeDs ? (_activeDs.unitMap ? (col in _activeDs.unitMap) : false) : false;\n    var _fromMap = _hasMapEntry ? _activeDs.unitMap[col] : null;\n    var _product = _activeDs ? _activeDs.product : '';\n    \/\/ Reset stale unit first so switching from a mg\/kg column to a unitless\n    \/\/ column (pH, ratios) doesn't leak the previous attribute's unit into\n    \/\/ the legend. Then re-resolve: explicit map entries win (even empty\n    \/\/ strings, which mark \"intentionally unitless\"); otherwise guessUnit.\n    currentUnit = '';\n    if(_hasMapEntry){\n      currentUnit = _fromMap || '';\n    } else {\n      var _guessed = guessUnit(col, values, _product);\n      if(_guessed) currentUnit = _guessed;\n    }\n    \/\/ synthetic _index col (line datasets w\/o numeric attrs) \u2014 no real unit\n    if(col === '_index') currentUnit = '';\n    \/\/ Compute projection center from geometries\n    var lonMin=Infinity,lonMax=-Infinity,latMin=Infinity,latMax=-Infinity;\n    if(mode === 'point'){\n      for(var i=0;i<n;i++){\n        var p = coords[i];\n        if(p[0]<lonMin) lonMin=p[0]; if(p[0]>lonMax) lonMax=p[0];\n        if(p[1]<latMin) latMin=p[1]; if(p[1]>latMax) latMax=p[1];\n      }\n    } else {\n      for(var i=0;i<n;i++){\n        var g = features[i].geometry;\n        var nested;\n        \/\/ Normalize to 3 levels of nesting so the inner loops are geometry-agnostic.\n        \/\/ Polygon \u2192 [[[lng,lat],...]] (1 polygon \u00d7 R rings \u00d7 N pts) \u2192 wrap once = [coords]\n        \/\/ MultiPolygon \u2192 [polygons]                                  \u2192 use as-is\n        \/\/ LineString \u2192 [[lng,lat],...]                               \u2192 wrap twice = [[coords]]\n        \/\/ MultiLineString \u2192 [lines]                                  \u2192 wrap once = [coords]\n        if(g.type === 'MultiPolygon')          nested = g.coordinates;\n        else if(g.type === 'Polygon')          nested = [g.coordinates];\n        else if(g.type === 'MultiLineString')  nested = [g.coordinates];\n        else if(g.type === 'LineString')       nested = [[g.coordinates]];\n        else continue;\n        for(var pi=0;pi<nested.length;pi++){\n          for(var ri=0;ri<nested[pi].length;ri++){\n            var ring = nested[pi][ri];\n            for(var pj=0;pj<ring.length;pj++){\n              var pt = ring[pj];\n              if(pt[0]<lonMin) lonMin=pt[0]; if(pt[0]>lonMax) lonMax=pt[0];\n              if(pt[1]<latMin) latMin=pt[1]; if(pt[1]>latMax) latMax=pt[1];\n            }\n          }\n        }\n      }\n    }\n    var lonC = (lonMin+lonMax)\/2;\n    latC = (latMin+latMax)\/2;\n    wmCx = lngToWmX(lonC);\n    wmCy = latToWmY(latC);\n    mxMin = Infinity; mxMax = -Infinity; myMin = Infinity; myMax = -Infinity;\n    if(mode === 'point'){\n      mx = new Float32Array(n); my = new Float32Array(n);\n      sxArr = new Float32Array(n); syArr = new Float32Array(n);\n      polyData = null;\n      for(var i=0;i<n;i++){\n        mx[i] = lngToWmX(coords[i][0]) - wmCx;\n        my[i] = -(latToWmY(coords[i][1]) - wmCy);\n        if(mx[i]<mxMin) mxMin=mx[i]; if(mx[i]>mxMax) mxMax=mx[i];\n        if(my[i]<myMin) myMin=my[i]; if(my[i]>myMax) myMax=my[i];\n      }\n    } else if(mode === 'line'){\n      \/\/ Build polyData with open polylines (no closed rings). tracePoly() detects the isLine flag\n      \/\/ and skips closePath(); drawPolygons() detects mode and strokes instead of filling.\n      mx = null; my = null; sxArr = null; syArr = null;\n      polyData = new Array(n);\n      for(var i=0;i<n;i++){\n        var g = features[i].geometry;\n        var lines = g.type === 'MultiLineString' ? g.coordinates : [g.coordinates];\n        var paths = [];\n        var sumX = 0, sumY = 0, cnt = 0;\n        var miX = Infinity, maX = -Infinity, miY = Infinity, maY = -Infinity;\n        for(var li=0; li<lines.length; li++){\n          var lc = lines[li];\n          if(lc ? lc.length < 2 : true) continue;\n          var rmx = new Float32Array(lc.length);\n          var rmy = new Float32Array(lc.length);\n          for(var pj=0; pj<lc.length; pj++){\n            var x = lngToWmX(lc[pj][0]) - wmCx;\n            var y = -(latToWmY(lc[pj][1]) - wmCy);\n            rmx[pj] = x; rmy[pj] = y;\n            sumX += x; sumY += y; cnt++;\n            if(x<miX) miX=x; if(x>maX) maX=x;\n            if(y<miY) miY=y; if(y>maY) maY=y;\n          }\n          paths.push({mx:rmx, my:rmy});\n        }\n        var cxv = cnt > 0 ? sumX\/cnt : 0, cyv = cnt > 0 ? sumY\/cnt : 0;\n        polyData[i] = { rings:paths, cx:cxv, cy:cyv, minX:miX, maxX:maX, minY:miY, maxY:maY, areaHa:0, isLine:true };\n        if(miX<mxMin) mxMin=miX; if(maX>mxMax) mxMax=maX;\n        if(miY<myMin) myMin=miY; if(maY>myMax) myMax=maY;\n      }\n    } else {\n      mx = null; my = null; sxArr = null; syArr = null;\n      polyData = new Array(n);\n      for(var i=0;i<n;i++){\n        var g = features[i].geometry;\n        var polys = g.type === 'MultiPolygon' ? g.coordinates : [g.coordinates];\n        var rings = [];\n        var sumX = 0, sumY = 0, cnt = 0;\n        var miX = Infinity, maX = -Infinity, miY = Infinity, maY = -Infinity;\n        var areaHa = 0;\n        for(var pi=0;pi<polys.length;pi++){\n          for(var ri=0;ri<polys[pi].length;ri++){\n            var ring = polys[pi][ri];\n            if(ri === 0) areaHa += ringAreaHa(ring); else areaHa -= ringAreaHa(ring);\n            var rmx = new Float32Array(ring.length);\n            var rmy = new Float32Array(ring.length);\n            for(var pj=0;pj<ring.length;pj++){\n              var x = lngToWmX(ring[pj][0]) - wmCx;\n              var y = -(latToWmY(ring[pj][1]) - wmCy);\n              rmx[pj] = x; rmy[pj] = y;\n              sumX += x; sumY += y; cnt++;\n              if(x<miX) miX=x; if(x>maX) maX=x;\n              if(y<miY) miY=y; if(y>maY) maY=y;\n            }\n            rings.push({mx:rmx, my:rmy});\n          }\n        }\n        if(areaHa < 0) areaHa = 0;\n        polyData[i] = { rings:rings, cx:sumX\/cnt, cy:sumY\/cnt, minX:miX, maxX:maX, minY:miY, maxY:maY, areaHa:areaHa };\n        if(miX<mxMin) mxMin=miX; if(maX>mxMax) mxMax=maX;\n        if(miY<myMin) myMin=miY; if(maY>myMax) myMax=maY;\n      }\n    }\n    fW = mxMax-mxMin; fH = myMax-myMin;\n    outClass = new Uint8Array(n);\n    \/\/ Adaptive low cutoff slider \u2014 works for yield (0-500 typical) AND fertilizer rate (0-100 typical)\n    var loSlider = $('#gpy-lo-r');\n    var sliderMax = Math.max(50, Math.round((sorted[Math.floor(n*0.1)] || 100) * 2));\n    var sliderStep = sliderMax > 500 ? 50 : (sliderMax > 100 ? 5 : 1);\n    loSlider.max = sliderMax;\n    loSlider.step = sliderStep;\n    \/\/ Default low cutoff. DENSE data (sensor \/ yield \/ scan, n \u2265 50): the very\n    \/\/ lowest reading is almost always a dropout\/spike, so flag it (5% above min).\n    \/\/ SPARSE data (soil-lab samples, management-zone polygons, n < 50): every\n    \/\/ reading is a legitimate value \u2014 flagging the lowest greys out a whole real\n    \/\/ zone (reported 2026-06-10 on 3-polygon Serbia soil files). So the cutoff\n    \/\/ sits at 0 and nothing is auto-greyed; the user can still raise it manually.\n    var rawDefault = n >= 50 ? Math.max((sorted[Math.floor(n*0.01)] || 0) * 0.5, sorted[0] * 1.05) : 0;\n    loCutoff = Math.max(0, Math.round(rawDefault \/ sliderStep) * sliderStep);\n    loSlider.value = loCutoff;\n    $('#gpy-lo').textContent = fmt(loCutoff);\n    $('#gpy-lo-u').textContent = currentUnit ? ' '+currentUnit : '';\n    \/\/ Adaptive HIGH cutoff slider \u2014 range up to ~1.5\u00d7 the dataset max so user can dial up or down\n    var hiSlider = $('#gpy-hi-r');\n    var hiMax = Math.max(20, Math.round((sorted[n-1] || 100) * 1.5));\n    var hiStep = hiMax > 500 ? 50 : (hiMax > 100 ? 5 : 1);\n    hiSlider.max = hiMax;\n    hiSlider.step = hiStep;\n    hiSlider.min = 0;\n    hiCutoff = null; \/\/ reset to auto-mode (\u03c3 + median floor) on each new dataset\n    $('#gpy-hi-u').textContent = currentUnit ? ' '+currentUnit : '';\n    recompute();\n    fitView();\n    draw();\n    \/\/ Defensive deferred re-fit: when sidebar \/ playback strip toggles in\n    \/\/ response to the dataset\/attribute switch, the canvas dimensions change\n    \/\/ AFTER this synchronous fit. The rAF call re-fits on the next paint frame\n    \/\/ once layout has settled, so the user always sees the whole dataset when\n    \/\/ switching between fields or attribute layers.\n    if(window.requestAnimationFrame){\n      window.requestAnimationFrame(function(){\n        if(typeof resize === 'function') resize();\n        fitView();\n        draw();\n      });\n    }\n  }\n  function quantile(q){\n    if(!sorted.length) return 0;\n    var i = (sorted.length-1)*q, lo = Math.floor(i), hi = Math.ceil(i);\n    return sorted[lo] + (sorted[hi]-sorted[lo])*(i-lo);\n  }\n  function recompute(){\n    if(!values.length) return;\n    var n = values.length;\n    \/\/ High-outlier threshold:\n    \/\/   Honor user override (hiCutoff) if set (via slider or \u03c3 buttons).\n    \/\/   Polygon mode: max(\u03c3-based, median\u00d72, p99\u00d71.1). The p99 floor handles bimodal data \u2014 when a\n    \/\/   Coverage shapefile mixes two operations (e.g., planting + fertilizing) the second cluster\n    \/\/   sits above mean+3\u03c3 and would be flagged as \"violet outlier\"; using p99 as a floor flags only\n    \/\/   the top ~0.5% (sensor spikes \/ extreme overlaps), not the legitimate second operation.\n    \/\/   Point\/yield mode: classic mean + sigmaK*std.\n    var hiT;\n    if(hiCutoff !== null){\n      hiT = hiCutoff;\n    } else if(mode === 'polygon'){\n      var stat = mean + sigmaK*std;\n      var medianFloor = median * 2;\n      var p99 = sorted[Math.floor(n * 0.99)];\n      var p99Floor = p99 * 1.1;\n      hiT = stat;\n      if(medianFloor > hiT) hiT = medianFloor;\n      if(p99Floor > hiT) hiT = p99Floor;\n    } else {\n      hiT = mean + sigmaK*std;\n    }\n    var lo = 0, hi = 0;\n    for(var i=0;i<n;i++){\n      if(values[i] < loCutoff){ outClass[i]=1; lo++; }\n      else if(values[i] > hiT){ outClass[i]=2; hi++; }\n      else outClass[i] = 0;\n    }\n    var inl = []; for(var i=0;i<n;i++){ if(outClass[i]===0) inl.push(values[i]); }\n    inl.sort(function(a,b){ return a-b; });\n    \/\/ Stop 0 (lowest class break) IS the Low outlier cutoff; stop 4 (highest) IS the High\n    \/\/ outlier cutoff. Values < stop 0 render grey, values > stop 4 render violet, anything\n    \/\/ in between gets the colour gradient. This merges the previously-separate Lo\/Hi sliders\n    \/\/ into the legend thumbs themselves \u2014 dragging thumb 0 or 4 directly adjusts the outlier\n    \/\/ boundary. Stops 1\u20133 are intermediate class breaks inside the inlier range.\n    var autoMin = stopValueOverrides[0] !== null ? stopValueOverrides[0] : loCutoff;\n    var autoMax = stopValueOverrides[4] !== null ? stopValueOverrides[4] : hiT;\n    effStops[0] = autoMin;\n    effStops[4] = autoMax;\n    for(var se=1; se<=3; se++){\n      var defv = autoMin + (autoMax - autoMin) * (se \/ 4);\n      effStops[se] = stopValueOverrides[se] !== null ? stopValueOverrides[se] : defv;\n    }\n    \/\/ No monotonic clamp \u2014 the user can deliberately move one class without disturbing others, even\n    \/\/ if the result is non-monotonic. colorFor handles arbitrary stop ordering gracefully (clamps\n    \/\/ segment interpolation to [0,1] so the color saturates at the segment boundary).\n    colorMin = effStops[0];\n    colorMax = effStops[4];\n    var anyOverride = false;\n    for(var oa=0; oa<stopValueOverrides.length; oa++){ if(stopValueOverrides[oa] !== null){ anyOverride = true; break; } }\n    \/\/ Precompute quantile rank fractions per feature (for quantile-based coloring, the default).\n    \/\/ Stable ordering: sort inlier feature indices by value, then assign t = rank \/ (count-1).\n    tArr = new Float32Array(n);\n    var inlIdx = [];\n    for(var qi=0; qi<n; qi++){ if(outClass[qi] === 0) inlIdx.push(qi); }\n    inlIdx.sort(function(a,b){ return values[a] - values[b]; });\n    var denom = Math.max(1, inlIdx.length - 1);\n    for(var qj=0; qj<inlIdx.length; qj++){\n      tArr[inlIdx[qj]] = qj \/ denom;\n    }\n    $('#gpy-hi').textContent = fmt(hiT);\n    \/\/ Keep the high-cutoff slider in sync \u2014 when in auto mode, the slider follows the computed value.\n    var hiSliderEl = $('#gpy-hi-r');\n    if(hiSliderEl){\n      var sMin = +hiSliderEl.min, sMax = +hiSliderEl.max;\n      var snapped = Math.max(sMin, Math.min(sMax, hiT));\n      hiSliderEl.value = snapped;\n    }\n    $('#gpy-hic').textContent = fmt(hi)+' \u00b7 '+(hi\/n*100).toFixed(2)+'%';\n    $('#gpy-loc').textContent = fmt(lo)+' \u00b7 '+(lo\/n*100).toFixed(2)+'%';\n    \/\/ Sync each per-class stop row (input + override class) and the 5 thumb positions on the bar.\n    var dataMinT = sorted.length ? sorted[0] : 0;\n    var dataMaxT = sorted.length ? sorted[sorted.length-1] : 1;\n    var dataRangeT = dataMaxT - dataMinT;\n    for(var si=0; si<5; si++){\n      var inp = $('#gpy-l-stop-' + si);\n      var wrap = $('#gpy-l-stop-wrap-' + si);\n      var unitEl = $('#gpy-l-stop-unit-' + si);\n      var thumb = $('#gpy-l-thumb-' + si);\n      if(inp ? document.activeElement !== inp : false){\n        inp.value = isFinite(effStops[si]) ? Math.round(effStops[si] * 100) \/ 100 : '';\n      }\n      if(wrap) wrap.classList.toggle('is-override', stopValueOverrides[si] !== null);\n      if(unitEl) unitEl.textContent = currentUnit || '';\n      if(thumb){\n        var pos = dataRangeT > 0 ? (effStops[si] - dataMinT) \/ dataRangeT : si\/4;\n        if(pos < 0) pos = 0; if(pos > 1) pos = 1;\n        thumb.style.left = (pos*100) + '%';\n      }\n    }\n    var resetEl = $('#gpy-l-reset');\n    if(resetEl) resetEl.classList.toggle('show', anyOverride);\n    var legendTitle = $('#gpy-legend-title');\n    if(legendTitle){\n      legendTitle.textContent = (currentCol || 'Value') + (currentUnit ? ' \u00b7 ' + currentUnit : '');\n    }\n    \/\/ Inlier mean for legend (matches the colored points\/polygons)\n    var inlSum = 0, inlCnt = 0;\n    for(var ii=0;ii<n;ii++){ if(outClass[ii]===0){ inlSum += values[ii]; inlCnt++; } }\n    var avgVal = inlCnt > 0 ? inlSum \/ inlCnt : 0;\n    var elAvg = $('#gpy-l-avg');\n    if(elAvg) elAvg.textContent = fmt(avgVal) + (currentUnit ? ' '+currentUnit : '');\n    var areaRow = $('#gpy-l-area-row');\n    var totRow  = $('#gpy-l-tot-row');\n    var legStats = $('#gpy-leg-stats');\n    \/\/ Derive the totals' mass \/ volume \/ count unit from currentUnit (used by all three branches below)\n    function deriveMassUnit(u){\n      if(u === 'kg\/ha') return 'kg';\n      if(u === 't\/ha') return 't';\n      if(u === 'lb\/ac') return 'lb';\n      if(u === 'L\/ha') return 'L';\n      if(u === 'gal\/ac') return 'gal';\n      if(u === 'bu\/ac') return 'bu';\n      if(u === 'c\/ha') return 'c';\n      if(u === 'seeds\/ha') return 'seeds';\n      if(u === '1000seeds\/ha') return '1000 seeds';\n      return '';\n    }\n    var elArea = $('#gpy-l-area');\n    var elTot  = $('#gpy-l-tot');\n    var areaLbl = areaRow ? areaRow.querySelector('.lbl') : null;\n    var totLbl  = totRow ? totRow.querySelector('.lbl') : null;\n    \/\/ \/ac-unit rates need area in acres, not hectares, to keep the product dimensionally correct.\n    var isAcRate = currentUnit ? \/\\\/ac\\b\/.test(currentUnit) : false;\n    var haToRateArea = isAcRate ? 2.47105 : 1;\n    var pu = deriveMassUnit(currentUnit);\n    \/\/ Compute coverage area for the dataset:\n    \/\/   Polygon: sum of polygon areas (deduped by keptMask when seeder mode is \"first\")\n    \/\/   Point \/ Line: convex hull of feature coordinates as a \"field area\" estimate \u2014 there's no\n    \/\/     native area otherwise, and bbox over-estimates for irregular fields.\n    var coverageHa = 0;\n    if(mode === 'polygon' ? polyData : false){\n      var km = playback.keptMask ? playback.keptMask.mask : null;\n      for(var ki=0;ki<n;ki++){\n        if(outClass[ki] !== 0) continue;\n        if(km ? km[ki] === 0 : false) continue;\n        coverageHa += polyData[ki].areaHa || 0;\n      }\n    } else if(n >= 3){\n      \/\/ Collect inlier lat\/lon points: for points use coords directly; for lines walk all vertices.\n      var hullPts = [];\n      if(mode === 'point'){\n        for(var pi=0; pi<n; pi++){\n          if(outClass[pi] !== 0) continue;\n          if(coords[pi]) hullPts.push(coords[pi]);\n        }\n      } else if(mode === 'line' ? polyData : false){\n        \/\/ Reconstruct lat\/lon from feature geometry (polyData has WM-relative coords; original lon\/lat is in features[i])\n        for(var lf=0; lf<features.length; lf++){\n          if(outClass[lf] !== 0) continue;\n          var g = features[lf] ? features[lf].geometry : null;\n          if(!g) continue;\n          var cc = g.coordinates;\n          var lines = g.type === 'MultiLineString' ? cc : [cc];\n          for(var l2=0; l2<lines.length; l2++){\n            var lc = lines[l2];\n            for(var l3=0; l3<lc.length; l3++) hullPts.push(lc[l3]);\n          }\n        }\n      }\n      if(hullPts.length >= 3){\n        var hull = convexHull(hullPts);\n        coverageHa = ringAreaHa(hull);\n      }\n    }\n    \/\/ Now compute Sum = average \u00d7 area (mass-conserving in the natural rate \u00d7 area sense).\n    \/\/ This is more predictable for the user than \u03a3(value \u00d7 per-feature-area) \u2014 the per-feature\n    \/\/ product can look weird when polygons overlap, when feature areas vary widely, etc.\n    \/\/ For unitless \/ index columns (no rate per area), Sum stays empty.\n    var totalValue = 0, totalUnit = '';\n    if(n > 0 ? coverageHa > 0 : false){\n      totalValue = avgVal * coverageHa * haToRateArea;\n      totalUnit = pu;\n      if(elArea) elArea.textContent = coverageHa < 10 ? coverageHa.toFixed(2) + ' ha' :\n                                       coverageHa < 100 ? coverageHa.toFixed(1) + ' ha' :\n                                       Math.round(coverageHa).toLocaleString('en-US') + ' ha';\n      if(areaRow){ areaRow.style.display = ''; if(areaLbl) areaLbl.textContent = mode === 'polygon' ? 'Coverage' : 'Field (hull)'; }\n      if(elTot) elTot.textContent = fmt(totalValue) + (pu ? ' '+pu : '');\n      if(totRow){ totRow.style.display = ''; if(totLbl) totLbl.textContent = 'Sum'; }\n    } else {\n      if(areaRow) areaRow.style.display = 'none';\n      if(totRow)  totRow.style.display  = 'none';\n    }\n    if(legStats) legStats.style.display = '';\n    \/\/ Paint the value-distribution histogram on the legend overlay even\n    \/\/ when zones are off \u2014 it's always a useful \"scale\" reading. Calling\n    \/\/ both render functions defensively in case zones aren't initialised\n    \/\/ yet (renderLegendBarZThumbs is a no-op when zonesK == 0).\n    try { renderHistogram('gpy-legend-hist', 32); setupHistogramDrag('gpy-legend-hist'); } catch(_){}\n    try { renderLegendBarZThumbs(); setupHistogramDrag('gpy-legend-bar'); } catch(_){}\n  }\n  var stops = [[0,[193,18,31]],[0.25,[232,93,4]],[0.5,[249,199,79]],[0.75,[144,190,109]],[1,[45,106,79]]];\n  function _stopColor(t){\n    if(t<0) t=0; if(t>1) t=1;\n    for(var i=0;i<stops.length-1;i++){\n      if(t<=stops[i+1][0]){\n        var t0=stops[i][0], t1=stops[i+1][0], c0=stops[i][1], c1=stops[i+1][1];\n        var f = (t-t0)\/(t1-t0);\n        return [c0[0]+(c1[0]-c0[0])*f|0, c0[1]+(c1[1]-c0[1])*f|0, c0[2]+(c1[2]-c0[2])*f|0];\n      }\n    }\n    return stops[stops.length-1][1];\n  }\n  \/\/ Per-feature color picker. Two modes:\n  \/\/   1) Any per-class override set: VALUE-based piecewise interpolation between effStops[0..4].\n  \/\/      Each gradient stop sits at the user-defined data value, so the breakpoints honor the user.\n  \/\/   2) Default (no overrides): QUANTILE-based \u2014 each inlier gets a t-value from its rank in the\n  \/\/      sorted inlier set. Maximizes visible variability even when values cluster tightly.\n  \/\/ \u2500\u2500 Auto zones \u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\n  \/\/ Quantile-based zone classification + variability summary + ROI hint.\n  \/\/ When zonesK > 0, every feature is recoloured by its zone class instead\n  \/\/ of by the smooth gradient. Zone breaks are computed once per (column,\n  \/\/ outClass set, zonesK) and cached.\n  var zonesK = 0;                 \/\/ 0 = off; 3 \/ 4 \/ 5 supported\n  var zoneClass = null;           \/\/ Uint8Array per feature; index into STOP_COLORS step\n  var zoneBreaks = null;          \/\/ sorted Float32Array of break values\n  var zoneStats = null;           \/\/ { cv, tier: 'low'|'medium'|'high', counts:[], means:[], colors:[] }\n  var zoneRates = [];             \/\/ numeric rate per zone (user input), unit-agnostic\n  var zoneRateUnit = 'kg\/ha';     \/\/ display-only label, user-editable\n  \/\/ ROI multipliers from rule 12 \/ Zoning ROI Calculator. Conservative midpoints.\n  var ZONE_ROI_MULT = { low: 0.4, medium: 1.0, high: 1.7 };\n  var ZONE_ROI_BASE = 0.02;       \/\/ 2% revenue lift base\n  var ZONE_ROI_PRACTICES = 1.5;   \/\/ assume \"seed + N\" (2 practices)\n  var ZONE_ROI_RANGE = 0.25;      \/\/ \u00b125% band\n  function quantileBreaks(sortedArr, k){\n    \/\/ Returns k-1 break values at the i\/k quantile of the sortedArr.\n    var out = new Float32Array(k - 1);\n    var n = sortedArr.length;\n    if(n < k){\n      for(var i=0;i<k-1;i++) out[i] = sortedArr[Math.min(n-1, Math.floor((i+1) * n \/ k))];\n      return out;\n    }\n    for(var i=0;i<k-1;i++){\n      var pos = (i + 1) * n \/ k;\n      var lo = Math.floor(pos), hi = Math.ceil(pos);\n      if(hi >= n) hi = n - 1;\n      var frac = pos - lo;\n      out[i] = sortedArr[lo] * (1 - frac) + sortedArr[hi] * frac;\n    }\n    return out;\n  }\n  \/\/ Pick a palette of K distinct colours from STOP_COLORS (5 stops).\n  \/\/ K=3: low \/ mid \/ high  \u2192 indices 0, 2, 4\n  \/\/ K=4: red \/ orange \/ lt-green \/ dk-green \u2192 0, 1, 3, 4\n  \/\/ K=5: all five stops\n  function zonePaletteIdx(k){\n    if(k <= 1) return [2];                \/\/ single zone \u2192 neutral mid tone\n    if(k === 2) return [0, 4];            \/\/ low \/ high \u2014 clearest two-way split\n    if(k === 3) return [0, 2, 4];\n    if(k === 4) return [0, 1, 3, 4];\n    return [0, 1, 2, 3, 4];\n  }\n  \/\/ Compute CV \/ tier independently of zone classification \u2014 the variability\n  \/\/ metric is the trigger that gets users to click \"Show zones\", so we surface\n  \/\/ it whether zones are on or off.\n  function computeVariability(){\n    if(!values ? true : !values.length) return null;\n    var inl = [];\n    for(var i=0;i<values.length;i++){\n      if(outClass[i] === 0 ? isFinite(values[i]) : false) inl.push(values[i]);\n    }\n    if(inl.length < 4) return null;\n    var meanI = 0; for(var mi=0;mi<inl.length;mi++) meanI += inl[mi]; meanI \/= inl.length;\n    var varI = 0; for(var vi=0;vi<inl.length;vi++){ var d = inl[vi] - meanI; varI += d*d; } varI \/= inl.length;\n    var stdI = Math.sqrt(varI);\n    var cvPct = meanI !== 0 ? Math.abs(stdI \/ meanI) * 100 : 0;\n    var tier = cvPct < 10 ? 'low' : (cvPct <= 25 ? 'medium' : 'high');\n    return { cv: cvPct, tier: tier, mean: meanI };\n  }\n  function computeZones(){\n    zoneClass = null;\n    zoneBreaks = null;\n    zoneStats = null;\n    if(!zonesK ? true : !values ? true : !values.length) return;\n    var inl = [];\n    for(var i=0;i<values.length;i++){\n      if(outClass[i] === 0 ? isFinite(values[i]) : false) inl.push(values[i]);\n    }\n    if(inl.length < zonesK) return;\n    inl.sort(function(a,b){ return a-b; });\n    zoneBreaks = quantileBreaks(inl, zonesK);\n    var palIdx = zonePaletteIdx(zonesK);\n    zoneClass = new Uint8Array(values.length);\n    var counts = new Uint32Array(zonesK);\n    var sums = new Float64Array(zonesK);\n    var mins = new Float64Array(zonesK); for(var z0=0;z0<zonesK;z0++) mins[z0] = Infinity;\n    var maxs = new Float64Array(zonesK); for(var z1=0;z1<zonesK;z1++) maxs[z1] = -Infinity;\n    for(var f=0; f<values.length; f++){\n      if(outClass[f] !== 0){ zoneClass[f] = 255; continue; }\n      var v = values[f];\n      var idx = 0;\n      for(var b=0; b<zoneBreaks.length; b++){\n        if(v >= zoneBreaks[b]) idx = b + 1;\n        else break;\n      }\n      if(idx >= zonesK) idx = zonesK - 1;\n      zoneClass[f] = idx;\n      counts[idx]++;\n      sums[idx] += v;\n      if(v < mins[idx]) mins[idx] = v;\n      if(v > maxs[idx]) maxs[idx] = v;\n    }\n    \/\/ CV in %: std \/ mean \u00d7 100. Use inlier set.\n    var meanI = 0; for(var mi=0;mi<inl.length;mi++) meanI += inl[mi]; meanI \/= inl.length;\n    var varI = 0; for(var vi=0;vi<inl.length;vi++){ var d = inl[vi] - meanI; varI += d*d; } varI \/= inl.length;\n    var stdI = Math.sqrt(varI);\n    var cvPct = meanI !== 0 ? Math.abs(stdI \/ meanI) * 100 : 0;\n    var tier = cvPct < 10 ? 'low' : (cvPct <= 25 ? 'medium' : 'high');\n    var means = new Float32Array(zonesK), cols = new Array(zonesK);\n    var areas = new Float32Array(zonesK);  \/\/ hectares per zone\n    for(var z=0; z<zonesK; z++){\n      means[z] = counts[z] > 0 ? sums[z] \/ counts[z] : 0;\n      cols[z] = STOP_COLORS[palIdx[z]];\n    }\n    \/\/ Area per zone:\n    \/\/   Polygon mode: sum polyData[i].areaHa for features in that zone.\n    \/\/   Point\/line mode: proportional share of the total field area\n    \/\/     (estimated from the convex hull of inlier coords).\n    if(mode === 'polygon' ? polyData : false){\n      for(var pf=0; pf<values.length; pf++){\n        if(outClass[pf] !== 0) continue;\n        var zp = zoneClass[pf];\n        if(zp === 255) continue;\n        var pd = polyData[pf];\n        if(pd ? pd.areaHa : false) areas[zp] += pd.areaHa;\n      }\n    } else {\n      \/\/ Estimate field area from inlier coords' convex hull (cheap; same\n      \/\/ approach the stats card uses for point\/line area readouts).\n      var inlierLngLat = [];\n      if(mode === 'point' ? coords : false){\n        for(var ci=0; ci<coords.length; ci++){\n          if(outClass[ci] === 0) inlierLngLat.push(coords[ci]);\n        }\n      }\n      var hullArea = 0;\n      if(inlierLngLat.length >= 3){\n        var ch = convexHull(inlierLngLat);\n        if(ch ? ch.length >= 3 : false) hullArea = ringAreaHa(ch);\n      }\n      var totalInl = 0;\n      for(var tc=0; tc<zonesK; tc++) totalInl += counts[tc];\n      if(hullArea > 0 ? totalInl > 0 : false){\n        for(var za=0; za<zonesK; za++){\n          areas[za] = hullArea * counts[za] \/ totalInl;\n        }\n      }\n    }\n    zoneStats = {\n      cv: cvPct, tier: tier,\n      counts: counts, means: means, mins: mins, maxs: maxs,\n      areas: areas, colors: cols,\n      meanAll: meanI\n    };\n    \/\/ Repaint the IDW background to reflect the freshly-computed zone\n    \/\/ breaks. Cheap; uses cached interpCache.values, no IDW recompute.\n    try { recolorInterpRaster(); } catch(_){}\n  }\n  function updateZonesPanel(){\n    var card = $('#gpy-zones-card');\n    var body = $('#gpy-zones-body');\n    if(!card ? true : !body) return;\n    \/\/ Hide card entirely on boundary datasets (nothing to zone).\n    \/\/ Polygon datasets (incl. pre-zoned soil-management polygons) can be zoned\n    \/\/ with as few as 1 feature \u2014 they colour the polygons directly, no IDW\n    \/\/ density needed (1 polygon = 1 zone, 2 = up to 2, etc.). Point\/yield zoning\n    \/\/ still wants \u2265 10 (its zone surface is IDW-interpolated and needs sample\n    \/\/ density to be meaningful).\n    var minForZones = mode === 'polygon' ? 1 : 10;\n    var canZone = !currentIsBoundary ? values.length >= minForZones : false;\n    card.style.display = canZone ? '' : 'none';\n    \/\/ Standalone GeoPard CTA stays visible at all times \u2014 moved off \"hide\n    \/\/ when zones are on\" because users wanted to see the brand pitch even\n    \/\/ mid-flow. Space for it was reclaimed by removing the sidebar\n    \/\/ Attribute card (the on-map chip handles attribute switching now).\n    var standalone = $('#gpy-standalone-cta');\n    if(standalone) standalone.style.display = '';\n    \/\/ CV \/ tier \u2014 ALWAYS shown when the card is visible (works as a trigger\n    \/\/ to invite users to click \"Show zones\"). Computed independently of\n    \/\/ zoneStats so it appears before any zone count is picked.\n    var vari = computeVariability();\n    var cvEl = $('#gpy-zones-cv-num');\n    var tierEl = $('#gpy-zones-cv-tier');\n    if(vari){\n      if(cvEl) cvEl.textContent = vari.cv.toFixed(1) + '%';\n      if(tierEl){\n        var lbl0 = vari.tier === 'low' ? 'Low' : (vari.tier === 'medium' ? 'Medium' : 'High');\n        tierEl.textContent = lbl0;\n        tierEl.className = 'gpy-zones-cv-tier is-' + (vari.tier === 'medium' ? 'med' : vari.tier);\n      }\n    } else {\n      if(cvEl) cvEl.textContent = '\u2014';\n      if(tierEl){ tierEl.textContent = '\u2014'; tierEl.className = 'gpy-zones-cv-tier'; }\n    }\n    if(!zonesK ? true : !zoneStats){\n      body.hidden = true;\n      return;\n    }\n    body.hidden = false;\n    \/\/ Stacked proportions bar.\n    var bar = $('#gpy-zones-bar');\n    if(bar){\n      bar.innerHTML = '';\n      var totalInl = 0;\n      for(var t=0;t<zoneStats.counts.length;t++) totalInl += zoneStats.counts[t];\n      if(totalInl <= 0) totalInl = 1;\n      for(var zi=0; zi<zoneStats.counts.length; zi++){\n        var sp = document.createElement('span');\n        var c = zoneStats.colors[zi];\n        sp.style.background = 'rgb('+c[0]+','+c[1]+','+c[2]+')';\n        sp.style.flex = (zoneStats.counts[zi] \/ totalInl) + ' 0 0';\n        bar.appendChild(sp);\n      }\n    }\n    \/\/ Zone rows: swatch + range + area (with unit). Area follows the active\n    \/\/ distance-unit toggle: hectares for metric, acres for imperial.\n    var useAc = distanceUnit === 'imperial';\n    var areaUnit = useAc ? 'ac' : 'ha';\n    function fmtArea(ha){\n      var v = useAc ? ha * 2.47105 : ha;\n      if(!isFinite(v) ? true : v <= 0) return '\u2014';\n      if(v >= 100) return Math.round(v) + ' ' + areaUnit;\n      if(v >= 10) return v.toFixed(1) + ' ' + areaUnit;\n      return v.toFixed(2) + ' ' + areaUnit;\n    }\n    \/\/ Merged zones \u00d7 rate table \u2014 each row carries swatch + label\/range +\n    \/\/ area + rate input, so the operator sees the full VRA prescription\n    \/\/ on one grid (zone, area to cover, rate to apply) instead of two\n    \/\/ separate side-by-side tables.\n    var list = $('#gpy-zones-list');\n    \/\/ Pre-populate zone rates first time with values calibrated around the\n    \/\/ zone mean \u00d7 50 (coarse default for rate-like units); user can edit each\n    \/\/ cell independently.\n    while(zoneRates.length < zonesK) zoneRates.push(null);\n    zoneRates.length = zonesK;\n    for(var zr2=0; zr2<zonesK; zr2++){\n      if(zoneRates[zr2] === null ? true : !isFinite(zoneRates[zr2])){\n        var seedVal = (zoneStats.means[zr2] > 0 ? zoneStats.means[zr2] : 1) * 50;\n        if(seedVal > 5000) seedVal = Math.round(seedVal \/ 100) * 100;\n        else if(seedVal > 500) seedVal = Math.round(seedVal \/ 10) * 10;\n        else seedVal = Math.round(seedVal);\n        if(seedVal < 1) seedVal = 1;\n        zoneRates[zr2] = seedVal;\n      }\n    }\n    if(list){\n      var rows = '';\n      for(var zr=0; zr<zoneStats.counts.length; zr++){\n        var col = zoneStats.colors[zr];\n        var swColor = 'rgb('+col[0]+','+col[1]+','+col[2]+')';\n        var rangeStr = zoneStats.counts[zr] > 0\n          ? (fmt(zoneStats.mins[zr]) + '\u2013' + fmt(zoneStats.maxs[zr]))\n          : '\u2014';\n        var areaHa = zoneStats.areas ? zoneStats.areas[zr] : 0;\n        rows += '<div class=\"gpy-zones-row\">' +\n                '<span class=\"gpy-zones-sw\" style=\"background:'+swColor+'\"><\/span>' +\n                '<span class=\"gpy-zones-rng\">Z'+(zr+1)+' \u00b7 '+rangeStr+'<\/span>' +\n                '<span class=\"gpy-zones-area\">'+fmtArea(areaHa)+'<\/span>' +\n                '<input type=\"number\" inputmode=\"decimal\" data-z=\"'+zr+'\" value=\"'+zoneRates[zr]+'\" min=\"0\" step=\"any\" aria-label=\"Rate for Z'+(zr+1)+'\">' +\n                '<\/div>';\n      }\n      list.innerHTML = rows;\n      var rInputs = list.querySelectorAll('input[data-z]');\n      for(var ri2=0; ri2<rInputs.length; ri2++){\n        rInputs[ri2].oninput = function(){\n          var zi = +this.dataset.z;\n          var v = parseFloat(this.value);\n          zoneRates[zi] = isFinite(v) ? v : 0;\n          renderRatesTotal();\n        };\n      }\n    }\n    var unitSel = $('#gpy-zones-unit');\n    if(unitSel){\n      \/\/ <select> with optgroups \u2014 sync the dropdown to the current state, and\n      \/\/ listen on change (input doesn't fire on selects).\n      unitSel.value = zoneRateUnit;\n      \/\/ If the stored unit isn't in the option list (legacy custom value),\n      \/\/ fall back to kg\/ha so the dropdown shows a valid selection.\n      if(unitSel.value !== zoneRateUnit){ zoneRateUnit = 'kg\/ha'; unitSel.value = 'kg\/ha'; }\n      unitSel.onchange = function(){\n        zoneRateUnit = this.value || 'kg\/ha';\n        renderRatesTotal();\n      };\n    }\n    \/\/ Target-average rate input. Smart-distribute on type: linear gradient\n    \/\/ (lower-value zones get more product, higher-value zones get less)\n    \/\/ area-weighted so the field-wide average lands exactly on the target.\n    var avgInput = $('#gpy-zones-avg-input');\n    if(avgInput){\n      avgInput.oninput = function(){\n        var target = parseFloat(this.value);\n        if(!isFinite(target) ? true : target <= 0) return;\n        distributeRatesFromAvg(target);\n      };\n    }\n    renderRatesTotal();\n    \/\/ Render the value-distribution histograms (sidebar + map overlay) +\n    \/\/ draggable break thumbs. Wired once per wrap via setupHistogramDrag\n    \/\/ (idempotent). Repaints on every updateZonesPanel so K changes \/\n    \/\/ attribute switches \/ break drags refresh BOTH views together.\n    try { renderHistogram('gpy-zones-hist', 48); setupHistogramDrag('gpy-zones-hist'); } catch(_){}\n    try { renderHistogram('gpy-legend-hist', 32); setupHistogramDrag('gpy-legend-hist'); } catch(_){}\n    try { renderLegendBarZThumbs(); setupHistogramDrag('gpy-legend-bar'); } catch(_){}\n    \/\/ ROI is expressed as a PERCENTAGE of gross revenue. The FDE doesn't know\n    \/\/ what crop \/ price \/ yield the user actually farms \u2014 we have a column of\n    \/\/ numeric values whose unit could be t\/ha, bu\/ac, lbs\/ac, pH, ppm, etc.\n    \/\/ Multiplying mean \u00d7 $200 was producing absurd $\/ha figures when the\n    \/\/ column wasn't a yield-in-t\/ha (e.g. soil pH \u00d7 $200 = nonsense). The\n    \/\/ percentage is the agronomically meaningful, unit-independent number.\n    \/\/\n    \/\/ A small corn-baseline $ figure ($2k\/ha typical revenue \u00d7 pct) is shown\n    \/\/ alongside as a \"for reference\" anchor \u2014 clearly labelled so users know\n    \/\/ it's a baseline, not their actual farm.\n    var central = ZONE_ROI_BASE * ZONE_ROI_MULT[zoneStats.tier] * ZONE_ROI_PRACTICES;\n    var loPct = central * (1 - ZONE_ROI_RANGE) * 100;\n    var hiPct = central * (1 + ZONE_ROI_RANGE) * 100;\n    var roiEl = $('#gpy-zones-roi-v');\n    if(roiEl){\n      roiEl.textContent = '+' + loPct.toFixed(1) + '\u2013' + hiPct.toFixed(1) + '% of gross revenue';\n    }\n    \/\/ Reference $ figure assuming a typical $2k\/ha corn revenue, surfaced as\n    \/\/ a smaller secondary line so the absolute number is clearly an example.\n    var refRevHa = 2000;\n    var refLo = refRevHa * central * (1 - ZONE_ROI_RANGE);\n    var refHi = refRevHa * central * (1 + ZONE_ROI_RANGE);\n    var refUseAc = distanceUnit === 'imperial';\n    var refDivisor = refUseAc ? 2.47105 : 1;\n    var refUnit = refUseAc ? '\/ac\/yr' : '\/ha\/yr';\n    var refEl = $('#gpy-zones-roi-ref');\n    if(refEl){\n      var rLo = refLo \/ refDivisor, rHi = refHi \/ refDivisor;\n      refEl.textContent = 'For example, at $' + (refUseAc ? '810' : '2000') + ' gross ' + refUnit.slice(1) + ' (corn-ish baseline): ~$' + Math.round(rLo) + '\u2013' + Math.round(rHi) + ' ' + refUnit;\n    }\n  }\n  \/\/ Reclassify all features into zones using the CURRENT zoneBreaks array\n  \/\/ (which may have been hand-edited by dragging a histogram thumb). Rebuilds\n  \/\/ zoneClass + zoneStats \u2014 same logic as computeZones() but without the\n  \/\/ quantileBreaks(inl, zonesK) step that would overwrite user edits. Cheap\n  \/\/ (O(features)); safe to call on every pointer-move during a drag.\n  function reclassifyWithBreaks(){\n    if(!zonesK ? true : !values ? true : !values.length ? true : !zoneBreaks) return;\n    var palIdx = zonePaletteIdx(zonesK);\n    if(!zoneClass) zoneClass = new Uint8Array(values.length);\n    var counts = new Uint32Array(zonesK);\n    var sums = new Float64Array(zonesK);\n    var mins = new Float64Array(zonesK); for(var z0=0;z0<zonesK;z0++) mins[z0] = Infinity;\n    var maxs = new Float64Array(zonesK); for(var z1=0;z1<zonesK;z1++) maxs[z1] = -Infinity;\n    for(var f=0; f<values.length; f++){\n      if(outClass[f] !== 0){ zoneClass[f] = 255; continue; }\n      var v = values[f];\n      var idx = 0;\n      for(var b=0; b<zoneBreaks.length; b++){\n        if(v >= zoneBreaks[b]) idx = b + 1;\n        else break;\n      }\n      if(idx >= zonesK) idx = zonesK - 1;\n      zoneClass[f] = idx;\n      counts[idx]++;\n      sums[idx] += v;\n      if(v < mins[idx]) mins[idx] = v;\n      if(v > maxs[idx]) maxs[idx] = v;\n    }\n    var means = new Float32Array(zonesK), cols = new Array(zonesK);\n    for(var z=0; z<zonesK; z++){\n      means[z] = counts[z] > 0 ? sums[z] \/ counts[z] : 0;\n      cols[z] = STOP_COLORS[palIdx[z]];\n    }\n    \/\/ Recompute per-zone area using the existing area-allocation logic in\n    \/\/ computeZones. Simplest: scale total area by zone counts. For sparse\n    \/\/ datasets this matches; for polygon mode the polygon-area path lives\n    \/\/ in computeZones itself. Re-running computeZones here would clobber\n    \/\/ zoneBreaks (it calls quantileBreaks). Instead, scale proportionally.\n    var totalCount = 0;\n    for(var zc=0; zc<zonesK; zc++) totalCount += counts[zc];\n    var totalAreaHa = 0;\n    if(zoneStats ? zoneStats.areas : false){\n      for(var za=0; za<zoneStats.areas.length; za++) totalAreaHa += zoneStats.areas[za];\n    }\n    var areas = new Float32Array(zonesK);\n    if(totalCount > 0 ? totalAreaHa > 0 : false){\n      for(var za2=0; za2<zonesK; za2++) areas[za2] = totalAreaHa * (counts[za2] \/ totalCount);\n    }\n    zoneStats = {\n      counts: counts, means: means, mins: mins, maxs: maxs,\n      colors: cols, areas: areas,\n      cv: zoneStats ? zoneStats.cv : 0,\n      tier: zoneStats ? zoneStats.tier : 'medium'\n    };\n  }\n  \/\/ Render the histogram + draggable break thumbs. Takes a wrap ID so a\n  \/\/ second compact histogram can be painted on the canvas legend overlay\n  \/\/ alongside the sidebar one \u2014 both share zoneBreaks, so dragging a thumb\n  \/\/ on either re-classifies and re-renders both.\n  \/\/ wrapId: 'gpy-zones-hist' (sidebar) or 'gpy-legend-hist' (map overlay).\n  \/\/ heightPx: drawing buffer height \u2014 sidebar uses 48 px, overlay 32 px.\n  function renderHistogram(wrapId, heightPx){\n    if(!wrapId) wrapId = 'gpy-zones-hist';\n    if(!heightPx) heightPx = 48;\n    var wrap = $('#'+wrapId);\n    var cnv = $('#'+wrapId+'-canvas');\n    var track = $('#'+wrapId+'-track');\n    var scaleEl = $('#'+wrapId+'-scale');\n    if(!wrap ? true : !cnv ? true : !track) return;\n    if(!values ? true : !values.length){ wrap.style.display = 'none'; return; }\n    \/\/ Histogram is always visible when data exists, even with zones off \u2014\n    \/\/ the distribution shape itself is useful (range, skew, modality). When\n    \/\/ zones are off, bars take their colour from the IDW gradient via\n    \/\/ colorForValue() and the K-1 zone-break thumbs are skipped.\n    var hasZones = zonesK > 0 ? (zoneBreaks ? zoneStats : false) : false;\n    wrap.style.display = '';\n    \/\/ Clip the X axis to the INLIER value range. A single high outlier (a\n    \/\/ sensor spike at 11,343 kg\/ha on a 2,000 kg\/ha soybean field, say) on\n    \/\/ the full-sorted axis squashes the meaningful distribution into the\n    \/\/ left ~30 % and leaves the rest of the histogram blank. The inlier\n    \/\/ range matches what the user actually farms \u2014 bars fill the width.\n    \/\/ The legend-bar's K-1 zone-break thumbs use the same range so they\n    \/\/ line up with the histogram thumbs above (the 5 color-stop thumbs\n    \/\/ that use the full sorted range are hidden while zones are on).\n    var vLo = Infinity, vHi = -Infinity;\n    for(var vi=0; vi<values.length; vi++){\n      if(outClass[vi] !== 0) continue;\n      var v = values[vi];\n      if(!isFinite(v)) continue;\n      if(v < vLo) vLo = v;\n      if(v > vHi) vHi = v;\n    }\n    if(!isFinite(vLo) ? true : !isFinite(vHi) ? true : vHi <= vLo){ wrap.style.display = 'none'; return; }\n    \/\/ 40-bin histogram, painted as alpha-blended bars (so dense distributions\n    \/\/ read like a smooth curve).\n    var nBins = 40;\n    var bins = new Uint32Array(nBins);\n    var maxBin = 0;\n    for(var bi=0; bi<values.length; bi++){\n      if(outClass[bi] !== 0) continue;\n      var bv = values[bi];\n      if(!isFinite(bv)) continue;\n      var t = (bv - vLo) \/ (vHi - vLo);\n      var bidx = Math.floor(t * nBins);\n      if(bidx < 0) bidx = 0; if(bidx >= nBins) bidx = nBins - 1;\n      bins[bidx]++;\n      if(bins[bidx] > maxBin) maxBin = bins[bidx];\n    }\n    \/\/ Fit canvas drawing buffer to its CSS size (for crisp lines on HiDPI).\n    var rect = cnv.getBoundingClientRect();\n    var dpr = window.devicePixelRatio || 1;\n    var cw = Math.max(40, Math.floor(rect.width));\n    var ch = heightPx;\n    cnv.width = cw * dpr;\n    cnv.height = ch * dpr;\n    var ctx2 = cnv.getContext('2d');\n    ctx2.setTransform(dpr, 0, 0, dpr, 0, 0);\n    ctx2.clearRect(0, 0, cw, ch);\n    \/\/ Background fill for the bars. When zones are on, each bin's bar takes\n    \/\/ the colour of its zone (so the histogram visually reflects the active\n    \/\/ classification). When zones are off, bars take the IDW gradient colour\n    \/\/ at the bin's centre value \u2014 the histogram still reads as a \"scale\".\n    var palIdx = hasZones ? zonePaletteIdx(zonesK) : null;\n    var pad = 2;\n    var barW = (cw - pad*2) \/ nBins;\n    for(var k=0; k<nBins; k++){\n      var binV = vLo + (k + 0.5) * ((vHi - vLo) \/ nBins);\n      var col;\n      if(hasZones){\n        var zIdx = 0;\n        for(var bb=0; bb<zoneBreaks.length; bb++){\n          if(binV >= zoneBreaks[bb]) zIdx = bb + 1;\n          else break;\n        }\n        if(zIdx >= zonesK) zIdx = zonesK - 1;\n        col = STOP_COLORS[palIdx[zIdx]];\n      } else {\n        col = colorForValue(binV);\n      }\n      ctx2.fillStyle = 'rgba('+col[0]+','+col[1]+','+col[2]+',0.85)';\n      var h = maxBin > 0 ? (bins[k] \/ maxBin) * (ch - 6) : 0;\n      ctx2.fillRect(pad + k*barW, ch - 4 - h, Math.max(1, barW - 0.5), h);\n    }\n    \/\/ Outlier indicators at the extreme left + right of the histogram.\n    \/\/ Grey for low outliers (outClass===1, values below loCutoff), violet\n    \/\/ for high outliers (outClass===2, above hiT). Drawn as a thin solid\n    \/\/ column at each edge, height proportional to outlier count (capped to\n    \/\/ the inlier max). The bars overlap the first\/last inlier bin position\n    \/\/ so the inlier-range axis used by the zone-break thumbs is unchanged.\n    var lowOut = 0, highOut = 0;\n    for(var oi=0; oi<values.length; oi++){\n      if(outClass[oi] === 1) lowOut++;\n      else if(outClass[oi] === 2) highOut++;\n    }\n    var outlierBarW = Math.max(3, Math.min(barW, 6));\n    if(lowOut > 0){\n      var hL = maxBin > 0 ? (lowOut \/ maxBin) * (ch - 6) : 0;\n      if(hL > ch - 6) hL = ch - 6;\n      ctx2.fillStyle = themeColors.grey ? themeColors.grey : 'rgba(170,170,170,0.9)';\n      ctx2.fillRect(pad, ch - 4 - hL, outlierBarW, hL);\n    }\n    if(highOut > 0){\n      var hH = maxBin > 0 ? (highOut \/ maxBin) * (ch - 6) : 0;\n      if(hH > ch - 6) hH = ch - 6;\n      ctx2.fillStyle = themeColors.violet ? themeColors.violet : 'rgba(168,85,247,0.9)';\n      ctx2.fillRect(cw - pad - outlierBarW, ch - 4 - hH, outlierBarW, hH);\n    }\n    \/\/ Build thumbs. Re-render from scratch so K changes (3 \u2192 4 \u2192 5) re-create\n    \/\/ the right thumb count without orphans. Use a marker class \u2014 the .gpy-\n    \/\/ zones-hist-thumb class drives the visual style but is shared by the\n    \/\/ overlay variant too via CSS scoping; the marker keeps removeChild\n    \/\/ scoped to this wrap.\n    var oldThumbs = wrap.querySelectorAll('[data-bi]');\n    for(var ot=0; ot<oldThumbs.length; ot++) oldThumbs[ot].parentNode.removeChild(oldThumbs[ot]);\n    \/\/ No thumbs when zones are off \u2014 the histogram becomes a passive\n    \/\/ distribution view (no break sliders).\n    if(!hasZones ? true : zoneBreaks.length === 0){\n      track.style.display = 'none';\n      if(scaleEl){\n        scaleEl.innerHTML = '<span class=\"lo\">'+fmt(vLo)+(currentUnit ? ' '+currentUnit : '')+'<\/span><span class=\"hi\">'+fmt(vHi)+'<\/span>';\n      }\n      wrap.dataset.vlo = vLo;\n      wrap.dataset.vhi = vHi;\n      return;\n    }\n    track.style.display = '';\n    for(var ti=0; ti<zoneBreaks.length; ti++){\n      var tv = zoneBreaks[ti];\n      var pct = (tv - vLo) \/ (vHi - vLo) * 100;\n      if(pct < 0) pct = 0; if(pct > 100) pct = 100;\n      var thumb = document.createElement('div');\n      thumb.className = 'gpy-zones-hist-thumb';\n      thumb.dataset.bi = ti;\n      thumb.style.left = pct + '%';\n      var readout = document.createElement('div');\n      readout.className = 'gpy-zones-hist-readout';\n      readout.textContent = fmt(tv);\n      thumb.appendChild(readout);\n      wrap.appendChild(thumb);\n    }\n    if(scaleEl){\n      scaleEl.innerHTML = '<span class=\"lo\">'+fmt(vLo)+(currentUnit ? ' '+currentUnit : '')+'<\/span><span class=\"hi\">'+fmt(vHi)+'<\/span>';\n    }\n    \/\/ Cache axis range on the wrap element so drag handlers can read it\n    \/\/ without re-scanning every pointer-move.\n    wrap.dataset.vlo = vLo;\n    wrap.dataset.vhi = vHi;\n  }\n  \/\/ Mirror the K-1 zone-break thumbs DIRECTLY onto the legend-bar, sharing\n  \/\/ zoneBreaks state with the sidebar + overlay histograms. When zones are\n  \/\/ active, the 5 color-stop thumbs are hidden and replaced by K-1 zone-\n  \/\/ break thumbs at the SAME X positions used by the histograms (full data\n  \/\/ range from sorted[0] \u2026 sorted[last]). Dragging any of the three thumb\n  \/\/ sets re-classifies + re-renders all three together.\n  function renderLegendBarZThumbs(){\n    var bar = $('#gpy-legend-bar');\n    if(!bar) return;\n    \/\/ Remove any prior zone-break thumbs (rebuilt from scratch on every\n    \/\/ updateZonesPanel so K changes don't leave orphans).\n    var prior = bar.querySelectorAll('[data-bi]');\n    for(var pi=0; pi<prior.length; pi++) prior[pi].parentNode.removeChild(prior[pi]);\n    \/\/ Color-stop thumbs are the 5 thumbs the user normally drags to anchor\n    \/\/ the gradient. When zones are on, we hide them so the bar shows only\n    \/\/ the zone breaks \u2014 clearer mental model, no two competing slider sets.\n    var stopThumbs = bar.querySelectorAll('.gpy-legend-thumb');\n    var showZones = zonesK > 0 ? zoneBreaks : null;\n    for(var si=0; si<stopThumbs.length; si++){\n      stopThumbs[si].style.display = showZones ? 'none' : '';\n    }\n    if(!showZones) return;\n    \/\/ Position uses the INLIER range \u2014 same axis the histogram uses. A\n    \/\/ single sensor outlier on the sorted-full range would have stretched\n    \/\/ the bar, pushing all the meaningful zone breaks into a thin cluster\n    \/\/ on the left. Inlier range matches the histogram bars above so the\n    \/\/ thumbs visually align.\n    if(!values ? true : !values.length) return;\n    var dataMin = Infinity, dataMax = -Infinity;\n    for(var bvi=0; bvi<values.length; bvi++){\n      if(outClass[bvi] !== 0) continue;\n      var bv = values[bvi];\n      if(!isFinite(bv)) continue;\n      if(bv < dataMin) dataMin = bv;\n      if(bv > dataMax) dataMax = bv;\n    }\n    if(!isFinite(dataMin) ? true : !isFinite(dataMax)) return;\n    var dataRange = dataMax - dataMin;\n    if(dataRange <= 0) return;\n    for(var ti=0; ti<zoneBreaks.length; ti++){\n      var tv = zoneBreaks[ti];\n      var pct = (tv - dataMin) \/ dataRange * 100;\n      if(pct < 0) pct = 0; if(pct > 100) pct = 100;\n      var thumb = document.createElement('div');\n      thumb.className = 'gpy-zones-hist-thumb gpy-legend-bar-zthumb';\n      thumb.dataset.bi = ti;\n      thumb.style.left = pct + '%';\n      var readout = document.createElement('div');\n      readout.className = 'gpy-zones-hist-readout';\n      readout.textContent = fmt(tv);\n      thumb.appendChild(readout);\n      bar.appendChild(thumb);\n    }\n    \/\/ Cache range on the bar so setupHistogramDrag can read it the same way\n    \/\/ it reads vlo\/vhi off the other histogram wraps.\n    bar.dataset.vlo = dataMin;\n    bar.dataset.vhi = dataMax;\n  }\n  \/\/ Single global drag handler attached once per wrap \u2014 uses event delegation\n  \/\/ so dynamically-rebuilt thumbs don't need re-binding. Both the sidebar\n  \/\/ histogram and the map-overlay histogram share zoneBreaks, so dragging\n  \/\/ either re-classifies and triggers updateZonesPanel which re-renders both.\n  function setupHistogramDrag(wrapId){\n    if(!wrapId) wrapId = 'gpy-zones-hist';\n    var wrap = $('#'+wrapId);\n    if(!wrap ? true : wrap._gpyDragWired) return;\n    wrap._gpyDragWired = true;\n    var dragState = null;\n    function onMove(e){\n      if(!dragState) return;\n      e.preventDefault();\n      var rect = wrap.getBoundingClientRect();\n      \/\/ Read pad from the actual track element so the same handler works\n      \/\/ for the sidebar histogram (7 px padding) AND the legend overlay\n      \/\/ (0 padding) without per-wrap branching.\n      var trackEl = wrap.querySelector('[id$=\"-track\"]');\n      var trackRect = trackEl ? trackEl.getBoundingClientRect() : rect;\n      var trackLeft = trackRect.left - rect.left;\n      var trackW = trackRect.width || (rect.width - trackLeft*2);\n      var pxX = (e.clientX !== undefined ? e.clientX : (e.touches ? e.touches[0].clientX : 0)) - rect.left - trackLeft;\n      var pct = Math.max(0, Math.min(1, pxX \/ trackW));\n      var vLo = parseFloat(wrap.dataset.vlo);\n      var vHi = parseFloat(wrap.dataset.vhi);\n      if(!isFinite(vLo) ? true : !isFinite(vHi)) return;\n      var newV = vLo + pct * (vHi - vLo);\n      \/\/ Keep monotonically increasing: clamp to neighbors with a small\n      \/\/ epsilon so two breaks can't cross.\n      var bi = dragState.bi;\n      var eps = (vHi - vLo) * 0.001;\n      var lo = bi > 0 ? zoneBreaks[bi-1] + eps : vLo;\n      var hi = bi < zoneBreaks.length - 1 ? zoneBreaks[bi+1] - eps : vHi;\n      if(newV < lo) newV = lo;\n      if(newV > hi) newV = hi;\n      zoneBreaks[bi] = newV;\n      dragState.thumb.style.left = ((newV - vLo) \/ (vHi - vLo) * 100) + '%';\n      var ro = dragState.thumb.querySelector('.gpy-zones-hist-readout');\n      if(ro) ro.textContent = fmt(newV);\n      \/\/ Reclassify + repaint live. The reclassify is O(features) \u2014 fast\n      \/\/ enough for real-time drag on the 17k-point soil scanner.\n      reclassifyWithBreaks();\n      \/\/ Recolour the cached IDW background raster too. This is cheap\n      \/\/ (~5 ms for 9216 cells) because it reuses interpCache.values; we're\n      \/\/ just repainting the offscreen canvas with new zone colors, NOT\n      \/\/ recomputing the k-nearest IDW.\n      try { recolorInterpRaster(); } catch(_){}\n      \/\/ Refresh per-zone rows + total + histogram bar colours.\n      try { updateZonesPanel(); } catch(_){}\n      try { draw(); } catch(_){}\n    }\n    function onUp(){\n      if(!dragState) return;\n      dragState.thumb.classList.remove('is-drag');\n      dragState = null;\n      document.removeEventListener('pointermove', onMove);\n      document.removeEventListener('pointerup', onUp);\n      document.removeEventListener('pointercancel', onUp);\n    }\n    wrap.addEventListener('pointerdown', function(e){\n      var t = e.target.closest ? e.target.closest('[data-bi]') : null;\n      if(!t) return;\n      e.preventDefault();\n      var bi = +t.dataset.bi;\n      if(!isFinite(bi)) return;\n      dragState = { bi: bi, thumb: t };\n      t.classList.add('is-drag');\n      document.addEventListener('pointermove', onMove);\n      document.addEventListener('pointerup', onUp);\n      document.addEventListener('pointercancel', onUp);\n    });\n  }\n  \/\/ Given a target field-wide average rate, set per-zone rates via a linear\n  \/\/ spread anchored on the MIDDLE zone(s): Z1 (lowest value) starts at\n  \/\/ 1-spread, ZK (highest value) at 1+spread, linear interpolation between\n  \/\/ so the middle zone sits near 1 (\u2248 target). Then scale by area weight\n  \/\/ so the area-weighted average lands EXACTLY on the target \u2014 the\n  \/\/ \u00b1spread percentage is a soft preference, the weighted average is the\n  \/\/ hard constraint. Standard \"production-replacement\" VRA strategy:\n  \/\/ apply MORE where the field is more productive, LESS where it's not.\n  \/\/ User can hand-edit any zone afterward \u2014 that overrides for that row.\n  function distributeRatesFromAvg(target){\n    if(!zoneStats ? true : !zoneStats.areas) return;\n    if(!zonesK) return;\n    if(!isFinite(target) ? true : target <= 0) return;\n    var K = zonesK;\n    var spread = 0.15;  \/\/ \u00b115% from middle (per user spec)\n    \/\/ Linear gradient: rs[0] = 1-spread (LOWER zone \u2192 less product),\n    \/\/ rs[K-1] = 1+spread (HIGHER zone \u2192 more product). Middle zone(s)\n    \/\/ sit near 1 (\u2248 target).\n    var rs = new Array(K);\n    var totalA = 0;\n    var weightedR = 0;\n    for(var i=0;i<K;i++){\n      var t = K > 1 ? (i \/ (K-1)) : 0.5;\n      rs[i] = 1 + spread * (2*t - 1);\n      var aHa = zoneStats.areas[i] || 0;\n      totalA += aHa;\n      weightedR += aHa * rs[i];\n    }\n    \/\/ Scale so the area-weighted average of rs hits 1 exactly \u2014 then\n    \/\/ target \u00d7 rs[i] \u00d7 scale is per-zone rate, and \u03a3(area \u00d7 rate) \/ \u03a3(area) = target.\n    var avgR = totalA > 0 ? weightedR \/ totalA : 1;\n    var scale = avgR > 0 ? 1 \/ avgR : 1;\n    for(var z=0;z<K;z++){\n      var raw = target * rs[z] * scale;\n      var rounded;\n      if(raw >= 1000) rounded = Math.round(raw \/ 10) * 10;\n      else if(raw >= 100) rounded = Math.round(raw);\n      else if(raw >= 10) rounded = Math.round(raw * 10) \/ 10;\n      else rounded = Math.round(raw * 100) \/ 100;\n      if(rounded < 0) rounded = 0;\n      zoneRates[z] = rounded;\n    }\n    if(root){\n      var rIn = root.querySelectorAll('#gpy-zones-list input[data-z]');\n      for(var ri=0; ri<rIn.length; ri++){\n        var zi = +rIn[ri].dataset.z;\n        if(zi >= 0 ? zi < K : false) rIn[ri].value = zoneRates[zi];\n      }\n    }\n    renderRatesTotal();\n    \/\/ Surface achieved weighted-average + total product right on the avg\n    \/\/ input row. Rounding inside the per-zone rates can shift the achieved\n    \/\/ average a hair off the typed target (e.g. target 100 \u2192 99.8); showing\n    \/\/ it confirms the smart distribute and removes \"did it work?\" ambiguity.\n    var statusEl = $('#gpy-zones-avg-status');\n    if(statusEl){\n      var realAvg = 0, realTot = 0, areaSum = 0;\n      for(var zi2=0; zi2<K; zi2++){\n        var a = zoneStats.areas[zi2] || 0;\n        realTot += a * zoneRates[zi2];\n        areaSum += a;\n      }\n      realAvg = areaSum > 0 ? realTot \/ areaSum : 0;\n      var unitTxt = zoneRateUnit || 'kg\/ha';\n      var perStripped = unitTxt.replace(\/\\s*\\\/\\s*(ha|ac|acre|hectare)s?\\s*$\/i, '');\n      var perAc = \/\\\/ac\/i.test(unitTxt);\n      var dispTot = perAc ? realTot \/ 2.47105 : realTot;\n      function _fmtN(n){\n        if(!isFinite(n) ? true : n === 0) return '0';\n        if(Math.abs(n) >= 1000) return Math.round(n).toLocaleString('en-US');\n        if(Math.abs(n) >= 100) return Math.round(n).toString();\n        if(Math.abs(n) >= 10) return (Math.round(n*10)\/10).toFixed(1);\n        return (Math.round(n*100)\/100).toFixed(2);\n      }\n      statusEl.textContent = '\u2248 ' + _fmtN(realAvg) + ' ' + unitTxt + ' \u00b7 ' + _fmtN(dispTot) + ' ' + perStripped + ' total';\n    }\n  }\n  \/\/ Compute \u03a3 rate \u00d7 area across zones (in the active distance unit) and\n  \/\/ compare against a uniform rate (mean of zone rates) over the total area.\n  \/\/ Surfaces the \"savings vs flat rate\" hook that's the actual point of VRA.\n  function renderRatesTotal(){\n    var totEl = $('#gpy-zones-rates-total-v');\n    var cmpEl = $('#gpy-zones-rates-cmp');\n    if(!totEl ? true : !zoneStats ? true : !zoneStats.areas) return;\n    var useAc = distanceUnit === 'imperial';\n    var areaUnit = useAc ? 'ac' : 'ha';\n    var unitTxt = zoneRateUnit ? zoneRateUnit : 'kg\/ha';\n    \/\/ Strip the per-area part from the unit if present so we can show a clean\n    \/\/ total like \"1,234 kg\" rather than \"1,234 kg\/ha\".\n    var perStripped = unitTxt.replace(\/\\s*\\\/\\s*(ha|ac|acre|hectare)s?\\s*$\/i, '');\n    var totalProduct = 0;\n    var totalAreaHa = 0;\n    var weightedMeanRate = 0;\n    for(var z=0; z<zonesK; z++){\n      var aHa = zoneStats.areas[z] || 0;\n      var rate = isFinite(zoneRates[z]) ? zoneRates[z] : 0;\n      totalProduct += aHa * rate;       \/\/ rate is per-ha; area in ha \u2192 result is units (kg, L, seeds, \u2026)\n      totalAreaHa += aHa;\n      weightedMeanRate += aHa * rate;\n    }\n    weightedMeanRate = totalAreaHa > 0 ? weightedMeanRate \/ totalAreaHa : 0;\n    \/\/ If the user typed an imperial unit (lb\/ac), the rate is per ac. Convert\n    \/\/ total via ac. Heuristic: detect \"\/ac\" in unit text.\n    var perAc = \/\\\/ac\/i.test(unitTxt);\n    var displayTotal = perAc ? totalProduct \/ 2.47105 : totalProduct;\n    var displayArea = useAc ? totalAreaHa * 2.47105 : totalAreaHa;\n    function fmtN(n){\n      if(!isFinite(n) ? true : n === 0) return '0';\n      if(Math.abs(n) >= 1000) return Math.round(n).toLocaleString('en-US');\n      if(Math.abs(n) >= 100) return Math.round(n).toString();\n      if(Math.abs(n) >= 10) return (Math.round(n*10)\/10).toFixed(1);\n      return (Math.round(n*100)\/100).toFixed(2);\n    }\n    totEl.textContent = fmtN(displayTotal) + ' ' + perStripped;\n    if(cmpEl){\n      if(weightedMeanRate > 0 ? totalAreaHa > 0 : false){\n        cmpEl.textContent = 'Avg ' + fmtN(weightedMeanRate) + ' ' + unitTxt + ' over ' + fmtN(displayArea) + ' ' + areaUnit;\n        cmpEl.className = 'gpy-zones-rates-cmp';\n      } else {\n        cmpEl.textContent = '';\n        cmpEl.className = 'gpy-zones-rates-cmp';\n      }\n    }\n  }\n  function setZonesK(k){\n    var requested = k | 0;\n    k = requested;\n    \/\/ Clamp to the number of available (finite, non-outlier) readings \u2014 you can't\n    \/\/ split 2 zone polygons into 5 quantile classes. Requesting more than the data\n    \/\/ supports used to silently produce NO zones (computeZones bailed on\n    \/\/ inl.length < zonesK); now it creates the most the data can support, down to a\n    \/\/ single zone (1 polygon = 1 zone).\n    if(k > 0 ? (values ? values.length : 0) : 0){\n      var avail = 0;\n      for(var ai=0; ai<values.length; ai++){ if(outClass[ai] === 0 ? isFinite(values[ai]) : false) avail++; }\n      if(k > avail) k = avail;            \/\/ \u2265 1 inlier \u21d2 at least one zone\n    }\n    zonesK = k | 0;\n    \/\/ Highlight the button the user CLICKED (requested), so the click registers\n    \/\/ even when the data supports fewer zones than the count on the button (e.g.\n    \/\/ clicking \"3\" on a 2-feature file renders 2 zones but keeps \"3\" lit).\n    var litZ = zonesK === 0 ? 0 : requested;\n    var btns = root.querySelectorAll('#gpy-zones-seg button');\n    for(var b=0; b<btns.length; b++){\n      btns[b].classList.toggle('on', +btns[b].dataset.z === litZ);\n    }\n    computeZones();\n    updateZonesPanel();\n    \/\/ The IDW interpolation values are still valid (they only depend on the\n    \/\/ attribute, not on zoneBreaks). Repaint the cached offscreen canvas with\n    \/\/ the new colors \u2014 cheap (~5 ms vs 50 ms for a full IDW rebuild).\n    try { recolorInterpRaster(); } catch(_){}\n    draw();\n  }\n  \/\/ Map a raw numeric value to a color via the active stop overrides or the\n  \/\/ auto-fitted gradient. Used by both per-feature rendering (via colorFor)\n  \/\/ and by the IDW interpolation grid (colorForValue from a Float32 cell).\n  function colorForValue(v){\n    \/\/ Auto-zones override: classify v into the active break buckets and\n    \/\/ return the categorical palette colour.\n    if(zonesK > 0 ? zoneBreaks : false){\n      var pal = zonePaletteIdx(zonesK);\n      var z = 0;\n      for(var zb=0; zb<zoneBreaks.length; zb++){\n        if(v >= zoneBreaks[zb]) z = zb + 1;\n        else break;\n      }\n      if(z >= zonesK) z = zonesK - 1;\n      return STOP_COLORS[pal[z]];\n    }\n    var anyO = false;\n    for(var ao=0; ao<stopValueOverrides.length; ao++){ if(stopValueOverrides[ao] !== null){ anyO = true; break; } }\n    if(anyO){\n      var pairs = [\n        [effStops[0], STOP_COLORS[0]],\n        [effStops[1], STOP_COLORS[1]],\n        [effStops[2], STOP_COLORS[2]],\n        [effStops[3], STOP_COLORS[3]],\n        [effStops[4], STOP_COLORS[4]]\n      ];\n      pairs.sort(function(a,b){ return a[0] - b[0]; });\n      if(v <= pairs[0][0]) return pairs[0][1];\n      if(v >= pairs[4][0]) return pairs[4][1];\n      for(var k=0; k<4; k++){\n        if(v <= pairs[k+1][0]){\n          var span = pairs[k+1][0] - pairs[k][0];\n          var tt = span > 0 ? (v - pairs[k][0]) \/ span : 0;\n          if(tt < 0) tt = 0; if(tt > 1) tt = 1;\n          var c0 = pairs[k][1], c1 = pairs[k+1][1];\n          return [c0[0]+(c1[0]-c0[0])*tt|0, c0[1]+(c1[1]-c0[1])*tt|0, c0[2]+(c1[2]-c0[2])*tt|0];\n        }\n      }\n      return pairs[4][1];\n    }\n    \/\/ No overrides \u2014 use the auto-fitted gradient via tArr scale. Compute t\n    \/\/ from the auto min\/max if available, otherwise default to mid.\n    if(effStops.length >= 2){\n      var lo = effStops[0], hi = effStops[4];\n      var t = (hi - lo > 0) ? (v - lo) \/ (hi - lo) : 0.5;\n      if(t < 0) t = 0; if(t > 1) t = 1;\n      return _stopColor(t);\n    }\n    return _stopColor(0.5);\n  }\n  function colorFor(idx){\n    \/\/ Auto-zones override (per-feature path): use cached zoneClass to skip\n    \/\/ the per-value bucket search in the hot draw loop.\n    if(zonesK > 0 ? zoneClass : false){\n      var zc = zoneClass[idx];\n      if(zc !== 255){\n        return STOP_COLORS[zonePaletteIdx(zonesK)[zc]];\n      }\n      \/\/ Fallthrough for outliers \u2014 keep their grey\/violet themeing.\n    }\n    var anyO = false;\n    for(var ao=0; ao<stopValueOverrides.length; ao++){ if(stopValueOverrides[ao] !== null){ anyO = true; break; } }\n    if(anyO){\n      var v = values[idx];\n      \/\/ Sort stops by value (preserving their original color index) so we always iterate in ascending\n      \/\/ order even when the user has set non-monotonic overrides \u2014 e.g. Min dragged past Low-mid.\n      var pairs = [\n        [effStops[0], STOP_COLORS[0]],\n        [effStops[1], STOP_COLORS[1]],\n        [effStops[2], STOP_COLORS[2]],\n        [effStops[3], STOP_COLORS[3]],\n        [effStops[4], STOP_COLORS[4]]\n      ];\n      pairs.sort(function(a,b){ return a[0] - b[0]; });\n      if(v <= pairs[0][0]) return pairs[0][1];\n      if(v >= pairs[4][0]) return pairs[4][1];\n      for(var k=0; k<4; k++){\n        if(v <= pairs[k+1][0]){\n          var span = pairs[k+1][0] - pairs[k][0];\n          var tt = span > 0 ? (v - pairs[k][0]) \/ span : 0;\n          if(tt < 0) tt = 0; if(tt > 1) tt = 1;\n          var c0 = pairs[k][1], c1 = pairs[k+1][1];\n          return [c0[0]+(c1[0]-c0[0])*tt|0, c0[1]+(c1[1]-c0[1])*tt|0, c0[2]+(c1[2]-c0[2])*tt|0];\n        }\n      }\n      return pairs[4][1];\n    }\n    var t = tArr ? tArr[idx] : 0.5;\n    return _stopColor(t);\n  }\n  function resize(){\n    if(!canvas.parentElement) return;\n    var r = canvas.parentElement.getBoundingClientRect();\n    W = r.width; H = r.height;\n    if(W<10||H<10) return;\n    canvas.width = W*DPR; canvas.height = H*DPR;\n    canvas.style.width = W+'px'; canvas.style.height = H+'px';\n    ctx.setTransform(DPR,0,0,DPR,0,0);\n    \/\/ Preserve the user's current zoom\/pan across canvas resizes. Auto-fit\n    \/\/ was kicking in whenever the sidebar grew (e.g. when zones turned on\n    \/\/ the body unhid \u2192 ResizeObserver fired \u2192 canvas snapped back to fit).\n    \/\/ First fit happens explicitly in activateDataset() and on the Reset\n    \/\/ View button (gpy-reset); resize() only redraws.\n    if(values.length){ draw(); }\n  }\n  function fitView(){\n    if(!fW) return;\n    var pad = 36;\n    var s = Math.min((W-2*pad)\/fW, (H-2*pad)\/fH);\n    view.scale = s;\n    view.tx = W\/2 - (mxMin+fW\/2)*s;\n    view.ty = H\/2 - (myMin+fH\/2)*s;\n  }\n  \/\/ Equipment description by operation type. Realistic specs but generic (not brand-specific) \u2014\n  \/\/ agronomists notice fake brand claims, but typical equipment classes are accurate.\n  \/\/ Working-width numbers reflect common North-American \/ EU mid-to-large operations.\n  var EQUIPMENT_BY_OP = {\n    harvest:     'Combine harvester \u00b7 9m draper header',\n    planting:    'Tractor \u00b7 24-row planter, 12m',\n    spraying:    'Self-propelled sprayer \u00b7 36m boom',\n    fertilizing: 'Tractor \u00b7 pneumatic spreader, 24m',\n    tillage:     'Tractor \u00b7 disc ripper, 6m',\n    application: 'Tractor \u00b7 field applicator',\n    operation:   'Tractor'\n  };\n  \/\/ Real-world throughput per op (ha\/h). Used to size playback duration so a real combine job\n  \/\/ (~6 ha\/h) plays slowly while a sprayer job (~60 ha\/h) plays faster \u2014 matching field experience.\n  var OP_THROUGHPUT_HA_PER_HR = {\n    harvest:     6,\n    planting:    10,\n    spraying:    60,\n    fertilizing: 25,\n    tillage:     6,\n    application: 15,\n    operation:   8\n  };\n  \/\/ Working width per op (meters). Defaults sized for TYPICAL FARMS (medium-sized\n  \/\/ operations, mixed-fleet equipment). Real width gets detected from file\n  \/\/ attributes (Swth_Wdth_, BoomWidth, etc.) when present \u2014 these table values\n  \/\/ are only the FALLBACK when no per-feature width attribute and no timestamp-\n  \/\/ group detection succeed. Per-op max caps prevent runaway widths (e.g.,\n  \/\/ attribute-claimed 100 m boom would be clamped down).\n  var OP_WIDTH_M = {\n    harvest:     9,   \/\/ 30 ft draper \/ 8-row corn head \u2014 typical farm combine\n    planting:    12,  \/\/ 16-row planter at 75 cm spacing\n    spraying:    24,  \/\/ 80 ft self-propelled sprayer\n    fertilizing: 15,  \/\/ medium pull spreader \/ dry box\n    tillage:     12,  \/\/ 40 ft field cultivator\n    application: 12,  \/\/ catch-all for variable-rate application\n    operation:   9    \/\/ generic fallback\n  };\n  \/\/ Hard caps per op \u2014 picked width is clamped to this even when file attributes\n  \/\/ claim something larger (file attrs sometimes report total boom span instead\n  \/\/ of actual section coverage and yield \"too wide\" visuals during playback).\n  var OP_WIDTH_MAX_M = {\n    harvest:     15,  \/\/ 50 ft draper is the upper end\n    planting:    24,  \/\/ 32-row planter\n    spraying:    40,  \/\/ 130 ft is the practical max for self-propelled\n    fertilizing: 30,\n    tillage:     18,\n    application: 24,\n    operation:   18\n  };\n  function equipmentWidthM(op){\n    return OP_WIDTH_M[op] ? OP_WIDTH_M[op] : 9;\n  }\n  function equipmentWidthMaxM(op){\n    return OP_WIDTH_MAX_M[op] ? OP_WIDTH_MAX_M[op] : 18;\n  }\n  \/\/ Compression factor: 1\u00d7 plays this much faster than real time. At 5, a real 10-hour combine\n  \/\/ job takes ~2h at 1\u00d7 and ~24 min at 5\u00d7 (default). Larger fields \u2192 longer playback, as expected.\n  \/\/ Most users will lean on 20\u00d7\/100\u00d7 presets for big fields; 1\u00d7 exists for near-real-time feel.\n  var PLAYBACK_SCALE = 5;\n  function equipmentLabel(op){\n    return EQUIPMENT_BY_OP[op] ? EQUIPMENT_BY_OP[op] : EQUIPMENT_BY_OP.operation;\n  }\n  \/\/ Draws a tractor + implement icon at (cx, cy) \u2014 where (cx, cy) is the IMPLEMENT BAR's center,\n  \/\/ not the cab's. This way the bar sits directly over the polygons being filled by playback.\n  \/\/ The cab is offset behind the bar for harvest (header pushes forward) and in front for towed\n  \/\/ implements (cab pulls the planter \/ sprayer \/ spreader).\n  function drawTractorSprite(cx, cy, heading){\n    var headerFront = playback.opLabel === 'harvest';\n    \/\/ Scale implement bar to real equipment width so it visually matches the swath band.\n    \/\/ Clamp between 12 and 120 px so it's always readable at any zoom level.\n    var realMperPx = Math.cos(latC * DEG) \/ view.scale;\n    \/\/ Sprite implement bar uses the DETECTED implement width (from data) where available,\n    \/\/ falling back to the OP_WIDTH_M table for the operation type. Multi-section fertilizer\n    \/\/ \/ planter \/ sprayer data exposes the real width via timestamp-grouped polygon spans;\n    \/\/ table widths are typical defaults that often don't match the actual machine.\n    var widthForSprite = playback.implementWidth ? playback.implementWidth : equipmentWidthM(playback.opLabel);\n    var swathRaw = widthForSprite \/ realMperPx;\n    var swathPxHalf = swathRaw \/ 2;\n    if(swathPxHalf < 6) swathPxHalf = 6;\n    if(swathPxHalf > 60) swathPxHalf = 60;\n    var barDepth = 6;  \/\/ pixels along travel direction\n    var cabSize = Math.max(8, Math.round(swathPxHalf * 0.35));\n    var noseOff = barDepth + 1;\n    ctx.save();\n    ctx.translate(cx, cy);\n    ctx.rotate(heading);\n    \/\/ Implement bar \u2014 spans equipment width perpendicular to travel. Saturated orange with a\n    \/\/ thick white outline so it's unambiguous on any background colour.\n    ctx.fillStyle = '#f76a0c';\n    ctx.strokeStyle = '#ffffff';\n    ctx.lineWidth = 2.5;\n    ctx.fillRect(-barDepth \/ 2, -swathPxHalf, barDepth, swathPxHalf * 2);\n    ctx.strokeRect(-barDepth \/ 2, -swathPxHalf, barDepth, swathPxHalf * 2);\n    \/\/ Cab \u2014 sized proportionally, offset in the lead\/trail direction.\n    ctx.fillStyle = '#145328';\n    var cabX = headerFront ? -(barDepth \/ 2 + cabSize) : (barDepth \/ 2);\n    ctx.fillRect(cabX, -cabSize \/ 2, cabSize, cabSize);\n    ctx.strokeRect(cabX, -cabSize \/ 2, cabSize, cabSize);\n    \/\/ Forward nose triangle at the leading tip.\n    ctx.fillStyle = '#22c55e';\n    ctx.beginPath();\n    if(headerFront){\n      ctx.moveTo(barDepth \/ 2 + noseOff, 0);\n      ctx.lineTo(barDepth \/ 2, -3); ctx.lineTo(barDepth \/ 2, 3);\n    } else {\n      var noseTip = barDepth \/ 2 + cabSize + noseOff;\n      ctx.moveTo(noseTip, 0);\n      ctx.lineTo(noseTip - noseOff, -3); ctx.lineTo(noseTip - noseOff, 3);\n    }\n    ctx.closePath();\n    ctx.fill(); ctx.stroke();\n    ctx.restore();\n    var label = equipmentLabel(playback.opLabel);\n    ctx.save();\n    ctx.font = '600 11.5px \"Poppins\", system-ui, -apple-system, sans-serif';\n    ctx.textBaseline = 'middle';\n    var tw = ctx.measureText(label).width;\n    var padX = 8, hh = 20;\n    var lx = cx + 22, ly = cy;\n    if(lx + tw + padX*2 > W) lx = cx - 22 - tw - padX*2;\n    if(lx < 0) lx = 4;\n    if(ly - hh\/2 < 0) ly = hh\/2 + 2;\n    if(ly + hh\/2 > H) ly = H - hh\/2 - 2;\n    ctx.fillStyle = 'rgba(255,255,255,0.94)';\n    ctx.strokeStyle = 'rgba(20,83,40,0.45)';\n    ctx.lineWidth = 1;\n    ctx.fillRect(lx, ly - hh\/2, tw + padX*2, hh);\n    ctx.strokeRect(lx, ly - hh\/2, tw + padX*2, hh);\n    ctx.fillStyle = '#145328';\n    ctx.fillText(label, lx + padX, ly);\n    ctx.restore();\n  }\n  function draw(){\n    var n = values.length;\n    if(!n){ ctx.clearRect(0,0,W,H); return; }\n    ctx.fillStyle = themeColors.canvasBg;\n    ctx.fillRect(0,0,W,H);\n    \/\/ optional grid overlay\n    if(showGrid){\n      ctx.strokeStyle = themeColors.grid; ctx.lineWidth = 1;\n      var gs = 50*view.scale;\n      if(gs > 15){\n        var x0 = view.tx%gs, y0 = view.ty%gs;\n        ctx.beginPath();\n        for(var x=x0;x<W;x+=gs){ ctx.moveTo(x,0); ctx.lineTo(x,H); }\n        for(var y=y0;y<H;y+=gs){ ctx.moveTo(0,y); ctx.lineTo(W,y); }\n        ctx.stroke();\n      }\n    }\n    if(mode === 'point'){\n      drawPoints();\n    } else {\n      drawPolygons();\n    }\n    \/\/ Field-hull overlay \u2014 one dashed outline per concave-hull cluster on\n    \/\/ playback.fieldHulls. Each cluster is a separate field; the overlay shows what\n    \/\/ is being treated as the field boundary so the user can see whether the U-turn\n    \/\/ clamp's \"inside the field\" check matches the visible polygons. Drawn after\n    \/\/ polygons so the line sits on top of the worked area but underneath the trail\n    \/\/ and sprite.\n    if(playback.fieldHulls ? playback.fieldHulls.length : false){\n      ctx.save();\n      ctx.strokeStyle = 'rgba(247, 106, 12, 0.85)';  \/\/ brand accent orange\n      ctx.lineWidth = 1.5;\n      ctx.setLineDash([8, 5]);\n      var hAll = playback.fieldHulls;\n      for(var hK=0; hK<hAll.length; hK++){\n        var hH = hAll[hK];\n        var hN = hH.x.length;\n        if(hN > 2){\n          ctx.beginPath();\n          for(var hI=0; hI<hN; hI++){\n            var hsx = hH.x[hI] * view.scale + view.tx;\n            var hsy = hH.y[hI] * view.scale + view.ty;\n            if(hI === 0) ctx.moveTo(hsx, hsy); else ctx.lineTo(hsx, hsy);\n          }\n          ctx.stroke();\n        }\n        \/\/ Interior data gaps \u2014 trees \/ ponds \/ refused zones inside the boundary.\n        \/\/ Rendered in the same dashed-orange style so they read as \"boundary too\".\n        if(hH.holes ? hH.holes.length : false){\n          for(var hoI=0; hoI<hH.holes.length; hoI++){\n            var hoH = hH.holes[hoI];\n            if(!hoH ? true : hoH.x.length < 3) continue;\n            ctx.beginPath();\n            for(var hoJ=0; hoJ<hoH.x.length; hoJ++){\n              var hosx = hoH.x[hoJ] * view.scale + view.tx;\n              var hosy = hoH.y[hoJ] * view.scale + view.ty;\n              if(hoJ === 0) ctx.moveTo(hosx, hosy); else ctx.lineTo(hosx, hosy);\n            }\n            ctx.stroke();\n          }\n        }\n      }\n      ctx.restore();\n    }\n    \/\/ Axis-arrow overlay \u2014 visible compass-style arrow per cluster showing the\n    \/\/ detected dominant heading. Anchored at the hull centroid; length proportional\n    \/\/ to the hull's diagonal (clamped). Lets the user spot a wrong axis visually\n    \/\/ without reading the hint line. Gated by showMachinePath \u2014 hidden by default\n    \/\/ (matches released live page).\n    if(showMachinePath ? (playback.fieldAxes ? playback.fieldAxes.length : false) : false){\n      ctx.save();\n      ctx.strokeStyle = 'rgba(20, 83, 40, 0.9)';  \/\/ brand primary dark green\n      ctx.fillStyle = 'rgba(20, 83, 40, 0.9)';\n      ctx.lineWidth = 2;\n      ctx.setLineDash([]);\n      var axAll = playback.fieldAxes;\n      var huAll = playback.fieldHulls;\n      for(var aK=0; aK<axAll.length; aK++){\n        var ax = axAll[aK];\n        if(!ax) continue;\n        var hu = huAll[aK];\n        if(!hu ? true : hu.x.length < 3) continue;\n        var cxM = 0, cyM = 0, ncm = hu.x.length - 1;\n        var hxMin = Infinity, hxMax = -Infinity, hyMin = Infinity, hyMax = -Infinity;\n        for(var ci=0; ci<ncm; ci++){\n          cxM += hu.x[ci]; cyM += hu.y[ci];\n          if(hu.x[ci] < hxMin) hxMin = hu.x[ci];\n          if(hu.x[ci] > hxMax) hxMax = hu.x[ci];\n          if(hu.y[ci] < hyMin) hyMin = hu.y[ci];\n          if(hu.y[ci] > hyMax) hyMax = hu.y[ci];\n        }\n        cxM \/= ncm; cyM \/= ncm;\n        var diagM = Math.sqrt((hxMax-hxMin)*(hxMax-hxMin) + (hyMax-hyMin)*(hyMax-hyMin));\n        var arrowLenM = diagM * 0.25;\n        var armLenPx = arrowLenM * view.scale;\n        if(armLenPx > 220) armLenPx = 220;\n        if(armLenPx < 60) armLenPx = 60;\n        var axCsx = cxM * view.scale + view.tx;\n        var axCsy = cyM * view.scale + view.ty;\n        \/\/ Heading direction in screen space. polyData stores Y already flipped to\n        \/\/ canvas convention (+Y = south), so uy here is canvas-Y direct \u2014 no extra\n        \/\/ sign flip needed when drawing.\n        var dxScr = ax.ux;\n        var dyScr = ax.uy;\n        var tipX = axCsx + dxScr * armLenPx;\n        var tipY = axCsy + dyScr * armLenPx;\n        var tailX = axCsx - dxScr * armLenPx * 0.5;\n        var tailY = axCsy - dyScr * armLenPx * 0.5;\n        ctx.beginPath();\n        ctx.moveTo(tailX, tailY);\n        ctx.lineTo(tipX, tipY);\n        ctx.stroke();\n        \/\/ Arrowhead\n        var headAng = Math.atan2(dyScr, dxScr);\n        var headSize = 10;\n        ctx.beginPath();\n        ctx.moveTo(tipX, tipY);\n        ctx.lineTo(tipX - headSize * Math.cos(headAng - 0.45), tipY - headSize * Math.sin(headAng - 0.45));\n        ctx.lineTo(tipX - headSize * Math.cos(headAng + 0.45), tipY - headSize * Math.sin(headAng + 0.45));\n        ctx.closePath();\n        ctx.fill();\n        \/\/ Heading label (deg from north). polyData stores Y flipped (canvas Y =\n        \/\/ south-positive); real north has uy_stored = -1. So real heading = atan2(\n        \/\/ east_real, north_real) = atan2(ux, -uy). Axis is direction-agnostic \u2014 pass\n        \/\/ at 91\u00b0 east is the same axis as pass at 271\u00b0 west \u2014 so normalize to [0, 180).\n        var hN = Math.atan2(ax.ux, -ax.uy) * 180 \/ Math.PI;\n        if(hN < 0) hN += 360;\n        if(hN >= 180) hN -= 180;\n        ctx.save();\n        ctx.fillStyle = 'rgba(20, 83, 40, 0.95)';\n        ctx.font = '12px ui-monospace, monospace';\n        ctx.textBaseline = 'middle';\n        ctx.fillText(hN.toFixed(0) + '\u00b0 \u00b7 ' + ax.source, tipX + 6, tipY);\n        ctx.restore();\n      }\n      ctx.restore();\n    }\n    \/\/ Whole-simulated-path overlay \u2014 renders the AB-line snake traversal as the\n    \/\/ planned trajectory: each cluster's AB lines connected in alternating direction\n    \/\/ (boustrophedon) with cubic-Bezier U-turn arcs between consecutive lines.\n    \/\/ Gated by showMachinePath \u2014 hidden by default (matches released live page).\n    if(showMachinePath ? (playback.abLines ? playback.abLines.perCluster.length : false) : false){\n      ctx.save();\n      ctx.strokeStyle = 'rgba(20, 83, 40, 0.70)';\n      ctx.lineWidth = 2;\n      ctx.lineCap = 'round';\n      ctx.setLineDash([6, 4]);\n      var perC = playback.abLines.perCluster;\n      var wMforAB = playback.implementWidth ? playback.implementWidth : 12;\n      var cosLatAB = Math.cos((typeof latC === 'number' ? latC : 0) * Math.PI \/ 180);\n      if(!(cosLatAB > 0)) cosLatAB = 1;\n      \/\/ U-turn Bezier control distance \u2248 1.7\u00d7 swath width so the arc rounds into a\n      \/\/ clear U not a V (matches existing headland U-turn rules in CLAUDE.md).\n      var urMerc = (wMforAB * 1.7) \/ cosLatAB;\n      ctx.beginPath();\n      for(var cAB=0; cAB<perC.length; cAB++){\n        var lns = perC[cAB];\n        if(!lns ? true : lns.length === 0) continue;\n        var prevEndX = null, prevEndY = null, prevUdx = 0, prevUdy = 0;\n        for(var li=0; li<lns.length; li++){\n          var L = lns[li];\n          var rev = (li % 2 === 1);\n          var sx0 = rev ? L.x1 : L.x0;\n          var sy0 = rev ? L.y1 : L.y0;\n          var sx1 = rev ? L.x0 : L.x1;\n          var sy1 = rev ? L.y0 : L.y1;\n          var dxL = sx1 - sx0;\n          var dyL = sy1 - sy0;\n          var lL = Math.sqrt(dxL*dxL + dyL*dyL);\n          var udx = lL > 0 ? dxL \/ lL : 0;\n          var udy = lL > 0 ? dyL \/ lL : 0;\n          if(prevEndX !== null){\n            \/\/ U-turn arc from prev-end to current-start. Both control points extend\n            \/\/ FORWARD along the PREVIOUS pass direction past their respective endpoints,\n            \/\/ looping the curve out past the field edge before doubling back into the\n            \/\/ next pass. See CLAUDE.md \"Headland U-turn shape\" for the geometry rules.\n            var cp0x = prevEndX + prevUdx * urMerc;\n            var cp0y = prevEndY + prevUdy * urMerc;\n            var cp1x = sx0 + prevUdx * urMerc;\n            var cp1y = sy0 + prevUdy * urMerc;\n            ctx.bezierCurveTo(\n              cp0x * view.scale + view.tx, cp0y * view.scale + view.ty,\n              cp1x * view.scale + view.tx, cp1y * view.scale + view.ty,\n              sx0 * view.scale + view.tx,  sy0 * view.scale + view.ty\n            );\n          } else {\n            ctx.moveTo(sx0 * view.scale + view.tx, sy0 * view.scale + view.ty);\n          }\n          ctx.lineTo(sx1 * view.scale + view.tx, sy1 * view.scale + view.ty);\n          prevEndX = sx1; prevEndY = sy1;\n          prevUdx = udx; prevUdy = udy;\n        }\n      }\n      ctx.stroke();\n      ctx.restore();\n    }\n    \/\/ AB-line overlay \u2014 synthesized parallel guidance lines that the simulated machine\n    \/\/ SHOULD follow. Drawn as thin solid green lines (distinct from the orange hull dash).\n    \/\/ Gated by showMachinePath \u2014 hidden by default (matches released live page).\n    if(showMachinePath ? (playback.abLines ? playback.abLines.flat.length : false) : false){\n      ctx.save();\n      ctx.strokeStyle = 'rgba(21, 112, 30, 0.55)';  \/\/ brand primary green at ~55% alpha\n      ctx.lineWidth = 1;\n      ctx.setLineDash([]);\n      var abAll = playback.abLines.flat;\n      ctx.beginPath();\n      for(var lK=0; lK<abAll.length; lK++){\n        var L = abAll[lK];\n        var lsx0 = L.x0 * view.scale + view.tx;\n        var lsy0 = L.y0 * view.scale + view.ty;\n        var lsx1 = L.x1 * view.scale + view.tx;\n        var lsy1 = L.y1 * view.scale + view.ty;\n        ctx.moveTo(lsx0, lsy0);\n        ctx.lineTo(lsx1, lsy1);\n      }\n      ctx.stroke();\n      ctx.restore();\n    }\n    \/\/ scale bar \u2014 true meters (Web Mercator distortion factor = cos(latC))\n    var realMperPx = Math.cos(latC*DEG) \/ view.scale;\n    var targetPx = 80;\n    var m = targetPx * realMperPx;\n    if(distanceUnit === 'imperial'){\n      \/\/ Imperial scale bar: snap to ft \/ mi\n      var ft = m * 3.28084;\n      var magI = Math.pow(10, Math.floor(Math.log10(ft)));\n      var normI = ft\/magI, snapI = 1; if(normI>=5) snapI=5; else if(normI>=2) snapI=2;\n      ft = snapI*magI;\n      m = ft \/ 3.28084;\n      var barPxI = m \/ realMperPx;\n      $('#gpy-sc-b').style.width = barPxI+'px';\n      $('#gpy-sc-t').textContent = ft >= 5280 ? (ft\/5280).toFixed(ft >= 52800 ? 0 : 2) + ' mi' : Math.round(ft) + ' ft';\n    } else {\n      var mag = Math.pow(10, Math.floor(Math.log10(m)));\n      var norm = m\/mag, snap = 1; if(norm>=5) snap=5; else if(norm>=2) snap=2;\n      m = snap*mag;\n      var barPx = m \/ realMperPx;\n      $('#gpy-sc-b').style.width = barPx+'px';\n      $('#gpy-sc-t').textContent = m>=1000 ? (m\/1000)+' km' : m+' m';\n    }\n    \/\/ Playback path + sprite. Draws (in order):\n    \/\/   1. Trail polyline through visited centroids (the \"where the tractor went\" line)\n    \/\/   2. Direction arrows along the trail at fixed pixel spacing\n    \/\/   3. Tractor sprite at the smoothly-interpolated head position\n    (function(){\n      if(!showMachinePath) return;\n      if(playback.idx <= 1) return;\n      if(currentIsBoundary) return;\n      \/\/ Hide trail entirely when playback hasn't been started yet for this dataset (initial full\n      \/\/ render shows everything at once, so a trail would be meaningless).\n      var fullRender = playback.idx >= n;\n      if(fullRender ? !playback.active : false) return;\n      var ordPB = playback.order;\n      var idxMax = playback.idx > n ? n : playback.idx;\n      var bnd = playback.boundaries;\n      \/\/ 1\u00b7SWATH \u2014 wide semi-transparent band of equipment-width meters along the visited path.\n      \/\/ Shows the actual coverage area: single passes appear light orange, overlap zones get\n      \/\/ darker because the alpha stacks. The user sees what was covered, not just where the\n      \/\/ tractor drove. Drawn UNDER the trail \/ arrows \/ sprite.\n      var realMperPxSwath = Math.cos(latC*DEG) \/ view.scale;\n      \/\/ Render the swath at the unique-coverage width so consecutive passes show as side-by-side\n      \/\/ bands rather than stacking. Uses detected implement width as the fallback ceiling.\n      var widthForSwath = playback.implementWidth ? playback.implementWidth : equipmentWidthM(playback.opLabel);\n      var swathWidthM = playback.effectiveSwath ? playback.effectiveSwath : widthForSwath;\n      var swathPx = swathWidthM \/ realMperPxSwath;\n      if(swathPx > 2){\n        ctx.save();\n        ctx.strokeStyle = 'rgba(247,106,12,0.20)';\n        ctx.lineWidth = swathPx;\n        ctx.lineCap = 'round';\n        ctx.lineJoin = 'round';\n        ctx.beginPath();\n        var swathMove = true;\n        var keptMaskSwath = playback.passKeptMask;\n        for(var swi=0; swi<idxMax; swi++){\n          if(keptMaskSwath ? !keptMaskSwath[swi] : false){ swathMove = true; continue; }\n          var sxs = pathCx(swi)*view.scale + view.tx;\n          var sys = pathCy(swi)*view.scale + view.ty;\n          if(bnd ? bnd[swi] : false) swathMove = true;\n          if(swathMove){ ctx.moveTo(sxs, sys); swathMove = false; } else { ctx.lineTo(sxs, sys); }\n        }\n        \/\/ Extend swath to live sprite or active Bezier so coverage tracks the equipment.\n        if(playback.active){\n          if(playback.turnAct ? playback.turnBezier : false){\n            var bz = playback.turnBezier;\n            var t1 = easeT(playback.turnFrac > 1 ? 1 : (playback.turnFrac < 0 ? 0 : playback.turnFrac));\n            var SUB = 16;\n            for(var ts=1; ts<=SUB; ts++){\n              var tt = (ts\/SUB) * t1;\n              var bx = bezierAt(bz, tt, 'x'), by = bezierAt(bz, tt, 'y');\n              ctx.lineTo(bx*view.scale + view.tx, by*view.scale + view.ty);\n            }\n          } else if(idxMax > 0){\n            var frac3 = playback.idxFloat - Math.floor(playback.idxFloat);\n            var iCur3 = idxMax - 1;\n            var iNxt3 = iCur3 + 1 < n ? iCur3 + 1 : iCur3;\n            var crossesBnd3 = bnd ? bnd[iNxt3] : false;\n            if(!crossesBnd3){\n              var hxL3 = spriteCx(iCur3), hyL3 = spriteCy(iCur3);\n              var nxL3 = spriteCx(iNxt3), nyL3 = spriteCy(iNxt3);\n              var liveXm3 = hxL3 + (nxL3 - hxL3) * frac3;\n              var liveYm3 = hyL3 + (nyL3 - hyL3) * frac3;\n              ctx.lineTo(liveXm3*view.scale + view.tx, liveYm3*view.scale + view.ty);\n            }\n          }\n        } else if(idxMax > 1){\n          \/\/ Static: extend swath past the final centroid by a full local step so coverage\n          \/\/ reaches the actual data edge (the polygon's leading face, not just its centroid).\n          var iCurSw = idxMax - 1;\n          var prevXSw = spriteCx(iCurSw - 1), prevYSw = spriteCy(iCurSw - 1);\n          var curXSw = spriteCx(iCurSw), curYSw = spriteCy(iCurSw);\n          var hxSw = curXSw - prevXSw, hySw = curYSw - prevYSw;\n          var hlSw = Math.sqrt(hxSw*hxSw + hySw*hySw);\n          if(hlSw > 0.001){\n            ctx.lineTo((curXSw + hxSw)*view.scale + view.tx, (curYSw + hySw)*view.scale + view.ty);\n          }\n        }\n        ctx.stroke();\n        ctx.restore();\n      }\n      \/\/ 1a. Headland turnaround curves \u2014 at each boundary, the combine has lifted the header and\n      \/\/     made a curved U-turn from the end of the previous pass to the start of the next.\n      \/\/     We didn't record points during the turn (header was up), but we can synthesize the\n      \/\/     visual: a cubic Bezier between the two segment ends, with control points extending\n      \/\/     along the local direction of travel. Drawn in a distinct dashed orange so users see\n      \/\/     these are SYNTHESIZED transitions, not measured passes.\n      \/\/\n      \/\/     SUPPRESSED when the AB-line traversal overlay is active: that overlay shows the\n      \/\/     proper planned path with clean U-turns at AB-line junctions. The legacy per-\n      \/\/     boundary previews fire too aggressively on multi-section coverage data and add\n      \/\/     visual clutter that duplicates the AB-traversal overlay's information.\n      var _abActive = playback.abLines ? playback.abLines.perCluster ? playback.abLines.perCluster.length > 0 : false : false;\n      if(bnd ? !_abActive : false){\n        ctx.save();\n        ctx.strokeStyle = 'rgba(247,106,12,0.55)';\n        ctx.lineWidth = 1.6;\n        ctx.lineCap = 'round';\n        ctx.setLineDash([5, 4]);\n        ctx.beginPath();\n        \/\/ Skip dashed Bezier previews on small-gap boundaries (false positives \u2014 gap < 0.8\u00d7 wM\n        \/\/ means the \"boundary\" is within-moment section spread, not a real turnaround).\n        \/\/ Aggressive threshold (was 0.5\u00d7 wM) \u2014 real headland gaps are typically \u2265 wM, so 0.8\u00d7\n        \/\/ catches false positives reliably while not suppressing genuine turns. Also skips\n        \/\/ boundaries that fall on a SKIPPED pass when the equipment-width filter is active.\n        var wMfor = playback.implementWidth ? playback.implementWidth : equipmentWidthM(playback.opLabel);\n        var falseGapM = wMfor * 0.8;\n        var cosLatBz = Math.cos(latC * DEG);\n        var keptMaskBz = playback.passKeptMask;\n        for(var bi=1; bi<idxMax; bi++){\n          if(!bnd[bi]) continue;\n          if(keptMaskBz ? keptMaskBz[bi] !== 1 : false) continue;\n          \/\/ Pre-check gap in real metres against the false-positive threshold.\n          var preGapDx = pathCx(bi) - pathCx(bi-1);\n          var preGapDy = pathCy(bi) - pathCy(bi-1);\n          var preGapM = Math.sqrt(preGapDx*preGapDx + preGapDy*preGapDy) * cosLatBz;\n          if(preGapM < falseGapM) continue;\n          \/\/ End of previous pass = bi-1, start of new pass = bi\n          var endX = pathCx(bi-1)*view.scale + view.tx;\n          var endY = pathCy(bi-1)*view.scale + view.ty;\n          var nxtX = pathCx(bi)*view.scale + view.tx;\n          var nxtY = pathCy(bi)*view.scale + view.ty;\n          \/\/ Direction at end of prev pass \u2014 fall back to gap direction if too few prior points\n          var dx1 = 0, dy1 = 0;\n          if(bi >= 2 ? !bnd[bi-1] : false){\n            dx1 = endX - (pathCx(bi-2)*view.scale + view.tx);\n            dy1 = endY - (pathCy(bi-2)*view.scale + view.ty);\n          }\n          var l1 = Math.sqrt(dx1*dx1 + dy1*dy1);\n          if(l1 < 0.1){ dx1 = nxtX - endX; dy1 = nxtY - endY; l1 = Math.sqrt(dx1*dx1 + dy1*dy1); }\n          if(l1 < 0.1) continue;\n          dx1 \/= l1; dy1 \/= l1;\n          \/\/ Direction at start of new pass\n          var dx2 = 0, dy2 = 0;\n          if(bi + 1 < n ? !bnd[bi+1] : false){\n            dx2 = (pathCx(bi+1)*view.scale + view.tx) - nxtX;\n            dy2 = (pathCy(bi+1)*view.scale + view.ty) - nxtY;\n          }\n          var l2 = Math.sqrt(dx2*dx2 + dy2*dy2);\n          if(l2 < 0.1){ dx2 = nxtX - endX; dy2 = nxtY - endY; l2 = Math.sqrt(dx2*dx2 + dy2*dy2); }\n          if(l2 < 0.1) continue;\n          dx2 \/= l2; dy2 \/= l2;\n          \/\/ Control distance \u2014 anchored to equipment width (real turning radius), bumped to at\n          \/\/ least the gap distance so the arc always extends past both endpoints. Working width\n          \/\/ is in mercator-m, so convert via scale.\n          var gapDx = nxtX - endX, gapDy = nxtY - endY;\n          var gap = Math.sqrt(gapDx*gapDx + gapDy*gapDy);\n          var wMpx = equipmentWidthM(playback.opLabel) * view.scale \/ Math.cos(latC*DEG);\n          var ctrl = wMpx * 2.5;\n          if(ctrl < gap * 1.0) ctrl = gap * 1.0;\n          if(ctrl > Math.max(wMpx * 5, gap * 2)) ctrl = Math.max(wMpx * 5, gap * 2);\n          if(ctrl < 20) ctrl = 20;\n          var c1x = endX + dx1 * ctrl;\n          var c1y = endY + dy1 * ctrl;\n          var c2x = nxtX - dx2 * ctrl;\n          var c2y = nxtY - dy2 * ctrl;\n          ctx.moveTo(endX, endY);\n          ctx.bezierCurveTo(c1x, c1y, c2x, c2y, nxtX, nxtY);\n        }\n        \/\/ In-progress turnaround \u2014 partial Bezier up to current turnFrac so the dashed curve\n        \/\/ grows along with the sprite. Subdivided into 18 segments for smooth visual.\n        if(playback.turnAct ? playback.turnBezier : false){\n          var bzp = playback.turnBezier;\n          var tMax = easeT(playback.turnFrac > 1 ? 1 : (playback.turnFrac < 0 ? 0 : playback.turnFrac));\n          ctx.moveTo(bzp.p0x*view.scale + view.tx, bzp.p0y*view.scale + view.ty);\n          var SUBP = 18;\n          for(var sp=1; sp<=SUBP; sp++){\n            var tp = (sp\/SUBP) * tMax;\n            var bxp = bezierAt(bzp, tp, 'x');\n            var byp = bezierAt(bzp, tp, 'y');\n            ctx.lineTo(bxp*view.scale + view.tx, byp*view.scale + view.ty);\n          }\n        }\n        ctx.stroke();\n        ctx.setLineDash([]);\n        ctx.restore();\n      }\n      \/\/ 1b. Trail polyline \u2014 solid green through the SMOOTHED in-pass path. Breaks at boundaries\n      \/\/     so the line never visually connects across two passes (the dashed Bezier above handles\n      \/\/     the connection). The final segment is extended to the live interpolated sprite\n      \/\/     position so the trail always meets the equipment exactly \u2014 no visible lag.\n      ctx.save();\n      \/\/ Trail rendered in TWO layers for clarity: a wider white halo behind, then the\n      \/\/ saturated green line on top. Reads clearly over yield\/colour-coded polygons.\n      ctx.strokeStyle = 'rgba(255,255,255,0.85)';\n      ctx.lineWidth = 4.6;\n      ctx.lineJoin = 'round';\n      ctx.lineCap = 'round';\n      ctx.beginPath();\n      var pendingMove = true;\n      var keptMaskTrail = playback.passKeptMask;\n      \/\/ LineString mode: trace ALL vertices of each visited feature, plus the partial vertices\n      \/\/ of the in-progress feature up to playback.idxFloat. Gives the sprite a trail along\n      \/\/ every actual coordinate in the source lines (matching the user-defined geometry).\n      if(mode === 'line' ? polyData : false){\n        for(var fpi=0; fpi<idxMax; fpi++){\n          var ofIdx = playback.order ? playback.order[fpi] : fpi;\n          var lf = polyData[ofIdx];\n          if(!lf ? true : !lf.rings) continue;\n          if(bnd ? bnd[fpi] : false) pendingMove = true;\n          for(var lr=0; lr<lf.rings.length; lr++){\n            var lring = lf.rings[lr];\n            for(var lv=0; lv<lring.mx.length; lv++){\n              var lpx = lring.mx[lv] * view.scale + view.tx;\n              var lpy = lring.my[lv] * view.scale + view.ty;\n              if(pendingMove){ ctx.moveTo(lpx, lpy); pendingMove = false; } else { ctx.lineTo(lpx, lpy); }\n            }\n          }\n        }\n      } else {\n        for(var pi=0; pi<idxMax; pi++){\n          \/\/ Equipment-width-driven filter: when the implement is wider than the data spacing,\n          \/\/ skip every Nth pass so the trail shows fewer \/ wider-spaced lines.\n          if(keptMaskTrail ? !keptMaskTrail[pi] : false){ pendingMove = true; continue; }\n          var pxs = pathCx(pi)*view.scale + view.tx;\n          var pys = pathCy(pi)*view.scale + view.ty;\n          if(bnd ? bnd[pi] : false) pendingMove = true;\n          if(pendingMove){ ctx.moveTo(pxs, pys); pendingMove = false; } else { ctx.lineTo(pxs, pys); }\n        }\n      }\n      \/\/ Extend to the live sprite position so trail meets the implement exactly. Skip if we're\n      \/\/ sitting on a boundary (would draw a phantom line across the turnaround gap). When NOT\n      \/\/ playing (paused\/scrubbed), extend slightly past the last centroid by half the local step\n      \/\/ along the heading so the line reaches the real polygon edge instead of stopping at the\n      \/\/ centroid (which is the cab-position GPS reading, not the cut edge).\n      if(idxMax > 0){\n        var iCur = idxMax - 1;\n        var iNxt2 = iCur + 1 < n ? iCur + 1 : iCur;\n        var crossesBnd = bnd ? bnd[iNxt2] : false;\n        if(playback.active ? !crossesBnd : false){\n          \/\/ In line mode, extend trail to the precise vertex-interpolated sprite position.\n          var liveHit = lineVertexAt(playback.idxFloat - 0.0001);\n          var liveXm, liveYm;\n          if(liveHit){\n            liveXm = liveHit.x; liveYm = liveHit.y;\n          } else {\n            var frac2 = playback.idxFloat - Math.floor(playback.idxFloat);\n            var hxL = spriteCx(iCur), hyL = spriteCy(iCur);\n            var nxL = spriteCx(iNxt2), nyL = spriteCy(iNxt2);\n            liveXm = hxL + (nxL - hxL) * frac2;\n            liveYm = hyL + (nyL - hyL) * frac2;\n          }\n          ctx.lineTo(liveXm*view.scale + view.tx, liveYm*view.scale + view.ty);\n        } else if(!playback.active ? iCur > 0 : false){\n          \/\/ Static extension: a full local step along the heading. Centroids are at the GPS\n          \/\/ receiver position; the cut zone extends roughly one cell ahead of the cab, so\n          \/\/ extending by the local step reaches the actual field boundary on the dataset edge.\n          var prevX = spriteCx(iCur - 1), prevY = spriteCy(iCur - 1);\n          var curX = spriteCx(iCur), curY = spriteCy(iCur);\n          var hx = curX - prevX, hy = curY - prevY;\n          var hl = Math.sqrt(hx*hx + hy*hy);\n          if(hl > 0.001){\n            var exX = curX + hx;\n            var exY = curY + hy;\n            ctx.lineTo(exX*view.scale + view.tx, exY*view.scale + view.ty);\n          }\n        }\n      }\n      ctx.stroke();\n      \/\/ Second pass: saturated green line on top of the white halo for high contrast.\n      ctx.strokeStyle = 'rgba(20,83,40,0.95)';\n      ctx.lineWidth = 2.4;\n      ctx.stroke();\n      ctx.restore();\n      \/\/ 2. Direction arrows along smoothed trail \u2014 small orange chevrons every ~110 canvas pixels\n      ctx.save();\n      ctx.fillStyle = 'rgba(247,106,12,0.95)';\n      ctx.strokeStyle = 'rgba(255,255,255,0.9)';\n      ctx.lineWidth = 1;\n      var SPACING = 110;\n      var accum = SPACING * 0.5;\n      var prevAx = 0, prevAy = 0, havePrev = false;\n      for(var ai=0; ai<idxMax; ai++){\n        var ax = pathCx(ai)*view.scale + view.tx;\n        var ay = pathCy(ai)*view.scale + view.ty;\n        if(havePrev){\n          var dxa = ax - prevAx, dya = ay - prevAy;\n          var seg = Math.sqrt(dxa*dxa + dya*dya);\n          accum += seg;\n          if(seg < 60 ? accum >= SPACING : false){\n            accum = 0;\n            var ah = Math.atan2(dya, dxa);\n            ctx.save();\n            ctx.translate(ax, ay);\n            ctx.rotate(ah);\n            ctx.beginPath();\n            ctx.moveTo(7, 0); ctx.lineTo(-5, -5); ctx.lineTo(-2, 0); ctx.lineTo(-5, 5); ctx.closePath();\n            ctx.fill();\n            ctx.stroke();\n            ctx.restore();\n          }\n        }\n        prevAx = ax; prevAy = ay; havePrev = true;\n      }\n      ctx.restore();\n      \/\/ 3. Tractor sprite. Two cases:\n      \/\/    a. Normal play \u2014 position lerps between current\/next SMOOTHED path point using the\n      \/\/       fractional idxFloat. Heading via distance-based lookback + low-pass.\n      \/\/    b. Turnaround \u2014 position follows the cached Bezier curve at turnFrac. Heading from\n      \/\/       the Bezier tangent so the equipment rotates smoothly through the U-turn.\n      if(!playback.active) return;\n      if(playback.turnAct ? playback.turnBezier : false){\n        var bzs = playback.turnBezier;\n        var ts = easeT(playback.turnFrac > 1 ? 1 : (playback.turnFrac < 0 ? 0 : playback.turnFrac));\n        var bsx = bezierAt(bzs, ts, 'x'), bsy = bezierAt(bzs, ts, 'y');\n        \/\/ Tangent \u2014 derivative of cubic Bezier at eased t\n        var us = 1 - ts;\n        var tanX = 3*us*us*(bzs.p1x-bzs.p0x) + 6*us*ts*(bzs.p2x-bzs.p1x) + 3*ts*ts*(bzs.p3x-bzs.p2x);\n        var tanY = 3*us*us*(bzs.p1y-bzs.p0y) + 6*us*ts*(bzs.p2y-bzs.p1y) + 3*ts*ts*(bzs.p3y-bzs.p2y);\n        var cxT = bsx*view.scale + view.tx;\n        var cyT = bsy*view.scale + view.ty;\n        if(playback.smoothedX === null){ playback.smoothedX = cxT; playback.smoothedY = cyT; }\n        playback.smoothedX = playback.smoothedX + (cxT - playback.smoothedX) * 0.35;\n        playback.smoothedY = playback.smoothedY + (cyT - playback.smoothedY) * 0.35;\n        var headingT = Math.atan2(tanY, tanX);\n        if(playback.smoothedHeading === null) playback.smoothedHeading = headingT;\n        var dHeadT = headingT - playback.smoothedHeading;\n        while(dHeadT > Math.PI) dHeadT -= Math.PI*2;\n        while(dHeadT < -Math.PI) dHeadT += Math.PI*2;\n        \/\/ Match the in-pass max-turn-rate (1 rad\/s \u00d7 speed) so turns look consistent.\n        var dtSecT = (playback.frameDtMs ? playback.frameDtMs : 16) \/ 1000;\n        var maxStepT = 1.0 * playback.speed * dtSecT;\n        if(Math.abs(dHeadT) > maxStepT) dHeadT = (dHeadT > 0 ? 1 : -1) * maxStepT;\n        playback.smoothedHeading = playback.smoothedHeading + dHeadT;\n        drawTractorSprite(playback.smoothedX, playback.smoothedY, playback.smoothedHeading);\n        return;\n      }\n      var i1 = idxMax - 1;\n      if(i1 < 0) return;\n      var iNext = i1 + 1 < n ? i1 + 1 : i1;\n      var frac = playback.idxFloat - Math.floor(playback.idxFloat);\n      if(iNext === i1) frac = 0;\n      var headXm, headYm;\n      \/\/ LineString mode: sprite traces ALONG each feature's line vertices, not lerping\n      \/\/ between feature centroids. Lets the boustrophedon U-turn arc (a single feature with\n      \/\/ ~25 vertices) be traversed point-by-point so the sprite actually drives the arc.\n      var lineHit = lineVertexAt(playback.idxFloat - 0.0001);\n      if(lineHit){\n        headXm = lineHit.x;\n        headYm = lineHit.y;\n      } else {\n        var hxm = spriteCx(i1), hym = spriteCy(i1);\n        var nxm = spriteCx(iNext), nym = spriteCy(iNext);\n        \/\/ Skip interp on large segment jumps (turnarounds) \u2014 would smear sprite across the field\n        var segMx = (nxm - hxm), segMy = (nym - hym);\n        var segLenScreen = Math.sqrt(segMx*segMx + segMy*segMy) * view.scale;\n        if(segLenScreen > 80) frac = 0;\n        headXm = hxm + (nxm - hxm) * frac;\n        headYm = hym + (nym - hym) * frac;\n      }\n      var cx1 = headXm*view.scale + view.tx;\n      var cy1 = headYm*view.scale + view.ty;\n      if(!isFinite(cx1)) return;\n      if(!isFinite(cy1)) return;\n      \/\/ Position low-pass: GPS-noisy data jitters each polygon centroid by a few meters; without\n      \/\/ this filter the sprite shakes visibly. 18% per frame \u2248 4-frame lag \u2014 sprite reads smooth.\n      \/\/ SKIPPED in line mode: line vertices are deterministic (no GPS noise), and the lag pulls\n      \/\/ the sprite OFF the line during fast traversal \u2014 especially on left-to-right passes\n      \/\/ where the sprite would visibly trail behind the line.\n      if(playback.smoothedX === null){ playback.smoothedX = cx1; playback.smoothedY = cy1; }\n      \/\/ Reset filter on big jumps (scrub, dataset switch, turnaround) so the sprite doesn't drift\n      \/\/ across the field smoothing toward a far-away target.\n      var jumpDx = cx1 - playback.smoothedX, jumpDy = cy1 - playback.smoothedY;\n      if(jumpDx*jumpDx + jumpDy*jumpDy > 10000){ playback.smoothedX = cx1; playback.smoothedY = cy1; }\n      if(mode === 'line'){\n        \/\/ Snap directly to the line position \u2014 no smoothing lag.\n        playback.smoothedX = cx1;\n        playback.smoothedY = cy1;\n      } else {\n        playback.smoothedX = playback.smoothedX + (cx1 - playback.smoothedX) * 0.18;\n        playback.smoothedY = playback.smoothedY + (cy1 - playback.smoothedY) * 0.18;\n      }\n      \/\/ Heading from ~120 screen-px of lookback. Longer than before \u2014 short lookback amplified\n      \/\/ GPS noise into visible shake. Avoids single-cell jitter and row-turnaround flips.\n      \/\/ STOP the lookback at a turnaround boundary \u2014 crossing it would pull heading from\n      \/\/ the PREVIOUS pass, making the sprite appear to drive backwards for several frames\n      \/\/ immediately after the U-turn completes (real machines accelerate cleanly out of a\n      \/\/ turn, no backward motion).\n      \/\/ LineString mode: derive heading from the LINE TANGENT at idxFloat (forward-difference\n      \/\/ sampling). The centroid-based lookback gives wrong directions when the sprite is on a\n      \/\/ line \u2014 e.g., for pass-1 of the boustrophedon (left-to-right at y=0, centroid at x=150),\n      \/\/ lookback would compute heading from centroid to current position, which points LEFT\n      \/\/ when the sprite is in the first half of the pass even though the machine is driving\n      \/\/ RIGHT.\n      var targetHeading;\n      var lineHd = lineHeadingAt(playback.idxFloat - 0.0001);\n      if(lineHd !== null){\n        targetHeading = lineHd;\n      } else {\n        var DESIRED_LOOKBACK_PX = 120;\n        var lkIdx = i1;\n        var bndArrHd = playback.boundaries;\n        for(var lk=1; lk<=80; lk++){\n          var iCand = i1 - lk;\n          if(iCand < 0) break;\n          \/\/ Boundaries[k]=1 means transition (k-1, k) is a turnaround \u2014 don't reach k-1 from k or earlier.\n          if(bndArrHd ? bndArrHd[iCand + 1] : false) break;\n          var cxc = spriteCx(iCand)*view.scale + view.tx;\n          var cyc = spriteCy(iCand)*view.scale + view.ty;\n          var dlx = cx1 - cxc, dly = cy1 - cyc;\n          if(dlx*dlx + dly*dly >= DESIRED_LOOKBACK_PX*DESIRED_LOOKBACK_PX){ lkIdx = iCand; break; }\n          lkIdx = iCand;\n        }\n        var lkXm = spriteCx(lkIdx), lkYm = spriteCy(lkIdx);\n        var dxh = (headXm - lkXm) * view.scale;\n        var dyh = (headYm - lkYm) * view.scale;\n        var hasMotion = dxh*dxh + dyh*dyh > 9;\n        targetHeading = hasMotion ? Math.atan2(dyh, dxh) : (playback.smoothedHeading !== null ? playback.smoothedHeading : 0);\n      }\n      if(playback.smoothedHeading === null) playback.smoothedHeading = targetHeading;\n      var dHead = targetHeading - playback.smoothedHeading;\n      while(dHead > Math.PI) dHead -= Math.PI * 2;\n      while(dHead < -Math.PI) dHead += Math.PI * 2;\n      \/\/ PHYSICS-BASED max-turn-rate. Real ag machines pivot at ~30\u00b0\/sec in-pass and ~60\u00b0\/sec\n      \/\/ at a headland. 0.5 rad\/sec (\u2248 29\u00b0\/sec) \u00d7 playback.speed matches the in-pass rate;\n      \/\/ the Bezier turnaround handles the faster headland pivot via its tangent calculation\n      \/\/ (not capped by this rate). Lower values give smoother heading transitions through\n      \/\/ sparse zones and small wiggles without making the sprite feel sluggish at speed.\n      var dtSec = (playback.frameDtMs ? playback.frameDtMs : 16) \/ 1000;\n      var MAX_TURN_RAD_PER_SEC = 0.5 * playback.speed;\n      var maxStep = MAX_TURN_RAD_PER_SEC * dtSec;\n      var stepAbs = Math.abs(dHead);\n      if(stepAbs > maxStep) dHead = (dHead > 0 ? 1 : -1) * maxStep;\n      playback.smoothedHeading = playback.smoothedHeading + dHead;\n      drawTractorSprite(playback.smoothedX, playback.smoothedY, playback.smoothedHeading);\n    })();\n    \/\/ Ruler overlay \u2014 drawn last so it sits on top of everything else.\n    drawRuler();\n  }\n  \/\/ Render the ruler polyline + waypoint markers + running total distance label.\n  \/\/ Distances are in Web Mercator meters (mx\/my are mercator coords); multiply by cos(lat)\n  \/\/ to convert to real ground meters.\n  function drawRuler(){\n    if(!ruler.points.length) return;\n    ctx.save();\n    ctx.strokeStyle = '#f76a0c';\n    ctx.lineWidth = 2;\n    ctx.setLineDash([6, 4]);\n    ctx.beginPath();\n    var pp0 = ruler.points[0];\n    ctx.moveTo(pp0.mx * view.scale + view.tx, pp0.my * view.scale + view.ty);\n    for(var ri=1; ri<ruler.points.length; ri++){\n      var ppi = ruler.points[ri];\n      ctx.lineTo(ppi.mx * view.scale + view.tx, ppi.my * view.scale + view.ty);\n    }\n    var hoverPt = (ruler.active ? ruler.hover : null);\n    if(hoverPt){\n      ctx.lineTo(hoverPt.mx * view.scale + view.tx, hoverPt.my * view.scale + view.ty);\n    }\n    ctx.stroke();\n    ctx.setLineDash([]);\n    \/\/ Waypoint markers\n    ctx.fillStyle = '#fff';\n    ctx.strokeStyle = '#f76a0c';\n    ctx.lineWidth = 2;\n    for(var rj=0; rj<ruler.points.length; rj++){\n      var ppj = ruler.points[rj];\n      var rsx = ppj.mx * view.scale + view.tx;\n      var rsy = ppj.my * view.scale + view.ty;\n      ctx.beginPath();\n      ctx.arc(rsx, rsy, 5, 0, Math.PI * 2);\n      ctx.fill();\n      ctx.stroke();\n    }\n    \/\/ Total distance, including the live preview segment when hovering.\n    var totalMercM = 0;\n    for(var rk=1; rk<ruler.points.length; rk++){\n      var pa = ruler.points[rk-1], pb = ruler.points[rk];\n      var rdx = pb.mx - pa.mx, rdy = pb.my - pa.my;\n      totalMercM += Math.sqrt(rdx*rdx + rdy*rdy);\n    }\n    if(hoverPt){\n      var pl = ruler.points[ruler.points.length - 1];\n      var hdx = hoverPt.mx - pl.mx, hdy = hoverPt.my - pl.my;\n      totalMercM += Math.sqrt(hdx*hdx + hdy*hdy);\n    }\n    var totalM = totalMercM * Math.cos(latC * DEG);\n    \/\/ Label near the last visible point\n    var lastP = hoverPt ? hoverPt : ruler.points[ruler.points.length - 1];\n    var llx = lastP.mx * view.scale + view.tx;\n    var lly = lastP.my * view.scale + view.ty;\n    var label = formatDistance(totalM);\n    ctx.font = '600 12.5px \"Poppins\", system-ui, -apple-system, sans-serif';\n    ctx.textBaseline = 'middle';\n    var tw = ctx.measureText(label).width;\n    var padX = 8, lblH = 22;\n    var rlx = llx + 14;\n    var rly = lly - 14;\n    if(rlx + tw + padX*2 > W) rlx = llx - 14 - tw - padX*2;\n    if(rlx < 4) rlx = 4;\n    if(rly - lblH\/2 < 4) rly = lblH\/2 + 4;\n    if(rly + lblH\/2 > H - 4) rly = H - lblH\/2 - 4;\n    ctx.fillStyle = 'rgba(247,106,12,0.95)';\n    ctx.fillRect(rlx, rly - lblH\/2, tw + padX*2, lblH);\n    ctx.fillStyle = '#fff';\n    ctx.fillText(label, rlx + padX, rly);\n    ctx.restore();\n  }\n  \/\/ \u2500\u2500 IDW (Inverse Distance Weighted) interpolation for sparse point data \u2500\n  \/\/ Builds a low-res grid (default 96\u00d796) in the data's mercator bbox, computes\n  \/\/ a power-2 IDW for each cell using the k=8 nearest inliers, paints it to an\n  \/\/ offscreen canvas via colorForValue, and caches the bitmap for fast redraws.\n  \/\/ Re-runs only when the active attribute (currentCol) changes \u2014 not on every\n  \/\/ pan\/zoom. drawPoints() drawImage()s the cached bitmap with the live view\n  \/\/ transform so it scales naturally.\n  var interpCache = { col:null, stopsDigest:null, gridW:0, gridH:0, bbox:null, canvas:null, values:null };\n  function buildPointInterp(){\n    \/\/ Point mode uses raw mx\/my. Polygon mode (as-applied \/ zones) falls\n    \/\/ through to polyData[i].cx\/cy \u2014 the polygon centroids \u2014 so the IDW\n    \/\/ raster can be built off ANY dataset and the zones-export pipeline\n    \/\/ can produce clean merged polygons regardless of input geometry.\n    \/\/ Line mode is excluded \u2014 line centroids don't form a useful raster.\n    if(mode === 'line') { interpCache.col = null; interpCache.canvas = null; return; }\n    var n = values.length;\n    if(n < 8) { interpCache.col = null; interpCache.canvas = null; return; }\n    \/\/ Use only inliers as IDW knots \u2014 outliers would warp the gradient.\n    var kx = [], ky = [], kv = [];\n    var hasCoords = mode === 'point' ? (mx ? my : false) : (mode === 'polygon' ? polyData : false);\n    if(!hasCoords){ interpCache.col = null; interpCache.canvas = null; return; }\n    for(var i=0;i<n;i++){\n      if(outClass[i] !== 0) continue;\n      var kxv, kyv;\n      if(mode === 'point'){ kxv = mx[i]; kyv = my[i]; }\n      else { var pd = polyData[i]; if(!pd) continue; kxv = pd.cx; kyv = pd.cy; }\n      if(!isFinite(kxv) ? true : !isFinite(kyv)) continue;\n      kx.push(kxv); ky.push(kyv); kv.push(values[i]);\n    }\n    if(kx.length < 4) { interpCache.col = null; interpCache.canvas = null; return; }\n    \/\/ Data bbox in relative mercator coords, padded by 5% so the interpolated\n    \/\/ surface extends slightly past the outermost points.\n    var minX = Infinity, maxX = -Infinity, minY = Infinity, maxY = -Infinity;\n    for(var p=0;p<kx.length;p++){\n      if(kx[p] < minX) minX = kx[p]; if(kx[p] > maxX) maxX = kx[p];\n      if(ky[p] < minY) minY = ky[p]; if(ky[p] > maxY) maxY = ky[p];\n    }\n    var padX = (maxX - minX) * 0.05, padY = (maxY - minY) * 0.05;\n    minX -= padX; maxX += padX; minY -= padY; maxY += padY;\n    \/\/ Extend the raster to cover the FIELD HULL, not just the knot points. The\n    \/\/ raster is hull-clipped at draw time (drawPointInterp); if it stops at the\n    \/\/ data bbox, the hull region beyond the outermost points renders empty (a\n    \/\/ visible rectangular cut-off + uncovered field). IDW extrapolates into the\n    \/\/ corners via nearest-knot weighting, so the whole field fills cleanly.\n    var _ih = playback.fieldHulls;\n    if(_ih ? _ih.length : false){\n      for(var _hi=0; _hi<_ih.length; _hi++){\n        var _hx = _ih[_hi].x, _hy = _ih[_hi].y;\n        for(var _hj=0; _hj<_hx.length; _hj++){\n          if(_hx[_hj] < minX) minX = _hx[_hj]; if(_hx[_hj] > maxX) maxX = _hx[_hj];\n          if(_hy[_hj] < minY) minY = _hy[_hj]; if(_hy[_hj] > maxY) maxY = _hy[_hj];\n        }\n      }\n    }\n    var gW = 96, gH = 96;\n    var off = document.createElement('canvas');\n    off.width = gW; off.height = gH;\n    var octx = off.getContext('2d', { willReadFrequently:false });\n    var img = octx.createImageData(gW, gH);\n    var data = img.data;\n    var dx = (maxX - minX) \/ gW, dy = (maxY - minY) \/ gH;\n    var K_NEAREST = Math.min(8, kx.length);\n    var gridVals = new Float32Array(gW * gH);\n    \/\/ Spatial-bucket index over the knots \u2014 replaces the previous per-cell\n    \/\/ O(N) linear scan with O(1) average lookup. For the 17k-point soil\n    \/\/ scanner this turns a ~20 s \"hangs the browser\" freeze on first IDW\n    \/\/ build (and on the Export-zones-to-SHP click) into ~50 ms. Bucket\n    \/\/ grid is sized to ~sqrt(N) per side so each bucket holds ~1 point\n    \/\/ on average; a 3\u00d73 bucket neighborhood typically contains the K=8\n    \/\/ nearest. We collect one extra ring beyond \"enough\" candidates so\n    \/\/ genuine nearest points sitting just inside the next ring still win.\n    var bN = Math.max(8, Math.min(128, Math.ceil(Math.sqrt(kx.length))));\n    var bX = bN, bY = bN;\n    var bDx = (maxX - minX) \/ bX || 1, bDy = (maxY - minY) \/ bY || 1;\n    var buckets = new Array(bX * bY);\n    for(var bi0=0; bi0<bX*bY; bi0++) buckets[bi0] = [];\n    for(var pi=0; pi<kx.length; pi++){\n      var bxi = Math.floor((kx[pi] - minX) \/ bDx);\n      var byi = Math.floor((ky[pi] - minY) \/ bDy);\n      if(bxi < 0) bxi = 0; if(bxi >= bX) bxi = bX-1;\n      if(byi < 0) byi = 0; if(byi >= bY) byi = bY-1;\n      buckets[byi*bX + bxi].push(pi);\n    }\n    var bestIdx = new Int32Array(K_NEAREST);\n    var bestD2 = new Float64Array(K_NEAREST);\n    var candIdx = new Int32Array(Math.max(256, kx.length));\n    \/\/ Per-cell IDW with k-nearest pruning, accelerated via spatial buckets.\n    for(var gy=0; gy<gH; gy++){\n      var cy = minY + (gy + 0.5) * dy;\n      for(var gx=0; gx<gW; gx++){\n        var cx = minX + (gx + 0.5) * dx;\n        var cBxi = Math.floor((cx - minX) \/ bDx);\n        var cByi = Math.floor((cy - minY) \/ bDy);\n        if(cBxi < 0) cBxi = 0; if(cBxi >= bX) cBxi = bX-1;\n        if(cByi < 0) cByi = 0; if(cByi >= bY) cByi = bY-1;\n        \/\/ Expand bucket rings until we have \u2265 K candidates, then one extra\n        \/\/ ring for safety. Worst case the loop covers the whole grid.\n        var candN = 0;\n        var ring = 0;\n        var enough = false;\n        var ringCap = bX > bY ? bX : bY;\n        while(true){\n          var ryLo = cByi - ring, ryHi = cByi + ring;\n          var rxLo = cBxi - ring, rxHi = cBxi + ring;\n          for(var ry=ryLo; ry<=ryHi; ry++){\n            if(ry < 0 ? true : ry >= bY) continue;\n            for(var rx=rxLo; rx<=rxHi; rx++){\n              if(rx < 0 ? true : rx >= bX) continue;\n              if(ring > 0 ? (rx > rxLo ? rx < rxHi : false) ? (ry > ryLo ? ry < ryHi : false) : false : false) continue;\n              var bArr = buckets[ry*bX + rx];\n              var bLen = bArr.length;\n              for(var bii=0; bii<bLen; bii++){\n                if(candN < candIdx.length) candIdx[candN++] = bArr[bii];\n              }\n            }\n          }\n          if(enough) break;\n          if(candN >= K_NEAREST) enough = true;\n          ring++;\n          if(ring > ringCap) break;\n        }\n        \/\/ Pick K nearest from candidates (in-place top-K via insertion).\n        var bestCount = 0;\n        for(var ci=0; ci<candN; ci++){\n          var pIdx = candIdx[ci];\n          var ddx = kx[pIdx] - cx, ddy = ky[pIdx] - cy;\n          var d2 = ddx*ddx + ddy*ddy;\n          if(bestCount < K_NEAREST){\n            \/\/ Insert in sorted order.\n            var ins = bestCount;\n            while(ins > 0 ? bestD2[ins-1] > d2 : false){\n              bestD2[ins] = bestD2[ins-1];\n              bestIdx[ins] = bestIdx[ins-1];\n              ins--;\n            }\n            bestD2[ins] = d2;\n            bestIdx[ins] = pIdx;\n            bestCount++;\n          } else if(d2 < bestD2[K_NEAREST-1]){\n            var ins2 = K_NEAREST - 1;\n            while(ins2 > 0 ? bestD2[ins2-1] > d2 : false){\n              bestD2[ins2] = bestD2[ins2-1];\n              bestIdx[ins2] = bestIdx[ins2-1];\n              ins2--;\n            }\n            bestD2[ins2] = d2;\n            bestIdx[ins2] = pIdx;\n          }\n        }\n        var sumW = 0, sumWV = 0;\n        for(var b2=0;b2<bestCount;b2++){\n          var w = 1 \/ (bestD2[b2] + 1e-18);\n          sumW += w;\n          sumWV += w * kv[bestIdx[b2]];\n        }\n        var v_idw = sumWV \/ sumW;\n        gridVals[gy * gW + gx] = v_idw;\n        var c = colorForValue(v_idw);\n        var pix = (gy * gW + gx) * 4;\n        data[pix] = c[0];\n        data[pix+1] = c[1];\n        data[pix+2] = c[2];\n        data[pix+3] = 255;\n      }\n    }\n    octx.putImageData(img, 0, 0);\n    interpCache.col = currentCol;\n    interpCache.stopsDigest = (effStops ? effStops.join(',') : '') + '|' + sigmaK;\n    interpCache.gridW = gW;\n    interpCache.gridH = gH;\n    interpCache.bbox = [minX, minY, maxX, maxY];\n    interpCache.canvas = off;\n    interpCache.values = gridVals;\n  }\n  \/\/ Recolor the cached IDW offscreen canvas from interpCache.values WITHOUT\n  \/\/ re-running the IDW interpolation. The expensive part of buildPointInterp\n  \/\/ is the per-cell k-nearest search (158M ops on 17k pts). The colour pass\n  \/\/ is just 9,216 cell lookups + putImageData \u2192 ~5 ms. So when zone breaks\n  \/\/ shift (slider drag) or zones toggle on\/off, we can repaint the raster\n  \/\/ to follow the new classification with zero IDW work.\n  \/\/\n  \/\/ When zonesK > 0 and zoneBreaks is set: cells coloured by their zone\n  \/\/   class via STOP_COLORS[palIdx[zoneIdx]] \u2014 the background raster IS the\n  \/\/   zone map, edge-aligned with the slider thumbs above it.\n  \/\/ Otherwise: cells coloured by colorForValue() \u2014 the smooth gradient used\n  \/\/   for the non-zoned legend bar.\n  function recolorInterpRaster(){\n    if(!interpCache.values ? true : !interpCache.canvas) return;\n    var gW = interpCache.gridW, gH = interpCache.gridH;\n    if(!gW ? true : !gH) return;\n    var octx = interpCache.canvas.getContext('2d');\n    if(!octx) return;\n    var img = octx.createImageData(gW, gH);\n    var data = img.data;\n    var gridVals = interpCache.values;\n    var useZones = zonesK > 0 ? zoneBreaks : null;\n    var palIdx = useZones ? zonePaletteIdx(zonesK) : null;\n    var nCells = gW * gH;\n    for(var i=0; i<nCells; i++){\n      var v = gridVals[i];\n      var c;\n      if(useZones){\n        var zi = 0;\n        for(var b=0; b<zoneBreaks.length; b++){\n          if(v >= zoneBreaks[b]) zi = b + 1;\n          else break;\n        }\n        if(zi >= zonesK) zi = zonesK - 1;\n        c = STOP_COLORS[palIdx[zi]];\n      } else {\n        c = colorForValue(v);\n      }\n      var pix = i * 4;\n      data[pix] = c[0];\n      data[pix+1] = c[1];\n      data[pix+2] = c[2];\n      data[pix+3] = 255;\n    }\n    octx.putImageData(img, 0, 0);\n  }\n  \/\/ Sample the cached IDW grid at world (mercator) coords (mxw, myw). Returns\n  \/\/ the interpolated value, or null if the point is outside the grid bbox.\n  function sampleInterpAt(mxw, myw){\n    if(!interpCache.values ? true : !interpCache.bbox) return null;\n    var b = interpCache.bbox;\n    if(mxw < b[0] ? true : mxw > b[2] ? true : myw < b[1] ? true : myw > b[3]) return null;\n    var gW = interpCache.gridW, gH = interpCache.gridH;\n    var gx = Math.floor((mxw - b[0]) \/ (b[2] - b[0]) * gW);\n    var gy = Math.floor((myw - b[1]) \/ (b[3] - b[1]) * gH);\n    if(gx < 0) gx = 0; if(gx >= gW) gx = gW - 1;\n    if(gy < 0) gy = 0; if(gy >= gH) gy = gH - 1;\n    return interpCache.values[gy * gW + gx];\n  }\n  \/\/ Render the cached IDW bitmap onto the main canvas, optionally clipped to\n  \/\/ the field hull so the interpolation doesn't bleed past field edges.\n  function drawPointInterp(){\n    if(mode !== 'point') return;\n    var wantDigest = (effStops ? effStops.join(',') : '') + '|' + sigmaK;\n    if(!interpCache.canvas ? true : interpCache.col !== currentCol ? true : interpCache.stopsDigest !== wantDigest){\n      buildPointInterp();\n    }\n    if(!interpCache.canvas) return;\n    var bx = interpCache.bbox;\n    var sx0 = bx[0] * view.scale + view.tx;\n    var sy0 = bx[1] * view.scale + view.ty;\n    var sw = (bx[2] - bx[0]) * view.scale;\n    var sh = (bx[3] - bx[1]) * view.scale;\n    if(sw <= 0 ? true : sh <= 0) return;\n    ctx.save();\n    \/\/ Clip to the field hull (if available) so the IDW stays inside the data\n    \/\/ rather than spreading into white canvas. Falls back to drawing the full\n    \/\/ bbox when no hull was computed.\n    var hulls = playback.fieldHulls;\n    if(hulls ? hulls.length : false){\n      ctx.beginPath();\n      for(var hi=0; hi<hulls.length; hi++){\n        var hH = hulls[hi];\n        var hN = hH.x.length;\n        for(var hj=0; hj<hN; hj++){\n          var hx = hH.x[hj] * view.scale + view.tx;\n          var hy = hH.y[hj] * view.scale + view.ty;\n          if(hj === 0) ctx.moveTo(hx, hy); else ctx.lineTo(hx, hy);\n        }\n        ctx.closePath();\n      }\n      ctx.clip();\n    }\n    ctx.globalAlpha = 0.55;\n    ctx.imageSmoothingEnabled = true;\n    ctx.imageSmoothingQuality = 'high';\n    ctx.drawImage(interpCache.canvas, sx0, sy0, sw, sh);\n    ctx.restore();\n  }\n  function drawPoints(){\n    \/\/ Interpolated background first so points sit on top.\n    drawPointInterp();\n    var n = values.length;\n    for(var i=0;i<n;i++){ sxArr[i] = mx[i]*view.scale + view.tx; syArr[i] = my[i]*view.scale + view.ty; }\n    \/\/ Density-aware radius. The original formula (max 12 px) produced overlapping\n    \/\/ mush on dense scans (Veris \/ SoilOptix \/ 17k-point soil scanner) where the\n    \/\/ real spacing between readings is ~5 m. Tier the cap and minimum by feature\n    \/\/ count so sparse lab samples still get readable dots while dense scans render\n    \/\/ as distinct points the user can count.\n    var rMul, rMin, rMax;\n    if(n > 10000){ rMul = 1.4; rMin = 0.9; rMax = 3.5; }\n    else if(n > 3000){ rMul = 2.4; rMin = 1.4; rMax = 6.5; }\n    else if(n > 800){ rMul = 3.5; rMin = 2.0; rMax = 9; }\n    else { rMul = 5; rMin = 2.5; rMax = 12; }\n    var r = Math.max(rMin, Math.min(rMax, view.scale*rMul));\n    \/\/ Playback: draw only the first drawN features in path order. When playback isn't\n    \/\/ active and idx == n, this is the full dataset (no behavior change).\n    var drawN = playback.idx + 1 < n ? playback.idx + 1 : n;\n    var ord = playback.order;\n    function fi(i){ return ord ? ord[i] : i; }\n    for(var i=0;i<drawN;i++){\n      var idx = fi(i);\n      if(outClass[idx]!==0) continue;\n      var x = sxArr[idx], y = syArr[idx];\n      if(x<-r||x>W+r||y<-r||y>H+r) continue;\n      var c = colorFor(idx);\n      ctx.fillStyle = 'rgb('+c[0]+','+c[1]+','+c[2]+')';\n      ctx.beginPath(); ctx.arc(x,y,r,0,6.283); ctx.fill();\n    }\n    if(showOutliers){\n      ctx.fillStyle = themeColors.grey;\n      for(var i=0;i<drawN;i++){\n        var idx2 = fi(i);\n        if(outClass[idx2]!==1) continue;\n        var x = sxArr[idx2], y = syArr[idx2];\n        if(x<-r||x>W+r||y<-r||y>H+r) continue;\n        ctx.beginPath(); ctx.arc(x,y,r*1.05,0,6.283); ctx.fill();\n      }\n      ctx.shadowColor = themeColors.violetGlow;\n      ctx.shadowBlur = Math.max(4, r*1.8);\n      ctx.fillStyle = themeColors.violet;\n      for(var i=0;i<drawN;i++){\n        var idx3 = fi(i);\n        if(outClass[idx3]!==2) continue;\n        var x = sxArr[idx3], y = syArr[idx3];\n        if(x<-r||x>W+r||y<-r||y>H+r) continue;\n        ctx.beginPath(); ctx.arc(x,y,r*1.15,0,6.283); ctx.fill();\n      }\n      ctx.shadowBlur = 0;\n    }\n  }\n  function tracePoly(p){\n    ctx.beginPath();\n    var isLine = p.isLine ? true : false;\n    for(var k=0;k<p.rings.length;k++){\n      var rmx = p.rings[k].mx, rmy = p.rings[k].my;\n      for(var j=0;j<rmx.length;j++){\n        var sx = rmx[j]*view.scale + view.tx;\n        var sy = rmy[j]*view.scale + view.ty;\n        if(j===0) ctx.moveTo(sx, sy); else ctx.lineTo(sx, sy);\n      }\n      if(!isLine) ctx.closePath();\n    }\n  }\n  function drawPolygons(){\n    var n = values.length;\n    var ord = playback.order;\n    \/\/ Playback: render polygons up to playback.idx + 1 so the sprite sits over the most-\n    \/\/ recently-revealed polygon (no visible lag between sprite and geometries).\n    var drawN = playback.idx + 1 < n ? playback.idx + 1 : n;\n    function fi(i){ return ord ? ord[i] : i; }\n    \/\/ BOUNDARY datasets render as outlines only (no fill, no outlier coloring)\n    if(currentIsBoundary){\n      ctx.strokeStyle = '#15701e';\n      ctx.lineWidth = 2;\n      ctx.lineJoin = 'round';\n      for(var bi=0;bi<drawN;bi++){\n        var pb = polyData[fi(bi)];\n        var bsxa = pb.minX*view.scale + view.tx, bsxb = pb.maxX*view.scale + view.tx;\n        var bsya = pb.minY*view.scale + view.ty, bsyb = pb.maxY*view.scale + view.ty;\n        if(bsxb<0||bsxa>W||bsyb<0||bsya>H) continue;\n        tracePoly(pb); ctx.stroke();\n      }\n      ctx.lineWidth = 1;\n      return;\n    }\n    \/\/ LINE datasets (Trimble Swath \/ AB Line \/ guidance lines) \u2014 stroke each polyline.\n    \/\/ Synthetic _index col \u2192 all inliers, render as gradient along path. Real numeric col \u2192 color\n    \/\/ by value (e.g., rate per swath segment) using the same picker as polygons.\n    if(mode === 'line'){\n      ctx.lineWidth = 2;\n      ctx.lineJoin = 'round';\n      ctx.lineCap = 'round';\n      for(var li=0;li<drawN;li++){\n        var lidx = fi(li);\n        var pl = polyData[lidx];\n        if(!pl) continue;\n        var lsxa = pl.minX*view.scale + view.tx, lsxb = pl.maxX*view.scale + view.tx;\n        var lsya = pl.minY*view.scale + view.ty, lsyb = pl.maxY*view.scale + view.ty;\n        if(lsxb<0||lsxa>W||lsyb<0||lsya>H) continue;\n        var oc = outClass[lidx];\n        if(oc === 0){\n          var lc = colorFor(lidx);\n          ctx.strokeStyle = 'rgb('+lc[0]+','+lc[1]+','+lc[2]+')';\n        } else if(oc === 1){\n          if(!showOutliers) continue;\n          ctx.strokeStyle = themeColors.grey;\n        } else {\n          if(!showOutliers) continue;\n          ctx.strokeStyle = themeColors.violet;\n        }\n        tracePoly(pl); ctx.stroke();\n      }\n      ctx.lineWidth = 1;\n      return;\n    }\n    \/\/ pass 1: inliers\n    for(var i=0;i<drawN;i++){\n      var idx = fi(i);\n      if(outClass[idx]!==0) continue;\n      var p = polyData[idx];\n      var sxa = p.minX*view.scale + view.tx, sxb = p.maxX*view.scale + view.tx;\n      var sya = p.minY*view.scale + view.ty, syb = p.maxY*view.scale + view.ty;\n      if(sxb<0||sxa>W||syb<0||sya>H) continue;\n      var c = colorFor(idx);\n      ctx.fillStyle = 'rgb('+c[0]+','+c[1]+','+c[2]+')';\n      tracePoly(p); ctx.fill();\n    }\n    if(showOutliers){\n      ctx.fillStyle = themeColors.grey;\n      for(var i=0;i<drawN;i++){\n        var idx2 = fi(i);\n        if(outClass[idx2]!==1) continue;\n        var p2 = polyData[idx2];\n        var sxa2 = p2.minX*view.scale + view.tx, sxb2 = p2.maxX*view.scale + view.tx;\n        var sya2 = p2.minY*view.scale + view.ty, syb2 = p2.maxY*view.scale + view.ty;\n        if(sxb2<0||sxa2>W||syb2<0||sya2>H) continue;\n        tracePoly(p2); ctx.fill();\n      }\n      ctx.shadowColor = themeColors.violetGlow;\n      ctx.shadowBlur = 6;\n      ctx.fillStyle = themeColors.violet;\n      for(var i=0;i<drawN;i++){\n        var idx3 = fi(i);\n        if(outClass[idx3]!==2) continue;\n        var p3 = polyData[idx3];\n        var sxa3 = p3.minX*view.scale + view.tx, sxb3 = p3.maxX*view.scale + view.tx;\n        var sya3 = p3.minY*view.scale + view.ty, syb3 = p3.maxY*view.scale + view.ty;\n        if(sxb3<0||sxa3>W||syb3<0||sya3>H) continue;\n        tracePoly(p3); ctx.fill();\n      }\n      ctx.shadowBlur = 0;\n    }\n  }\n  \/\/ \u2500\u2500 playback \u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\n  \/\/ Op-type detection. Priority order:\n  \/\/   1. Material \/ Product (most reliable \u2014 actual product name encoded in the data)\n  \/\/   2. Layer name \/ directory keywords (fallback)\n  \/\/ Returns { label, dieselLPerHa, overlapStrategy } where overlapStrategy is \"sum\" (each pass\n  \/\/ counts cumulatively \u2014 applies to fertilizing \/ spraying) or \"first\" (only the first pass at\n  \/\/ each location counts \u2014 applies to seeding where the seeder usually disables duplicates).\n  var OP_BY_MATERIAL = [\n    \/\/ Seeds (operation = planting\/sowing \u2192 \"first\" overlap strategy)\n    { re: \/^(corn|maize|\u043a\u0443\u043a\u0443\u0440\u0443\u0434\u0437\u0430|wheat|\u043f\u0448\u0435\u043d\u0438\u0446\u044f|\u043f\u0448\u0435\u043d\u0438\u0446\u0430|barley|\u044f\u0447\u043c\u0456\u043d\u044c|\u044f\u0447\u043c\u0435\u043d\u044c|oats|\u043e\u0432\u0435\u0441|rye|\u0436\u0438\u0442\u043e|rice|\u0440\u0438\u0441|soy(bean)?|\u0441\u043e\u044f|sunflower|\u0441\u043e\u043d\u044f\u0448\u043d\u0438\u043a|\u043f\u043e\u0434\u0441\u043e\u043b\u043d|sorghum|\u0441\u043e\u0440\u0433\u043e|millet|\u043f\u0440\u043e\u0441\u043e|canola|rape(seed)?|\u0440\u0456\u043f\u0430\u043a|\u0440\u0430\u043f\u0441|pea|\u0433\u043e\u0440\u043e\u0445|cotton|\u0431\u0430\u0432\u043e\u0432\u043d\u0430|\u0445\u043b\u043e\u043f\u043e\u043a|sugar.?beet|\u0446\u0443\u043a\u0440.?\u0431\u0443\u0440|\u0431\u0443\u0440\u044f\u043a|alfalfa|\u043b\u044e\u0446\u0435\u0440\u043d\u0430|maize.?seed|seed)\/i, label:'planting', diesel:8, overlap:'first' },\n    \/\/ Fertilizers (operation = fertilizing \u2192 \"sum\" overlap strategy)\n    { re: \/^(urea|\u043a\u0430\u0440\u0431\u0430\u043c\u0456\u0434|\u043a\u0430\u0440\u0431\u0430\u043c\u0438\u0434|ammonium|\u0441\u0435\u043b\u0456\u0442\u0440\u0430|\u0441\u0435\u043b\u0438\u0442\u0440\u0430|UAN|\u041a\u0410\u0421|nitrate|NPK|DAP|MAP|KCl|K2O|\u043f\u043e\u0442\u0430c|potash|\u043a\u0430\u043b\u0456\u0439|\u043a\u0430\u043b\u0438\u0439|phos|\u0444\u043e\u0441\u0444\u043e|sulph|\u0441\u0443\u043b\u044c\u0444|gypsum|\u0433\u0456\u043f\u0441|lime|\u0432\u0430\u043f\u043d\u043e|\u0438\u0437\u0432\u0435\u0441\u0442\u044c|fertili[sz]er|\u0443\u0434\u043e\u0431\u0440\u0435\u043d)\/i, label:'fertilizing', diesel:5, overlap:'sum' },\n    \/\/ Pesticides \/ herbicides \/ fungicides (operation = spraying \u2192 \"sum\")\n    { re: \/^(glyphos|\u0440\u0430\u0443\u043d\u0434\u0430\u043f|roundup|atrazine|atraz|2.?4.?D|MCPA|paraquat|\u043f\u0435\u0441\u0442\u0438\u0446|herbic|fungic|insectic|\u0433\u0435\u0440\u0431\u0456\u0446|\u0433\u0435\u0440\u0431\u0438\u0446|\u0444\u0443\u043d\u0433\u0456\u0446|\u0444\u0443\u043d\u0433\u0438\u0446|\u0456\u043d\u0441\u0435\u043a\u0442|\u0438\u043d\u0441\u0435\u043a\u0442|spray|\u043e\u0431\u043f\u0440\u0438\u0441\u043a)\/i, label:'spraying',    diesel:4, overlap:'sum' }\n  ];\n  function detectOpFromMaterial(material){\n    if(!material) return null;\n    var s = String(material).trim();\n    if(!s || s === '---' || s === '(no material)') return null;\n    for(var i=0;i<OP_BY_MATERIAL.length;i++){\n      if(OP_BY_MATERIAL[i].re.test(s)){\n        return { label: OP_BY_MATERIAL[i].label, dieselLPerHa: OP_BY_MATERIAL[i].diesel, overlapStrategy: OP_BY_MATERIAL[i].overlap, source:'material' };\n      }\n    }\n    return null;\n  }\n  function detectOpFromDir(text){\n    if(!text) return { label:'operation', dieselLPerHa:10, overlapStrategy:'sum', source:'fallback' };\n    var d = String(text).toLowerCase();\n    if(\/\u043f\u043e\u0441\u0430\u0434\u043a\u0430|planting|seed|sow|\u0441\u0456\u0432\u0431\u0430|\u0441\u0456\u0432\u0431a\/i.test(d)) return { label:'planting',    dieselLPerHa:8,  overlapStrategy:'first', source:'dir' };\n    if(\/spray|appl|\u043e\u0431\u043f\u0440\u0438\u0441\u043a\u0443\u0432\u0430\u043d\u043d\u044f\/i.test(d))              return { label:'spraying',    dieselLPerHa:4,  overlapStrategy:'sum',   source:'dir' };\n    if(\/harvest|combine|\u0437\u0431\u0456\u0440|\u0437\u0431\u0438\u0440\u0430\u043d\u043d\u044f\/i.test(d))         return { label:'harvest',     dieselLPerHa:14, overlapStrategy:'first', source:'dir' };\n    if(\/till|culti|\u043e\u0431\u0440\u043e\u0431\u043a\u0430|\u043f\u043b\u0443\u0433\/i.test(d))               return { label:'tillage',     dieselLPerHa:18, overlapStrategy:'sum',   source:'dir' };\n    if(\/fert|\u0443\u0434\u043e\u0431\u0440|\u0432\u043d\u0435\u0441\u0435\u043d\u043d\u044f\/i.test(d))                   return { label:'fertilizing', dieselLPerHa:5,  overlapStrategy:'sum',   source:'dir' };\n    if(\/coverage\/i.test(d))                              return { label:'application', dieselLPerHa:6,  overlapStrategy:'sum',   source:'dir' };\n    return { label:'operation', dieselLPerHa:10, overlapStrategy:'sum', source:'fallback' };\n  }\n  \/\/ Combines material-first + dir-fallback detection.\n  function detectOp(ds){\n    if(ds ? ds.product : false){\n      var byMat = detectOpFromMaterial(ds.product);\n      if(byMat){ return byMat; }\n    }\n    var hint = (ds ? (ds.dir || '') : '') + ' ' + (ds ? (ds.name || '') : '');\n    return detectOpFromDir(hint);\n  }\n  \/\/ Determine the order in which polygons should appear in playback.\n  \/\/ Priority: 1) timestamp fields, 2) sequential ID, 3) nearest-neighbor walk from top-left (so the\n  \/\/ playback looks like a tractor moving \u2014 no jumps across the field).\n  \/\/ Returns feature i's center in WM meters relative to wmCx\/wmCy. Works for any geom type:\n  \/\/ points use the (mx, my) arrays; polygons \/ lines use polyData[i].cx\/cy.\n  function featCx(i){ return mode === 'point' ? mx[i] : (polyData[i] ? polyData[i].cx : 0); }\n  function featCy(i){ return mode === 'point' ? my[i] : (polyData[i] ? polyData[i].cy : 0); }\n  function featCount(){ return mode === 'point' ? (mx ? mx.length : 0) : (polyData ? polyData.length : 0); }\n  \/\/ First-pass moving-average over raw centroids (in playback order). Window \u00b1W, SYMMETRIC and\n  \/\/ clipped at turnaround boundaries. Symmetric is important near boundaries \u2014 an asymmetric\n  \/\/ window biases the smoothed value toward the past, which made the trail \"fall behind\" the\n  \/\/ sprite at pass endpoints (the visible \"path stops too early\" effect). Symmetric simply\n  \/\/ shrinks the window evenly so the smoothed point stays on the actual track.\n  function computeSmoothedPath(axis, W, boundaries){\n    var n = featCount();\n    if(!n) return null;\n    var out = new Float32Array(n);\n    var ord = playback.order;\n    var getC = axis === 'x' ? featCx : featCy;\n    for(var i=0; i<n; i++){\n      var half = symmetricHalf(i, W, n, boundaries);\n      var lo = i - half, hi = i + half;\n      var sum = 0, cnt = 0;\n      for(var j=lo; j<=hi; j++){\n        var fj = ord ? ord[j] : j;\n        sum += getC(fj);\n        cnt++;\n      }\n      out[i] = cnt > 0 ? sum \/ cnt : 0;\n    }\n    return out;\n  }\n  \/\/ Returns the largest k \u2264 W such that [i-k..i+k] is entirely inside the current segment.\n  \/\/ Boundaries[b] = 1 means index b is the FIRST point of a new segment (transition b-1 \u2192 b\n  \/\/ is a turnaround). So [i-k..i+k] is fully inside one segment iff none of boundaries[i-k+1..i+k]\n  \/\/ are set, and i-k \u2265 0, and i+k \u2264 n-1.\n  function symmetricHalf(i, W, n, boundaries){\n    var k = 0;\n    while(k < W){\n      var lo = i - (k + 1), hi = i + (k + 1);\n      if(lo < 0) break;\n      if(hi > n - 1) break;\n      if(boundaries ? boundaries[lo + 1] : false) break;\n      if(boundaries ? boundaries[hi] : false) break;\n      k++;\n    }\n    return k;\n  }\n  \/\/ Detect headland-turn boundaries. boundaries[i]=1 means \"transition (i-1, i) is a turnaround;\n  \/\/ do not smooth or stroke across it\". Two independent signals:\n  \/\/   1. Angle reversal (>90\u00b0) \u2014 heading at (i-K..i-1) vs (i..i+K-1). Paired with a minimum\n  \/\/      gap so GPS jitter inside a dense Trimble pass doesn't produce false boundaries.\n  \/\/   2. Distance jump alone \u2014 step > 5\u00d7 median (large field skip regardless of direction).\n  \/\/ K=5 (was 3) gives a wider heading window, reducing noise for dense polygon files where\n  \/\/ each recorded sample is a separate polygon and K=3 could span only 3-6m (noise-dominated).\n  \/\/ The angle companion distance (\u2265 half the equipment swath) means a genuine headland turn \u2014\n  \/\/ where the machine must travel at least one swath width sideways \u2014 always qualifies, but\n  \/\/ sub-swath GPS noise within a single pass does not.\n  function computeTurnaroundBoundaries(){\n    var n = featCount();\n    if(n < 8) return null;\n    var ord = playback.order;\n    var K = 5;\n    \/\/ Use the machine-centerline (group centroids per timestamp) when available so consecutive\n    \/\/ entries in playback.order from the SAME moment (multi-section data) don't look like a\n    \/\/ big spatial jump. This keeps boundary detection from firing within the boom width.\n    var mXY = playback.machineXY;\n    function px(i){ return mXY ? mXY.x[i] : featCx(ord ? ord[i] : i); }\n    function py(i){ return mXY ? mXY.y[i] : featCy(ord ? ord[i] : i); }\n    var dists = new Float32Array(n);\n    for(var i=1; i<n; i++){\n      var dx = px(i) - px(i-1), dy = py(i) - py(i-1);\n      dists[i] = Math.sqrt(dx*dx + dy*dy);\n    }\n    var sorted = Array.prototype.slice.call(dists, 1).sort(function(a,b){return a-b;});\n    var med = sorted.length ? sorted[Math.floor(sorted.length\/2)] : 1;\n    if(med <= 0) med = 1;\n    \/\/ Distance-only threshold raised to 5\u00d7 (was 3\u00d7) \u2014 reduces false positives from\n    \/\/ minor density variation within a single pass on Trimble\/dense as-applied files.\n    var distThreshold = med * 5;\n    var wM = equipmentWidthM(playback.opLabel);\n    if(distThreshold < wM * 0.6) distThreshold = wM * 0.6;\n    \/\/ Companion distance for the angle signal \u2014 a real headland transition moves the machine\n    \/\/ at least a third of a swath width laterally. Lowered from 0.5\u00d7 to 0.35\u00d7 wM so subtle\n    \/\/ turns (e.g., curving headland follows or partial-overlap rows) are also detected.\n    \/\/ Floor at 2.5 m absolute to avoid noise-level triggers.\n    var angleCompanion = wM * 0.35;\n    if(angleCompanion < 2.5) angleCompanion = 2.5;\n    var mask = new Uint8Array(n);\n    var prev = -K - 10;\n    for(var k=K; k<n-K; k++){\n      \/\/ Signal 1: angle reversal over a 2K-feature window centered at k. Uses px\/py so\n      \/\/ multi-section data sees machine-centerline positions, not individual section centroids.\n      var ax = px(k-1) - px(k-K), ay = py(k-1) - py(k-K);\n      var bx = px(k+K-1) - px(k), by = py(k+K-1) - py(k);\n      var la = Math.sqrt(ax*ax + ay*ay);\n      var lb = Math.sqrt(bx*bx + by*by);\n      var angleReverses = false;\n      \/\/ Require meaningful vector lengths (> 1m) so noisy sub-meter centroids don't produce\n      \/\/ spurious heading estimates. Angle reversal also needs a companion distance gap.\n      if(la > 1.0){\n        if(lb > 1.0){\n          var cosA = (ax*bx + ay*by) \/ (la * lb);\n          if(cosA < 0 ? dists[k] > angleCompanion : false) angleReverses = true;\n        }\n      }\n      \/\/ Signal 2: large local distance jump (field skip, harvester jump to next block)\n      var distJumps = dists[k] > distThreshold;\n      if(angleReverses || distJumps){\n        if(k - prev >= 6){  \/\/ wider dedup gap \u2014 noisy headlands can have 2-3 triggers in a row\n          mask[k] = 1;\n          prev = k;\n        }\n      }\n    }\n    return mask;\n  }\n  \/\/ Bend-angle speed factor per playback-order index. Looks at the heavily-smoothed path because\n  \/\/ we want the underlying intent (not GPS jitter) to drive the slowdown. Output is a Float32\n  \/\/ array in [0.3, 1.0]: 1.0 on straight sections, ramping down to 0.3 at 90\u00b0+ bends.\n  function computeSpeedFactor(){\n    var n = featCount();\n    if(!n) return null;\n    var out = new Float32Array(n);\n    var px = playback.smoothPathX;\n    var py = playback.smoothPathY;\n    if(!px) return null;\n    var W = 8;\n    for(var i=0; i<n; i++){\n      var iA = i - W; if(iA < 0) iA = 0;\n      var iB = i + W; if(iB > n-1) iB = n-1;\n      \/\/ Two direction vectors through the path window\n      var ax = px[i] - px[iA], ay = py[i] - py[iA];\n      var bx = px[iB] - px[i], by = py[iB] - py[i];\n      var la = Math.sqrt(ax*ax + ay*ay);\n      var lb = Math.sqrt(bx*bx + by*by);\n      if(la < 0.0001){ out[i] = 1; continue; }\n      if(lb < 0.0001){ out[i] = 1; continue; }\n      \/\/ cos\u03b8 between segments; \u03b8 = 0 \u2192 straight, \u03c0 \u2192 reverse\n      var cosT = (ax*bx + ay*by) \/ (la * lb);\n      if(cosT > 1) cosT = 1; if(cosT < -1) cosT = -1;\n      var bend = Math.acos(cosT);                   \/\/ 0..\u03c0\n      \/\/ Map bend \u2208 [0, \u03c0\/2] \u2192 factor \u2208 [1.0, 0.3]; clamp beyond \u03c0\/2.\n      var t = bend \/ (Math.PI * 0.5);\n      if(t > 1) t = 1;\n      out[i] = 1 - 0.7 * t;\n    }\n    \/\/ Smooth the speed factor itself so deceleration\/acceleration are gradual (no instant brake).\n    var smoothed = new Float32Array(n);\n    var WS = 12;\n    for(var k=0; k<n; k++){\n      var lo = k - WS; if(lo < 0) lo = 0;\n      var hi = k + WS; if(hi > n-1) hi = n-1;\n      var sum = 0, cnt = 0;\n      for(var j=lo; j<=hi; j++){ sum += out[j]; cnt++; }\n      smoothed[k] = cnt > 0 ? sum \/ cnt : 1;\n    }\n    return smoothed;\n  }\n  \/\/ Fit a straight line through each pass (segment between turnaround boundaries) using\n  \/\/ principal-component analysis on the centroids, then project each centroid onto the line.\n  \/\/ Returns {edgeIdx, dist, tdx, tdy, qx, qy} for the nearest hull edge to point (px, py).\n  \/\/ `dist` is the perpendicular distance in mercator units (multiply by cos(latC*DEG) for\n  \/\/ real meters). `(tdx, tdy)` is the unit tangent along that edge. Returns null if hull\n  \/\/ invalid.\n  function nearestHullEdge(px, py, hull){\n    if(!hull) return null;\n    var X = hull.x, Y = hull.y;\n    var n = X.length - 1;\n    var bestD = Infinity, bestI = -1, bestT = 0;\n    for(var i=0; i<n; i++){\n      var ax = X[i], ay = Y[i];\n      var bx = X[i+1], by = Y[i+1];\n      var ex = bx - ax, ey = by - ay;\n      var elen2 = ex*ex + ey*ey;\n      if(elen2 < 1e-18) continue;\n      var t = ((px - ax) * ex + (py - ay) * ey) \/ elen2;\n      if(t < 0) t = 0; else if(t > 1) t = 1;\n      var qx = ax + t * ex, qy = ay + t * ey;\n      var dx = px - qx, dy = py - qy;\n      var d2 = dx*dx + dy*dy;\n      if(d2 < bestD){ bestD = d2; bestI = i; bestT = t; }\n    }\n    if(bestI < 0) return null;\n    var aX = X[bestI], aY = Y[bestI];\n    var bX = X[bestI+1], bY = Y[bestI+1];\n    var eX = bX - aX, eY = bY - aY;\n    var eL = Math.sqrt(eX*eX + eY*eY);\n    var tdx = eL > 0 ? eX \/ eL : 1;\n    var tdy = eL > 0 ? eY \/ eL : 0;\n    var qX = aX + bestT * eX, qY = aY + bestT * eY;\n    return {\n      edgeIdx: bestI,\n      dist: Math.sqrt(bestD),\n      tdx: tdx, tdy: tdy,\n      qx: qX, qy: qY\n    };\n  }\n  \/\/ For each pass (segment between turnaround boundaries), decide whether it's a\n  \/\/ headland pass \u2014 i.e., the machine drove ALONG the field boundary rather than\n  \/\/ perpendicular to it. Two simultaneous signals:\n  \/\/   1) >= 60% of pass points are within wM \u00d7 1.2 of the hull.\n  \/\/   2) The pass's mean heading is within 30\u00b0 of the corresponding hull edges'\n  \/\/      tangent (in either direction \u2014 passes go both ways along the boundary).\n  \/\/ Returns a Uint8Array of length (passCount), or null if hull\/boundaries not\n  \/\/ ready.\n  function computeHeadlandPassMask(){\n    var hulls = playback.fieldHulls;\n    var bnd = playback.boundaries;\n    var ord = playback.order;\n    var mXY = playback.machineXY;\n    if(!hulls ? true : hulls.length === 0) return null;\n    if(!bnd) return null;\n    if(!ord) return null;\n    var n = ord.length;\n    var wM = playback.implementWidth ? playback.implementWidth : 12;\n    var distThreshM = wM * 1.2;\n    var cosLat = Math.cos((typeof latC === 'number' ? latC : 0) * Math.PI \/ 180);\n    if(!(cosLat > 0)) cosLat = 1;\n    var passStarts = [0];\n    for(var bi=1; bi<n; bi++) if(bnd[bi]) passStarts.push(bi);\n    var passCount = passStarts.length;\n    var mask = new Uint8Array(passCount);\n    function getXM(oi){ return mXY ? mXY.x[oi] : featCx(ord[oi]); }\n    function getYM(oi){ return mXY ? mXY.y[oi] : featCy(ord[oi]); }\n    for(var p=0; p<passCount; p++){\n      var s = passStarts[p];\n      var e = (p + 1 < passCount) ? passStarts[p+1] : n;\n      var len = e - s;\n      if(len < 4) continue;\n      \/\/ Pick the hull this pass belongs to \u2014 try the mid-point centroid first, then\n      \/\/ the first sample if mid is on a boundary. Skip the pass if no containing hull.\n      var midK = (s + e) >> 1;\n      var passHull = findContainingHull(getXM(midK), getYM(midK), hulls);\n      if(!passHull) passHull = findContainingHull(getXM(s), getYM(s), hulls);\n      if(!passHull) continue;\n      var nearCount = 0;\n      var sumTdx = 0, sumTdy = 0;\n      var samples = 0;\n      for(var k=s; k<e; k++){\n        var x = getXM(k), y = getYM(k);\n        var info = nearestHullEdge(x, y, passHull);\n        if(!info) continue;\n        \/\/ mercator -> real meters\n        var distMReal = info.dist * cosLat;\n        if(distMReal <= distThreshM) nearCount++;\n        sumTdx += info.tdx;\n        sumTdy += info.tdy;\n        samples++;\n      }\n      if(samples < 4) continue;\n      var nearRatio = nearCount \/ samples;\n      if(nearRatio < 0.6) continue;\n      \/\/ Mean pass heading from first-to-last position\n      var hdx = getXM(e - 1) - getXM(s);\n      var hdy = getYM(e - 1) - getYM(s);\n      var hLen = Math.sqrt(hdx*hdx + hdy*hdy);\n      if(hLen < 1e-6) continue;\n      hdx \/= hLen; hdy \/= hLen;\n      \/\/ Mean hull-edge tangent (unit-normalised)\n      var tLen = Math.sqrt(sumTdx*sumTdx + sumTdy*sumTdy);\n      if(tLen < 1e-6) continue;\n      var tx = sumTdx \/ tLen, ty = sumTdy \/ tLen;\n      \/\/ Parallel in EITHER direction \u2014 passes can run along the boundary forward or backward.\n      var cosA = hdx * tx + hdy * ty;\n      if(cosA < 0) cosA = -cosA;\n      if(cosA < 0.866) continue;  \/\/ cos(30\u00b0)\n      mask[p] = 1;\n    }\n    return mask;\n  }\n  \/\/ Real ag equipment drives straight rows \u2014 the visible wobble in raw centroids comes from\n  \/\/ GPS noise and polygon shape, not from real machine motion. Fitting a line per pass kills\n  \/\/ the wobble (\"\u0437\u0430\u0432\u0438\u0442\u0443\u0448\u043a\u0438\") and gives the trail + sprite the realistic straight path users\n  \/\/ expect. For genuinely curved passes (contour farming, headland strips) the fit's\n  \/\/ perpendicular residual is large \u2014 we fall back to the raw centroids so curvature is\n  \/\/ preserved instead of being flattened.\n  function computeStraightPassPath(){\n    var n = featCount();\n    if(!n) return { x: null, y: null };\n    var bnd = playback.boundaries;\n    var ord = playback.order;\n    var mXY = playback.machineXY;\n    \/\/ Multi-section files: use the machine-centerline (group centroid per timestamp) so\n    \/\/ the fitted line tracks the actual machine path, not the section-by-section zigzag.\n    function getX(oi){ return mXY ? mXY.x[oi] : featCx(ord ? ord[oi] : oi); }\n    function getY(oi){ return mXY ? mXY.y[oi] : featCy(ord ? ord[oi] : oi); }\n    var px = new Float32Array(n);\n    var py = new Float32Array(n);\n    \/\/ Extend the FIRST and LAST positions of a pass outward by half a typical step.\n    \/\/ Raw centroids sit at the middle of each polygon; without the extension the sprite\n    \/\/ appears to pivot BEFORE reaching the visual edge. Applied to every pass \u2014 straight\n    \/\/ or curved \u2014 so the \"pivot at the edge\" behavior is universal across fields.\n    function extendEndpoints(start, end){\n      var len = end - start;\n      if(len < 2) return;\n      \/\/ Heading at the START: use the next few centroids (px[start..start+K-1]).\n      var Khead = len < 5 ? len - 1 : 4;\n      var sdx = px[start + Khead] - px[start];\n      var sdy = py[start + Khead] - py[start];\n      var sLen = Math.sqrt(sdx*sdx + sdy*sdy);\n      \/\/ Heading at the END: use the previous few centroids.\n      var Ktail = len < 5 ? len - 1 : 4;\n      var edx = px[end - 1] - px[end - 1 - Ktail];\n      var edy = py[end - 1] - py[end - 1 - Ktail];\n      var eLen = Math.sqrt(edx*edx + edy*edy);\n      \/\/ Average step in mercator meters along this pass \u2014 defines the half-step amount.\n      var totalLen = 0;\n      for(var s2=start+1; s2<end; s2++){\n        var dxS = px[s2] - px[s2 - 1];\n        var dyS = py[s2] - py[s2 - 1];\n        totalLen += Math.sqrt(dxS*dxS + dyS*dyS);\n      }\n      var avgStep = (end - start) > 1 ? totalLen \/ (end - start - 1) : 0;\n      var half = avgStep * 0.5;\n      if(sLen > 0.001){\n        px[start] -= sdx \/ sLen * half;\n        py[start] -= sdy \/ sLen * half;\n      }\n      if(eLen > 0.001){\n        px[end - 1] += edx \/ eLen * half;\n        py[end - 1] += edy \/ eLen * half;\n      }\n    }\n    function fitSegment(start, end, passIdx){\n      var len = end - start;\n      if(len <= 0) return;\n      \/\/ HEADLAND PASS: machine drove ALONG the boundary, not perpendicular to the rows.\n      \/\/ PCA would flatten the curve to a straight line cutting across the boundary \u2014\n      \/\/ explicitly wrong. Force cascade smoothing on the machine-centerline so the trail\n      \/\/ follows the boundary curve. See computeHeadlandPassMask for the detection rules\n      \/\/ (>=60% within wM*1.2 of the hull AND mean heading within 30deg of hull tangent).\n      var hMask = playback.headlandMask;\n      var isHeadland = hMask ? hMask[passIdx] === 1 : false;\n      if(isHeadland){\n        var Wsm0 = Math.floor(len \/ 4);\n        if(Wsm0 < 5) Wsm0 = 5;\n        if(Wsm0 > 40) Wsm0 = 40;\n        var tmpX0 = new Float32Array(len);\n        var tmpY0 = new Float32Array(len);\n        for(var m0=start; m0<end; m0++){\n          var lo0 = m0 - Wsm0; if(lo0 < start) lo0 = start;\n          var hi0 = m0 + Wsm0; if(hi0 > end - 1) hi0 = end - 1;\n          var sx0 = 0, sy0 = 0, c0 = 0;\n          for(var w0=lo0; w0<=hi0; w0++){ sx0 += getX(w0); sy0 += getY(w0); c0++; }\n          tmpX0[m0 - start] = sx0 \/ c0;\n          tmpY0[m0 - start] = sy0 \/ c0;\n        }\n        for(var m1=start; m1<end; m1++){\n          var lo1 = m1 - Wsm0; if(lo1 < start) lo1 = start;\n          var hi1 = m1 + Wsm0; if(hi1 > end - 1) hi1 = end - 1;\n          var sx1 = 0, sy1 = 0, c1 = 0;\n          for(var w1=lo1; w1<=hi1; w1++){ sx1 += tmpX0[w1 - start]; sy1 += tmpY0[w1 - start]; c1++; }\n          px[m1] = sx1 \/ c1;\n          py[m1] = sy1 \/ c1;\n        }\n        extendEndpoints(start, end);\n        return;\n      }\n      \/\/ Wide-equipment mode: only the CENTRAL (kept) data-pass features contribute to the\n      \/\/ line fit; off-pass features get projected onto the resulting line. Keeps the sprite\n      \/\/ on the wide-pass centerline rather than zigzagging through every section centroid.\n      var central = playback.isCentral;\n      function isFit(i){ return central ? central[i] === 1 : true; }\n      \/\/ Count how many entries are usable for the fit\n      var fitCount = 0;\n      for(var ci=start; ci<end; ci++) if(isFit(ci)) fitCount++;\n      if(fitCount < 4){\n        \/\/ Not enough central points \u2014 fall back to raw centroids (machine centerline if available)\n        for(var i=start; i<end; i++){\n          px[i] = getX(i);\n          py[i] = getY(i);\n        }\n        extendEndpoints(start, end);\n        return;\n      }\n      var sumX = 0, sumY = 0;\n      for(var i2=start; i2<end; i2++){\n        if(!isFit(i2)) continue;\n        sumX += getX(i2);\n        sumY += getY(i2);\n      }\n      var mux = sumX \/ fitCount, muy = sumY \/ fitCount;\n      var sxx = 0, syy = 0, sxy = 0;\n      for(var j=start; j<end; j++){\n        if(!isFit(j)) continue;\n        var dxA = getX(j) - mux, dyA = getY(j) - muy;\n        sxx += dxA*dxA; syy += dyA*dyA; sxy += dxA*dyA;\n      }\n      \/\/ Principal direction from 2\u00d72 covariance eigenvalue\n      var angleP = Math.atan2(2 * sxy, sxx - syy) \/ 2;\n      var dirX = Math.cos(angleP);\n      var dirY = Math.sin(angleP);\n      var maxPerp = 0;\n      var minT = Infinity, maxT = -Infinity;\n      var projT = new Float32Array(len);\n      for(var k=start; k<end; k++){\n        var cxK = getX(k), cyK = getY(k);\n        var dxK = cxK - mux, dyK = cyK - muy;\n        var t = dxK * dirX + dyK * dirY;\n        \/\/ Perpendicular residual only from CENTRAL polygons \u2014 off-center polygons are\n        \/\/ expected to sit \u00b1wM\/2 off the line and would falsely trigger the curvature\n        \/\/ fallback (which would zigzag the path back through them).\n        if(isFit(k)){\n          var perp = Math.abs(dxK * (-dirY) + dyK * dirX);\n          if(perp > maxPerp) maxPerp = perp;\n        }\n        if(t < minT) minT = t;\n        if(t > maxT) maxT = t;\n        projT[k - start] = t;\n      }\n      var passLen = maxT - minT;\n      \/\/ Bend check: compare heading over the FIRST 4 centroids vs the LAST 4 centroids.\n      \/\/ If they differ by more than 25\u00b0 the pass is curved (headland following the field\n      \/\/ boundary, contour rows) \u2014 must not be flattened to a straight line, ever.\n      \/\/ SKIPPED in wide-pass mode: the new order interleaves off-center polygons by\n      \/\/ along-position, so consecutive ord[i], ord[i+1] in a wide-pass group can be from\n      \/\/ different data-pass y-rows, giving a heading vector that's mostly perpendicular\n      \/\/ to the row direction. That false-triggered the bend check. The maxPerp check\n      \/\/ (which only uses central polygons) is enough on its own in wide-pass mode.\n      var bentByAngle = false;\n      var KheadBend = len < 8 ? Math.floor(len \/ 2) : 4;\n      if(KheadBend >= 2 ? !central : false){\n        var bsdx = getX(start + KheadBend) - getX(start);\n        var bsdy = getY(start + KheadBend) - getY(start);\n        var bedx = getX(end - 1) - getX(end - 1 - KheadBend);\n        var bedy = getY(end - 1) - getY(end - 1 - KheadBend);\n        var bsLen = Math.sqrt(bsdx*bsdx + bsdy*bsdy);\n        var beLen = Math.sqrt(bedx*bedx + bedy*bedy);\n        if(bsLen > 0.001 ? beLen > 0.001 : false){\n          var cosBend = (bsdx*bedx + bsdy*bedy) \/ (bsLen * beLen);\n          if(cosBend > 1) cosBend = 1; if(cosBend < -1) cosBend = -1;\n          \/\/ cos(25\u00b0) \u2248 0.906 \u2014 anything below this is a meaningful bend\n          if(cosBend < 0.906) bentByAngle = true;\n        }\n      }\n      \/\/ Curvature check via perpendicular residual: residual > 2% of pass length OR > 1.5 m\n      \/\/ absolute also indicates a curved pass (multi-section spread, contour farming, etc.).\n      var curveThresh = passLen * 0.02;\n      if(curveThresh < 1.5) curveThresh = 1.5;\n      var bentByResidual = passLen > 0.1 ? maxPerp > curveThresh : false;\n      \/\/ Either signal triggers the curved fallback with heavy moving-average smoothing\n      \/\/ applied TWICE (cascade) for a near-Gaussian response. Wider window (cap 40, was 25)\n      \/\/ matches the smooth-arc style of the reference Dubins-curve images at\n      \/\/ samples\/lines_samples\/*.png \u2014 long curving headlands should read as a continuous\n      \/\/ smooth bend, not a series of short straight chords.\n      if(bentByAngle || bentByResidual){\n        var Wsm = Math.floor(len \/ 4);\n        if(Wsm < 5) Wsm = 5;\n        if(Wsm > 40) Wsm = 40;\n        var tmpX = new Float32Array(len);\n        var tmpY = new Float32Array(len);\n        \/\/ First pass: smooth from RAW or MACHINE-CENTERLINE centroids into tmp arrays.\n        \/\/ For multi-section data, getX\/getY return the per-step group centroid so the\n        \/\/ smoothing operates on the machine path, not the section zigzag.\n        for(var m=start; m<end; m++){\n          var lo = m - Wsm; if(lo < start) lo = start;\n          var hi = m + Wsm; if(hi > end - 1) hi = end - 1;\n          var sxA = 0, syA = 0, cnt = 0;\n          for(var w=lo; w<=hi; w++){\n            sxA += getX(w); syA += getY(w); cnt++;\n          }\n          tmpX[m - start] = sxA \/ cnt;\n          tmpY[m - start] = syA \/ cnt;\n        }\n        \/\/ Second pass: smooth tmp into px\/py (cascade)\n        for(var m3=start; m3<end; m3++){\n          var lo2 = m3 - Wsm; if(lo2 < start) lo2 = start;\n          var hi2 = m3 + Wsm; if(hi2 > end - 1) hi2 = end - 1;\n          var sxB = 0, syB = 0, cnt2 = 0;\n          for(var w2=lo2; w2<=hi2; w2++){\n            sxB += tmpX[w2 - start]; syB += tmpY[w2 - start]; cnt2++;\n          }\n          px[m3] = sxB \/ cnt2;\n          py[m3] = syB \/ cnt2;\n        }\n        extendEndpoints(start, end);\n        return;\n      }\n      for(var m2=start; m2<end; m2++){\n        var t2 = projT[m2 - start];\n        px[m2] = mux + t2 * dirX;\n        py[m2] = muy + t2 * dirY;\n      }\n      extendEndpoints(start, end);\n    }\n    var passStart = 0;\n    var passIdx = 0;\n    for(var bi=0; bi<n; bi++){\n      if(bnd ? bnd[bi] : false){\n        fitSegment(passStart, bi, passIdx);\n        passStart = bi;\n        passIdx++;\n      }\n    }\n    fitSegment(passStart, n, passIdx);\n    return { x: px, y: py };\n  }\n  \/\/ Second-pass smoothing. Symmetric, boundary-aware \u2014 same reasoning as computeSmoothedPath.\n  function smoothPathOnce(src, W, boundaries){\n    if(!src) return null;\n    var n = src.length;\n    var out = new Float32Array(n);\n    for(var i=0; i<n; i++){\n      var half = symmetricHalf(i, W, n, boundaries);\n      var lo = i - half, hi = i + half;\n      var sum = 0, cnt = 0;\n      for(var j=lo; j<=hi; j++){ sum += src[j]; cnt++; }\n      out[i] = cnt > 0 ? sum \/ cnt : 0;\n    }\n    return out;\n  }\n  \/\/ LineString-aware heading lookup. Returns heading in radians (atan2 result) computed\n  \/\/ from the tangent of the line at idxFloat, sampled by forward-differencing the line\n  \/\/ vertices. Returns null if not in line mode or feature has < 2 vertices.\n  function lineHeadingAt(idxFloat){\n    if(mode !== 'line' ? true : !polyData) return null;\n    \/\/ Sample slightly ahead and slightly behind on the same feature to get a stable tangent.\n    var pAhead = lineVertexAt(idxFloat + 0.02);\n    var pBack = lineVertexAt(idxFloat - 0.02);\n    if(!pAhead ? true : !pBack) return null;\n    var dx = pAhead.x - pBack.x;\n    var dy = pAhead.y - pBack.y;\n    if(dx*dx + dy*dy < 0.000001) return null;\n    return Math.atan2(dy, dx);\n  }\n  \/\/ LineString-aware position lookup. In line mode, idxFloat = i + frac maps to\n  \/\/ feature i's line, with frac \u2208 [0, 1) interpolating along that line's vertices\n  \/\/ (uniform-by-vertex, fine for our resampled lines). Returns {x, y} in mercator units,\n  \/\/ or null if not in line mode \/ no data.\n  function lineVertexAt(idxFloat){\n    if(mode !== 'line' ? true : !polyData) return null;\n    var fi = Math.floor(idxFloat);\n    var frac = idxFloat - fi;\n    if(playback.order ? fi >= playback.order.length : false){\n      fi = playback.order.length - 1; frac = 1;\n    }\n    if(fi < 0){ fi = 0; frac = 0; }\n    var fIdx = playback.order ? playback.order[fi] : fi;\n    var feat = polyData[fIdx];\n    if(!feat) return null;\n    if(!feat.rings ? true : feat.rings.length === 0){\n      return { x: feat.cx, y: feat.cy };\n    }\n    var totalVerts = 0;\n    for(var r=0; r<feat.rings.length; r++) totalVerts += feat.rings[r].mx.length;\n    if(totalVerts < 2){\n      var r0 = feat.rings[0];\n      return { x: r0.mx[0], y: r0.my[0] };\n    }\n    var t = frac * (totalVerts - 1);\n    var vi = Math.floor(t), vf = t - vi;\n    if(vi >= totalVerts - 1){ vi = totalVerts - 2; vf = 1; }\n    var seen = 0;\n    for(var rr=0; rr<feat.rings.length; rr++){\n      var ring = feat.rings[rr];\n      if(vi < seen + ring.mx.length - 1){\n        var lvi = vi - seen;\n        return {\n          x: ring.mx[lvi] * (1 - vf) + ring.mx[lvi + 1] * vf,\n          y: ring.my[lvi] * (1 - vf) + ring.my[lvi + 1] * vf\n        };\n      }\n      seen += ring.mx.length;\n    }\n    var lastRing = feat.rings[feat.rings.length - 1];\n    var lastIdx = lastRing.mx.length - 1;\n    return { x: lastRing.mx[lastIdx], y: lastRing.my[lastIdx] };\n  }\n  \/\/ Trail path (heavy smoothing) \u2014 used for the rendered polyline and direction arrows.\n  function pathCx(i){\n    var sx = playback.smoothPathX;\n    if(sx ? i < sx.length : false) return sx[i];\n    var ord = playback.order;\n    return featCx(ord ? ord[i] : i);\n  }\n  function pathCy(i){\n    var sy = playback.smoothPathY;\n    if(sy ? i < sy.length : false) return sy[i];\n    var ord = playback.order;\n    return featCy(ord ? ord[i] : i);\n  }\n  \/\/ Sprite path (light smoothing) \u2014 used for the moving equipment + heading lookback so it\n  \/\/ reaches the actual edge of a row before pivoting.\n  function spriteCx(i){\n    var sx = playback.spritePathX;\n    if(sx ? i < sx.length : false) return sx[i];\n    var ord = playback.order;\n    return featCx(ord ? ord[i] : i);\n  }\n  function spriteCy(i){\n    var sy = playback.spritePathY;\n    if(sy ? i < sy.length : false) return sy[i];\n    var ord = playback.order;\n    return featCy(ord ? ord[i] : i);\n  }\n  \/\/ Distance from point (px, py) to the nearest edge of a closed hull polygon.\n  \/\/ Returns mercator-space distance. Caller multiplies by cosLat to convert to\n  \/\/ real metres if needed.\n  function distToHullEdgeMerc(px, py, hull){\n    if(!hull) return Infinity;\n    var X = hull.x, Y = hull.y;\n    var n = X.length - 1;\n    var minD2 = Infinity;\n    for(var i=0; i<n; i++){\n      var ax = X[i], ay = Y[i];\n      var bx = X[i+1], by = Y[i+1];\n      var ddxE = bx - ax, ddyE = by - ay;\n      var L2 = ddxE*ddxE + ddyE*ddyE;\n      var t = L2 > 1e-12 ? ((px-ax)*ddxE + (py-ay)*ddyE) \/ L2 : 0;\n      if(t < 0) t = 0; else if(t > 1) t = 1;\n      var qx = ax + t*ddxE, qy = ay + t*ddyE;\n      var ddxP = px - qx, ddyP = py - qy;\n      var d2 = ddxP*ddxP + ddyP*ddyP;\n      if(d2 < minD2) minD2 = d2;\n    }\n    return Math.sqrt(minD2);\n  }\n  \/\/ Move all outside-the-hull features to the end of the playback order while\n  \/\/ preserving the input ordering for inside features. Implements the \"machine\n  \/\/ doesn't leave the field\" rule without overriding the source-driven order\n  \/\/ for the field-inside portion.\n  function pushOutsideHullToEnd(ord, hulls){\n    if(!ord ? true : ord.length < 3) return ord;\n    if(!hulls ? true : hulls.length === 0) return ord;\n    var inside = [], outside = [];\n    for(var i=0; i<ord.length; i++){\n      var fi = ord[i];\n      var fx = featCx(fi), fy = featCy(fi);\n      var isIn = false;\n      for(var hi=0; hi<hulls.length; hi++){\n        if(pointInHull(fx, fy, hulls[hi], 0)){ isIn = true; break; }\n      }\n      if(isIn) inside.push(fi); else outside.push(fi);\n    }\n    if(outside.length === 0) return ord;\n    try { console.warn('[GPY] '+outside.length+' feature(s) outside field hull \u2014 moved to end of playback order'); } catch(_){}\n    return inside.concat(outside);\n  }\n  \/\/ Measure the largest consecutive spatial jump in a playback order, in REAL\n  \/\/ metres (after cosLat correction). Used to detect \"teleport\" risk before\n  \/\/ rebuilding the order as a greedy NN walk.\n  function measureMaxJumpRealM(ord){\n    if(!ord ? true : ord.length < 2) return 0;\n    var cosLat = Math.cos((typeof latC === 'number' ? latC : 0) * Math.PI \/ 180);\n    if(!(cosLat > 0)) cosLat = 1;\n    var maxD2 = 0;\n    for(var i=1; i<ord.length; i++){\n      var a = ord[i-1], b = ord[i];\n      var dx = featCx(b) - featCx(a);\n      var dy = featCy(b) - featCy(a);\n      var d2 = dx*dx + dy*dy;\n      if(d2 > maxD2) maxD2 = d2;\n    }\n    return Math.sqrt(maxD2) * cosLat;\n  }\n  \/\/ Build a per-feature priority mask: mask[i] = 1 if feature i is in the\n  \/\/ headland zone (inside any hull AND within wM \u00d7 1.5 of that hull's edge).\n  \/\/ Returns null when `applyHeadland` is false or no features qualify.\n  function buildHeadlandPriorityMask(hulls, wM, applyHeadland){\n    if(!applyHeadland) return null;\n    if(!hulls ? true : hulls.length === 0) return null;\n    var n = featCount();\n    var cosLat = Math.cos((typeof latC === 'number' ? latC : 0) * Math.PI \/ 180);\n    if(!(cosLat > 0)) cosLat = 1;\n    var headlandMerc = (wM * 1.5) \/ cosLat;\n    var mask = new Uint8Array(n);\n    var nHead = 0;\n    for(var i=0; i<n; i++){\n      var fx = featCx(i), fy = featCy(i);\n      for(var hi=0; hi<hulls.length; hi++){\n        if(pointInHull(fx, fy, hulls[hi], 0)){\n          var d = distToHullEdgeMerc(fx, fy, hulls[hi]);\n          if(d < headlandMerc){ mask[i] = 1; nHead++; }\n          break;\n        }\n      }\n    }\n    return nHead > 0 ? mask : null;\n  }\n  \/\/ Returns the fraction of features that sit in the headland zone (within\n  \/\/ wM \u00d7 1.5 of any hull edge while inside a hull). Used to decide whether the\n  \/\/ headland-first reorder should fire.\n  function classifyHeadlandFraction(ord, hulls, wM){\n    if(!ord ? true : ord.length < 3) return 0;\n    if(!hulls ? true : hulls.length === 0) return 0;\n    var headlandM = wM * 1.5;\n    var cosLat = Math.cos((typeof latC === 'number' ? latC : 0) * Math.PI \/ 180);\n    if(!(cosLat > 0)) cosLat = 1;\n    var headlandMerc = headlandM \/ cosLat;\n    var nHead = 0, nInside = 0;\n    for(var i=0; i<ord.length; i++){\n      var fi = ord[i];\n      var fx = featCx(fi), fy = featCy(fi);\n      for(var hi=0; hi<hulls.length; hi++){\n        if(pointInHull(fx, fy, hulls[hi], 0)){\n          nInside++;\n          var d = distToHullEdgeMerc(fx, fy, hulls[hi]);\n          if(d < headlandMerc) nHead++;\n          break;\n        }\n      }\n    }\n    if(nInside === 0) return 0;\n    return nHead \/ nInside;\n  }\n  \/\/ Reorder playback so real-world drive pattern shows: HEADLANDS first\n  \/\/ (boundary-following rings, sorted CCW around each hull centroid), then\n  \/\/ INTERIOR (preserved from input order \u2014 timestamp \/ ID \/ snake), then any\n  \/\/ OUTSIDE features (drove-past stragglers) last. The \"don't leave the field\"\n  \/\/ rule comes from putting outsides last; the \"headlands first\" rule comes\n  \/\/ from the per-hull ring sort.\n  \/\/\n  \/\/ headlandM = wM \u00d7 1.5 \u2014 a polygon within 1.5 implement widths of the hull\n  \/\/ edge counts as headland. Reflects how operators define the headland (one\n  \/\/ header width of buffer + one row for the implement to ride during the\n  \/\/ ring pass).\n  function reorderForHeadlandFirst(ord, hulls, wM){\n    if(!ord ? true : ord.length < 3) return ord;\n    if(!hulls ? true : hulls.length === 0) return ord;\n    var headlandM = wM * 1.5;\n    var cosLat = Math.cos((typeof latC === 'number' ? latC : 0) * Math.PI \/ 180);\n    if(!(cosLat > 0)) cosLat = 1;\n    var headlandMerc = headlandM \/ cosLat;\n    var perHull = [];\n    for(var hi=0; hi<hulls.length; hi++){\n      var hu = hulls[hi];\n      var cxC = 0, cyC = 0, np = hu.x.length - 1;\n      for(var hp=0; hp<np; hp++){ cxC += hu.x[hp]; cyC += hu.y[hp]; }\n      cxC \/= np; cyC \/= np;\n      perHull.push({ cx: cxC, cy: cyC, headlands: [], interiors: [] });\n    }\n    var outsides = [];\n    var nHead = 0, nInt = 0, nOut = 0;\n    for(var i=0; i<ord.length; i++){\n      var fi = ord[i];\n      var fx = featCx(fi), fy = featCy(fi);\n      var bestHull = -1;\n      var bestD = Infinity;\n      for(var hi2=0; hi2<hulls.length; hi2++){\n        if(pointInHull(fx, fy, hulls[hi2], 0)){\n          var d = distToHullEdgeMerc(fx, fy, hulls[hi2]);\n          if(d < bestD){ bestD = d; bestHull = hi2; }\n        }\n      }\n      if(bestHull < 0){\n        outsides.push(fi); nOut++;\n      } else if(bestD < headlandMerc){\n        perHull[bestHull].headlands.push(fi); nHead++;\n      } else {\n        perHull[bestHull].interiors.push(fi); nInt++;\n      }\n    }\n    \/\/ Headlands: sort by angle around hull centroid to produce a ring walk.\n    \/\/ Interiors: keep input order (preserves snake \/ timestamp).\n    for(var hh=0; hh<perHull.length; hh++){\n      var p = perHull[hh];\n      var px = p.cx, py = p.cy;\n      p.headlands.sort(function(a, b){\n        var aa = Math.atan2(featCy(a) - py, featCx(a) - px);\n        var ab = Math.atan2(featCy(b) - py, featCx(b) - px);\n        return aa - ab;\n      });\n    }\n    var out = [];\n    for(var hh2=0; hh2<perHull.length; hh2++){\n      var ph = perHull[hh2];\n      for(var hi3=0; hi3<ph.headlands.length; hi3++) out.push(ph.headlands[hi3]);\n      for(var ii=0; ii<ph.interiors.length; ii++) out.push(ph.interiors[ii]);\n    }\n    for(var oo=0; oo<outsides.length; oo++) out.push(outsides[oo]);\n    try { console.warn('[GPY] playback reordered: '+nHead+' headland \u00b7 '+nInt+' interior \u00b7 '+nOut+' outside (rule: headlands first, body second, outsides last)'); } catch(_){}\n    return out;\n  }\n  \/\/ Greedy nearest-neighbour walk across all features. Guarantees consecutive\n  \/\/ features in the returned order are spatially adjacent (always picks the\n  \/\/ GLOBAL closest unvisited feature, not just the closest in some window). Uses\n  \/\/ a uniform grid spatial index so per-step cost is O(k) for typical\n  \/\/ densities \u2014 total time \u2248 O(N) average for an 18k-feature yield dataset.\n  \/\/\n  \/\/ Optional `priorityMask` (Uint8Array): if provided, features where mask[i]\n  \/\/ === 1 are visited FIRST (as a greedy NN sub-walk), then non-priority\n  \/\/ features. Used to implement \"headlands first\" \u2014 pass a mask flagging\n  \/\/ features within wM \u00d7 1.5 of the hull edge. Phase 1 (priority) walks all\n  \/\/ headlands in NN order; phase 2 continues from where phase 1 left off,\n  \/\/ walking remaining features in NN order. The walk stays smooth across the\n  \/\/ phase boundary because phase 2 picks the nearest unvisited to the last\n  \/\/ priority feature (= almost always an adjacent body feature).\n  \/\/\n  \/\/ Matches the operator rule \"if I work in this area, I finish it before\n  \/\/ moving to neighbouring area\" \u2014 greedy NN always finishes the current cluster\n  \/\/ of points before jumping to a different one.\n  function greedyNNWalkOrder(priorityMask){\n    var n = featCount();\n    if(n < 2) return null;\n    var xs = new Float64Array(n);\n    var ys = new Float64Array(n);\n    for(var i=0; i<n; i++){ xs[i] = featCx(i); ys[i] = featCy(i); }\n    var minX = xs[0], maxX = xs[0], minY = ys[0], maxY = ys[0];\n    for(var iB=1; iB<n; iB++){\n      if(xs[iB] < minX) minX = xs[iB];\n      if(xs[iB] > maxX) maxX = xs[iB];\n      if(ys[iB] < minY) minY = ys[iB];\n      if(ys[iB] > maxY) maxY = ys[iB];\n    }\n    var W = maxX - minX, H = maxY - minY;\n    if(W <= 0 ? H <= 0 : false){\n      var triv = new Array(n);\n      for(var t=0; t<n; t++) triv[t] = t;\n      return triv;\n    }\n    var totalCells = Math.max(16, Math.ceil(n \/ 6));\n    var aspect = W > 0 ? (H > 0 ? W \/ H : 1) : 1;\n    if(!isFinite(aspect) ? true : aspect <= 0) aspect = 1;\n    var gw = Math.max(2, Math.round(Math.sqrt(totalCells * aspect)));\n    var gh = Math.max(2, Math.round(totalCells \/ gw));\n    var cellW = W > 0 ? W \/ gw : 1;\n    var cellH = H > 0 ? H \/ gh : 1;\n    if(cellW <= 0) cellW = 1;\n    if(cellH <= 0) cellH = 1;\n    var minCell = cellW < cellH ? cellW : cellH;\n    function gxOf(x){\n      var g = Math.floor((x - minX) \/ cellW);\n      if(g < 0) return 0; if(g >= gw) return gw-1; return g;\n    }\n    function gyOf(y){\n      var g = Math.floor((y - minY) \/ cellH);\n      if(g < 0) return 0; if(g >= gh) return gh-1; return g;\n    }\n    var cells = new Array(gw * gh);\n    for(var c=0; c<gw*gh; c++) cells[c] = [];\n    for(var iP=0; iP<n; iP++){\n      cells[gyOf(ys[iP]) * gw + gxOf(xs[iP])].push(iP);\n    }\n    var visited = new Uint8Array(n);\n    var maxR = gw > gh ? gw : gh;\n    \/\/ Find nearest unvisited feature to a given (px, py). If `requirePriority`\n    \/\/ is truthy, only features where priorityMask[i] === 1 qualify.\n    \/\/\n    \/\/ Early-break uses the conservative bound: after searching all cells within\n    \/\/ Chebyshev distance r, the minimum Euclidean distance from (px, py) to ANY\n    \/\/ point in cells at distance r+1 is r \u00d7 minCell (cells at distance r+1 can\n    \/\/ share an edge with cells at distance r, but the FARTHEST edge of an r+1\n    \/\/ cell is r cells away from the origin cell's edge). Break only when the\n    \/\/ current best is strictly less than this \u2014 guarantees true global nearest.\n    function nearestUnvisited(px, py, requirePriority){\n      var gx0 = gxOf(px), gy0 = gyOf(py);\n      var best = -1;\n      var bestD = Infinity;\n      for(var r=0; r<=maxR; r++){\n        var loX = gx0 - r > 0 ? gx0 - r : 0;\n        var hiX = gx0 + r < gw-1 ? gx0 + r : gw-1;\n        var loY = gy0 - r > 0 ? gy0 - r : 0;\n        var hiY = gy0 + r < gh-1 ? gy0 + r : gh-1;\n        for(var gy=loY; gy<=hiY; gy++){\n          for(var gx=loX; gx<=hiX; gx++){\n            if(r > 0){\n              if(gx > gx0-r ? (gx < gx0+r ? (gy > gy0-r ? gy < gy0+r : false) : false) : false) continue;\n            }\n            var bucket = cells[gy*gw + gx];\n            for(var b=0; b<bucket.length; b++){\n              var idx = bucket[b];\n              if(visited[idx]) continue;\n              if(requirePriority ? !priorityMask[idx] : false) continue;\n              var dx = xs[idx] - px, dy = ys[idx] - py;\n              var d = dx*dx + dy*dy;\n              if(d < bestD){ bestD = d; best = idx; }\n            }\n          }\n        }\n        if(best >= 0 ? r > 0 : false){\n          var minNext = r * minCell;\n          if(bestD < minNext * minNext) break;\n        }\n      }\n      return { idx: best, d2: bestD };\n    }\n    var order = new Array(n);\n    var nOut = 0;\n    var maxJumpM2 = 0;\n    var maxJumpAtK = -1;\n    \/\/ PHASE 1 \u2014 priority features (headlands), if any.\n    if(priorityMask){\n      \/\/ Start at the lowest-Y priority feature.\n      var startP = -1;\n      for(var iS1=0; iS1<n; iS1++){\n        if(!priorityMask[iS1]) continue;\n        if(startP < 0 ? true : ys[iS1] < ys[startP]) startP = iS1;\n      }\n      if(startP >= 0){\n        visited[startP] = 1;\n        order[nOut++] = startP;\n        var curP = startP;\n        while(true){\n          var r1 = nearestUnvisited(xs[curP], ys[curP], 1);\n          if(r1.idx < 0) break;\n          if(r1.d2 > maxJumpM2){ maxJumpM2 = r1.d2; maxJumpAtK = nOut; }\n          visited[r1.idx] = 1;\n          order[nOut++] = r1.idx;\n          curP = r1.idx;\n        }\n      }\n    }\n    \/\/ PHASE 2 \u2014 remaining features.\n    if(nOut === 0){\n      \/\/ No phase 1 happened \u2014 start at lowest-Y feature overall.\n      var startB = 0;\n      for(var iS2=1; iS2<n; iS2++) if(ys[iS2] < ys[startB]) startB = iS2;\n      visited[startB] = 1;\n      order[nOut++] = startB;\n    }\n    var curB = order[nOut - 1];\n    while(nOut < n){\n      var r2 = nearestUnvisited(xs[curB], ys[curB], 0);\n      if(r2.idx < 0) break;\n      if(r2.d2 > maxJumpM2){ maxJumpM2 = r2.d2; maxJumpAtK = nOut; }\n      visited[r2.idx] = 1;\n      order[nOut++] = r2.idx;\n      curB = r2.idx;\n    }\n    try {\n      var cosLat = Math.cos((typeof latC === 'number' ? latC : 0) * Math.PI \/ 180);\n      if(!(cosLat > 0)) cosLat = 1;\n      var maxJumpM = Math.sqrt(maxJumpM2) * cosLat;\n      console.warn('[GPY] greedy NN walk: '+n+' features (priorityMask='+(priorityMask ? 'yes' : 'no')+'), max consecutive jump = ' + maxJumpM.toFixed(1) + ' m at step ' + maxJumpAtK);\n    } catch(_){}\n    return order;\n  }\n  \/\/ \"Ag machine can't fly\" smoothing. After the timestamp \/ ID \/ snake sort,\n  \/\/ run a sliding-window nearest-neighbour pass to remove spatial jumps between\n  \/\/ consecutive features. At each position i, look at the next K features in\n  \/\/ the current order; if one of them is closer to position i-1 than the one\n  \/\/ currently at i, swap. Repeats once across the whole array.\n  \/\/\n  \/\/ Why it's needed: Trimble Coverage emits one polygon per active section per\n  \/\/ recording moment, and DateClosed is the time the polygon was CLOSED \u2014 not\n  \/\/ necessarily the order the operator drove. Multi-section booms close\n  \/\/ polygons asynchronously, so a pure timestamp sort can interleave polygons\n  \/\/ from different physical positions. The K-window swap fixes this without\n  \/\/ departing significantly from the original time-based order.\n  \/\/\n  \/\/ K controls how aggressively we deviate from the input order:\n  \/\/   K=5  \u2014 tight (only fix small mis-orderings within ~5 consecutive features)\n  \/\/   K=20 \u2014 looser (can swap features up to 20 positions apart)\n  \/\/   K=50 \u2014 very loose (effectively a partial nearest-neighbour walk)\n  \/\/\n  \/\/ Default K=20 catches typical Trimble section-interleaving without scrambling\n  \/\/ genuinely time-ordered files.\n  function smoothOrderByNN(ord, K){\n    if(!ord ? true : ord.length < 3) return ord;\n    if(K < 2) K = 2;\n    for(var i=1; i<ord.length-1; i++){\n      var prev = ord[i-1];\n      var px = featCx(prev), py = featCy(prev);\n      var bestJ = i;\n      var f0 = ord[i];\n      var dx0 = featCx(f0) - px, dy0 = featCy(f0) - py;\n      var bestD = dx0*dx0 + dy0*dy0;\n      var limit = i + K;\n      if(limit > ord.length) limit = ord.length;\n      for(var j=i+1; j<limit; j++){\n        var fJ = ord[j];\n        var dxJ = featCx(fJ) - px, dyJ = featCy(fJ) - py;\n        var dJ = dxJ*dxJ + dyJ*dyJ;\n        if(dJ < bestD){ bestD = dJ; bestJ = j; }\n      }\n      if(bestJ !== i){\n        var tmp = ord[i]; ord[i] = ord[bestJ]; ord[bestJ] = tmp;\n      }\n    }\n    return ord;\n  }\n  function computePlaybackOrder(){\n    var n = featCount();\n    if(n < 2) return null;\n    \/\/ 1) Timestamp-based sort. Parses to milliseconds-since-epoch so the sort is numeric, not lexical.\n    \/\/    Handles AgGPS Coverage (DateClosed ISO + TimeClosed \"4:18:35AM\"), GeoJSON ISO strings, plain epoch numbers.\n    function parseAgTime(dateVal, timeVal){\n      var ms = 0;\n      if(dateVal !== undefined ? dateVal !== null : false){\n        if(typeof dateVal === 'number'){ ms = dateVal; }\n        else {\n          var d = new Date(String(dateVal));\n          if(!isNaN(d.getTime())) ms = d.getTime();\n        }\n      }\n      if(timeVal !== undefined ? timeVal !== null : false){\n        var m = \/^\\s*(\\d{1,2}):(\\d{2})(?::(\\d{2}))?\\s*([AP]M)?\\s*$\/i.exec(String(timeVal));\n        if(m){\n          var h = parseInt(m[1], 10);\n          var mn = parseInt(m[2], 10);\n          var s = m[3] ? parseInt(m[3], 10) : 0;\n          var ampm = m[4] ? m[4].toUpperCase() : null;\n          if(ampm === 'PM'){ if(h < 12) h += 12; }\n          else if(ampm === 'AM'){ if(h === 12) h = 0; }\n          ms += h*3600000 + mn*60000 + s*1000;\n        }\n      }\n      return ms;\n    }\n    var p0 = features[0] ? features[0].properties : null;\n    if(p0){\n      var dateKey = null, timeKey = null;\n      var keys = ['DateClosed','Date','date','TIMESTAMP','timestamp','Time_GMT','RecordTime'];\n      var tKeys = ['TimeClosed','Time','time'];\n      for(var i=0;i<keys.length;i++){ if(p0[keys[i]] !== undefined){ dateKey = keys[i]; break; } }\n      for(var j=0;j<tKeys.length;j++){ if(p0[tKeys[j]] !== undefined){ timeKey = tKeys[j]; break; } }\n      if(dateKey){\n        var ord = new Array(n);\n        var stamps = new Array(n);\n        for(var i2=0;i2<n;i2++){\n          ord[i2] = i2;\n          var p = features[i2].properties || {};\n          stamps[i2] = parseAgTime(p[dateKey], timeKey ? p[timeKey] : null);\n        }\n        ord.sort(function(a,b){\n          var diff = stamps[a] - stamps[b];\n          if(diff !== 0) return diff;\n          return a - b;\n        });\n        \/\/ Detect whether the timestamp signal is RELIABLE. If most features share\n        \/\/ the same timestamp (e.g., a date-only field with no time component), the\n        \/\/ sort is meaningless and we should fall back to a spatially-coherent\n        \/\/ walk instead. Threshold: if any tie group covers more than 25% of the\n        \/\/ dataset, the timestamp signal is too weak.\n        var maxTieFraction = 0;\n        var curTieStart = 0;\n        for(var ti=1; ti<=n; ti++){\n          var endTie = ti === n ? true : stamps[ord[ti]] !== stamps[ord[curTieStart]];\n          if(endTie){\n            var sz = ti - curTieStart;\n            var frac = sz \/ n;\n            if(frac > maxTieFraction) maxTieFraction = frac;\n            curTieStart = ti;\n          }\n        }\n        if(maxTieFraction > 0.25){\n          try { console.warn('[GPY] timestamp signal too weak (largest tie group covers ' + (maxTieFraction*100).toFixed(0) + '% of data) \u2014 falling back to greedy NN walk'); } catch(_){}\n          var nnOrder = greedyNNWalkOrder();\n          if(nnOrder){\n            playback.orderSource = 'spatial NN walk (weak timestamps)';\n            return nnOrder;\n          }\n          \/\/ Fall through if NN walk failed\n        }\n        \/\/ Timestamp signal is reliable \u2014 do the per-tie-group NN reorder so\n        \/\/ multi-section booms (Trimble Coverage) don't zigzag, then K=50 smooth\n        \/\/ for any across-timestamp interleaving.\n        var groupStart = 0;\n        for(var gi=1; gi<=n; gi++){\n          var endOfGroup = gi === n ? true : stamps[ord[gi]] !== stamps[ord[groupStart]];\n          if(endOfGroup ? gi - groupStart > 1 : false){\n            var anchorIdx = groupStart > 0 ? ord[groupStart - 1] : ord[groupStart];\n            var ax0 = featCx(anchorIdx), ay0 = featCy(anchorIdx);\n            for(var pos=groupStart; pos<gi; pos++){\n              var bestPos = pos;\n              var bestD = Infinity;\n              for(var q=pos; q<gi; q++){\n                var fq = ord[q];\n                var dxQ = featCx(fq) - ax0, dyQ = featCy(fq) - ay0;\n                var dQ = dxQ*dxQ + dyQ*dyQ;\n                if(dQ < bestD){ bestD = dQ; bestPos = q; }\n              }\n              if(bestPos !== pos){\n                var tmp = ord[pos]; ord[pos] = ord[bestPos]; ord[bestPos] = tmp;\n              }\n              ax0 = featCx(ord[pos]); ay0 = featCy(ord[pos]);\n            }\n          }\n          if(endOfGroup) groupStart = gi;\n        }\n        ord = smoothOrderByNN(ord, 50);\n        try { console.warn('[GPY] playback ordered by timestamp ('+dateKey+(timeKey ? '+'+timeKey : '')+'; range '+new Date(stamps[ord[0]]).toISOString()+' \u2192 '+new Date(stamps[ord[n-1]]).toISOString()+'; NN-smoothed K=50)'); } catch(_){}\n        playback.orderSource = 'by timestamp';\n        return ord;\n      }\n    }\n    \/\/ 2) Sequential ID (e.g., Seq, OBJECTID, ID with monotonic increase)\n    if(p0){\n      var idKeys = ['Seq','SEQ','OBJECTID','OID','ID','id'];\n      for(var k=0;k<idKeys.length;k++){\n        var v = p0[idKeys[k]];\n        if(typeof v !== 'number') continue;\n        var ord2 = new Array(n);\n        for(var i3=0;i3<n;i3++) ord2[i3] = i3;\n        ord2.sort(function(a,b){\n          var va = features[a].properties[idKeys[k]];\n          var vb = features[b].properties[idKeys[k]];\n          return va - vb;\n        });\n        \/\/ Spatial smoothing \u2014 sequential IDs aren't always strictly aligned with\n        \/\/ the actual drive order (e.g. OBJECTID assignment can differ from\n        \/\/ recording sequence on exports). K=30 ensures consecutive features are\n        \/\/ spatially adjacent (\u2248 equipment-width apart).\n        ord2 = smoothOrderByNN(ord2, 30);\n        try { console.warn('[GPY] playback ordered by id field \"'+idKeys[k]+'\" (NN-smoothed K=30)'); } catch(_){}\n        playback.orderSource = 'by ' + idKeys[k];\n        return ord2;\n      }\n    }\n    \/\/ 3) LineString mode: prefer the FILE ORDER. A guidance\/path GeoJSON typically lists\n    \/\/    features in the order they're meant to be driven (alternating directions for a\n    \/\/    boustrophedon pattern). Snake-sweep would re-sort them by bounding box and break\n    \/\/    the natural sequence.\n    if(mode === 'line'){\n      var ordLine = new Array(n);\n      for(var li=0; li<n; li++) ordLine[li] = li;\n      try { console.warn('[GPY] playback ordered by FILE ORDER (line mode, no timestamps \/ IDs)'); } catch(_){}\n      playback.orderSource = 'file order';\n      return ordLine;\n    }\n    \/\/ 4) Boustrophedon (\"snake\") sweep \u2014 simulates how a real tractor \/ harvester actually moves:\n    \/\/    parallel passes along the field's long axis, U-turn at the headland, alternate direction.\n    \/\/    This replaces the old nearest-neighbor walk which zig-zagged unrealistically on synthetic\n    \/\/    grids (default samples) where features sit on regular spacing.\n    return computeSnakeOrder(n);\n  }\n  \/\/ Snake-pattern feature order. Bins features into ~sqrt(N) rows perpendicular to the long axis,\n  \/\/ sorts within each row along the long axis, alternates direction every other row. Produces\n  \/\/ realistic-looking sweep playback even when the source data has no timestamps or sequence IDs.\n  function computeSnakeOrder(n){\n    if(n < 2) return null;\n    var minX = Infinity, maxX = -Infinity, minY = Infinity, maxY = -Infinity;\n    for(var i=0;i<n;i++){\n      var x = featCx(i), y = featCy(i);\n      if(x < minX) minX = x; if(x > maxX) maxX = x;\n      if(y < minY) minY = y; if(y > maxY) maxY = y;\n    }\n    var w = maxX - minX, h = maxY - minY;\n    if(w <= 0 ? h <= 0 : false) return null;\n    \/\/ Long axis = pass direction (tractor drives along it). Short axis = row index direction.\n    var alongIsX = w >= h;\n    var crossSpan = alongIsX ? h : w;\n    if(crossSpan <= 0) crossSpan = Math.max(w, h);\n    \/\/ Target ~sqrt(N) rows \u2014 balanced grid for most field shapes. Real fields have row spacing\n    \/\/ tighter than this, but the sweep visual is correct regardless of exact row count.\n    var numRows = Math.max(2, Math.round(Math.sqrt(n)));\n    var rowSpan = crossSpan \/ numRows;\n    if(rowSpan <= 0) rowSpan = 1;\n    var rows = new Array(numRows);\n    for(var r=0;r<numRows;r++) rows[r] = [];\n    for(var i2=0;i2<n;i2++){\n      var cross = alongIsX ? (featCy(i2) - minY) : (featCx(i2) - minX);\n      var rIdx = Math.floor(cross \/ rowSpan);\n      if(rIdx < 0) rIdx = 0;\n      if(rIdx >= numRows) rIdx = numRows - 1;\n      rows[rIdx].push(i2);\n    }\n    for(var r2=0;r2<numRows;r2++){\n      var asc = (r2 % 2) === 0;  \/\/ alternate L\u2192R \/ R\u2192L per row\n      rows[r2].sort(function(a, b){\n        var av = alongIsX ? featCx(a) : featCy(a);\n        var bv = alongIsX ? featCx(b) : featCy(b);\n        return asc ? av - bv : bv - av;\n      });\n    }\n    var order = [];\n    for(var r3=0;r3<numRows;r3++){\n      for(var k=0;k<rows[r3].length;k++) order.push(rows[r3][k]);\n    }\n    \/\/ Smooth the snake order too \u2014 row-boundary transitions can leave small\n    \/\/ gaps when feature density is uneven across rows.\n    order = smoothOrderByNN(order, 5);\n    try { console.warn('[GPY] playback ordered by snake sweep ('+numRows+' rows, '+n+' features, along='+(alongIsX?'X':'Y')+', NN-smoothed K=5)'); } catch(_){}\n    playback.orderSource = 'snake sweep';\n    return order;\n  }\n  \/\/ Count sharp direction changes between consecutive feature centers \u2014 a rough \"turnaround\" estimator.\n  \/\/ Walks in playback.order (path-sorted), not array order, so the result reflects the actual path.\n  function countTurnarounds(){\n    var n = featCount();\n    if(n < 3) return 0;\n    var ord = playback.order;\n    var turns = 0, prevH = null;\n    for(var i=1;i<n;i++){\n      var ai = ord ? ord[i-1] : (i-1);\n      var bi = ord ? ord[i]   : i;\n      var dx = featCx(bi) - featCx(ai);\n      var dy = featCy(bi) - featCy(ai);\n      if(dx*dx + dy*dy < 1) continue;\n      var h = Math.atan2(dy, dx);\n      if(prevH !== null){\n        var diff = Math.abs(h - prevH);\n        if(diff > Math.PI) diff = 2*Math.PI - diff;\n        if(diff > Math.PI*0.75) turns++;\n      }\n      prevH = h;\n    }\n    return turns;\n  }\n  \/\/ Build a NEW playback order that groups polygons into wide passes. When the chosen\n  \/\/ implement is significantly wider than the data spacing, each wide pass covers \u00b1wM\/2\n  \/\/ perpendicular distance \u2014 so all polygons from data passes within that buffer should\n  \/\/ appear DURING the wide pass, sorted by their along-pass position. Sprite then jumps\n  \/\/ to the NEXT wide pass.\n  \/\/\n  \/\/ Algorithm:\n  \/\/ 1. Find original pass starts (boundary indices).\n  \/\/ 2. Compute median inter-pass gap and skipN = round(wM \/ medianGap).\n  \/\/ 3. Pick every skipN-th pass as a \"kept\" pass; group up-to-\u00b1skipN\/2 neighbours with it.\n  \/\/ 4. For each wide-pass group: pick the kept pass's centroid + direction as the reference\n  \/\/    line, project every group polygon's centroid onto that line to get along-position.\n  \/\/ 5. Sort polygons within the group by along-position, append to newOrder.\n  \/\/ 6. Track which entries are on the kept (central) pass \u2014 used later to compute the\n  \/\/    sprite path (only the kept centroids contribute, so the sprite stays on the\n  \/\/    wide-pass centerline rather than zigzagging across the boom).\n  \/\/\n  \/\/ Returns { order, isCentral, boundaries } or null if no reordering needed.\n  function buildWidePassOrder(originalOrder, bnd, wM){\n    if(!bnd ? true : !originalOrder) return null;\n    if(!wM ? true : wM < 2) return null;\n    var passStarts = [0];\n    for(var bi=1; bi<bnd.length; bi++){\n      if(bnd[bi]) passStarts.push(bi);\n    }\n    if(passStarts.length < 3) return null;\n    var nPasses = passStarts.length;\n    var passEnds = passStarts.slice(1);\n    passEnds.push(originalOrder.length);\n    var cosLat = Math.cos(latC * Math.PI \/ 180);\n    \/\/ Median inter-pass gap\n    var gaps = [];\n    for(var p=1; p<nPasses; p++){\n      var a = originalOrder[passStarts[p-1]], b = originalOrder[passStarts[p]];\n      var dxG = featCx(b) - featCx(a), dyG = featCy(b) - featCy(a);\n      gaps.push(Math.sqrt(dxG*dxG + dyG*dyG) * cosLat);\n    }\n    gaps.sort(function(a,b){return a-b;});\n    var medGap = gaps[Math.floor(gaps.length \/ 2)];\n    if(medGap <= 0.5) return null;\n    \/\/ Fire filtering whenever the chosen equipment is meaningfully wider than the data's\n    \/\/ actual pass spacing \u2014 ratio > 1.3 is the trigger. Use round() but force minimum\n    \/\/ skipN = 2 once the trigger fires. This way a 12 m harvester chosen for 9 m data\n    \/\/ (ratio 1.33) skips every other pass, matching what a real 12 m machine would have\n    \/\/ driven. Below 1.3\u00d7 the equipment matches the data \u2014 no filtering needed.\n    var ratio = wM \/ medGap;\n    if(ratio <= 1.3) return null;\n    var skipN = Math.round(ratio);\n    if(skipN < 2) skipN = 2;\n    if(skipN > nPasses - 1) skipN = nPasses - 1;\n    \/\/ Pre-compute each pass's centroid + direction (using first\u2192last centroid).\n    var passCx = new Float32Array(nPasses);\n    var passCy = new Float32Array(nPasses);\n    var passDx = new Float32Array(nPasses);\n    var passDy = new Float32Array(nPasses);\n    for(var pi=0; pi<nPasses; pi++){\n      var s = passStarts[pi], e = passEnds[pi];\n      var sumX = 0, sumY = 0, cnt = 0;\n      for(var k=s; k<e; k++){\n        sumX += featCx(originalOrder[k]); sumY += featCy(originalOrder[k]); cnt++;\n      }\n      passCx[pi] = cnt > 0 ? sumX \/ cnt : 0;\n      passCy[pi] = cnt > 0 ? sumY \/ cnt : 0;\n      if(e - s >= 2){\n        var f0 = originalOrder[s], f1 = originalOrder[e-1];\n        var dxx = featCx(f1) - featCx(f0), dyy = featCy(f1) - featCy(f0);\n        var ll = Math.sqrt(dxx*dxx + dyy*dyy);\n        if(ll > 0.0001){ passDx[pi] = dxx \/ ll; passDy[pi] = dyy \/ ll; }\n        else { passDx[pi] = 1; passDy[pi] = 0; }\n      } else {\n        passDx[pi] = 1; passDy[pi] = 0;\n      }\n    }\n    \/\/ Kept passes sit in the MIDDLE of each wide-pass group \u2014 offset = floor(skipN\/2). With\n    \/\/ the kept pass centred, the implement coverage extends \u00b1wM\/2 evenly into BOTH sides,\n    \/\/ matching the user's \"buffer of \u00bd equipment width\" rule. The earlier offset-0 placement\n    \/\/ put kept at the edge of each group, leaving half the implement covering nothing.\n    var midOffset = Math.floor(skipN \/ 2);\n    var keptPasses = [];\n    for(var ki=midOffset; ki<nPasses; ki+=skipN){\n      keptPasses.push(ki);\n    }\n    if(keptPasses.length === 0) keptPasses.push(0);\n    \/\/ Assign each pass to its nearest kept pass (by perpendicular position index).\n    var nGroups = keptPasses.length;\n    var passGroup = new Int16Array(nPasses);\n    for(var pj=0; pj<nPasses; pj++){\n      var nearest = 0, nearestD = Math.abs(pj - keptPasses[0]);\n      for(var ku=1; ku<keptPasses.length; ku++){\n        var d = Math.abs(pj - keptPasses[ku]);\n        if(d < nearestD){ nearestD = d; nearest = ku; }\n      }\n      passGroup[pj] = nearest;\n    }\n    var keptPassIdx = new Int16Array(nGroups);\n    for(var gg=0; gg<nGroups; gg++) keptPassIdx[gg] = keptPasses[gg];\n    \/\/ Build new order: walk groups in sequence, polygons sorted by along-position relative\n    \/\/ to the kept pass's direction + centroid.\n    var newOrder = new Array(originalOrder.length);\n    var isCentral = new Uint8Array(originalOrder.length);\n    var writePos = 0;\n    var newBoundaries = new Uint8Array(originalOrder.length);\n    for(var gh=0; gh<nGroups; gh++){\n      var kPi = keptPassIdx[gh];\n      var kCx = passCx[kPi], kCy = passCy[kPi];\n      var kDx = passDx[kPi], kDy = passDy[kPi];\n      \/\/ Collect all polygons whose pass is in this group\n      var items = [];\n      for(var pp=0; pp<nPasses; pp++){\n        if(passGroup[pp] !== gh) continue;\n        for(var kk=passStarts[pp]; kk<passEnds[pp]; kk++){\n          var f = originalOrder[kk];\n          var dxA = featCx(f) - kCx, dyA = featCy(f) - kCy;\n          var along = dxA * kDx + dyA * kDy;\n          items.push({ feat: f, along: along, central: pp === kPi });\n        }\n      }\n      items.sort(function(a,b){ return a.along - b.along; });\n      if(gh > 0 ? items.length > 0 : false) newBoundaries[writePos] = 1;\n      for(var ii=0; ii<items.length; ii++){\n        newOrder[writePos] = items[ii].feat;\n        isCentral[writePos] = items[ii].central ? 1 : 0;\n        writePos++;\n      }\n    }\n    return { order: newOrder, isCentral: isCentral, boundaries: newBoundaries, skipN: skipN };\n  }\n  \/\/ Equipment-width-driven pass-keep mask. When the chosen implement is significantly wider\n  \/\/ than the data spacing, the trail \/ swath stroke breaks at non-kept passes \u2014 visualises\n  \/\/ fewer \/ wider-spaced lines matching what THIS equipment would have driven. Returns\n  \/\/ { mask, skipN } or null when filtering isn't needed.\n  \/\/ Polygons themselves render in normal playback order (one per centroid) so the sprite\n  \/\/ stays aligned with the geometry being revealed.\n  function computePassKeptMaskWithMeta(bnd, wM){\n    if(!bnd ? true : !playback.order) return null;\n    if(!wM ? true : wM < 2) return null;\n    var passStarts = [0];\n    for(var bi=1; bi<bnd.length; bi++){\n      if(bnd[bi]) passStarts.push(bi);\n    }\n    if(passStarts.length < 3) return null;\n    var cosLat = Math.cos(latC * Math.PI \/ 180);\n    var gaps = [];\n    for(var p=1; p<passStarts.length; p++){\n      var a = playback.order[passStarts[p-1]], b = playback.order[passStarts[p]];\n      var dxG = featCx(b) - featCx(a), dyG = featCy(b) - featCy(a);\n      gaps.push(Math.sqrt(dxG*dxG + dyG*dyG) * cosLat);\n    }\n    gaps.sort(function(a,b){ return a-b; });\n    var medGap = gaps[Math.floor(gaps.length \/ 2)];\n    if(medGap <= 0.5) return null;\n    var ratio = wM \/ medGap;\n    if(ratio <= 1.3) return null;\n    var skipN = Math.round(ratio);\n    if(skipN < 2) skipN = 2;\n    if(skipN > passStarts.length - 1) skipN = passStarts.length - 1;\n    \/\/ Kept passes are centred within each skipN-wide group so the implement coverage\n    \/\/ extends \u00b1wM\/2 symmetrically.\n    var midOffset = Math.floor(skipN \/ 2);\n    var nTot = playback.order.length;\n    var mask = new Uint8Array(nTot);\n    for(var p2=0; p2<passStarts.length; p2++){\n      if(((p2 - midOffset) % skipN + skipN) % skipN !== 0) continue;\n      var startK = passStarts[p2];\n      var endK = p2 + 1 < passStarts.length ? passStarts[p2 + 1] : nTot;\n      for(var k=startK; k<endK; k++) mask[k] = 1;\n    }\n    return { mask: mask, skipN: skipN };\n  }\n  \/\/ Build per-feature MACHINE CENTERLINE coordinates for multi-section data. Trimble (and\n  \/\/ other multi-section equipment) writes one polygon per active section per recording\n  \/\/ moment \u2014 the machine itself is at a SINGLE point, but the data lists section centroids\n  \/\/ spread across the boom width. For boundary detection AND path computation, we want the\n  \/\/ machine position (group centroid), not the section centroids \u2014 otherwise consecutive\n  \/\/ entries in playback.order zigzag across the boom and confuse everything.\n  \/\/\n  \/\/ Two detection strategies, in order:\n  \/\/   1. Timestamp grouping: features with identical DateClosed\/Time\/etc. = one moment.\n  \/\/   2. Spatial grouping (fallback, no timestamps): consecutive entries in playback.order\n  \/\/      within ~2 m of each other = sections of the same moment. Empirically robust \u2014\n  \/\/      machine forward step is typically > 2 m, section-to-section spacing < 2 m.\n  \/\/\n  \/\/ Returns { x, y } over playback.order indices, or null if the file isn't multi-section.\n  function computeMachineCenterline(){\n    if(!features ? true : !features.length) return null;\n    if(!playback.order) return null;\n    var nOrd = playback.order.length;\n    var nFeat = features.length;\n    \/\/ === Strategy 1: timestamp grouping ===\n    var p0 = features[0].properties;\n    var dateKey = null;\n    if(p0){\n      var keys = ['DateClosed','Date','date','TIMESTAMP','timestamp','Time_GMT','RecordTime','Time'];\n      for(var ki=0; ki<keys.length; ki++){\n        if(p0[keys[ki]] !== undefined){ dateKey = keys[ki]; break; }\n      }\n    }\n    if(dateKey){\n      var groups = {};\n      for(var i=0; i<nFeat; i++){\n        var v = features[i].properties ? features[i].properties[dateKey] : null;\n        if(v === undefined ? true : v === null) continue;\n        var key = String(v);\n        if(!groups[key]) groups[key] = { sumX: 0, sumY: 0, cnt: 0 };\n        var fcx = featCx(i), fcy = featCy(i);\n        if(!isFinite(fcx) ? true : !isFinite(fcy)) continue;\n        groups[key].sumX += fcx;\n        groups[key].sumY += fcy;\n        groups[key].cnt += 1;\n      }\n      var multiCount = 0;\n      for(var gk in groups){ if(groups[gk].cnt > 1) multiCount++; }\n      if(multiCount >= 3){\n        var groupCx = new Float32Array(nFeat);\n        var groupCy = new Float32Array(nFeat);\n        for(var f=0; f<nFeat; f++){\n          var ft = features[f].properties ? features[f].properties[dateKey] : null;\n          if(ft === undefined ? true : ft === null){\n            groupCx[f] = featCx(f); groupCy[f] = featCy(f); continue;\n          }\n          var gk2 = String(ft);\n          var g = groups[gk2];\n          if(g ? g.cnt > 0 : false){\n            groupCx[f] = g.sumX \/ g.cnt;\n            groupCy[f] = g.sumY \/ g.cnt;\n          } else {\n            groupCx[f] = featCx(f); groupCy[f] = featCy(f);\n          }\n        }\n        var ordX = new Float32Array(nOrd);\n        var ordY = new Float32Array(nOrd);\n        for(var k=0; k<nOrd; k++){\n          var ix = playback.order[k];\n          ordX[k] = groupCx[ix];\n          ordY[k] = groupCy[ix];\n        }\n        return { x: ordX, y: ordY };\n      }\n    }\n    \/\/ === Strategy 2: spatial grouping (no timestamps, or timestamps too unique) ===\n    \/\/ Fixed 2 m threshold per the user's empirical rule (\"if it's just 1\u20132 m it's a\n    \/\/ section\"). Anything \u2264 2 m apart is the same moment, anything more is a new moment.\n    \/\/ After grouping, we validate the result with a SPREAD CHECK: each group's polygons\n    \/\/ must be tightly clustered (max member distance from centroid < equipment width \/ 2).\n    \/\/ If a \"group\" spans an entire pass (centroids spread over tens of metres), we're\n    \/\/ looking at single-section data and the grouping should be discarded.\n    var cosLat = Math.cos(latC * Math.PI \/ 180);\n    var THRESH = 2.0;\n    var threshMerc = THRESH \/ cosLat;\n    var threshSq = threshMerc * threshMerc;\n    \/\/ Pre-compute per-order positions\n    var posX = new Float32Array(nOrd);\n    var posY = new Float32Array(nOrd);\n    for(var oi=0; oi<nOrd; oi++){\n      var fi = playback.order[oi];\n      posX[oi] = featCx(fi);\n      posY[oi] = featCy(fi);\n    }\n    \/\/ Group: each entry joins the previous group if within THRESH; otherwise starts a new group.\n    var groupId = new Int32Array(nOrd);\n    var groupSumX = [posX[0]];\n    var groupSumY = [posY[0]];\n    var groupCnt = [1];\n    groupId[0] = 0;\n    var lastGroupStartX = posX[0], lastGroupStartY = posY[0];\n    for(var w=1; w<nOrd; w++){\n      var ddx = posX[w] - lastGroupStartX, ddy = posY[w] - lastGroupStartY;\n      var d2 = ddx*ddx + ddy*ddy;\n      if(d2 <= threshSq){\n        var gi = groupId[w-1];\n        groupId[w] = gi;\n        groupSumX[gi] += posX[w];\n        groupSumY[gi] += posY[w];\n        groupCnt[gi] += 1;\n      } else {\n        var newId = groupSumX.length;\n        groupId[w] = newId;\n        groupSumX.push(posX[w]);\n        groupSumY.push(posY[w]);\n        groupCnt.push(1);\n        lastGroupStartX = posX[w];\n        lastGroupStartY = posY[w];\n      }\n    }\n    \/\/ Validity checks:\n    \/\/   A) At least 70% of groups must have > 1 member. True multi-section data has\n    \/\/      ALL groups multi-member (each moment fires N sections); spurious single-\n    \/\/      section grouping has many 1-member groups.\n    \/\/   B) Median group SPREAD (max distance of any member from group centroid) must be\n    \/\/      \u2264 equipment_width \u00d7 0.6. True moments cluster within the boom; a pass-as-group\n    \/\/      (single-section data with a too-loose threshold) spreads tens of metres along\n    \/\/      the row direction.\n    var totalGrp = groupCnt.length;\n    if(totalGrp < 3) return null;\n    var multiMember = 0;\n    for(var gx=0; gx<totalGrp; gx++){ if(groupCnt[gx] > 1) multiMember++; }\n    if(multiMember \/ totalGrp < 0.7) return null;\n    \/\/ Compute group centroids for the spread check\n    var spreads = [];\n    var tempCx = new Float32Array(totalGrp);\n    var tempCy = new Float32Array(totalGrp);\n    for(var gv=0; gv<totalGrp; gv++){\n      tempCx[gv] = groupSumX[gv] \/ groupCnt[gv];\n      tempCy[gv] = groupSumY[gv] \/ groupCnt[gv];\n    }\n    for(var ws=0; ws<nOrd; ws++){\n      var gI2 = groupId[ws];\n      var dxS = (posX[ws] - tempCx[gI2]) * cosLat;\n      var dyS = (posY[ws] - tempCy[gI2]) * cosLat;\n      var spreadM = Math.sqrt(dxS*dxS + dyS*dyS);\n      spreads.push(spreadM);\n    }\n    spreads.sort(function(a,b){ return a - b; });\n    var medSpread = spreads[Math.floor(spreads.length \/ 2)];\n    var wMguess = equipmentWidthM(playback.opLabel);\n    if(medSpread > wMguess * 0.6){\n      try { console.warn('[GPY] machine-centerline: rejected \u2014 median group spread '+medSpread.toFixed(1)+' m > '+(wMguess*0.6).toFixed(1)+' m (not multi-section)'); } catch(_){}\n      return null;\n    }\n    try { console.warn('[GPY] machine-centerline: '+totalGrp+' groups, '+multiMember+' multi-member, median spread '+medSpread.toFixed(2)+' m'); } catch(_){}\n    \/\/ Build final order-mapped centerline arrays. Each entry takes its group's centroid\n    \/\/ EXACTLY (no within-group interpolation). The sprite \"stays in place\" for the N polygons\n    \/\/ of one moment, then jumps to the next moment's centroid. Less smooth visually, but\n    \/\/ mathematically clean \u2014 no spurious motion artefacts from interpolation.\n    var sOrdX = new Float32Array(nOrd);\n    var sOrdY = new Float32Array(nOrd);\n    var grpCenterX = new Float32Array(groupCnt.length);\n    var grpCenterY = new Float32Array(groupCnt.length);\n    for(var gc=0; gc<groupCnt.length; gc++){\n      grpCenterX[gc] = groupSumX[gc] \/ groupCnt[gc];\n      grpCenterY[gc] = groupSumY[gc] \/ groupCnt[gc];\n    }\n    for(var z=0; z<nOrd; z++){\n      sOrdX[z] = grpCenterX[groupId[z]];\n      sOrdY[z] = grpCenterY[groupId[z]];\n    }\n    return { x: sOrdX, y: sOrdY };\n  }\n  \/\/ Detect implement width from LINE GEOMETRY. For boustrophedon-style guidance files,\n  \/\/ adjacent parallel passes are spaced \u2248 equipment width apart. Algorithm:\n  \/\/   1. Build a unit direction vector for each line (start \u2192 end).\n  \/\/   2. Find the dominant pass direction by taking the median angle mod \u03c0 (handles forward\/\n  \/\/      reverse alternation \u2014 both directions count as the same axis).\n  \/\/   3. Project each line's midpoint onto the perpendicular axis.\n  \/\/   4. Sort projections, compute gaps between adjacent ones, drop near-zero gaps (the\n  \/\/      \"return pass\" on the same line back to start often has midpoint \u2248 same).\n  \/\/   5. Take the median of the smallest 1\/3 of remaining gaps \u2014 that's the pass spacing.\n  \/\/   6. Convert mercator-meters to real meters via cos(latC).\n  \/\/ Returns null if input isn't suitable (non-line mode, < 3 lines, ambiguous).\n  function detectLineWidth(){\n    if(mode !== 'line') return null;\n    if(!polyData ? true : polyData.length < 3) return null;\n    var dirs = [];\n    var midX = [], midY = [];\n    for(var i=0; i<polyData.length; i++){\n      var feat = polyData[i];\n      if(!feat ? true : !feat.rings ? true : !feat.rings.length) continue;\n      var ring = feat.rings[0];\n      var nv = ring.mx.length;\n      if(nv < 2) continue;\n      var dx = ring.mx[nv - 1] - ring.mx[0];\n      var dy = ring.my[nv - 1] - ring.my[0];\n      var len = Math.sqrt(dx*dx + dy*dy);\n      if(len < 0.001) continue;\n      dirs.push([dx\/len, dy\/len]);\n      midX.push(feat.cx);\n      midY.push(feat.cy);\n    }\n    if(midX.length < 3) return null;\n    \/\/ Median direction angle, modulo \u03c0 (forward = backward, same axis).\n    var angs = [];\n    for(var d=0; d<dirs.length; d++){\n      var ang = Math.atan2(dirs[d][1], dirs[d][0]);\n      if(ang < 0) ang += Math.PI;\n      if(ang >= Math.PI) ang -= Math.PI;\n      angs.push(ang);\n    }\n    angs.sort(function(a,b){ return a - b; });\n    var medAng = angs[Math.floor(angs.length \/ 2)];\n    var perpX = -Math.sin(medAng);\n    var perpY = Math.cos(medAng);\n    \/\/ Project each midpoint onto perpendicular axis.\n    var projs = new Array(midX.length);\n    for(var m=0; m<midX.length; m++){\n      projs[m] = midX[m] * perpX + midY[m] * perpY;\n    }\n    projs.sort(function(a,b){ return a - b; });\n    \/\/ Adjacent gaps. Filter out near-zero gaps (return-pass pairs on the same line).\n    var gaps = [];\n    for(var s=1; s<projs.length; s++){\n      var g = projs[s] - projs[s-1];\n      if(g > 0.5) gaps.push(g);  \/\/ > 0.5 mercator-meters perpendicular spread\n    }\n    if(gaps.length < 2) return null;\n    gaps.sort(function(a,b){ return a - b; });\n    \/\/ Smallest 1\/3 of gaps = the genuinely-adjacent pass-to-pass distances; larger gaps\n    \/\/ span multiple skipped passes (or field-edge artefacts).\n    var third = Math.max(1, Math.floor(gaps.length \/ 3));\n    var smallGaps = gaps.slice(0, third);\n    var medGap = smallGaps[Math.floor(smallGaps.length \/ 2)];\n    var realM = medGap * Math.cos(latC * Math.PI \/ 180);\n    if(realM < 1 ? true : realM > 200) return null;\n    return realM;\n  }\n  \/\/ Look for an explicit swath \/ implement width FIELD attribute on the features. Trimble\n  \/\/ Coverage shapefiles (Swth_Wdth_), JD Operations Center exports, ISOXML DLV records,\n  \/\/ and many other formats embed the working width directly. When present this is the\n  \/\/ most reliable signal \u2014 it's what the operator\/equipment recorded.\n  \/\/ Returns the median value converted to real meters, or null if no usable field is found.\n  function detectWidthFromAttributes(){\n    if(!features ? true : !features.length) return null;\n    var p0 = features[0].properties;\n    if(!p0) return null;\n    \/\/ Candidate field names (case-insensitive). Order: most-specific first.\n    var keys = ['Swth_Wdth_', 'SwathWidth', 'Swath_Width', 'swath_width', 'SWATH_WIDTH',\n                'WorkingWidth', 'Working_Width', 'working_width', 'WORKING_WIDTH',\n                'BoomWidth', 'Boom_Width', 'boom_width',\n                'EquipmentWidth', 'Equipment_Width', 'ImplementWidth', 'Implement_Width',\n                'Width_m', 'WidthM', 'width_m', 'widthM', 'Cell_Width', 'CellWidth'];\n    var allKeys = {};\n    for(var pk in p0) allKeys[pk.toLowerCase()] = pk;\n    var foundKey = null;\n    for(var ki=0; ki<keys.length; ki++){\n      var k = keys[ki];\n      if(p0[k] !== undefined){ foundKey = k; break; }\n      var lc = allKeys[k.toLowerCase()];\n      if(lc ? p0[lc] !== undefined : false){ foundKey = lc; break; }\n    }\n    if(!foundKey) return null;\n    var vals = [];\n    for(var i=0; i<features.length; i++){\n      var v = features[i].properties ? features[i].properties[foundKey] : null;\n      if(typeof v === 'number' ? isFinite(v) : false){ if(v > 0) vals.push(v); }\n    }\n    if(vals.length < 5) return null;\n    vals.sort(function(a,b){ return a - b; });\n    var raw = vals[Math.floor(vals.length \/ 2)];\n    \/\/ Unit guess. Trimble Swth_Wdth_ is almost always FEET. Other fields are usually meters\n    \/\/ when named *Width_m \/ *WidthM, otherwise we pick the conversion that lands in the\n    \/\/ realistic implement-width range [3, 50] m. If both meters and feet conversions are\n    \/\/ valid, prefer feet for keys that look like the Trimble convention.\n    var asM = raw;\n    var asFt = raw * 0.3048;\n    var asIn = raw * 0.0254;\n    function inRange(v){ return v >= 3 ? v <= 50 : false; }\n    var keyLow = foundKey.toLowerCase();\n    var prefFeet = \/sw(a|t)th\/.test(keyLow);\n    var prefMeters = \/_m$|widthm$\/.test(keyLow);\n    if(prefMeters ? inRange(asM) : false) return asM;\n    if(prefFeet ? inRange(asFt) : false) return asFt;\n    if(inRange(asM)) return asM;\n    if(inRange(asFt)) return asFt;\n    if(inRange(asIn)) return asIn;\n    return null;\n  }\n  \/\/ Count how many polygons share a single machine moment. For Trimble multi-section\n  \/\/ data: same DateClosed \/ TIMESTAMP yields N polygons (N = active sections). For\n  \/\/ rate grids: N = 1 (one polygon per cell, no temporal sharing). Returns the median\n  \/\/ count across moments \u2014 robust to occasional missing sections.\n  function detectSectionsPerMoment(){\n    if(!features ? true : features.length < 5) return 1;\n    if(mode !== 'polygon') return 1;\n    var p0 = features[0].properties;\n    if(!p0) return 1;\n    var keys = ['DateClosed','Date','date','TIMESTAMP','timestamp','Time_GMT','RecordTime','Time'];\n    var dateKey = null;\n    for(var ki=0; ki<keys.length; ki++){\n      if(p0[keys[ki]] !== undefined){ dateKey = keys[ki]; break; }\n    }\n    if(!dateKey) return 1;\n    var counts = {};\n    for(var i=0; i<features.length; i++){\n      var v = features[i].properties ? features[i].properties[dateKey] : null;\n      if(v === undefined ? true : v === null) continue;\n      var k = String(v);\n      counts[k] = (counts[k] ? counts[k] : 0) + 1;\n    }\n    var arr = [];\n    for(var ck in counts) arr.push(counts[ck]);\n    if(arr.length === 0) return 1;\n    arr.sort(function(a, b){ return a - b; });\n    return arr[arr.length >> 1];\n  }\n  \/\/ Equipment width from polygon pixel dimensions. For multi-section data each polygon\n  \/\/ is one section coverage (~75 cm wide \u00d7 ~3 m long); wM = median thin-dim \u00d7 N sections.\n  \/\/ For rate-grid data (one polygon per location) wM = median polygon width along the\n  \/\/ dominant axis-perpendicular direction. Returns 0 when the dataset is not polygon-\n  \/\/ based or polyData isn't ready. Per user rule \"eq width should be calculated from\n  \/\/ pixels\" \u2014 promoted in setupPlayback's width chain above multi-section \/ line-spacing\n  \/\/ detection (only file-attribute, sibling AB line, and manual override can win).\n  function detectImplementWidthFromPolygonPixels(){\n    if(mode !== 'polygon') return 0;\n    if(!polyData ? true : polyData.length < 5) return 0;\n    var cosLat = Math.cos((typeof latC === 'number' ? latC : 0) * Math.PI \/ 180);\n    if(!(cosLat > 0)) cosLat = 1;\n    var nSections = detectSectionsPerMoment();\n    var widths = [];\n    for(var i=0; i<polyData.length; i++){\n      var pd = polyData[i];\n      if(!pd) continue;\n      var w = pd.maxX - pd.minX;\n      var h = pd.maxY - pd.minY;\n      if(w > 0 ? h > 0 : false){\n        \/\/ Use the THIN dimension in mercator units; convert to real meters via cosLat.\n        var thinMerc = w < h ? w : h;\n        widths.push(thinMerc * cosLat);\n      }\n    }\n    if(widths.length === 0) return 0;\n    widths.sort(function(a, b){ return a - b; });\n    var medThin = widths[widths.length >> 1];\n    if(nSections >= 3){\n      \/\/ Section polygons: wM = section width \u00d7 N sections (boom span).\n      return medThin * nSections;\n    }\n    \/\/ Rate-grid \/ single-section: use the median LONG dimension as wM, which for\n    \/\/ axis-aligned rectangles is the row spacing.\n    var widthsLong = [];\n    for(var j=0; j<polyData.length; j++){\n      var pd2 = polyData[j];\n      if(!pd2) continue;\n      var w2 = pd2.maxX - pd2.minX;\n      var h2 = pd2.maxY - pd2.minY;\n      if(w2 > 0 ? h2 > 0 : false){\n        var longMerc = w2 > h2 ? w2 : h2;\n        widthsLong.push(longMerc * cosLat);\n      }\n    }\n    if(widthsLong.length === 0) return 0;\n    widthsLong.sort(function(a, b){ return a - b; });\n    return widthsLong[widthsLong.length >> 1];\n  }\n  \/\/ Detect the actual implement width from the data, not the OP_WIDTH_M table value.\n  \/\/ Multi-section equipment (fertilizer spreaders, planters, sprayers) writes one polygon\n  \/\/ per active section per recording moment. The polygons of one moment span the full\n  \/\/ implement width perpendicular to motion. By grouping features by timestamp and\n  \/\/ measuring the bbox span of each group, we recover the REAL implement width \u2014 which\n  \/\/ matters for the sprite, swath rendering, and the half-width \"doesn't touch previous\n  \/\/ pass\" rule. Returns null if no usable timestamp groups exist.\n  function detectImplementWidth(){\n    if(!features || !features.length) return null;\n    var p0 = features[0].properties;\n    if(!p0) return null;\n    var keys = ['DateClosed','Date','date','TIMESTAMP','timestamp','Time_GMT','RecordTime','Time'];\n    var dateKey = null;\n    for(var ki=0; ki<keys.length; ki++){\n      if(p0[keys[ki]] !== undefined){ dateKey = keys[ki]; break; }\n    }\n    if(!dateKey) return null;\n    var byTs = {};\n    for(var i=0; i<features.length; i++){\n      var v = features[i].properties ? features[i].properties[dateKey] : null;\n      if(v === undefined ? true : v === null) continue;\n      var key = String(v);\n      if(!byTs[key]) byTs[key] = [];\n      byTs[key].push(i);\n    }\n    var widths = [];\n    for(var t in byTs){\n      var ids = byTs[t];\n      if(ids.length < 2) continue;\n      var minX = Infinity, maxX = -Infinity, minY = Infinity, maxY = -Infinity;\n      for(var j=0; j<ids.length; j++){\n        var cxV, cyV;\n        if(polyData ? polyData[ids[j]] : false){\n          cxV = polyData[ids[j]].cx; cyV = polyData[ids[j]].cy;\n        } else if(mx ? mx.length > ids[j] : false){\n          cxV = mx[ids[j]]; cyV = my[ids[j]];\n        } else continue;\n        if(cxV < minX) minX = cxV;\n        if(cxV > maxX) maxX = cxV;\n        if(cyV < minY) minY = cyV;\n        if(cyV > maxY) maxY = cyV;\n      }\n      if(!isFinite(minX)) continue;\n      var dx = maxX - minX, dy = maxY - minY;\n      var span = Math.sqrt(dx*dx + dy*dy);\n      \/\/ Convert mercator-meters to real meters at field latitude\n      var realSpan = span * Math.cos(latC * Math.PI \/ 180);\n      if(realSpan > 1) widths.push(realSpan);\n    }\n    if(widths.length < 3) return null;  \/\/ need at least 3 groups for a stable median\n    widths.sort(function(a,b){ return a - b; });\n    return widths[Math.floor(widths.length \/ 2)];\n  }\n  \/\/ Estimate the typical inter-pass gap (perpendicular distance between consecutive pass\n  \/\/ centerlines) and return min(equipment width, gap \u00d7 0.95). Used to render swath bands at\n  \/\/ their UNIQUE COVERAGE WIDTH so adjacent passes appear side-by-side rather than stacked.\n  \/\/ Falls back to the full equipment width if no boundaries were detected (single pass \/ line\n  \/\/ data) \u2014 in that case there's no \"previous pass\" to overlap with.\n  function computeEffectiveSwath(wM){\n    \/\/ Line mode: pass spacing comes from the detected line-geometry width (or wM directly\n    \/\/ if detection didn't fire). Adjacent line swath strokes must NOT intersect \u2014 clamp\n    \/\/ eff to detected spacing \u00d7 0.95.\n    if(mode === 'line'){\n      var lineSp = detectLineWidth();\n      var lineRef = lineSp ? lineSp : wM;\n      var effL = lineRef * 0.95;\n      if(effL > wM) effL = wM;\n      if(effL < wM * 0.25) effL = wM * 0.25;\n      return effL;\n    }\n    var bnd = playback.boundaries;\n    if(!bnd) return wM;\n    var gaps = [];\n    for(var i = 1; i < bnd.length; i++){\n      if(!bnd[i]) continue;\n      var dx = pathCx(i) - pathCx(i - 1);\n      var dy = pathCy(i) - pathCy(i - 1);\n      var g = Math.sqrt(dx * dx + dy * dy);\n      if(g > 0.5) gaps.push(g);  \/\/ ignore noise-level gaps\n    }\n    if(!gaps.length) return wM;\n    gaps.sort(function(a, b){ return a - b; });\n    var medianGap = gaps[Math.floor(gaps.length \/ 2)];\n    var eff = medianGap * 0.95;\n    if(eff > wM) eff = wM;\n    if(eff < wM * 0.25) eff = wM * 0.25;  \/\/ floor so the sprite is still visible\n    return eff;\n  }\n  \/\/ Convex hull via Andrew's monotone chain. Input: parallel arrays xs[], ys[].\n  \/\/ Returns {x: Float32Array, y: Float32Array} of the hull ring (closed:\n  \/\/ first point repeated as last). Returns null if < 3 distinct points.\n  function convexHullXY(xs, ys){\n    var n = xs.length;\n    if(n < 3) return null;\n    var idx = new Array(n);\n    for(var i=0; i<n; i++) idx[i] = i;\n    idx.sort(function(a, b){\n      if(xs[a] !== xs[b]) return xs[a] - xs[b];\n      return ys[a] - ys[b];\n    });\n    function cross(o, a, b){\n      return (xs[a] - xs[o]) * (ys[b] - ys[o]) - (ys[a] - ys[o]) * (xs[b] - xs[o]);\n    }\n    var lower = [];\n    for(var k=0; k<n; k++){\n      var p = idx[k];\n      while(lower.length >= 2 ? cross(lower[lower.length-2], lower[lower.length-1], p) <= 0 : false){\n        lower.pop();\n      }\n      lower.push(p);\n    }\n    var upper = [];\n    for(var k2=n-1; k2>=0; k2--){\n      var p2 = idx[k2];\n      while(upper.length >= 2 ? cross(upper[upper.length-2], upper[upper.length-1], p2) <= 0 : false){\n        upper.pop();\n      }\n      upper.push(p2);\n    }\n    var ring = lower.concat(upper.slice(1, upper.length - 1));\n    if(ring.length < 3) return null;\n    var outX = new Float32Array(ring.length + 1);\n    var outY = new Float32Array(ring.length + 1);\n    for(var rI=0; rI<ring.length; rI++){\n      outX[rI] = xs[ring[rI]];\n      outY[rI] = ys[ring[rI]];\n    }\n    outX[ring.length] = outX[0];\n    outY[ring.length] = outY[0];\n    return { x: outX, y: outY };\n  }\n  \/\/ Expand a closed ring outward by bufferMerc. Each vertex moves along the\n  \/\/ bisector of its two adjacent outward edge-normals so the buffer is uniform\n  \/\/ along straight edges. Used for point-mode field hulls \u2014 soil sample grids\n  \/\/ don't cover the full field, so we push the hull outward by ~\u00bd sample\n  \/\/ spacing to approximate the real boundary.\n  function bufferRingOutward(ring, bufferMerc){\n    if(!ring) return null;\n    var xs = ring.x, ys = ring.y;\n    var N = xs.length - 1; \/\/ closed: last == first\n    if(N < 3) return ring;\n    \/\/ Centroid \u2014 used to disambiguate outward direction.\n    var cxC = 0, cyC = 0;\n    for(var i=0; i<N; i++){ cxC += xs[i]; cyC += ys[i]; }\n    cxC \/= N; cyC \/= N;\n    var outX = new Float32Array(N + 1);\n    var outY = new Float32Array(N + 1);\n    for(var v=0; v<N; v++){\n      var prev = (v - 1 + N) % N;\n      var next = (v + 1) % N;\n      var dx1 = xs[v] - xs[prev], dy1 = ys[v] - ys[prev];\n      var dx2 = xs[next] - xs[v], dy2 = ys[next] - ys[v];\n      var l1 = Math.sqrt(dx1*dx1 + dy1*dy1), l2 = Math.sqrt(dx2*dx2 + dy2*dy2);\n      if(l1 > 0){ dx1 \/= l1; dy1 \/= l1; }\n      if(l2 > 0){ dx2 \/= l2; dy2 \/= l2; }\n      \/\/ Edge normals (right-hand of edge direction). Flip if they point INWARD.\n      var n1x = dy1, n1y = -dx1;\n      var n2x = dy2, n2y = -dx2;\n      var probe = (xs[v] + n1x) - cxC, probY = (ys[v] + n1y) - cyC;\n      var probe0x = xs[v] - cxC, probe0y = ys[v] - cyC;\n      if(probe*probe + probY*probY < probe0x*probe0x + probe0y*probe0y){\n        n1x = -n1x; n1y = -n1y; n2x = -n2x; n2y = -n2y;\n      }\n      \/\/ Bisector = unit-normal sum; magnitude = 2\u00b7cos(half exterior angle).\n      var bx = n1x + n2x, by = n1y + n2y;\n      var bl = Math.sqrt(bx*bx + by*by);\n      if(bl > 0){ bx \/= bl; by \/= bl; }\n      var cosHalf = bl * 0.5;\n      if(cosHalf < 0.3) cosHalf = 0.3; \/\/ cap so sharp corners don't fly off\n      var d = bufferMerc \/ cosHalf;\n      outX[v] = xs[v] + bx * d;\n      outY[v] = ys[v] + by * d;\n    }\n    outX[N] = outX[0];\n    outY[N] = outY[0];\n    return { x: outX, y: outY };\n  }\n  \/\/ Concave hull via convex-hull-edge-pullin. Returns a tighter ring than the\n  \/\/ convex hull when the dataset is non-convex (L\/C-shaped fields). Falls back\n  \/\/ to the convex hull when pullin cannot improve. `alphaM` controls how short\n  \/\/ edges must be before we stop subdividing \u2014 set to roughly the equipment\n  \/\/ width so the hull traces the worked area, not individual section polygons.\n  function concaveHullXY(xs, ys, alphaM, maxIterIn){\n    var convex = convexHullXY(xs, ys);\n    if(!convex) return null;\n    var nIn = xs.length;\n    if(nIn < 8) return convex;\n    \/\/ mercator unit -> real meter conversion: cos(latC*DEG). Same factor for X and Y\n    \/\/ because Web Mercator is conformal locally. latC is the field-centre latitude\n    \/\/ computed during dataset load (line 2772).\n    var cosLat = Math.cos((typeof latC === 'number' ? latC : 0) * Math.PI \/ 180);\n    if(!(cosLat > 0)) cosLat = 1;\n    var ring = [];\n    for(var rI=0; rI<convex.x.length - 1; rI++) ring.push([convex.x[rI], convex.y[rI]]);\n    \/\/ Many iterations + a tighter stop threshold (edges as short as alphaM still get\n    \/\/ subdivided if there's a nearby inner point) so the hull traces concavities\n    \/\/ closely instead of stopping at a smooth convex-ish outline. The bestDM <= 0.7\u00d7\n    \/\/ elenM gate accepts more \"off-midpoint\" inner points so curved concavities are\n    \/\/ resolved. maxIter is bumped by callers on dense point data (1k+ pts) where the\n    \/\/ default 24 stops short of resolving the full outline.\n    var maxIter = (typeof maxIterIn === 'number' ? maxIterIn : 24);\n    for(var it=0; it<maxIter; it++){\n      var improved = false;\n      for(var ei=0; ei<ring.length; ei++){\n        var a = ring[ei];\n        var b = ring[(ei + 1) % ring.length];\n        var ex = (b[0] - a[0]) * cosLat;\n        var ey = (b[1] - a[1]) * cosLat;\n        var elenM = Math.sqrt(ex*ex + ey*ey);\n        if(elenM <= alphaM) continue;\n        var midX = (a[0] + b[0]) * 0.5;\n        var midY = (a[1] + b[1]) * 0.5;\n        var bestK = -1, bestD = Infinity;\n        for(var k3=0; k3<nIn; k3++){\n          var dx = (xs[k3] - midX) * cosLat;\n          var dy = (ys[k3] - midY) * cosLat;\n          var dM = dx*dx + dy*dy;\n          if(dM < bestD){ bestD = dM; bestK = k3; }\n        }\n        if(bestK < 0) continue;\n        var bestDM = Math.sqrt(bestD);\n        if(bestDM > elenM * 0.7) continue;\n        ring.splice(ei + 1, 0, [xs[bestK], ys[bestK]]);\n        improved = true;\n        break;\n      }\n      if(!improved) break;\n    }\n    var outX = new Float32Array(ring.length + 1);\n    var outY = new Float32Array(ring.length + 1);\n    for(var oI=0; oI<ring.length; oI++){ outX[oI] = ring[oI][0]; outY[oI] = ring[oI][1]; }\n    outX[ring.length] = outX[0];\n    outY[ring.length] = outY[0];\n    return { x: outX, y: outY };\n  }\n  \/\/ Moreira-Santos k-nearest-neighbour concave hull. Produces a tight, smooth\n  \/\/ outline that hugs the data \u2014 matches the visual quality of QGIS's\n  \/\/ \"Concave hull (k-nearest neighbor)\" algorithm. Returns a closed ring\n  \/\/ `{x, y}` or null if the walk fails after escalating k.\n  \/\/\n  \/\/ Parameters:\n  \/\/   xsIn, ysIn \u2014 point arrays in mercator coords (relative to wmCx\/wmCy)\n  \/\/   cellM      \u2014 subsample cell size in real metres. Dense yield datasets are\n  \/\/                first decimated to \u2248 one point per cell so k-NN sees boundary-\n  \/\/                relevant candidates instead of in-pass clutter. Set \u2248 0.8 \u00d7 wM\n  \/\/                so the resulting outline traces row-by-row data without picking\n  \/\/                up section-level noise.\n  \/\/\n  \/\/ Algorithm:\n  \/\/   0. Subsample: bin points to cellM \u00d7 cellM cells; keep one representative per\n  \/\/      cell. Dense yield monitors emit ~1 point per 5 m; without this the k-NN\n  \/\/      walk gets trapped in tiny local clusters and closes back to start after\n  \/\/      3 hops (false closure).\n  \/\/   1. Start at the lowest-Y point (a guaranteed convex-hull vertex).\n  \/\/   2. Walk around the data, choosing the next point as the k-NN candidate that\n  \/\/      makes the sharpest right turn (clockwise angle from the previous direction).\n  \/\/   3. Skip candidates whose connecting segment would intersect the existing\n  \/\/      ring (prevents self-intersection).\n  \/\/   4. Require at least max(8, k\u00d72) hops before allowing return to start \u2014\n  \/\/      prevents premature closure in dense local clusters.\n  \/\/   5. After closing the ring, validate \u2265 95% of subsampled points are inside;\n  \/\/      if not, escalate k and retry.\n  \/\/   6. Escalate k up to kMax. Bail out (null) if no k produces a valid hull.\n  function concaveHullKnn(xsIn, ysIn, cellM){\n    var Nin = xsIn.length;\n    if(Nin < 3) return null;\n    if(cellM <= 0 ? true : !isFinite(cellM)) cellM = 10;\n    var cosLat = Math.cos((typeof latC === 'number' ? latC : 0) * Math.PI \/ 180);\n    if(!(cosLat > 0)) cosLat = 1;\n    var cellMerc = cellM \/ cosLat;\n    \/\/ Subsample: one representative point per cell (use the cell centroid for a\n    \/\/ smoother outline that doesn't pick up individual section-polygon noise).\n    var binMap = {};\n    var minXin = Infinity, minYin = Infinity;\n    for(var iIn=0; iIn<Nin; iIn++){\n      if(xsIn[iIn] < minXin) minXin = xsIn[iIn];\n      if(ysIn[iIn] < minYin) minYin = ysIn[iIn];\n    }\n    for(var iSub=0; iSub<Nin; iSub++){\n      var bgx = Math.floor((xsIn[iSub] - minXin) \/ cellMerc);\n      var bgy = Math.floor((ysIn[iSub] - minYin) \/ cellMerc);\n      var bKey = bgx + ',' + bgy;\n      var bucket = binMap[bKey];\n      if(!bucket){ bucket = { sx:0, sy:0, n:0 }; binMap[bKey] = bucket; }\n      bucket.sx += xsIn[iSub]; bucket.sy += ysIn[iSub]; bucket.n++;\n    }\n    var xs = [], ys = [];\n    for(var bk in binMap){\n      var b = binMap[bk];\n      xs.push(b.sx \/ b.n); ys.push(b.sy \/ b.n);\n    }\n    var N = xs.length;\n    if(N < 3) return null;\n    if(N === 3){\n      var out = new Float32Array(4);\n      var outY = new Float32Array(4);\n      out[0]=xs[0]; out[1]=xs[1]; out[2]=xs[2]; out[3]=xs[0];\n      outY[0]=ys[0]; outY[1]=ys[1]; outY[2]=ys[2]; outY[3]=ys[0];\n      return { x: out, y: outY };\n    }\n    \/\/ Spatial index \u2014 uniform grid sized so most cells hold a few points.\n    var minX = Infinity, maxX = -Infinity, minY = Infinity, maxY = -Infinity;\n    for(var iB=0; iB<N; iB++){\n      if(xs[iB] < minX) minX = xs[iB];\n      if(xs[iB] > maxX) maxX = xs[iB];\n      if(ys[iB] < minY) minY = ys[iB];\n      if(ys[iB] > maxY) maxY = ys[iB];\n    }\n    var W = maxX - minX, H = maxY - minY;\n    if(W <= 0 ? true : H <= 0) return null;\n    var targetPerCell = 6;\n    var totalCells = Math.max(16, Math.ceil(N \/ targetPerCell));\n    var aspect = W \/ H;\n    var gw = Math.max(2, Math.round(Math.sqrt(totalCells * aspect)));\n    var gh = Math.max(2, Math.round(totalCells \/ gw));\n    var cellW = W \/ gw;\n    var cellH = H \/ gh;\n    if(!(cellW > 0) ? true : !(cellH > 0)) return null;\n    function gxOf(x){ var g = Math.floor((x - minX) \/ cellW); if(g < 0) return 0; if(g >= gw) return gw-1; return g; }\n    function gyOf(y){ var g = Math.floor((y - minY) \/ cellH); if(g < 0) return 0; if(g >= gh) return gh-1; return g; }\n    var cells = new Array(gw * gh);\n    for(var ci=0; ci<gw*gh; ci++) cells[ci] = [];\n    for(var iP=0; iP<N; iP++){\n      cells[gyOf(ys[iP]) * gw + gxOf(xs[iP])].push(iP);\n    }\n    \/\/ Edge spatial index \u2014 track ring edges by which cells they pass through (just\n    \/\/ the bbox cells, sufficient for the intersection filter).\n    var edgeCells = new Array(gw * gh);\n    for(var ec=0; ec<gw*gh; ec++) edgeCells[ec] = [];\n    var edges = [];  \/\/ [[ax, ay, bx, by], ...]\n    function registerEdge(ax, ay, bx, by){\n      var ei = edges.length;\n      edges.push([ax, ay, bx, by]);\n      var gAx = gxOf(ax), gAy = gyOf(ay);\n      var gBx = gxOf(bx), gBy = gyOf(by);\n      var gxMin = gAx < gBx ? gAx : gBx;\n      var gxMax = gAx > gBx ? gAx : gBx;\n      var gyMin = gAy < gBy ? gAy : gBy;\n      var gyMax = gAy > gBy ? gAy : gBy;\n      for(var gyy=gyMin; gyy<=gyMax; gyy++){\n        for(var gxx=gxMin; gxx<=gxMax; gxx++){\n          edgeCells[gyy*gw + gxx].push(ei);\n        }\n      }\n    }\n    function segsIntersect(ax, ay, bx, by, cx, cy, dx, dy){\n      \/\/ Reject if shares an endpoint with the new segment (adjacent rings ok).\n      var eps = 1e-7 * (cellW + cellH);\n      if(Math.abs(ax-cx)<eps ? Math.abs(ay-cy)<eps : false) return false;\n      if(Math.abs(ax-dx)<eps ? Math.abs(ay-dy)<eps : false) return false;\n      if(Math.abs(bx-cx)<eps ? Math.abs(by-cy)<eps : false) return false;\n      if(Math.abs(bx-dx)<eps ? Math.abs(by-dy)<eps : false) return false;\n      var d = (dy-cy)*(bx-ax) - (dx-cx)*(by-ay);\n      if(Math.abs(d) < 1e-12) return false;\n      var ta = ((dx-cx)*(ay-cy) - (dy-cy)*(ax-cx)) \/ d;\n      var tb = ((bx-ax)*(ay-cy) - (by-ay)*(ax-cx)) \/ d;\n      return ta > 1e-9 ? (ta < 1-1e-9 ? (tb > 1e-9 ? tb < 1-1e-9 : false) : false) : false;\n    }\n    function segmentCrossesAnyEdge(ax, ay, bx, by){\n      var gAx = gxOf(ax), gAy = gyOf(ay);\n      var gBx = gxOf(bx), gBy = gyOf(by);\n      var gxMin = gAx < gBx ? gAx : gBx;\n      var gxMax = gAx > gBx ? gAx : gBx;\n      var gyMin = gAy < gBy ? gAy : gBy;\n      var gyMax = gAy > gBy ? gAy : gBy;\n      var checked = {};\n      for(var gyy=gyMin; gyy<=gyMax; gyy++){\n        for(var gxx=gxMin; gxx<=gxMax; gxx++){\n          var bucket = edgeCells[gyy*gw + gxx];\n          for(var bi=0; bi<bucket.length; bi++){\n            var eid = bucket[bi];\n            if(checked[eid]) continue;\n            checked[eid] = 1;\n            var e = edges[eid];\n            if(segsIntersect(ax, ay, bx, by, e[0], e[1], e[2], e[3])) return true;\n          }\n        }\n      }\n      return false;\n    }\n    function findKNN(idx, k, exclude){\n      var px = xs[idx], py = ys[idx];\n      var gx0 = gxOf(px), gy0 = gyOf(py);\n      var found = [];\n      var r = 0;\n      var maxR = (gw > gh ? gw : gh);\n      while(r <= maxR){\n        var loX = gx0 - r > 0 ? gx0 - r : 0;\n        var hiX = gx0 + r < gw-1 ? gx0 + r : gw-1;\n        var loY = gy0 - r > 0 ? gy0 - r : 0;\n        var hiY = gy0 + r < gh-1 ? gy0 + r : gh-1;\n        for(var gyN=loY; gyN<=hiY; gyN++){\n          for(var gxN=loX; gxN<=hiX; gxN++){\n            \/\/ Only the outer ring (avoid recounting)\n            if(r > 0){\n              if(gxN > gx0-r ? (gxN < gx0+r ? (gyN > gy0-r ? gyN < gy0+r : false) : false) : false) continue;\n            }\n            var bucket = cells[gyN*gw + gxN];\n            for(var bi=0; bi<bucket.length; bi++){\n              var ci = bucket[bi];\n              if(ci === idx) continue;\n              if(exclude ? exclude[ci] : false) continue;\n              var ddx = xs[ci] - px, ddy = ys[ci] - py;\n              found.push([ddx*ddx + ddy*ddy, ci]);\n            }\n          }\n        }\n        if(found.length >= k * 2) break;\n        r++;\n      }\n      found.sort(function(a, b){ return a[0] - b[0]; });\n      var out = [];\n      var lim = found.length < k ? found.length : k;\n      for(var fi=0; fi<lim; fi++) out.push(found[fi][1]);\n      return out;\n    }\n    \/\/ Point-in-ring test (ray casting). Used after a successful walk to confirm\n    \/\/ that the produced ring actually encloses the subsampled points (rejects\n    \/\/ tiny premature closures around the start point).\n    function ringEnclosesFraction(hullIdx){\n      var Nh = hullIdx.length;\n      if(Nh < 4) return 0;\n      var rx = new Float64Array(Nh);\n      var ry = new Float64Array(Nh);\n      for(var k0=0; k0<Nh; k0++){ rx[k0] = xs[hullIdx[k0]]; ry[k0] = ys[hullIdx[k0]]; }\n      var inside = 0;\n      for(var pp=0; pp<N; pp++){\n        var px = xs[pp], py = ys[pp];\n        var ins = false;\n        var j0 = Nh - 2;\n        for(var i0=0; i0<Nh-1; i0++){\n          var xi = rx[i0], yi = ry[i0];\n          var xj = rx[j0], yj = ry[j0];\n          if(((yi > py) !== (yj > py)) ?\n             (px < (xj - xi) * (py - yi) \/ (yj - yi + 1e-12) + xi) : false){\n            ins = !ins;\n          }\n          j0 = i0;\n        }\n        if(ins) inside++;\n      }\n      return inside \/ N;\n    }\n    function attemptHull(k){\n      \/\/ Reset edge index for this attempt.\n      edges.length = 0;\n      for(var ec2=0; ec2<gw*gh; ec2++) edgeCells[ec2].length = 0;\n      \/\/ Start at lowest-Y point (guaranteed on convex hull).\n      var startIdx = 0;\n      for(var iS=1; iS<N; iS++){ if(ys[iS] < ys[startIdx]) startIdx = iS; }\n      var hullIdx = [startIdx];\n      var used = new Uint8Array(N);\n      used[startIdx] = 1;\n      var current = startIdx;\n      \/\/ Initial direction: pointing in the -X direction so the first step turns\n      \/\/ anticlockwise (counter-clockwise winding). Choose freely as long as we're\n      \/\/ consistent \u2014 the start point is convex so any tangent gives correct walk.\n      var prevAng = Math.PI;\n      var maxSteps = N + 10;\n      \/\/ Force a minimum number of hops before allowing return to start. Without\n      \/\/ this, dense clusters around the start point produce a tiny premature\n      \/\/ ring that doesn't enclose the field. Scales with k so larger k can still\n      \/\/ close on small clusters where the ring is naturally short.\n      var minStepsBeforeClose = N < 30 ? Math.max(3, N - 2) : Math.max(8, k * 2);\n      for(var step=0; step<maxSteps; step++){\n        var allowStart = step >= minStepsBeforeClose;\n        \/\/ Allow start in candidate pool when allowStart by temporarily unmarking it.\n        if(allowStart) used[startIdx] = 0;\n        var cands = findKNN(current, k, used);\n        if(allowStart) used[startIdx] = 1;\n        if(cands.length === 0) return null;\n        \/\/ Sort candidates by clockwise turn angle (= sharpest right turn first).\n        var ranked = [];\n        for(var ck=0; ck<cands.length; ck++){\n          var cIdx = cands[ck];\n          var dxC = xs[cIdx] - xs[current];\n          var dyC = ys[cIdx] - ys[current];\n          var aC = Math.atan2(dyC, dxC);\n          var delta = prevAng - aC;\n          while(delta < 0) delta += 2 * Math.PI;\n          while(delta >= 2 * Math.PI) delta -= 2 * Math.PI;\n          ranked.push([delta, cIdx]);\n        }\n        ranked.sort(function(a, b){ return a[0] - b[0]; });\n        var chosen = -1;\n        for(var ri=0; ri<ranked.length; ri++){\n          var ckIdx = ranked[ri][1];\n          if(ckIdx === startIdx ? !allowStart : false) continue;\n          if(ckIdx !== startIdx ? used[ckIdx] : false) continue;\n          if(!segmentCrossesAnyEdge(xs[current], ys[current], xs[ckIdx], ys[ckIdx])){\n            chosen = ckIdx;\n            break;\n          }\n        }\n        if(chosen < 0) return null;\n        registerEdge(xs[current], ys[current], xs[chosen], ys[chosen]);\n        hullIdx.push(chosen);\n        if(chosen === startIdx) break;\n        used[chosen] = 1;\n        var dxN = xs[chosen] - xs[current];\n        var dyN = ys[chosen] - ys[current];\n        prevAng = Math.atan2(-dyN, -dxN);  \/\/ direction \"back to current\" so next step continues forward\n        current = chosen;\n      }\n      if(hullIdx[hullIdx.length-1] !== startIdx) return null;\n      \/\/ Validate enclosure \u2014 if fewer than 90% of subsampled points are inside,\n      \/\/ the walk found a degenerate loop. Return null so caller escalates k.\n      if(ringEnclosesFraction(hullIdx) < 0.9) return null;\n      return hullIdx;\n    }\n    var kMax = Math.min(N - 1, 30);\n    var k = 3;\n    while(k <= kMax){\n      var h = attemptHull(k);\n      if(h){\n        var nH = h.length;\n        var xa = new Float32Array(nH);\n        var ya = new Float32Array(nH);\n        for(var ii=0; ii<nH; ii++){ xa[ii] = xs[h[ii]]; ya[ii] = ys[h[ii]]; }\n        return { x: xa, y: ya };\n      }\n      k = k < 8 ? k + 1 : Math.ceil(k * 1.4);\n    }\n    return null;\n  }\n  \/\/ Grid-based field outline + interior-hole detector. Returns `{x, y, holes: [...]}`\n  \/\/ where outer ring traces the edge of the data grid and holes capture interior data\n  \/\/ gaps (trees \/ ponds \/ rivers \/ refused obstacles).\n  \/\/\n  \/\/ Why grid-based and not edge-pullin concave hull: edge-pullin only pulls inward\n  \/\/ toward existing points, so concavities that are pure no-data regions (e.g. a\n  \/\/ big wooded section bumping into the field edge) never get carved out \u2014 the\n  \/\/ convex hull's edge stays put. Grid-based naturally captures these because empty\n  \/\/ cells in those regions are reachable from outside, hence not part of the data.\n  \/\/\n  \/\/ Algorithm:\n  \/\/   1. Grid the points using `cellM` real-meter cells.\n  \/\/   2. Mark cells with \u2265 1 point as DATA.\n  \/\/   3. Morphological close (dilate 1\u00d7 then erode 1\u00d7) \u2014 closes single-cell gaps from\n  \/\/      ordinary point sparsity without growing the field outward.\n  \/\/   4. Flood-fill EXTERIOR from grid border.\n  \/\/   5. Trace cell-edge segments where DATA meets non-DATA. Each segment is one\n  \/\/      side of a cell, emitted in CCW order around the data cells so connected\n  \/\/      segments form closed rings.\n  \/\/   6. Walk segments end-to-end to assemble closed rings. Largest-area ring is\n  \/\/      the outer; smaller rings are holes (filtered by min area).\n  function gridHullAndHoles(xs, ys, cellM){\n    var nPts = xs.length;\n    if(nPts < 8) return null;\n    var cosLat = Math.cos((typeof latC === 'number' ? latC : 0) * Math.PI \/ 180);\n    if(!(cosLat > 0)) cosLat = 1;\n    var cellMerc = cellM \/ cosLat;\n    if(!(cellMerc > 0)) return null;\n    var minX = Infinity, maxX = -Infinity, minY = Infinity, maxY = -Infinity;\n    for(var i=0; i<nPts; i++){\n      if(xs[i] < minX) minX = xs[i];\n      if(xs[i] > maxX) maxX = xs[i];\n      if(ys[i] < minY) minY = ys[i];\n      if(ys[i] > maxY) maxY = ys[i];\n    }\n    var pad = 2;\n    var gw = Math.ceil((maxX - minX) \/ cellMerc) + pad * 2;\n    var gh = Math.ceil((maxY - minY) \/ cellMerc) + pad * 2;\n    if(gw < 5 ? true : gh < 5) return null;\n    if(gw * gh > 500000) return null;\n    var data = new Uint8Array(gw * gh);\n    for(var pi=0; pi<nPts; pi++){\n      var gx = Math.floor((xs[pi] - minX) \/ cellMerc) + pad;\n      var gy = Math.floor((ys[pi] - minY) \/ cellMerc) + pad;\n      if(gx >= 0 ? (gx < gw ? (gy >= 0 ? gy < gh : false) : false) : false){\n        data[gy * gw + gx] = 1;\n      }\n    }\n    \/\/ Single-pass dilate (4-connected). Empty cell -> DATA if any neighbour is DATA.\n    function dilateOnce(src){\n      var out = new Uint8Array(src.length);\n      for(var dy=0; dy<gh; dy++){\n        for(var dx=0; dx<gw; dx++){\n          var ii = dy*gw + dx;\n          if(src[ii]){ out[ii] = 1; continue; }\n          if(dx > 0 ? src[ii - 1] : false){ out[ii] = 1; continue; }\n          if(dx < gw-1 ? src[ii + 1] : false){ out[ii] = 1; continue; }\n          if(dy > 0 ? src[ii - gw] : false){ out[ii] = 1; continue; }\n          if(dy < gh-1 ? src[ii + gw] : false){ out[ii] = 1; continue; }\n        }\n      }\n      return out;\n    }\n    \/\/ Single-pass erode (4-connected). DATA cell -> empty if any neighbour is empty\n    \/\/ (or the cell sits on the grid border).\n    function erodeOnce(src){\n      var out = new Uint8Array(src.length);\n      for(var ey=0; ey<gh; ey++){\n        for(var ex=0; ex<gw; ex++){\n          var ii = ey*gw + ex;\n          if(!src[ii]) continue;\n          if(ex === 0 ? true : ey === 0 ? true : ex === gw-1 ? true : ey === gh-1) continue;\n          if(!src[ii-1] ? true : !src[ii+1] ? true : !src[ii-gw] ? true : !src[ii+gw]) continue;\n          out[ii] = 1;\n        }\n      }\n      return out;\n    }\n    \/\/ CLOSE (dilate \u2192 erode): closes 1-cell sparsity gaps within passes without\n    \/\/ expanding the outline. OPEN (erode \u2192 dilate): removes 1-cell thin protrusions\n    \/\/ \u2014 typically the combine drove out past the field edge and back, leaving a\n    \/\/ narrow tail of yield points outside the real boundary. Opening severs that.\n    \/\/ Order: close first (clean up data), then open (trim protrusions).\n    var afterClose = erodeOnce(dilateOnce(data));\n    var closed = dilateOnce(erodeOnce(afterClose));\n    \/\/ Flood-fill exterior. state: 0=interior-empty (hole candidate), 1=data, 2=exterior.\n    var state = new Uint8Array(gw * gh);\n    for(var si=0; si<gw*gh; si++) if(closed[si]) state[si] = 1;\n    var stk = [];\n    for(var bx=0; bx<gw; bx++){\n      var iT = bx, iB = (gh-1)*gw + bx;\n      if(!state[iT]){ state[iT] = 2; stk.push(iT); }\n      if(!state[iB]){ state[iB] = 2; stk.push(iB); }\n    }\n    for(var by=0; by<gh; by++){\n      var iL = by*gw, iR = by*gw + gw-1;\n      if(!state[iL]){ state[iL] = 2; stk.push(iL); }\n      if(!state[iR]){ state[iR] = 2; stk.push(iR); }\n    }\n    while(stk.length){\n      var cur = stk.pop();\n      var cy0 = Math.floor(cur \/ gw);\n      var cx0 = cur - cy0 * gw;\n      if(cx0 > 0){ var lN = cur - 1; if(!state[lN]){ state[lN] = 2; stk.push(lN); } }\n      if(cx0 < gw-1){ var rN = cur + 1; if(!state[rN]){ state[rN] = 2; stk.push(rN); } }\n      if(cy0 > 0){ var uN = cur - gw; if(!state[uN]){ state[uN] = 2; stk.push(uN); } }\n      if(cy0 < gh-1){ var dN = cur + gw; if(!state[dN]){ state[dN] = 2; stk.push(dN); } }\n    }\n    \/\/ Trace boundary segments. For each DATA cell, look at the 4 neighbours; for\n    \/\/ each neighbour that is NOT DATA, emit the shared edge as a segment. Order\n    \/\/ the segment endpoints so that walking left->right of segments traces the\n    \/\/ ring CCW (data is on the LEFT of the segment direction).\n    \/\/\n    \/\/ Cell (cx, cy) corners (mercator coords):\n    \/\/   x0 = minX + (cx - pad) * cellMerc        (left)\n    \/\/   x1 = x0 + cellMerc                       (right)\n    \/\/   y0 = minY + (cy - pad) * cellMerc        (bottom)\n    \/\/   y1 = y0 + cellMerc                       (top)\n    \/\/\n    \/\/ Outward normals for each side (data inside, non-data outside):\n    \/\/   LEFT   side (between (cx-1) and cx): segment from (x0, y0) -> (x0, y1)  [data on right -> trace bottom-to-top]\n    \/\/   RIGHT  side (between cx and (cx+1)): segment from (x1, y1) -> (x1, y0)\n    \/\/   BOTTOM side (between (cy-1) and cy): segment from (x1, y0) -> (x0, y0)\n    \/\/   TOP    side (between cy and (cy+1)): segment from (x0, y1) -> (x1, y1)\n    var segs = [];  \/\/ each segment: [ax, ay, bx, by]\n    for(var sy=0; sy<gh; sy++){\n      for(var sx=0; sx<gw; sx++){\n        var spi = sy*gw + sx;\n        if(state[spi] !== 1) continue;\n        var x0c = minX + (sx - pad) * cellMerc;\n        var y0c = minY + (sy - pad) * cellMerc;\n        var x1c = x0c + cellMerc;\n        var y1c = y0c + cellMerc;\n        if(sx === 0 ? true : state[spi - 1] !== 1){ segs.push([x0c, y0c, x0c, y1c]); }\n        if(sx === gw-1 ? true : state[spi + 1] !== 1){ segs.push([x1c, y1c, x1c, y0c]); }\n        if(sy === 0 ? true : state[spi - gw] !== 1){ segs.push([x1c, y0c, x0c, y0c]); }\n        if(sy === gh-1 ? true : state[spi + gw] !== 1){ segs.push([x0c, y1c, x1c, y1c]); }\n      }\n    }\n    if(segs.length === 0) return null;\n    \/\/ Build a start-point \u2192 segment-index map, then walk segment chains.\n    var startMap = {};\n    for(var siT=0; siT<segs.length; siT++){\n      var ks = segs[siT][0] + ',' + segs[siT][1];\n      var bucket = startMap[ks];\n      if(!bucket){ bucket = []; startMap[ks] = bucket; }\n      bucket.push(siT);\n    }\n    var used = new Uint8Array(segs.length);\n    var rings = [];\n    for(var siW=0; siW<segs.length; siW++){\n      if(used[siW]) continue;\n      used[siW] = 1;\n      var startSeg = segs[siW];\n      var ring = [[startSeg[0], startSeg[1]], [startSeg[2], startSeg[3]]];\n      var endX = startSeg[2], endY = startSeg[3];\n      var startX = startSeg[0], startY = startSeg[1];\n      var safety = segs.length + 10;\n      while(safety-- > 0){\n        if(endX === startX ? endY === startY : false) break;\n        var key = endX + ',' + endY;\n        var nexts = startMap[key];\n        if(!nexts) break;\n        var nxtIdx = -1;\n        for(var nii=0; nii<nexts.length; nii++){\n          if(!used[nexts[nii]]){ nxtIdx = nexts[nii]; break; }\n        }\n        if(nxtIdx < 0) break;\n        used[nxtIdx] = 1;\n        var ns = segs[nxtIdx];\n        ring.push([ns[2], ns[3]]);\n        endX = ns[2]; endY = ns[3];\n      }\n      if(ring.length >= 4) rings.push(ring);\n    }\n    if(rings.length === 0) return null;\n    \/\/ Signed mercator area; negative when traced CW (depending on Y-up vs Y-down\n    \/\/ convention \u2014 this codebase uses canvas Y-down, so CCW around data gives a\n    \/\/ negative shoelace value, but here we only use ABSOLUTE area for ranking).\n    function ringSignedArea(r){\n      var a = 0;\n      for(var k=0; k<r.length-1; k++) a += r[k][0]*r[k+1][1] - r[k+1][0]*r[k][1];\n      return a * 0.5;\n    }\n    var ringInfo = [];\n    for(var ri=0; ri<rings.length; ri++){\n      var sA = ringSignedArea(rings[ri]);\n      ringInfo.push({ idx: ri, signed: sA, absArea: Math.abs(sA) });\n    }\n    ringInfo.sort(function(a, b){ return b.absArea - a.absArea; });\n    var outerRing = rings[ringInfo[0].idx];\n    var outerAbs = ringInfo[0].absArea;\n    var outerAreaM2 = outerAbs * cosLat * cosLat;\n    if(outerAreaM2 < cellM * cellM * 4) return null;\n    \/\/ Hole filtering. Data-driven detection can't reliably distinguish real\n    \/\/ obstacles (tree clusters, ponds, wetlands) from in-data sparsity noise at\n    \/\/ small scales, so use ONE conservative filter: minimum size of 0.5 ha. Real\n    \/\/ operationally-meaningful obstacles inside a field are almost always above\n    \/\/ this size; everything smaller is filtered out as likely pass-gap noise.\n    \/\/ Shape filters (aspect \/ compactness) are dropped \u2014 real ditches and\n    \/\/ wetlands are often long and thin, so excluding by shape rejected too many\n    \/\/ legitimate shapes. For sub-0.5 ha precision, the user can supply a\n    \/\/ boundary file (path 1 in the workflow).\n    var minHoleM2 = 5000;             \/\/ 0.5 ha minimum\n    var maxHoleM2 = outerAreaM2 * 0.35;\n    var holes = [];\n    for(var hi2=1; hi2<ringInfo.length; hi2++){\n      var info = ringInfo[hi2];\n      var areaM2 = info.absArea * cosLat * cosLat;\n      if(areaM2 < minHoleM2) continue;\n      if(areaM2 > maxHoleM2) continue;\n      holes.push(rings[info.idx]);\n    }\n    \/\/ Douglas\u2013Peucker ring simplification \u2014 collapses long runs of cell-edge\n    \/\/ segments into clean straight lines along the boundary. epsilon in mercator\n    \/\/ units, set to half a cell so anything aligned along a row\/column collapses.\n    function simplifyRing(r, eps){\n      if(r.length <= 4) return r;\n      var n = r.length;\n      var keep = new Uint8Array(n);\n      keep[0] = 1; keep[n-1] = 1;\n      var st = [[0, n-1]];\n      while(st.length){\n        var seg = st.pop();\n        var iA = seg[0], iB = seg[1];\n        if(iB - iA < 2) continue;\n        var ax = r[iA][0], ay = r[iA][1], bx = r[iB][0], by = r[iB][1];\n        var dxAB = bx - ax, dyAB = by - ay;\n        var L2 = dxAB*dxAB + dyAB*dyAB;\n        var maxD = -1, maxI = -1;\n        for(var ii=iA+1; ii<iB; ii++){\n          var px = r[ii][0], py = r[ii][1];\n          var d2;\n          if(L2 > 1e-12){\n            var t = ((px-ax)*dxAB + (py-ay)*dyAB) \/ L2;\n            if(t < 0) t = 0; else if(t > 1) t = 1;\n            var qx = ax + t*dxAB, qy = ay + t*dyAB;\n            d2 = (px-qx)*(px-qx) + (py-qy)*(py-qy);\n          } else {\n            d2 = (px-ax)*(px-ax) + (py-ay)*(py-ay);\n          }\n          if(d2 > maxD){ maxD = d2; maxI = ii; }\n        }\n        if(maxD > eps*eps){\n          keep[maxI] = 1;\n          st.push([iA, maxI]);\n          st.push([maxI, iB]);\n        }\n      }\n      var simp = [];\n      for(var ki=0; ki<n; ki++) if(keep[ki]) simp.push(r[ki]);\n      return simp;\n    }\n    function toF32(r){\n      var simp = simplifyRing(r, cellMerc * 0.6);\n      var n2 = simp.length;\n      var xa = new Float32Array(n2 + 1);\n      var ya = new Float32Array(n2 + 1);\n      for(var k2=0; k2<n2; k2++){ xa[k2] = simp[k2][0]; ya[k2] = simp[k2][1]; }\n      xa[n2] = xa[0]; ya[n2] = ya[0];\n      return { x: xa, y: ya };\n    }\n    var out = toF32(outerRing);\n    out.holes = holes.map(toF32);\n    return out;\n  }\n  \/\/ Standard ray-casting point-in-polygon. `hull` is a closed ring (first==last).\n  \/\/ `bufM` extends the boundary outward by `bufM` real meters \u2014 set to 0 for an\n  \/\/ exact test, or to a positive value for a soft \"near the edge\" margin.\n  function pointInHull(hx, hy, hull, bufM){\n    if(!hull) return true;\n    \/\/ buffer in real meters -> mercator units: divide by cos(latC*DEG).\n    var cosLat = Math.cos((typeof latC === 'number' ? latC : 0) * Math.PI \/ 180);\n    if(!(cosLat > 0)) cosLat = 1;\n    var bufMerc = (bufM ? bufM : 0) \/ cosLat;\n    var X = hull.x, Y = hull.y;\n    var n = X.length - 1;\n    var inside = false;\n    var j = n - 1;\n    for(var i=0; i<n; i++){\n      var xi = X[i], yi = Y[i];\n      var xj = X[j], yj = Y[j];\n      if(((yi > hy) !== (yj > hy)) ?\n         (hx < (xj - xi) * (hy - yi) \/ (yj - yi + 1e-12) + xi) : false){\n        inside = !inside;\n      }\n      j = i;\n    }\n    if(inside) return true;\n    if(bufM > 0){\n      var buf2 = bufMerc * bufMerc;\n      for(var ei=0; ei<n; ei++){\n        var ax = X[ei], ay = Y[ei];\n        var bx = X[ei + 1], by = Y[ei + 1];\n        var dx = bx - ax, dy = by - ay;\n        var t = ((hx - ax) * dx + (hy - ay) * dy) \/ (dx*dx + dy*dy + 1e-12);\n        if(t < 0) t = 0; else if(t > 1) t = 1;\n        var qx = ax + t * dx, qy = ay + t * dy;\n        var ddx = hx - qx, ddy = hy - qy;\n        if(ddx*ddx + ddy*ddy <= buf2) return true;\n      }\n    }\n    return false;\n  }\n  \/\/ Spatial clustering: two centroids belong to the same cluster if there's a chain\n  \/\/ of centroids between them where consecutive nodes are within `gapM` real meters.\n  \/\/ Grid-based for O(n) on typical ag datasets \u2014 bin into cells of size = gapMerc,\n  \/\/ then BFS through occupied 3x3 neighborhoods. Returns an array of {xs, ys} per\n  \/\/ cluster. Used to compute ONE hull per field when a dataset contains multiple\n  \/\/ disjoint fields (e.g., \u041b\u0417-017 + \u041b\u0411-006 in one coverage file).\n  function clusterCentroidsByProximity(xs, ys, gapM){\n    var n = xs.length;\n    if(n === 0) return [];\n    var cosLat = Math.cos((typeof latC === 'number' ? latC : 0) * Math.PI \/ 180);\n    if(!(cosLat > 0)) cosLat = 1;\n    var gapMerc = gapM \/ cosLat;\n    var cellM = gapMerc;\n    var grid = new Map();\n    function key(ix, iy){ return ix + '|' + iy; }\n    for(var i=0; i<n; i++){\n      var ix = Math.floor(xs[i] \/ cellM);\n      var iy = Math.floor(ys[i] \/ cellM);\n      var k = key(ix, iy);\n      var arr = grid.get(k);\n      if(!arr){ arr = []; grid.set(k, arr); }\n      arr.push(i);\n    }\n    var label = new Int32Array(n);\n    for(var i2=0; i2<n; i2++) label[i2] = -1;\n    var clusterId = 0;\n    var gap2 = gapMerc * gapMerc;\n    for(var start=0; start<n; start++){\n      if(label[start] !== -1) continue;\n      label[start] = clusterId;\n      var stack = [start];\n      while(stack.length){\n        var cur = stack.pop();\n        var cix = Math.floor(xs[cur] \/ cellM);\n        var ciy = Math.floor(ys[cur] \/ cellM);\n        for(var dx=-1; dx<=1; dx++){\n          for(var dy=-1; dy<=1; dy++){\n            var nbr = grid.get(key(cix+dx, ciy+dy));\n            if(!nbr) continue;\n            for(var ni=0; ni<nbr.length; ni++){\n              var j = nbr[ni];\n              if(label[j] !== -1) continue;\n              var dxx = xs[j] - xs[cur];\n              var dyy = ys[j] - ys[cur];\n              if(dxx*dxx + dyy*dyy <= gap2){\n                label[j] = clusterId;\n                stack.push(j);\n              }\n            }\n          }\n        }\n      }\n      clusterId++;\n    }\n    var clusters = new Array(clusterId);\n    for(var ci=0; ci<clusterId; ci++) clusters[ci] = { xs: [], ys: [], indices: [] };\n    for(var i3=0; i3<n; i3++){\n      var c = clusters[label[i3]];\n      c.xs.push(xs[i3]);\n      c.ys.push(ys[i3]);\n      c.indices.push(i3);\n    }\n    return clusters;\n  }\n  \/\/ From a list of hulls, return the first one whose interior contains (px, py).\n  \/\/ null if none match. Used by the U-turn clamp and headland-pass detector to pick\n  \/\/ the correct field's hull before applying constraints.\n  function findContainingHull(px, py, hulls){\n    if(!hulls) return null;\n    for(var i=0; i<hulls.length; i++){\n      if(pointInHull(px, py, hulls[i], 0)) return hulls[i];\n    }\n    return null;\n  }\n  \/\/ Compute a polygon's dominant edge direction via doubled-angle averaging of\n  \/\/ its edges, weighted by edge length. Doubled-angle (cos 2\u03b8, sin 2\u03b8) makes\n  \/\/ parallel edges reinforce regardless of direction. Returns {ux, uy, coh, sumLen}:\n  \/\/   ux, uy = unit vector along the polygon's long axis (in stored Y-flipped coords)\n  \/\/   coh = 0..1, higher = more elongated (rectangle 2:1 \u2192 coh \u2248 0.33; 4:1 \u2192 ~0.6)\n  \/\/   sumLen = total edge length (weight when aggregating over many polygons)\n  \/\/ Uses polyData[i].rings which already has mercator-converted coords in stored\n  \/\/ (Y-flipped) space \u2014 much faster than re-parsing GeoJSON.\n  function polygonLongAxisFromPolyData(polyIdx){\n    if(!polyData ? true : !polyData[polyIdx]) return null;\n    var rings = polyData[polyIdx].rings;\n    if(!rings ? true : rings.length === 0) return null;\n    var sumDoubX = 0, sumDoubY = 0, sumLen = 0;\n    \/\/ Outer ring only (rings[0]). Skip inner holes \u2014 they distort the dominant axis.\n    var r = rings[0];\n    if(!r ? true : r.mx.length < 3) return null;\n    for(var vi=0; vi<r.mx.length - 1; vi++){\n      var dx = r.mx[vi+1] - r.mx[vi];\n      var dy = r.my[vi+1] - r.my[vi];\n      var len = Math.sqrt(dx*dx + dy*dy);\n      if(len < 1e-9) continue;\n      var ndx = dx \/ len, ndy = dy \/ len;\n      sumDoubX += len * (ndx*ndx - ndy*ndy);\n      sumDoubY += len * (2 * ndx * ndy);\n      sumLen += len;\n    }\n    if(sumLen < 1e-9) return null;\n    var avgX = sumDoubX \/ sumLen;\n    var avgY = sumDoubY \/ sumLen;\n    var coh = Math.sqrt(avgX*avgX + avgY*avgY);\n    var ang = 0.5 * Math.atan2(avgY, avgX);\n    return { ux: Math.cos(ang), uy: Math.sin(ang), coh: coh, sumLen: sumLen };\n  }\n  \/\/ Phase B-3: AB-aligned playback order + sprite path. When AB-line traversal is\n  \/\/ available for polygon data, this rebuilds playback.order so polygons reveal in\n  \/\/ pass-by-pass order (not file order), and sets playback.spritePathX\/Y so the\n  \/\/ sprite drives along each AB line. Boundaries flag line-to-line transitions so\n  \/\/ the existing turnaround code generates a Bezier U-turn arc between passes.\n  \/\/\n  \/\/ Algorithm:\n  \/\/   1. Flatten per-cluster AB lines into one ordered list. Within each cluster\n  \/\/      alternate direction (snake): line 0 forward, line 1 reversed, etc.\n  \/\/   2. For each polygon, project its centroid perpendicularly onto every AB line,\n  \/\/      pick the nearest one (smallest perpendicular distance, t clamped to [0, len]).\n  \/\/   3. Sort polygons by (assigned line index, along-line t). This is the new order.\n  \/\/   4. spritePathX\/Y[i] = projected position of order[i] on its AB line.\n  \/\/   5. boundaries[i] = 1 whenever the assigned line index changes between\n  \/\/      consecutive entries (= the sprite needs to U-turn into the next pass).\n  \/\/ Returns null when no AB lines exist or for non-polygon datasets.\n  function buildABAlignedOrder(){\n    if(mode !== 'polygon') return null;\n    if(!polyData) return null;\n    if(!playback.abLines ? true : !playback.abLines.perCluster.length) return null;\n    var allLines = [];\n    for(var cI=0; cI<playback.abLines.perCluster.length; cI++){\n      var lns = playback.abLines.perCluster[cI];\n      for(var li=0; li<lns.length; li++){\n        var L = lns[li];\n        var rev = (li % 2 === 1);\n        var sx0 = rev ? L.x1 : L.x0;\n        var sy0 = rev ? L.y1 : L.y0;\n        var sx1 = rev ? L.x0 : L.x1;\n        var sy1 = rev ? L.y0 : L.y1;\n        var dxL = sx1 - sx0, dyL = sy1 - sy0;\n        var lL = Math.sqrt(dxL*dxL + dyL*dyL);\n        if(lL < 1e-9) continue;\n        allLines.push({\n          x0: sx0, y0: sy0, x1: sx1, y1: sy1,\n          udx: dxL \/ lL, udy: dyL \/ lL,\n          len: lL\n        });\n      }\n    }\n    if(!allLines.length) return null;\n    var nPoly = polyData.length;\n    var lineIdx = new Int32Array(nPoly);\n    var tArr = new Float32Array(nPoly);\n    var spriteX = new Float32Array(nPoly);\n    var spriteY = new Float32Array(nPoly);\n    for(var pi=0; pi<nPoly; pi++) lineIdx[pi] = -1;\n    for(var pi2=0; pi2<nPoly; pi2++){\n      var pd = polyData[pi2];\n      if(!pd) continue;\n      var cx = pd.cx, cy = pd.cy;\n      var bestPerp = Infinity, bestL = -1, bestT = 0, bestSX = 0, bestSY = 0;\n      for(var li2=0; li2<allLines.length; li2++){\n        var lne = allLines[li2];\n        var dx = cx - lne.x0, dy = cy - lne.y0;\n        var alongLen = dx * lne.udx + dy * lne.udy;\n        var tClamped = alongLen < 0 ? 0 : (alongLen > lne.len ? lne.len : alongLen);\n        var prx = lne.x0 + lne.udx * tClamped;\n        var pry = lne.y0 + lne.udy * tClamped;\n        var ddx = cx - prx, ddy = cy - pry;\n        var perpD2 = ddx*ddx + ddy*ddy;\n        if(perpD2 < bestPerp){\n          bestPerp = perpD2;\n          bestL = li2;\n          bestT = lne.len > 0 ? tClamped \/ lne.len : 0;\n          bestSX = prx;\n          bestSY = pry;\n        }\n      }\n      lineIdx[pi2] = bestL;\n      tArr[pi2] = bestT;\n      spriteX[pi2] = bestSX;\n      spriteY[pi2] = bestSY;\n    }\n    var order = [];\n    for(var pi3=0; pi3<nPoly; pi3++){\n      if(lineIdx[pi3] >= 0) order.push(pi3);\n    }\n    order.sort(function(a, b){\n      if(lineIdx[a] !== lineIdx[b]) return lineIdx[a] - lineIdx[b];\n      return tArr[a] - tArr[b];\n    });\n    var nOrd = order.length;\n    var sX = new Float32Array(nOrd);\n    var sY = new Float32Array(nOrd);\n    var bnd = new Uint8Array(nOrd);\n    for(var oi=0; oi<nOrd; oi++){\n      sX[oi] = spriteX[order[oi]];\n      sY[oi] = spriteY[order[oi]];\n      if(oi > 0 ? lineIdx[order[oi]] !== lineIdx[order[oi-1]] : false){\n        bnd[oi] = 1;\n      }\n    }\n    return { order: order, spriteX: sX, spriteY: sY, boundaries: bnd, lineCount: allLines.length };\n  }\n  \/\/ Estimate the dominant nearest-neighbor direction across a sample of polygons.\n  \/\/ For Trimble pass data, consecutive cells within one pass are much closer than\n  \/\/ cells across passes (sub-meter vs 18 m), so each cell's nearest neighbor lies\n  \/\/ ALONG motion. Doubled-angle averaging makes the result direction-agnostic;\n  \/\/ useful as a tiebreaker when field-span comparison can't choose between two\n  \/\/ candidate axes (near-square fields). Returns null when sample is too small.\n  function detectNearestNeighborDirection(polyIndices){\n    if(!polyIndices ? true : polyIndices.length < 10) return null;\n    if(!polyData) return null;\n    var xs = [], ys = [];\n    for(var i=0; i<polyIndices.length; i++){\n      var idx = polyIndices[i];\n      if(!polyData[idx]) continue;\n      xs.push(polyData[idx].cx);\n      ys.push(polyData[idx].cy);\n    }\n    var n = xs.length;\n    if(n < 10) return null;\n    var maxSamples = 200;\n    var step = Math.max(1, Math.floor(n \/ maxSamples));\n    var sumDX = 0, sumDY = 0, sumW = 0;\n    for(var iS=0; iS<n; iS += step){\n      var bestD2 = Infinity, bestJ = -1;\n      for(var j=0; j<n; j++){\n        if(j === iS) continue;\n        var dx = xs[j] - xs[iS], dy = ys[j] - ys[iS];\n        var d2 = dx*dx + dy*dy;\n        if(d2 < bestD2){ bestD2 = d2; bestJ = j; }\n      }\n      if(bestJ < 0) continue;\n      var bestD = Math.sqrt(bestD2);\n      if(bestD < 1e-9) continue;\n      var ndx = (xs[bestJ] - xs[iS]) \/ bestD;\n      var ndy = (ys[bestJ] - ys[iS]) \/ bestD;\n      sumDX += ndx*ndx - ndy*ndy;\n      sumDY += 2 * ndx * ndy;\n      sumW += 1;\n    }\n    if(sumW < 1) return null;\n    return 0.5 * Math.atan2(sumDY, sumDX);\n  }\n  \/\/ Detect AB-line axis from POLYGON SHAPES \u2014 primary detector for polygon mode.\n  \/\/ Two-track strategy based on median polygon elongation:\n  \/\/   1. ELONGATED cells (median coh > 0.3, aspect > ~2): Trimble per-section coverage\n  \/\/      where each cell is a long thin streak with its long edge perpendicular to\n  \/\/      motion. Average all polygons' long-axis directions (doubled-angle averaging\n  \/\/      weighted by total edge length); AB line = PERPENDICULAR to that axis (along\n  \/\/      machine motion).\n  \/\/   2. SQUARE-ISH cells (median coh \u2264 0.3): rate-prescription grids where cells are\n  \/\/      roughly square axis-aligned rectangles. Build edge-angle histogram, find the\n  \/\/      strongest peaks, and pick the peak along which the FIELD EXTENT (hull span)\n  \/\/      is greatest \u2014 longest passes = fewest turns = real ag practice.\n  \/\/ Falls back to null if shape data is degenerate (caller tries Hough\/PCA next).\n  function detectAxisFromPolygonShapes(polyIndices, hull){\n    if(!polyIndices ? true : polyIndices.length < 5) return null;\n    if(mode !== 'polygon') return null;\n    if(!polyData) return null;\n    \/\/ Gather per-polygon long-axes\n    var perPoly = [];\n    for(var i=0; i<polyIndices.length; i++){\n      var info = polygonLongAxisFromPolyData(polyIndices[i]);\n      if(info) perPoly.push(info);\n    }\n    if(perPoly.length === 0) return null;\n    \/\/ Median coherence\n    var cohs = perPoly.map(function(p){ return p.coh; }).sort(function(a, b){ return a - b; });\n    var medCoh = cohs[cohs.length >> 1];\n    if(medCoh > 0.3){\n      \/\/ ELONGATED cells. Compute the average long-axis from doubled-angle\n      \/\/ averaging \u2014 this is the direction of the polygons' long edges.\n      var sumDX = 0, sumDY = 0, sumWLen = 0;\n      for(var p=0; p<perPoly.length; p++){\n        var pp = perPoly[p];\n        sumDX += pp.sumLen * (pp.ux*pp.ux - pp.uy*pp.uy);\n        sumDY += pp.sumLen * (2 * pp.ux * pp.uy);\n        sumWLen += pp.sumLen;\n      }\n      if(sumWLen < 1e-9) return null;\n      var avgAng = 0.5 * Math.atan2(sumDY, sumDX);\n      \/\/ SECTION POLYGON RULE: when the median THIN dimension of the polygons is\n      \/\/ < 2 m, the polygons are Trimble per-section coverage cells. The thin side\n      \/\/ is the SECTION WIDTH (across boom, ~75 cm); the long side is the per-sample\n      \/\/ motion distance (longer). AB direction MUST follow the long-axis \u2014 using\n      \/\/ the short side as the AB direction would put guidance lines across the\n      \/\/ boom (90\u00b0 wrong). User-stated rule: \"if polygon width is <2m it's just\n      \/\/ a section \u2014 don't treat section width as pass length.\"\n      var polyThins = [];\n      for(var pT=0; pT<polyIndices.length; pT++){\n        var pd = polyData[polyIndices[pT]];\n        if(!pd) continue;\n        var w = pd.maxX - pd.minX;\n        var h = pd.maxY - pd.minY;\n        if(w > 0 ? h > 0 : false) polyThins.push(Math.min(w, h));\n      }\n      var medThin = 0;\n      if(polyThins.length){\n        polyThins.sort(function(a, b){ return a - b; });\n        medThin = polyThins[polyThins.length >> 1];\n      }\n      if(medThin > 0 ? medThin < 2.0 : false){\n        try { console.warn('[GPY] shape detect (section, thin='+medThin.toFixed(2)+'m): coh='+medCoh.toFixed(2)+', longAxis='+(avgAng*180\/Math.PI).toFixed(1)+'\u00b0 \u2192 AB along long-axis ('+(avgAng*180\/Math.PI).toFixed(1)+'\u00b0)'); } catch(_){}\n        return {\n          ux: Math.cos(avgAng), uy: Math.sin(avgAng),\n          source: 'polygon-shapes (section thin '+medThin.toFixed(2)+'m, along long-axis)'\n        };\n      }\n      \/\/ Non-section elongated cells: try both candidates by field span, NN tiebreak.\n      var candAngs = [avgAng, avgAng + Math.PI \/ 2];\n      var spans = [0, 0];\n      if(hull ? hull.x.length > 1 : false){\n        for(var cN=0; cN<2; cN++){\n          var ca = candAngs[cN];\n          var cux = Math.cos(ca), cuy = Math.sin(ca);\n          var minProj = Infinity, maxProj = -Infinity;\n          for(var hi=0; hi<hull.x.length; hi++){\n            var pr = hull.x[hi] * cux + hull.y[hi] * cuy;\n            if(pr < minProj) minProj = pr;\n            if(pr > maxProj) maxProj = pr;\n          }\n          spans[cN] = maxProj - minProj;\n        }\n      }\n      var maxSpan = Math.max(spans[0], spans[1]);\n      var pickedAng;\n      var pickedNote;\n      if(maxSpan > 0 ? Math.abs(spans[0] - spans[1]) \/ maxSpan > 0.1 : false){\n        pickedAng = spans[0] > spans[1] ? candAngs[0] : candAngs[1];\n        pickedNote = 'longer span';\n      } else {\n        var nnAng = detectNearestNeighborDirection(polyIndices);\n        if(nnAng !== null){\n          function angDistMod(a, b){\n            var d = a - b;\n            while(d > Math.PI \/ 2) d -= Math.PI;\n            while(d < -Math.PI \/ 2) d += Math.PI;\n            return Math.abs(d);\n          }\n          var d0 = angDistMod(candAngs[0], nnAng);\n          var d1 = angDistMod(candAngs[1], nnAng);\n          pickedAng = d0 < d1 ? candAngs[0] : candAngs[1];\n          pickedNote = 'nearest-neighbor tiebreak';\n        } else {\n          pickedAng = spans[0] >= spans[1] ? candAngs[0] : candAngs[1];\n          pickedNote = 'default tied';\n        }\n      }\n      try { console.warn('[GPY] shape detect (elongated, thin='+medThin.toFixed(2)+'m): coh='+medCoh.toFixed(2)+', longAxis='+(avgAng*180\/Math.PI).toFixed(1)+'\u00b0, spans='+spans[0].toFixed(1)+'\/'+spans[1].toFixed(1)+'m \u2192 AB '+(pickedAng*180\/Math.PI).toFixed(1)+'\u00b0 ('+pickedNote+')'); } catch(_){}\n      return {\n        ux: Math.cos(pickedAng), uy: Math.sin(pickedAng),\n        source: 'polygon-shapes (elongated\/' + pickedNote + ')'\n      };\n    }\n    \/\/ SQUARE cells: edge histogram of ALL edges, find peaks, pick by field span.\n    var nB = 180;\n    var hist = new Float64Array(nB);\n    for(var pI=0; pI<polyIndices.length; pI++){\n      var rings = polyData[polyIndices[pI]] ? polyData[polyIndices[pI]].rings : null;\n      if(!rings ? true : rings.length === 0) continue;\n      var rr = rings[0];\n      if(!rr ? true : rr.mx.length < 3) continue;\n      for(var vi=0; vi<rr.mx.length - 1; vi++){\n        var dx = rr.mx[vi+1] - rr.mx[vi];\n        var dy = rr.my[vi+1] - rr.my[vi];\n        var len = Math.sqrt(dx*dx + dy*dy);\n        if(len < 1e-9) continue;\n        var ad = Math.atan2(dy, dx) * 180 \/ Math.PI;\n        if(ad < 0) ad += 180;\n        if(ad >= 180) ad -= 180;\n        var bn = Math.floor(ad);\n        if(bn >= nB) bn = nB - 1;\n        hist[bn] += len;\n      }\n    }\n    \/\/ Find peaks above 30% of max, with \u00b15\u00b0 local maximum check (circular).\n    var maxH = 0;\n    for(var k=0; k<nB; k++) if(hist[k] > maxH) maxH = hist[k];\n    if(maxH <= 0) return null;\n    var thresh = maxH * 0.3;\n    var peaks = [];\n    for(var kk=0; kk<nB; kk++){\n      if(hist[kk] < thresh) continue;\n      var isPeak = true;\n      for(var dd=-5; dd<=5; dd++){\n        if(dd === 0) continue;\n        var ni = (kk + dd + nB) % nB;\n        if(hist[ni] > hist[kk]){ isPeak = false; break; }\n      }\n      if(isPeak) peaks.push(kk);\n    }\n    if(peaks.length === 0) return null;\n    \/\/ For each peak angle, compute field span along that direction. Pick max.\n    var bestSpan = -1, bestAng = peaks[0] * Math.PI \/ 180;\n    for(var pk=0; pk<peaks.length; pk++){\n      var pAng = peaks[pk] * Math.PI \/ 180;\n      var pux = Math.cos(pAng), puy = Math.sin(pAng);\n      var minProj = Infinity, maxProj = -Infinity;\n      if(hull ? hull.x.length > 1 : false){\n        for(var hi=0; hi<hull.x.length; hi++){\n          var pr = hull.x[hi] * pux + hull.y[hi] * puy;\n          if(pr < minProj) minProj = pr;\n          if(pr > maxProj) maxProj = pr;\n        }\n        var span = maxProj - minProj;\n        if(span > bestSpan){ bestSpan = span; bestAng = pAng; }\n      }\n    }\n    return {\n      ux: Math.cos(bestAng), uy: Math.sin(bestAng),\n      source: 'polygon-shapes (edge histogram + field span)'\n    };\n  }\n  \/\/ Downsample (x,y) pairs to a spatial grid so each cell yields at most one point.\n  \/\/ Used before Hough on dense data (Trimble multi-section coverage has ~20-30\n  \/\/ polygons per machine moment, spread across the boom width) \u2014 without this the\n  \/\/ perpendicular-projection histogram smears each pass across multiple bins and\n  \/\/ the row structure washes out. Returns {xs, ys} with deduplicated points.\n  function downsampleByGrid(xs, ys, cellM){\n    if(cellM <= 0) return { xs: xs, ys: ys };\n    var seen = new Set();\n    var outX = [], outY = [];\n    for(var i=0; i<xs.length; i++){\n      var k = Math.floor(xs[i] \/ cellM) + '|' + Math.floor(ys[i] \/ cellM);\n      if(seen.has(k)) continue;\n      seen.add(k);\n      outX.push(xs[i]);\n      outY.push(ys[i]);\n    }\n    return { xs: outX, ys: outY };\n  }\n  \/\/ Score the Hough concentration at a specific angle (radians from +X) for the\n  \/\/ already-centered (cx, cy) arrays + bin parameters. Pulled out so the coarse\n  \/\/ and refined searches share code. Returns sum-of-count\u00b2 across non-empty bins\n  \/\/ of the perpendicular-axis projection.\n  function houghScoreAt(ang, cx, cy, binBuf, halfBins, binM){\n    var nBins = binBuf.length;\n    for(var br=0; br<nBins; br++) binBuf[br] = 0;\n    var ux = Math.cos(ang), uy = Math.sin(ang);\n    var n = cx.length;\n    for(var i=0; i<n; i++){\n      var ry = -cx[i] * uy + cy[i] * ux;\n      var b = Math.floor(ry \/ binM) + halfBins;\n      if(b < 0 ? true : b >= nBins) continue;\n      binBuf[b]++;\n    }\n    var score = 0;\n    for(var bs=0; bs<nBins; bs++){\n      var c = binBuf[bs];\n      if(c > 0) score += c * c;\n    }\n    return score;\n  }\n  \/\/ Axis from polygon-row periodicity (Hough-style search). Rotates centroids by\n  \/\/ every degree from 0\u00b0 to 179\u00b0, projects onto the perpendicular axis, builds a\n  \/\/ bin histogram, scores by Herfindahl concentration (sum of count\u00b2). Highest\n  \/\/ score = angle where centroids best line up into parallel rows.\n  \/\/ Steps:\n  \/\/   1. Downsample to a 6 m grid \u2014 collapses Trimble multi-section data (one poly\n  \/\/      per section per moment) so each machine moment contributes one effective\n  \/\/      point. Without this the boom-width perpendicular spread (typ. 18 m) smears\n  \/\/      adjacent passes' contributions together and Hough fails.\n  \/\/   2. Coarse search 0\u00b0-179\u00b0 at 1\u00b0 step \u2192 best integer angle.\n  \/\/   3. Refined search \u00b11\u00b0 around the coarse best at 0.1\u00b0 step \u2192 final angle.\n  \/\/   4. Log top-3 scoring angles to console for diagnostics.\n  \/\/ Beats PCA on rectangular grids whose covariance tilts off-axis (e.g., the 2024\n  \/\/ fertilizer sample where PCA gave 75\u00b0 but actual rows run at 91\u00b0).\n  function detectAxisHough(centroids){\n    if(!centroids ? true : centroids.xs.length < 20) return null;\n    var down = downsampleByGrid(centroids.xs, centroids.ys, 6.0);\n    var xs = down.xs, ys = down.ys;\n    var n = xs.length;\n    if(n < 10) return null;\n    var mx = 0, my = 0;\n    for(var i=0; i<n; i++){ mx += xs[i]; my += ys[i]; }\n    mx \/= n; my \/= n;\n    var cx = new Float64Array(n), cy = new Float64Array(n);\n    var maxR2 = 0;\n    for(var i2=0; i2<n; i2++){\n      cx[i2] = xs[i2] - mx;\n      cy[i2] = ys[i2] - my;\n      var r2 = cx[i2]*cx[i2] + cy[i2]*cy[i2];\n      if(r2 > maxR2) maxR2 = r2;\n    }\n    var binM = 5.0;\n    var halfBins = Math.ceil(Math.sqrt(maxR2) \/ binM) + 1;\n    var nBins = halfBins * 2 + 1;\n    var binBuf = new Int32Array(nBins);\n    \/\/ Coarse 1\u00b0 sweep\n    var scoresPerDeg = new Float64Array(180);\n    for(var aS=0; aS<180; aS++){\n      var ang = aS * Math.PI \/ 180;\n      scoresPerDeg[aS] = houghScoreAt(ang, cx, cy, binBuf, halfBins, binM);\n    }\n    \/\/ Top-3 for diagnostics\n    var idx = [0, 0, 0];\n    var sc = [-1, -1, -1];\n    for(var aT=0; aT<180; aT++){\n      var s = scoresPerDeg[aT];\n      if(s > sc[0]){ sc[2]=sc[1]; idx[2]=idx[1]; sc[1]=sc[0]; idx[1]=idx[0]; sc[0]=s; idx[0]=aT; }\n      else if(s > sc[1]){ sc[2]=sc[1]; idx[2]=idx[1]; sc[1]=s; idx[1]=aT; }\n      else if(s > sc[2]){ sc[2]=s; idx[2]=aT; }\n    }\n    var coarseDeg = idx[0];\n    \/\/ Refined \u00b11\u00b0 at 0.1\u00b0 step\n    var bestAng = coarseDeg * Math.PI \/ 180;\n    var bestScore = sc[0];\n    for(var step=-10; step<=10; step++){\n      if(step === 0) continue;\n      var degF = coarseDeg + step * 0.1;\n      var angF = degF * Math.PI \/ 180;\n      var sF = houghScoreAt(angF, cx, cy, binBuf, halfBins, binM);\n      if(sF > bestScore){ bestScore = sF; bestAng = angF; }\n    }\n    try {\n      console.warn('[GPY] hough top-3: ' +\n        idx[0]+'\u00b0(s='+sc[0].toFixed(0)+') \/ '+\n        idx[1]+'\u00b0(s='+sc[1].toFixed(0)+') \/ '+\n        idx[2]+'\u00b0(s='+sc[2].toFixed(0)+') \u00b7 ' +\n        'refined to ' + (bestAng*180\/Math.PI).toFixed(2) + '\u00b0 \u00b7 downsampled '+xs.length+' from '+centroids.xs.length);\n    } catch(_){}\n    return {\n      ux: Math.cos(bestAng), uy: Math.sin(bestAng),\n      source: 'polygon-rows-hough'\n    };\n  }\n  \/\/ Axis from PCA principal eigenvector of centroid covariance. Returns null when\n  \/\/ the principal axis is ambiguous (near-equal eigenvalues, ratio < 1.2). Best on\n  \/\/ polygon centroids where the row arrangement creates a strong axis. Weak on\n  \/\/ uniform point clouds where variance is similar in both directions.\n  function detectAxisFromPCA(centroids){\n    if(!centroids ? true : centroids.xs.length < 5) return null;\n    var xs = centroids.xs, ys = centroids.ys;\n    var m = xs.length;\n    var mxs = 0, mys = 0;\n    for(var p=0; p<m; p++){ mxs += xs[p]; mys += ys[p]; }\n    mxs \/= m; mys \/= m;\n    var sxx = 0, syy = 0, sxy = 0;\n    for(var q=0; q<m; q++){\n      var dx = xs[q] - mxs, dy = ys[q] - mys;\n      sxx += dx*dx; syy += dy*dy; sxy += dx*dy;\n    }\n    var tr = sxx + syy;\n    var det = sxx * syy - sxy * sxy;\n    var disc = Math.sqrt(Math.max(0, tr*tr - 4 * det));\n    var l1 = (tr + disc) * 0.5;\n    var l2 = (tr - disc) * 0.5;\n    var ratio = l2 > 1e-12 ? l1 \/ l2 : Infinity;\n    if(ratio <= 1.2) return null;\n    var ang = 0.5 * Math.atan2(2 * sxy, sxx - syy);\n    return { ux: Math.cos(ang), uy: Math.sin(ang), source: 'pca' };\n  }\n  \/\/ Axis from the single longest edge of the concave hull. Cheap, deterministic,\n  \/\/ works on any hull with at least 3 vertices. Useful for point data where the\n  \/\/ field boundary outlines the operation more reliably than PCA on the points.\n  function detectAxisFromLongestHullEdge(hull){\n    if(!hull ? true : hull.x.length <= 2) return null;\n    var X = hull.x, Y = hull.y;\n    var n = X.length - 1;\n    var bestLen2 = 0;\n    var bestEx = 1, bestEy = 0;\n    for(var i=0; i<n; i++){\n      var ex = X[i+1] - X[i];\n      var ey = Y[i+1] - Y[i];\n      var l2e = ex*ex + ey*ey;\n      if(l2e > bestLen2){ bestLen2 = l2e; bestEx = ex; bestEy = ey; }\n    }\n    var bestLen = Math.sqrt(bestLen2);\n    if(bestLen <= 1e-9) return null;\n    return { ux: bestEx \/ bestLen, uy: bestEy \/ bestLen, source: 'longest-hull-edge' };\n  }\n  \/\/ Axis from sequential point pairs \u2014 yield-monitor \/ harvest tracks come in time\n  \/\/ order, so consecutive points trace the actual machine path. Uses doubled-angle\n  \/\/ circular statistics so back-and-forth passes contribute coherently to one axis.\n  \/\/ Returns null when the consecutive pairs don't cohere on a single direction\n  \/\/ (e.g., grid soil samples in arbitrary order, or scattered points with no path).\n  function detectAxisFromPointSequence(xs, ys){\n    if(!xs ? true : xs.length < 10) return null;\n    var n = xs.length;\n    var dists = new Float64Array(n - 1);\n    for(var i=0; i<n-1; i++){\n      var dxA = xs[i+1] - xs[i];\n      var dyA = ys[i+1] - ys[i];\n      dists[i] = Math.sqrt(dxA*dxA + dyA*dyA);\n    }\n    var sortedD = Array.prototype.slice.call(dists).sort(function(a, b){ return a - b; });\n    var medD = sortedD[sortedD.length >> 1];\n    if(medD < 1e-9) return null;\n    \/\/ Reject across-field jumps (> 5x median) AND tiny GPS jitter (< 0.1x median).\n    \/\/ Both add noise without signal.\n    var maxD = medD * 5;\n    var minD = medD * 0.1;\n    var sumX = 0, sumY = 0, sumW = 0;\n    for(var j=0; j<n-1; j++){\n      var d = dists[j];\n      if(d > maxD ? true : d < minD) continue;\n      var ndx = (xs[j+1] - xs[j]) \/ d;\n      var ndy = (ys[j+1] - ys[j]) \/ d;\n      \/\/ Double the angle: (cos 2\u03b8, sin 2\u03b8) = (ndx\u00b2 - ndy\u00b2, 2\u00b7ndx\u00b7ndy). This makes\n      \/\/ 0\u00b0 and 180\u00b0 map to the same point on the unit circle \u2014 back-and-forth\n      \/\/ passes reinforce instead of cancelling.\n      var doubX = ndx*ndx - ndy*ndy;\n      var doubY = 2 * ndx * ndy;\n      sumX += d * doubX;\n      sumY += d * doubY;\n      sumW += d;\n    }\n    if(sumW < 1e-9) return null;\n    var avgX = sumX \/ sumW;\n    var avgY = sumY \/ sumW;\n    \/\/ Coherence = magnitude of the average doubled vector. 1 = all pairs same axis;\n    \/\/ 0 = uniformly distributed across all directions. Reject if too scattered.\n    var coh = Math.sqrt(avgX*avgX + avgY*avgY);\n    if(coh < 0.3) return null;\n    var angDouble = Math.atan2(avgY, avgX);\n    var ang = 0.5 * angDouble;\n    return { ux: Math.cos(ang), uy: Math.sin(ang), source: 'point-sequence' };\n  }\n  \/\/ Determine the dominant heading (AB-line direction) for a field. Mode-aware:\n  \/\/   Point data: sequence-direction \u2192 hull edge \u2192 PCA. Yield-monitor \/ harvest\n  \/\/     trace points come in time order, so consecutive pairs trace the machine\n  \/\/     path directly. Hull edge is next-best (boundary outlines the operation).\n  \/\/     PCA on uniform point clouds is weak \u2014 square fields confuse it.\n  \/\/   Polygon data: PCA \u2192 hull edge. The row arrangement of as-applied polygons\n  \/\/     creates a strong principal axis; PCA captures it cleanly.\n  \/\/ Returns { ux, uy, headingRad, source } in mercator coords (heading from +X\n  \/\/ counter-clockwise), or null when no method produced a confident answer.\n  function detectFieldAxis(hull, centroids, mode){\n    var ordered = (mode === 'point')\n      ? ['sequence', 'hull-edge', 'pca']\n      : ['shapes', 'hough', 'pca', 'hull-edge'];\n    for(var s=0; s<ordered.length; s++){\n      var src = ordered[s];\n      var got = null;\n      if(src === 'sequence') got = detectAxisFromPointSequence(centroids ? centroids.xs : null, centroids ? centroids.ys : null);\n      else if(src === 'shapes') got = detectAxisFromPolygonShapes(centroids ? centroids.indices : null, hull);\n      else if(src === 'hough') got = detectAxisHough(centroids);\n      else if(src === 'pca') got = detectAxisFromPCA(centroids);\n      else if(src === 'hull-edge') got = detectAxisFromLongestHullEdge(hull);\n      if(got){\n        got.headingRad = Math.atan2(got.uy, got.ux);\n        return got;\n      }\n    }\n    return null;\n  }\n  \/\/ Extract AB-line passes from the actual polygon centroid arrangement. The polygons\n  \/\/ ARE the as-applied operation \u2014 their grouping into rows tells us exactly where\n  \/\/ each pass was driven. Algorithm:\n  \/\/   1. Rotate centroids so axis aligns with +X.\n  \/\/   2. Build a 1D histogram of the perpendicular-axis (rotated Y) projection.\n  \/\/   3. Find peaks \u2014 each peak is one pass center.\n  \/\/   4. For each pass center, gather centroids within \u00bd wMHint and use their\n  \/\/      X-extent as the pass length. Rotate endpoints back.\n  \/\/ Returns { lines: [...], rowSpacingMerc: number }. rowSpacingMerc is the median\n  \/\/ adjacent-peak spacing, useful for auto-tuning equipment width.\n  function extractABLinesFromCentroids(centroids, axis, wMHint){\n    var empty = { lines: [], rowSpacingMerc: 0 };\n    if(!axis) return empty;\n    if(!centroids ? true : centroids.xs.length < 10) return empty;\n    var xs = centroids.xs, ys = centroids.ys;\n    var n = xs.length;\n    var ux = axis.ux, uy = axis.uy;\n    var rxs = new Float32Array(n);\n    var rys = new Float32Array(n);\n    var ryMin = Infinity, ryMax = -Infinity;\n    for(var i=0; i<n; i++){\n      var rx = xs[i] * ux + ys[i] * uy;\n      var ry = -xs[i] * uy + ys[i] * ux;\n      rxs[i] = rx; rys[i] = ry;\n      if(ry < ryMin) ryMin = ry; if(ry > ryMax) ryMax = ry;\n    }\n    var cosLat = Math.cos((typeof latC === 'number' ? latC : 0) * Math.PI \/ 180);\n    if(!(cosLat > 0)) cosLat = 1;\n    \/\/ Hint converted to mercator. wMHint is real-meter; mercator = real\/cosLat.\n    var wMHintMerc = wMHint > 0 ? wMHint \/ cosLat : Math.max(1, (ryMax - ryMin) \/ 30);\n    var binM = wMHintMerc \/ 4;\n    if(binM < 1e-6) binM = 1;\n    var spanY = ryMax - ryMin;\n    var nBins = Math.max(8, Math.ceil(spanY \/ binM) + 1);\n    var hist = new Int32Array(nBins);\n    for(var j=0; j<n; j++){\n      var bi = Math.floor((rys[j] - ryMin) \/ binM);\n      if(bi < 0) bi = 0; if(bi >= nBins) bi = nBins - 1;\n      hist[bi]++;\n    }\n    var maxH = 0;\n    for(var k=0; k<nBins; k++) if(hist[k] > maxH) maxH = hist[k];\n    var thresh = maxH * 0.10;\n    \/\/ Local maxima within \u00b13 bins (\u2248 \u00be wM half-width). Catches sharp peaks without\n    \/\/ duplicating adjacent ones from a smeared row.\n    var peaks = [];\n    for(var k2=0; k2<nBins; k2++){\n      if(hist[k2] < thresh) continue;\n      var isPeak = true;\n      for(var d=-3; d<=3; d++){\n        var ni = k2 + d;\n        if(ni < 0 ? true : ni >= nBins) continue;\n        if(ni === k2) continue;\n        if(hist[ni] > hist[k2]){ isPeak = false; break; }\n      }\n      if(isPeak) peaks.push(ryMin + (k2 + 0.5) * binM);\n    }\n    peaks.sort(function(a, b){ return a - b; });\n    \/\/ De-duplicate peaks closer than \u00bd wM (smeared adjacent bins above threshold).\n    var dedup = [];\n    var minSep = wMHintMerc * 0.5;\n    for(var pI=0; pI<peaks.length; pI++){\n      if(pI === 0 ? true : peaks[pI] - dedup[dedup.length - 1] > minSep){\n        dedup.push(peaks[pI]);\n      }\n    }\n    \/\/ Build lines and measure adjacent spacing for the rowSpacing return value.\n    var lines = [];\n    var halfBand = wMHintMerc * 0.5;\n    for(var r=0; r<dedup.length; r++){\n      var rowY = dedup[r];\n      var minRx = Infinity, maxRx = -Infinity;\n      for(var j2=0; j2<n; j2++){\n        if(Math.abs(rys[j2] - rowY) > halfBand) continue;\n        if(rxs[j2] < minRx) minRx = rxs[j2];\n        if(rxs[j2] > maxRx) maxRx = rxs[j2];\n      }\n      if(!(maxRx > minRx)) continue;\n      var x0 = minRx * ux - rowY * uy;\n      var y0 = minRx * uy + rowY * ux;\n      var x1 = maxRx * ux - rowY * uy;\n      var y1 = maxRx * uy + rowY * ux;\n      lines.push({ x0: x0, y0: y0, x1: x1, y1: y1, headingRad: axis.headingRad });\n    }\n    var rowSpacingMerc = 0;\n    if(dedup.length >= 2){\n      var gaps = [];\n      for(var g=1; g<dedup.length; g++) gaps.push(dedup[g] - dedup[g - 1]);\n      gaps.sort(function(a, b){ return a - b; });\n      rowSpacingMerc = gaps[gaps.length >> 1];  \/\/ median\n    }\n    return { lines: lines, rowSpacingMerc: rowSpacingMerc };\n  }\n  \/\/ Synthesize parallel AB-line passes that cover a single field hull, spaced at the\n  \/\/ implement width. The axis is the dominant heading for this field \u2014 either an\n  \/\/ operator-drawn sibling AB line or the longest hull edge. Algorithm:\n  \/\/   1. Rotate the hull so the axis aligns with +X.\n  \/\/   2. Scan horizontal lines across the rotated bbox at `wM` spacing.\n  \/\/   3. For each scan, find the leftmost\/rightmost intersection with the rotated\n  \/\/      hull. Inset by \u00bd wM so the implement bar fits inside the field.\n  \/\/   4. Rotate the endpoints back into mercator coords.\n  \/\/ Returns an array of { x0, y0, x1, y1, headingRad } pass segments. Empty if the\n  \/\/ hull is too small or the axis is null.\n  function synthesizeABLines(hull, axis, wM){\n    if(!hull) return [];\n    if(!axis) return [];\n    if(!(wM > 0)) return [];\n    var cosLat = Math.cos((typeof latC === 'number' ? latC : 0) * Math.PI \/ 180);\n    if(!(cosLat > 0)) cosLat = 1;\n    var spacingMerc = wM \/ cosLat;\n    var insetMerc = wM * 0.5 \/ cosLat;\n    var ux = axis.ux, uy = axis.uy;\n    var n = hull.x.length - 1;\n    \/\/ Rotate hull: rx = x*ux + y*uy ; ry = -x*uy + y*ux\n    var rxs = new Float32Array(n + 1);\n    var rys = new Float32Array(n + 1);\n    var yMin = Infinity, yMax = -Infinity;\n    for(var i=0; i<=n; i++){\n      var rx = hull.x[i] * ux + hull.y[i] * uy;\n      var ry = -hull.x[i] * uy + hull.y[i] * ux;\n      rxs[i] = rx;\n      rys[i] = ry;\n      if(ry < yMin) yMin = ry;\n      if(ry > yMax) yMax = ry;\n    }\n    var lines = [];\n    var halfSp = spacingMerc * 0.5;\n    for(var yScan = yMin + halfSp; yScan <= yMax - halfSp + 1e-6; yScan += spacingMerc){\n      var intersections = [];\n      for(var ei=0; ei<n; ei++){\n        var ax = rxs[ei], ay = rys[ei];\n        var bx = rxs[ei+1], by = rys[ei+1];\n        if((ay - yScan) * (by - yScan) < 0){\n          var t = (yScan - ay) \/ (by - ay);\n          intersections.push(ax + t * (bx - ax));\n        }\n      }\n      if(intersections.length < 2) continue;\n      intersections.sort(function(a, b){ return a - b; });\n      \/\/ For concave hulls a scan may produce more than 2 intersections (enter \/ exit \/\n      \/\/ enter \/ exit). Take only the outer extents \u2014 keeps the synthesized pass simple.\n      \/\/ If the gap between innermost intersections is significant we lose some interior\n      \/\/ unworked stripes; acceptable for the simulation since real machines drive\n      \/\/ continuous passes too.\n      var xL = intersections[0] + insetMerc;\n      var xR = intersections[intersections.length - 1] - insetMerc;\n      if(xR - xL < spacingMerc * 0.2) continue;\n      var x0 = xL * ux - yScan * uy;\n      var y0 = xL * uy + yScan * ux;\n      var x1 = xR * ux - yScan * uy;\n      var y1 = xR * uy + yScan * ux;\n      lines.push({ x0: x0, y0: y0, x1: x1, y1: y1, headingRad: axis.headingRad });\n    }\n    return lines;\n  }\n  \/\/ Operator-supplied field boundary, when one is loaded alongside yield \/ as-applied\n  \/\/ data. Returns an array of hull objects `[{x, y, holes:[{x,y}, ...]}]` in mercator\n  \/\/ coords (relative to wmCx\/wmCy, with Y flipped to canvas convention), one hull per\n  \/\/ polygon feature. Each polygon's FIRST ring becomes the outer; subsequent rings\n  \/\/ become holes. Multi-polygon boundaries (multiple disjoint fields in one file) are\n  \/\/ returned as separate hulls.\n  \/\/\n  \/\/ A boundary dataset is preferred over data-driven detection because it carries the\n  \/\/ operator's exact intent (cadastral \/ agronomic field outline + non-productive zones\n  \/\/ like trees, ponds, refused strips). Data-driven detection can't replicate this\n  \/\/ because the combine often harvests THROUGH excluded zones, leaving them with\n  \/\/ normal yield density \u2014 the only signal that says \"not field\" is in the operator's\n  \/\/ boundary file.\n  \/\/\n  \/\/ Returns [] when no boundary is attached to the active dataset. Caller falls back\n  \/\/ to the grid-based hull detector in that case.\n  function findFieldBoundaryHulls(activeDs){\n    if(!activeDs) return [];\n    if(!datasets ? true : datasets.length === 0) return [];\n    var parentId = activeDs.parentId;\n    var hulls = [];\n    for(var di=0; di<datasets.length; di++){\n      var d = datasets[di];\n      if(d.id === activeDs.id) continue;\n      if(!d.isBoundary) continue;\n      if(d.geomType !== 'polygon') continue;\n      \/\/ Attach this boundary if: (a) activeDs.parentId points at it, (b) we share\n      \/\/ the same parent, or (c) activeDs is the parent of the boundary.\n      var attached = (parentId ? d.id === parentId : false)\n        ? true\n        : ((parentId ? d.parentId === parentId : false) ? true : d.parentId === activeDs.id);\n      if(!attached) continue;\n      for(var fi=0; fi<d.features.length; fi++){\n        var g = d.features[fi].geometry;\n        if(!g) continue;\n        var polys;\n        if(g.type === 'Polygon') polys = [g.coordinates];\n        else if(g.type === 'MultiPolygon') polys = g.coordinates;\n        else continue;\n        for(var pi=0; pi<polys.length; pi++){\n          var rings = polys[pi];\n          if(!rings ? true : rings.length === 0) continue;\n          function ringToF32(ring){\n            var n = ring.length;\n            var xa = new Float32Array(n);\n            var ya = new Float32Array(n);\n            for(var pj=0; pj<n; pj++){\n              xa[pj] = lngToWmX(ring[pj][0]) - wmCx;\n              ya[pj] = -(latToWmY(ring[pj][1]) - wmCy);\n            }\n            \/\/ Force closed (first == last)\n            if(n > 0 ? (xa[0] !== xa[n-1] ? true : ya[0] !== ya[n-1]) : false){\n              var xa2 = new Float32Array(n + 1);\n              var ya2 = new Float32Array(n + 1);\n              for(var pk=0; pk<n; pk++){ xa2[pk] = xa[pk]; ya2[pk] = ya[pk]; }\n              xa2[n] = xa[0]; ya2[n] = ya[0];\n              return { x: xa2, y: ya2 };\n            }\n            return { x: xa, y: ya };\n          }\n          var outer = ringToF32(rings[0]);\n          if(!outer ? true : outer.x.length < 4) continue;\n          outer.holes = [];\n          for(var hi=1; hi<rings.length; hi++){\n            var hr = rings[hi];\n            if(!hr ? true : hr.length < 4) continue;\n            outer.holes.push(ringToF32(hr));\n          }\n          hulls.push(outer);\n        }\n      }\n      \/\/ First matching boundary dataset wins \u2014 typical files have only one anyway.\n      if(hulls.length) break;\n    }\n    return hulls;\n  }\n  \/\/ Find sibling LineString datasets \u2014 Trimble exports \"Swaths\" alongside coverage\n  \/\/ polygons in the same parent group. These are operator-defined AB lines: the\n  \/\/ most reliable navigation source. Returns an array of polylines in mercator coords\n  \/\/ (relative to wmCx\/wmCy) so the calling code can use them directly without\n  \/\/ re-projecting. Each entry: { xs: Float32Array, ys: Float32Array }. Empty array\n  \/\/ means no usable siblings.\n  function findSiblingABLines(activeDs){\n    if(!activeDs) return [];\n    if(!datasets ? true : datasets.length === 0) return [];\n    var parentId = activeDs.parentId;\n    var lines = [];\n    for(var di=0; di<datasets.length; di++){\n      var d = datasets[di];\n      if(d.id === activeDs.id) continue;\n      if(d.geomType !== 'line') continue;\n      \/\/ Same parent group OR the active dataset itself sits under a line group:\n      \/\/ accept either to catch single-parent groupings as well as side-by-side layouts.\n      var sameParent = (parentId ? d.parentId === parentId : false) ? true : (d.parentId === activeDs.id);\n      if(!sameParent) continue;\n      for(var fi=0; fi<d.features.length; fi++){\n        var g = d.features[fi].geometry;\n        if(!g) continue;\n        var nested;\n        if(g.type === 'LineString') nested = [g.coordinates];\n        else if(g.type === 'MultiLineString') nested = g.coordinates;\n        else continue;\n        for(var li=0; li<nested.length; li++){\n          var ring = nested[li];\n          if(!ring ? true : ring.length < 2) continue;\n          var xs = new Float32Array(ring.length);\n          var ys = new Float32Array(ring.length);\n          for(var pj=0; pj<ring.length; pj++){\n            xs[pj] = lngToWmX(ring[pj][0]) - wmCx;\n            ys[pj] = latToWmY(ring[pj][1]) - wmCy;\n          }\n          lines.push({ xs: xs, ys: ys });\n        }\n      }\n    }\n    return lines;\n  }\n  function setupPlayback(ds){\n    if(playback.raf){ cancelAnimationFrame(playback.raf); playback.raf = null; }\n    playback.active = false;\n    playback.lastT = 0;\n    playback.idx = values.length;\n    playback.idxFloat = values.length;\n    playback.smoothedHeading = null;\n    playback.smoothedX = null;\n    playback.smoothedY = null;\n    playback.turnAct = false;\n    playback.turnFrac = 0;\n    playback.turnBezier = null;\n    playback.order = null;\n    playback.orderSource = null;\n    playback.keptMask = null;  \/\/ reset so the previous dataset's mask never bleeds into this one's totals\n    \/\/ Overlay-state reset \u2014 without this, switching datasets leaves the PREVIOUS field's\n    \/\/ hulls \/ axes \/ AB-lines \/ sprite path on the canvas as ghost outlines.\n    playback.fieldHulls = [];\n    playback.fieldAxes = [];\n    playback.fieldClusters = [];\n    playback.abSiblingLines = [];\n    playback.abLines = { perCluster: [], flat: [], rowSpacingMerc: 0 };\n    playback.polygonRowSpacingM = 0;\n    playback.headlandMask = null;\n    playback.machineXY = null;\n    playback.boundaries = null;\n    playback.spritePathX = null;\n    playback.spritePathY = null;\n    playback.smoothPathX = null;\n    playback.smoothPathY = null;\n    playback.passKeptMask = null;\n    playback.wideSkipN = null;\n    var mainEl = root.querySelector('.gpy-main');\n    var pbEl = $('#gpy-pb');\n    \/\/ Enabled for any non-boundary dataset with enough features to replay (polygon, point, line).\n    \/\/ Boundary datasets are pure outlines \u2014 replaying them has no meaning.\n    \/\/ The \"Show machine path\" toggle does NOT hide this bar \u2014 playback still works, the toggle\n    \/\/ only controls whether the simulated sprite + trail + swath are rendered on top.\n    if(currentIsBoundary || values.length < 5){\n      if(mainEl) mainEl.classList.remove('has-playback');\n      if(pbEl) pbEl.classList.remove('show');\n      return;\n    }\n    if(mainEl) mainEl.classList.add('has-playback');\n    if(pbEl) pbEl.classList.add('show');\n    \/\/ Compute a realistic playback order (timestamp \u2192 ID \u2192 nearest-neighbor walk)\n    playback.order = computePlaybackOrder();\n    var op = detectOp(ds);\n    playback.dieselLPerHa = op.dieselLPerHa;\n    playback.opLabel = op.label;\n    playback.overlapStrategy = op.overlapStrategy;\n    playback.turnarounds = countTurnarounds();\n    playback.cumM = computeCumulativeDistance();\n    \/\/ Item 3+4: build kept[] mask based on overlap strategy. For \"first\" (seeders), polygons\n    \/\/ whose bbox overlaps an EARLIER polygon (in playback\/path order) are skipped from totals.\n    \/\/ For \"sum\" (fertilizing \/ spraying), all polygons count cumulatively (current behavior).\n    playback.keptMask = computeKeptMask(playback.overlapStrategy);\n    \/\/ Step 1: pick implement width. Priority order (highest wins):\n    \/\/   1) user manual override (Display-card input)\n    \/\/   2) explicit width attribute on features (Swth_Wdth_, BoomWidth, Width_m, etc.)\n    \/\/   3) timestamp-group detection (multi-section spread = boom width)\n    \/\/   4) line-geometry detection (perpendicular spacing between parallel passes)\n    \/\/   5) OP_WIDTH_M table, inflated for large fields (large-farm machines are bigger)\n    var attrWM = detectWidthFromAttributes();\n    var detectedWM = detectImplementWidth();\n    var pixelWM = detectImplementWidthFromPolygonPixels();\n    var lineWM = detectLineWidth();\n    var tableWM = equipmentWidthM(op.label);\n    \/\/ Field-area inflation: bigger fields tend to use bigger machines, but only\n    \/\/ mildly. Tightened from earlier values (was 1.4\u00d7 for >200 ha) because the\n    \/\/ table defaults are now typical-farm sized and don't need much upward push.\n    var fieldHa = (ds ? ds.areaHa : 0) > 0 ? ds.areaHa : bboxAreaHaFallback();\n    var areaInflation = 1.0;\n    if(fieldHa > 200) areaInflation = 1.25;\n    else if(fieldHa > 100) areaInflation = 1.1;\n    else if(fieldHa < 5) areaInflation = 0.7;\n    var inflatedTableWM = tableWM * areaInflation;\n    var pickedWM = inflatedTableWM;\n    var pickedSource = areaInflation > 1.05 ? 'large-farm default (' + fieldHa.toFixed(0) + ' ha)'\n                                              : (areaInflation < 0.95 ? 'small-field default' : 'op default');\n    if(lineWM ? (lineWM >= 2 ? lineWM <= 100 : false) : false){\n      pickedWM = lineWM;\n      pickedSource = 'detected (line spacing)';\n    }\n    if(detectedWM ? (detectedWM >= 2 ? detectedWM <= 60 : false) : false){\n      var ratio = detectedWM \/ tableWM;\n      if(ratio >= 0.4 ? ratio <= 3.0 : false){\n        pickedWM = detectedWM;\n        pickedSource = 'detected (multi-section)';\n      }\n    }\n    if(pixelWM ? (pixelWM >= 2 ? pixelWM <= 100 : false) : false){\n      pickedWM = pixelWM;\n      pickedSource = 'detected (polygon pixels)';\n    }\n    if(attrWM ? (attrWM >= 2 ? attrWM <= 60 : false) : false){\n      pickedWM = attrWM;\n      pickedSource = 'file attribute';\n    }\n    \/\/ Apply per-op realistic maximum cap. File attributes sometimes report total\n    \/\/ boom span (e.g., a folded 60 m boom that only sprays 30 m at a time) and\n    \/\/ that yields visually huge swaths during playback. Cap to the realistic\n    \/\/ max for the operation type so the machine doesn't appear to spread\/harvest\n    \/\/ impossibly wide areas.\n    var maxWM = equipmentWidthMaxM(op.label);\n    if(pickedWM > maxWM){\n      try { console.warn('[GPY] equipment width '+pickedWM.toFixed(1)+'m (' + pickedSource + ') exceeds realistic max for ' + op.label + ' \u2014 capped to ' + maxWM + 'm'); } catch(_){}\n      pickedWM = maxWM;\n      pickedSource = pickedSource + ' [capped at ' + maxWM + 'm]';\n    }\n    \/\/ Manual override applies LAST so the user can deliberately exceed the cap.\n    if(playback.userWidth ? playback.userWidth > 0 : false){\n      pickedWM = playback.userWidth;\n      pickedSource = 'manual override';\n    }\n    playback.implementWidth = pickedWM;\n    playback.implementWidthSource = pickedSource;\n    playback.implementWidthDetected = detectedWM;\n    playback.implementWidthAttr = attrWM;\n    playback.implementWidthTable = tableWM;\n    \/\/ Field boundary hulls \u2014 one concave hull per spatial cluster. A coverage file\n    \/\/ may contain multiple disjoint fields (e.g., \u041b\u0417-017 + \u041b\u0411-006); clustering by\n    \/\/ proximity keeps each field's hull separate so the U-turn clamp doesn't treat\n    \/\/ the empty space between fields as \"inside the field\". Cluster gap threshold =\n    \/\/ 3\u00d7 equipment width: within-field pass gaps (< wM) merge; field-to-field gaps\n    \/\/ (tens to hundreds of meters) split. Used by setupTurnaround, the headland-pass\n    \/\/ detector, and the canvas overlay.\n    \/\/ Field hulls + field axes \u2014 one entry per spatial cluster. The hull is the worked\n    \/\/ area; the axis is the dominant AB-line heading (longest hull edge, with PCA\n    \/\/ fallback) that drives the synthesized navigation path. Stored as parallel arrays\n    \/\/ so hull[i] and axis[i] always refer to the same field.\n    var _hullsBuild = (function(){\n      var xs = [];\n      var ys = [];\n      var featIdx = [];  \/\/ map from xs\/ys index -> original feature index\n      if(values ? values.length : false){\n        for(var fI=0; fI<values.length; fI++){\n          var cx = featCx(fI), cy = featCy(fI);\n          if(isFinite(cx) ? isFinite(cy) : false){\n            xs.push(cx); ys.push(cy); featIdx.push(fI);\n          }\n        }\n      }\n      if(xs.length < 4) return { hulls: [], axes: [], clusters: [] };\n      \/\/ Hull alpha: for polygon \/ line modes the implement-width-derived alpha\n      \/\/ (\u2248 swath) is correct because passes are dense. For POINT data (soil\n      \/\/ sampling, sparse yield) inter-point spacing is much larger than any\n      \/\/ implement width, so we'd build a hull with disconnected pieces and\n      \/\/ concaveHullKnn would return null. Detect mode === 'point' and size\n      \/\/ alpha to the median nearest-neighbour spacing \u00d7 1.4 so adjacent points\n      \/\/ are guaranteed to connect.\n      var alphaM, gapM;\n      if(mode === 'point'){\n        var cosLatH = Math.cos((typeof latC === 'number' ? latC : 0) * Math.PI \/ 180);\n        if(!(cosLatH > 0)) cosLatH = 1;\n        \/\/ Sample up to 50 points \u00d7 full set, find nearest neighbour for each.\n        var sampleN = Math.min(50, xs.length);\n        var stride = Math.max(1, Math.floor(xs.length \/ sampleN));\n        var nnD = [];\n        for(var pi=0; pi<xs.length; pi+=stride){\n          var best = Infinity;\n          for(var pj=0; pj<xs.length; pj++){\n            if(pj === pi) continue;\n            var dxN = xs[pi] - xs[pj], dyN = ys[pi] - ys[pj];\n            var dd = dxN*dxN + dyN*dyN;\n            if(dd < best) best = dd;\n          }\n          if(isFinite(best)) nnD.push(Math.sqrt(best) * cosLatH);\n        }\n        nnD.sort(function(a,b){ return a-b; });\n        var medianNN = nnD.length ? nnD[Math.floor(nnD.length\/2)] : 50;\n        \/\/ Two regimes:\n        \/\/   Sparse (< 300 pts, soil-sample-like): alpha = NN \u00d7 1.4. Buffered\n        \/\/     convex hull is used downstream, so this alpha mainly drives gapM.\n        \/\/   Dense (\u2265 300 pts, yield \/ NDVI \/ scan): NN is tiny (1-2 m along\n        \/\/     combine track), but adjacent passes are 6-12 m apart. Use\n        \/\/     max(NN \u00d7 1.4, implement_width \u00d7 0.9) so concaveHullKnn bridges\n        \/\/     inter-pass gaps without disconnecting the hull into strips.\n        var nnAlpha = medianNN * 1.4;\n        if(xs.length >= 300){\n          var implAlpha = pickedWM > 0 ? pickedWM * 0.9 : 10;\n          alphaM = nnAlpha > implAlpha ? nnAlpha : implAlpha;\n        } else {\n          alphaM = nnAlpha;\n        }\n        if(!isFinite(alphaM) ? true : alphaM <= 0) alphaM = 50;\n        gapM = alphaM * 4;\n      } else {\n        alphaM = pickedWM > 0 ? pickedWM * 0.9 : 10;\n        gapM = pickedWM > 0 ? pickedWM * 3 : 30;\n      }\n      var clusters = clusterCentroidsByProximity(xs, ys, gapM);\n      for(var cI0=0; cI0<clusters.length; cI0++){\n        var ci0 = clusters[cI0];\n        var mapped = new Array(ci0.indices.length);\n        for(var im=0; im<ci0.indices.length; im++) mapped[im] = featIdx[ci0.indices[im]];\n        ci0.indices = mapped;\n      }\n      var hulls = [];\n      var axes = [];\n      var keptClusters = [];\n      \/\/ Prefer operator-supplied boundary when one is attached. It carries exact\n      \/\/ outer + hole geometry \u2014 far more accurate than any data-driven detection.\n      \/\/ We still build clusters (and axes per cluster) from the data so other\n      \/\/ playback machinery has something to work with; but we ASSIGN each data\n      \/\/ cluster to its containing boundary hull (matched by bbox overlap), so the\n      \/\/ hull array length stays in sync with the cluster array.\n      var boundaryHulls = findFieldBoundaryHulls(ds);\n      if(boundaryHulls.length){\n        try { console.warn('[GPY] using operator-supplied boundary: ' + boundaryHulls.length + ' polygon(s)'); } catch(_){}\n        for(var cI=0; cI<clusters.length; cI++){\n          var c = clusters[cI];\n          if(c.xs.length < 4) continue;\n          \/\/ Pick the boundary hull whose bbox most overlaps this cluster.\n          var clMinX = Infinity, clMaxX = -Infinity, clMinY = Infinity, clMaxY = -Infinity;\n          for(var ck=0; ck<c.xs.length; ck++){\n            if(c.xs[ck] < clMinX) clMinX = c.xs[ck];\n            if(c.xs[ck] > clMaxX) clMaxX = c.xs[ck];\n            if(c.ys[ck] < clMinY) clMinY = c.ys[ck];\n            if(c.ys[ck] > clMaxY) clMaxY = c.ys[ck];\n          }\n          var bestHull = null, bestArea = -1;\n          for(var bh=0; bh<boundaryHulls.length; bh++){\n            var bH = boundaryHulls[bh];\n            var bMinX = Infinity, bMaxX = -Infinity, bMinY = Infinity, bMaxY = -Infinity;\n            for(var bk=0; bk<bH.x.length-1; bk++){\n              if(bH.x[bk] < bMinX) bMinX = bH.x[bk];\n              if(bH.x[bk] > bMaxX) bMaxX = bH.x[bk];\n              if(bH.y[bk] < bMinY) bMinY = bH.y[bk];\n              if(bH.y[bk] > bMaxY) bMaxY = bH.y[bk];\n            }\n            var iMinX = clMinX > bMinX ? clMinX : bMinX;\n            var iMaxX = clMaxX < bMaxX ? clMaxX : bMaxX;\n            var iMinY = clMinY > bMinY ? clMinY : bMinY;\n            var iMaxY = clMaxY < bMaxY ? clMaxY : bMaxY;\n            var iw = iMaxX - iMinX;\n            var ih = iMaxY - iMinY;\n            if(iw <= 0 ? true : ih <= 0) continue;\n            var ovA = iw * ih;\n            if(ovA > bestArea){ bestArea = ovA; bestHull = bH; }\n          }\n          if(!bestHull) bestHull = boundaryHulls[0];\n          hulls.push(bestHull);\n          axes.push(detectFieldAxis(bestHull, c, mode));\n          keptClusters.push(c);\n        }\n      } else {\n        for(var cI2=0; cI2<clusters.length; cI2++){\n          var c2 = clusters[cI2];\n          if(c2.xs.length < 4) continue;\n          var h = null;\n          \/\/ POINT data \u2014 two regimes, each using the right algorithm:\n          \/\/\n          \/\/   SPARSE soil-sample grids (< 300 pts, NN ~30-100 m): the right\n          \/\/   tool is concaveHullXY (edge-pullin from convex hull) \u2014 it\n          \/\/   inserts ACTUAL sample points into the hull, producing an\n          \/\/   outline that visits real samples. maxIter stays \u2264 48 because\n          \/\/   sparse data converges fast; concaveHullXY isn't designed for\n          \/\/   many iterations (no already-in-ring filter \u2192 self-intersections\n          \/\/   appear when forced past its sweet spot).\n          \/\/\n          \/\/   DENSE yield \/ NDVI \/ EC (\u2265 300 pts, NN ~1-2 m): concaveHullKnn\n          \/\/   with a SMALL cellM. The cellM controls how aggressively dense\n          \/\/   points are subsampled before the k-NN walk \u2014 passing cellM \u2248\n          \/\/   NN \u00d7 1.2 keeps almost every source point, so the hull traces\n          \/\/   individual combine measurements rather than a grid-subsampled\n          \/\/   approximation. gridHullAndHoles is still consulted for\n          \/\/   interior holes (mouth \/ pond cutouts).\n          if(mode === 'point'){\n            var cosLatB = Math.cos((typeof latC === 'number' ? latC : 0) * Math.PI \/ 180);\n            if(!(cosLatB > 0)) cosLatB = 1;\n            var sparse = c2.xs.length < 300;\n            if(sparse){\n              \/\/ Sparse scattered samples (soil \/ penetrometer \u2014 few points): a tight\n              \/\/ edge-pullin concave hull carves notches that can leave a sampled point\n              \/\/ OUTSIDE the boundary and leave field area uninterpolated. Use the CONVEX\n              \/\/ hull + outward buffer so EVERY sampled point sits inside the field and the\n              \/\/ extent reads as one clean shape. Concave tracing stays for DENSE data\n              \/\/ (the else branch), where points actually trace a worked edge.\n              \/\/ (2026-06-09: was concaveHullXY edge-pullin; changed after a penetrometer\n              \/\/ sample showed an excluded point + a notched, under-covering boundary.)\n              var concH = convexHullXY(c2.xs, c2.ys);\n              if(concH){\n                var bufferM = (alphaM > 0 ? alphaM : 50) * 0.35;\n                h = bufferRingOutward(concH, bufferM \/ cosLatB);\n                if(h) h.holes = [];\n              }\n            } else {\n              \/\/ Dense yield: tight outline via small-cell k-NN concave hull.\n              \/\/ medianNN was computed in the outer point-mode branch via\n              \/\/ alphaM = max(NN\u00d71.4, implWidth\u00d70.9); recover NN \u2248 alphaM\/1.4\n              \/\/ when nn-derived, fall back to implWidth-derived otherwise.\n              var nnEstM = alphaM \/ 1.4;\n              if(nnEstM < 1) nnEstM = 1;\n              var cellM = nnEstM * 1.2;                          \/\/ \u2248 NN \u00d7 1.2\n              if(cellM < 2) cellM = 2;                           \/\/ never finer than 2 m (runtime guard)\n              var denseH = concaveHullKnn(c2.xs, c2.ys, cellM);\n              var gridH2 = gridHullAndHoles(c2.xs, c2.ys, alphaM * 0.8);\n              if(denseH){\n                denseH.holes = gridH2 ? (gridH2.holes ? gridH2.holes : []) : [];\n                h = denseH;\n              } else if(gridH2){\n                h = gridH2;\n              }\n            }\n          }\n          if(!h){\n            \/\/ Polygon \/ line modes \u2014 k-NN concave hull + grid-hole detection\n            \/\/ (matches QGIS-style tight outline of the worked area).\n            var outerH = concaveHullKnn(c2.xs, c2.ys, alphaM * 0.8);\n            var gridH = gridHullAndHoles(c2.xs, c2.ys, alphaM * 0.8);\n            if(outerH){\n              outerH.holes = gridH ? (gridH.holes ? gridH.holes : []) : [];\n              h = outerH;\n            } else if(gridH){\n              h = gridH;\n            } else {\n              h = concaveHullXY(c2.xs, c2.ys, alphaM);\n              if(h) h.holes = [];\n            }\n          }\n          if(!h) continue;\n          if(!h.holes) h.holes = [];\n          hulls.push(h);\n          axes.push(detectFieldAxis(h, c2, mode));\n          keptClusters.push(c2);\n        }\n      }\n      return { hulls: hulls, axes: axes, clusters: keptClusters };\n    })();\n    playback.fieldHulls = _hullsBuild.hulls;\n    playback.fieldAxes = _hullsBuild.axes;\n    playback.fieldClusters = _hullsBuild.clusters;\n    \/\/ \"Never teleport\" rule: re-walk the playback order as a single greedy NN\n    \/\/ walk whenever the order has ANY consecutive pair more than MAX_JUMP_M\n    \/\/ apart. With a hull available, build a priority mask for features in the\n    \/\/ headland zone (wM \u00d7 1.5 of edge) so the walk does headlands first\n    \/\/ automatically. This INTEGRATES headland-first into the NN walk instead\n    \/\/ of as a post-process \u2014 preserves spatial smoothness across the whole\n    \/\/ order, no abrupt reorder-jumps at the headland\/body boundary.\n    \/\/\n    \/\/ The walk fires when EITHER:\n    \/\/   - The current order has a max-jump exceeding MAX_JUMP_M (\u2248 5 \u00d7 wM)\n    \/\/   - A meaningful headland pattern exists (\u2265 8% in headland zone) and\n    \/\/     the order isn't already enforcing headland-first\n    var rebuilt = false;\n    var jumpThresholdM = pickedWM * 3;\n    if(playback.fieldHulls.length){\n      var headlandFrac = classifyHeadlandFraction(playback.order, playback.fieldHulls, pickedWM);\n      var maxJumpM = measureMaxJumpRealM(playback.order);\n      var needRebuild = (maxJumpM > jumpThresholdM) ? true : (headlandFrac >= 0.08);\n      if(needRebuild){\n        var priorityMask = buildHeadlandPriorityMask(playback.fieldHulls, pickedWM, headlandFrac >= 0.08);\n        var nnOrder = greedyNNWalkOrder(priorityMask);\n        if(nnOrder){\n          playback.order = nnOrder;\n          rebuilt = true;\n          playback.orderSource = (playback.orderSource ? playback.orderSource + ' \u2192 ' : '') + 'NN walk' + (priorityMask ? ' + headlands first' : '');\n          var newMaxJump = measureMaxJumpRealM(playback.order);\n          try { console.warn('[GPY] order rebuilt as greedy NN walk: headlandFrac=' + (headlandFrac * 100).toFixed(0) + '%, prevMaxJump=' + maxJumpM.toFixed(0) + 'm \u2192 newMaxJump=' + newMaxJump.toFixed(0) + 'm (threshold ' + jumpThresholdM.toFixed(0) + 'm)'); } catch(_){}\n        }\n      }\n    }\n    if(!rebuilt){\n      var maxJumpM2 = measureMaxJumpRealM(playback.order);\n      if(maxJumpM2 > jumpThresholdM){\n        var nnOrder2 = greedyNNWalkOrder(null);\n        if(nnOrder2){\n          playback.order = nnOrder2;\n          rebuilt = true;\n          playback.orderSource = (playback.orderSource ? playback.orderSource + ' \u2192 ' : '') + 'NN walk';\n          var newMaxJump2 = measureMaxJumpRealM(playback.order);\n          try { console.warn('[GPY] order rebuilt as greedy NN walk (no hulls): prevMaxJump=' + maxJumpM2.toFixed(0) + 'm \u2192 newMaxJump=' + newMaxJump2.toFixed(0) + 'm'); } catch(_){}\n        }\n      }\n    }\n    \/\/ CRITICAL: if the order was rebuilt, the cumulative-distance array built\n    \/\/ earlier (line above setupPlayback hull build) reflects the OLD order and\n    \/\/ is now stale. Distance-based pacing in playbackLoop reads cm[idx] in the\n    \/\/ CURRENT order, so a stale cm causes either stalls (pacing thinks the\n    \/\/ step covered far more than it did \u2192 rate clamped to 0.02) or sprints\n    \/\/ (pacing thinks nothing was covered \u2192 rate clamped to 3). Recompute.\n    if(rebuilt){\n      playback.cumM = computeCumulativeDistance();\n    }\n    \/\/ Sibling AB lines (operator-defined Swaths) \u2014 when present, override the axis-\n    \/\/ detector heading per cluster with the direction of the longest sibling line that\n    \/\/ crosses that cluster. Most reliable signal: the operator literally drew these.\n    playback.abSiblingLines = findSiblingABLines(ds);\n    if(playback.abSiblingLines.length){\n      for(var hAi=0; hAi<playback.fieldHulls.length; hAi++){\n        var hPick = playback.fieldHulls[hAi];\n        var bestLineLen = 0;\n        var bestLineUx = 0, bestLineUy = 0;\n        for(var lI=0; lI<playback.abSiblingLines.length; lI++){\n          var ln = playback.abSiblingLines[lI];\n          if(ln.xs.length < 2) continue;\n          \/\/ A sibling line counts toward this cluster when its MIDPOINT sits inside\n          \/\/ (or within 0.5 wM of) the cluster's hull. Endpoint-based gating misfired\n          \/\/ on lines that ran past the field edge; midpoint is the most robust signal\n          \/\/ that the line actually belongs to this cluster.\n          var midX, midY;\n          if(ln.xs.length === 2){\n            midX = (ln.xs[0] + ln.xs[1]) * 0.5;\n            midY = (ln.ys[0] + ln.ys[1]) * 0.5;\n          } else {\n            var midIdx = (ln.xs.length - 1) >> 1;\n            midX = ln.xs[midIdx];\n            midY = ln.ys[midIdx];\n          }\n          if(!pointInHull(midX, midY, hPick, playback.implementWidth * 0.5)) continue;\n          \/\/ Direction from endpoints; longest line in the cluster wins.\n          var dxL = ln.xs[ln.xs.length - 1] - ln.xs[0];\n          var dyL = ln.ys[ln.ys.length - 1] - ln.ys[0];\n          var lL = Math.sqrt(dxL*dxL + dyL*dyL);\n          if(lL > bestLineLen){ bestLineLen = lL; bestLineUx = dxL \/ lL; bestLineUy = dyL \/ lL; }\n        }\n        if(bestLineLen > 1e-9){\n          playback.fieldAxes[hAi] = {\n            ux: bestLineUx, uy: bestLineUy,\n            headingRad: Math.atan2(bestLineUy, bestLineUx),\n            source: 'sibling-ab-line'\n          };\n        }\n      }\n    }\n    \/\/ Manual heading override \u2014 applied last so it wins over both sibling AB lines and\n    \/\/ longest-edge auto-detection. Convention is standard ag: heading degrees clockwise\n    \/\/ from north (0\u00b0 = north, 90\u00b0 = east). polyData stores Y flipped (canvas-Y =\n    \/\/ south-positive), so real north \u2192 stored uy = -cos(h). ux unchanged. Lets users\n    \/\/ correct cases where auto-detection picked the wrong axis on a near-square field.\n    if(typeof playback.userHeadingRad === 'number'){\n      var mhUx = Math.sin(playback.userHeadingRad);\n      var mhUy = -Math.cos(playback.userHeadingRad);\n      for(var mhI=0; mhI<playback.fieldAxes.length; mhI++){\n        playback.fieldAxes[mhI] = {\n          ux: mhUx, uy: mhUy,\n          headingRad: playback.userHeadingRad,\n          source: 'manual'\n        };\n      }\n    }\n    \/\/ Build AB-line passes per cluster. Primary: extract from actual polygon centroid\n    \/\/ positions (polygons ARE the operation, their row arrangement IS the navigation\n    \/\/ truth). Fallback: hull-bbox scan when the cluster has too few polygons or the\n    \/\/ centroid extractor produced no peaks. Median row spacing from the extractor is\n    \/\/ surfaced as a polygon-derived wM estimate that can re-pick the implement width.\n    function buildABLinesPass(useWM){\n      var per = [];\n      var flat = [];\n      var rowSpacings = [];\n      for(var hAi=0; hAi<playback.fieldHulls.length; hAi++){\n        var ext = extractABLinesFromCentroids(playback.fieldClusters[hAi], playback.fieldAxes[hAi], useWM);\n        var lns = ext.lines;\n        if(ext.rowSpacingMerc > 0) rowSpacings.push(ext.rowSpacingMerc);\n        if(lns.length === 0){\n          lns = synthesizeABLines(playback.fieldHulls[hAi], playback.fieldAxes[hAi], useWM);\n        }\n        per.push(lns);\n        for(var lI=0; lI<lns.length; lI++) flat.push(lns[lI]);\n      }\n      var medRowSp = 0;\n      if(rowSpacings.length){\n        rowSpacings.sort(function(a, b){ return a - b; });\n        medRowSp = rowSpacings[rowSpacings.length >> 1];\n      }\n      return { perCluster: per, flat: flat, rowSpacingMerc: medRowSp };\n    }\n    playback.abLines = buildABLinesPass(pickedWM);\n    \/\/ Polygon-derived equipment width estimate. Converts mercator row spacing to real\n    \/\/ meters via cos(latC). User's priority: polygons drive wM when no stronger signal\n    \/\/ (attribute, multi-section timestamps) won. If the polygon-row-spacing is in\n    \/\/ range AND differs from the currently-picked wM by > 20%, override and re-extract\n    \/\/ AB lines using the corrected width.\n    var _polyRowM = (function(){\n      var sp = playback.abLines.rowSpacingMerc;\n      if(!(sp > 0)) return 0;\n      var cosLat = Math.cos((typeof latC === 'number' ? latC : 0) * Math.PI \/ 180);\n      if(!(cosLat > 0)) cosLat = 1;\n      return sp * cosLat;\n    })();\n    playback.polygonRowSpacingM = _polyRowM;\n    \/\/ Polygon-rows is the user-stated primary signal for implement width \u2014 the\n    \/\/ polygons ARE the as-applied \/ as-planted record. For coverage data with\n    \/\/ multi-section timestamps, polygon-row spacing \u2248 pass spacing \u2248 implement width.\n    \/\/ For rate-prescription grids, polygon-row spacing = grid resolution (operational\n    \/\/ granularity). Either way the user wants polygons to win when present. Beats\n    \/\/ attribute + multi-section detection; loses only to a manual override.\n    var _polyPerHa = (fieldHa > 0 ? values.length \/ fieldHa : 0);\n    var _userSet = playback.userWidth ? playback.userWidth > 0 : false;\n    if(_polyRowM >= 2 ? (_polyRowM <= 100 ? !_userSet : false) : false){\n      pickedWM = _polyRowM;\n      pickedSource = 'detected (polygon rows)';\n      playback.implementWidth = pickedWM;\n      playback.implementWidthSource = pickedSource;\n      playback.abLines = buildABLinesPass(pickedWM);\n    }\n    playback.polyPerHa = _polyPerHa;\n    try {\n      var hCounts = playback.fieldHulls.map(function(h){ return h.x.length; }).join(',');\n      var aHeads = playback.fieldAxes.map(function(a){ return a ? (a.headingRad * 180\/Math.PI).toFixed(1)+'\u00b0\/'+a.source : 'null'; }).join(' | ');\n      var abCounts = playback.abLines.perCluster.map(function(a){ return a.length; }).join(',');\n      var pixDiag = pixelWM ? '; pixels: ' + pixelWM.toFixed(2) + 'm' : '';\n      console.warn('[GPY] field hulls built: ' + playback.fieldHulls.length + ' clusters (vertices: ' + hCounts + '); axes: ' + aHeads + '; sibling AB lines: ' + playback.abSiblingLines.length + '; AB passes: ' + abCounts + '; polygon row-spacing: ' + playback.polygonRowSpacingM.toFixed(2) + 'm' + pixDiag + '; picked wM: ' + pickedWM.toFixed(2) + 'm ('+pickedSource+')');\n    } catch(_){}\n    \/\/ Multi-section data \u2014 Trimble writes one polygon per active section per moment, so the\n    \/\/ raw centroids zigzag across the boom. Compute the per-step \"machine centerline\" (group\n    \/\/ centroid by timestamp) and use it for boundary detection \/ path \/ sprite. Individual\n    \/\/ section polygons still render at their actual offset positions.\n    playback.machineXY = computeMachineCenterline();\n    \/\/ Step 2: boundary detection using the chosen implement width.\n    playback.boundaries = computeTurnaroundBoundaries();\n    \/\/ Headland-pass mask: flags passes whose machine-centerline runs near and parallel\n    \/\/ to the field hull. Consumed by computeStraightPassPath.fitSegment to skip the PCA\n    \/\/ linear fit (which would flatten the boundary curve) and apply cascade smoothing\n    \/\/ directly, so the rendered trail follows the boundary instead of cutting across it.\n    playback.headlandMask = computeHeadlandPassMask();\n    try {\n      if(playback.headlandMask){\n        var hCount = 0;\n        var hList = [];\n        for(var hI=0; hI<playback.headlandMask.length; hI++){\n          if(playback.headlandMask[hI]){ hCount++; hList.push(hI); }\n        }\n        console.warn('[GPY] headland passes: '+hCount+'\/'+playback.headlandMask.length+' (indices: '+hList.join(',')+')');\n      }\n    } catch(_){}\n    \/\/ Step 3: equipment-width-driven pass filter for the TRAIL only. When the chosen\n    \/\/ implement is wider than the data spacing, the trail \/ swath stroke breaks at non-kept\n    \/\/ passes \u2014 visualises fewer \/ wider-spaced lines matching what THIS equipment would have\n    \/\/ driven. POLYGONS render normally in playback order at their actual positions, so the\n    \/\/ sprite stays aligned with the polygons being revealed (no reordering, no projection\n    \/\/ onto a synthetic central line).\n    \/\/ Count how many boundaries were detected \u2014 diagnostic for false-positive boundary issues.\n    if(playback.boundaries){\n      var bCount = 0;\n      for(var bcI=0; bcI<playback.boundaries.length; bcI++) if(playback.boundaries[bcI]) bCount++;\n      try { console.warn('[GPY] boundary detection: '+bCount+' boundaries on '+playback.order.length+' features, machineXY='+(playback.machineXY ? 'YES' : 'no')); } catch(_){}\n    }\n    playback.isCentral = null;\n    var passKeep = computePassKeptMaskWithMeta(playback.boundaries, pickedWM);\n    playback.passKeptMask = passKeep ? passKeep.mask : null;\n    playback.wideSkipN = passKeep ? passKeep.skipN : 1;\n    \/\/ EQUIPMENT WIDTH DRIVES THE PATH: the keptMask filters BOTH the trail visual AND the\n    \/\/ U-turn animations. Trail only shows on kept passes; U-turns only fire between\n    \/\/ consecutive kept passes. Sprite still traverses every polygon in playback.order,\n    \/\/ but visually the user sees fewer-and-wider passes matching the chosen equipment.\n    if(passKeep){\n      try { console.warn('[GPY] equipment width = '+pickedWM.toFixed(1)+' m drives path: skipN='+passKeep.skipN+' (trail + U-turns filter every '+passKeep.skipN+'th pass)'); } catch(_){}\n    } else {\n      try { console.warn('[GPY] equipment width = '+pickedWM.toFixed(1)+' m matches data spacing \u2014 no pass filter'); } catch(_){}\n    }\n    \/\/ Per-pass linear fit. The fitted line is what both the trail AND the sprite follow.\n    \/\/ Polygons \"light up\" when their idxFloat is reached \u2014 they appear AS the sprite passes\n    \/\/ close to them (the fit line is by definition close to the polygon centroids in any\n    \/\/ straight pass; the curve fallback handles wobbly \/ curved passes). Going BACK to\n    \/\/ sprite-on-fit-line trades a tiny alignment offset for smooth, realistic motion.\n    var straight = computeStraightPassPath();\n    playback.smoothPathX = straight.x;\n    playback.smoothPathY = straight.y;\n    playback.spritePathX = straight.x;\n    playback.spritePathY = straight.y;\n    \/\/ Phase B-3: when AB-line traversal is available for polygon data, REPLACE the\n    \/\/ centroid-order path with the AB-aligned snake traversal. Polygons reveal in\n    \/\/ along-AB-line order (pass by pass), the sprite drives along each AB line, and\n    \/\/ line-to-line transitions become turnaround boundaries that the existing\n    \/\/ setupTurnaround code arcs through with a Bezier U-turn. Point data keeps file\n    \/\/ order per user spec (\"for points use just id appearance\").\n    if(mode === 'polygon' ? (playback.abLines ? playback.abLines.perCluster.length > 0 : false) : false){\n      var abAligned = buildABAlignedOrder();\n      if(abAligned ? abAligned.order.length > 0 : false){\n        playback.order = abAligned.order;\n        playback.spritePathX = abAligned.spriteX;\n        playback.spritePathY = abAligned.spriteY;\n        playback.smoothPathX = abAligned.spriteX;\n        playback.smoothPathY = abAligned.spriteY;\n        playback.boundaries = abAligned.boundaries;\n        playback.abAligned = true;\n        playback.idx = playback.order.length;\n        playback.idxFloat = playback.order.length;\n        try { console.warn('[GPY] Phase B-3 AB-aligned order: '+abAligned.order.length+' polys across '+abAligned.lineCount+' AB lines'); } catch(_){}\n      }\n    }\n    \/\/ Per-index speed multiplier so the equipment SLOWS at sharp bends.\n    playback.speedFactor = computeSpeedFactor();\n    \/\/ Reflect in the sidebar Equipment-width input + hint.\n    var widthIn = $('#gpy-wm-in');\n    if(widthIn ? !playback.userWidth : false){\n      widthIn.value = '';\n      widthIn.placeholder = pickedWM.toFixed(1);\n    }\n    var widthHint = $('#gpy-wm-hint');\n    if(widthHint){\n      var hintTxt = pickedWM.toFixed(1) + ' m \u00b7 ' + pickedSource;\n      if(detectedWM ? Math.abs(detectedWM - pickedWM) > 0.5 : false){\n        hintTxt += ' (detected ' + detectedWM.toFixed(1) + ' m)';\n      }\n      if(playback.wideSkipN ? playback.wideSkipN > 1 : false){\n        hintTxt += ' \u00b7 path skips ' + (playback.wideSkipN - 1) + ' of every ' + playback.wideSkipN + ' passes';\n      }\n      widthHint.textContent = hintTxt;\n    }\n    \/\/ Effective swath width for visual rendering. Real operators drive parallel passes spaced\n    \/\/ approximately equipment-width apart for efficiency; if the data shows a SMALLER gap\n    \/\/ between consecutive pass centerlines (overlap pattern), we render the swath at the\n    \/\/ ACTUAL UNIQUE COVERAGE WIDTH = min(equipment width, typical pass gap \u00d7 0.95).\n    playback.effectiveSwath = computeEffectiveSwath(playback.implementWidth);\n    \/\/ Area-based duration: total real seconds to cover the field at this op's typical throughput,\n    \/\/ compressed by PLAYBACK_SCALE so it stays watchable. Bigger fields take longer to replay.\n    var fieldAreaHa = (ds ? ds.areaHa : 0) > 0 ? ds.areaHa : bboxAreaHaFallback();\n    var thr = OP_THROUGHPUT_HA_PER_HR[op.label] ? OP_THROUGHPUT_HA_PER_HR[op.label] : 8;\n    var realSec = (fieldAreaHa \/ thr) * 3600;\n    playback.totalSec1x = Math.max(15, realSec \/ PLAYBACK_SCALE);\n    try { console.warn('[GPY] op detected:', op.label, '(source='+op.source+', overlap='+op.overlapStrategy+', kept='+(playback.keptMask ? playback.keptMask.kept : 'n\/a')+'\/'+values.length+'); area='+fieldAreaHa.toFixed(1)+'ha, throughput='+thr+'ha\/h \u2192 1\u00d7 = '+Math.round(playback.totalSec1x)+'s; equipmentWidth='+pickedWM.toFixed(1)+'m ('+pickedSource+'); wideSkipN='+(playback.wideSkipN||1)); } catch(_){}\n    \/\/ Refresh hint AFTER wide-pass setup so the skip-N annotation is live.\n    var widthHintLate = $('#gpy-wm-hint');\n    if(widthHintLate){\n      var hintLate = pickedWM.toFixed(1) + ' m \u00b7 ' + pickedSource;\n      if(detectedWM ? Math.abs(detectedWM - pickedWM) > 0.5 : false){\n        hintLate += ' (multi-section ' + detectedWM.toFixed(1) + ' m)';\n      }\n      if(pixelWM ? Math.abs(pixelWM - pickedWM) > 0.5 : false){\n        hintLate += ' (pixels ' + pixelWM.toFixed(1) + ' m)';\n      }\n      if(playback.polygonRowSpacingM ? Math.abs(playback.polygonRowSpacingM - pickedWM) > 0.5 : false){\n        hintLate += ' (polygon rows ' + playback.polygonRowSpacingM.toFixed(1) + ' m)';\n      }\n      if(playback.wideSkipN ? playback.wideSkipN > 1 : false){\n        hintLate += ' \u00b7 path keeps 1 of ' + playback.wideSkipN + ' passes';\n      }\n      widthHintLate.textContent = hintLate;\n    }\n    try { syncHeadingHint(); } catch(_){}\n    updatePlaybackUI();\n  }\n  \/\/ Returns bbox area in hectares for the current dataset (used when ds.areaHa is unknown,\n  \/\/ e.g. point yield logs or LineString swaths). The 0.6 fill factor approximates the share\n  \/\/ of bbox that's actually inside the field (fields are rarely perfect rectangles).\n  function bboxAreaHaFallback(){\n    var minX = Infinity, maxX = -Infinity, minY = Infinity, maxY = -Infinity;\n    if(mode === 'point'){\n      if(!mx) return 20;\n      if(!mx.length) return 20;\n      for(var bi=0; bi<mx.length; bi++){\n        var bx = mx[bi], by = my[bi];\n        if(bx < minX) minX = bx;\n        if(bx > maxX) maxX = bx;\n        if(by < minY) minY = by;\n        if(by > maxY) maxY = by;\n      }\n    } else {\n      if(!polyData) return 20;\n      if(!polyData.length) return 20;\n      for(var bj=0; bj<polyData.length; bj++){\n        var pp = polyData[bj];\n        if(pp.minX < minX) minX = pp.minX;\n        if(pp.maxX > maxX) maxX = pp.maxX;\n        if(pp.minY < minY) minY = pp.minY;\n        if(pp.maxY > maxY) maxY = pp.maxY;\n      }\n    }\n    if(!isFinite(minX)) return 20;\n    if(!isFinite(maxX)) return 20;\n    if(!isFinite(minY)) return 20;\n    if(!isFinite(maxY)) return 20;\n    var ha = ((maxX - minX) * (maxY - minY)) \/ 10000 * 0.6;\n    return Math.max(1, ha);\n  }\n  \/\/ Item 3 + 4: build a \"kept\" mask for the polygon dataset based on the operation's overlap strategy.\n  \/\/   \"sum\"   (fertilizing \/ spraying): every pass at each spot counts \u2192 all polygons kept.\n  \/\/   \"first\" (seeding): only the FIRST polygon (in playback \/ path order) is kept at each spot;\n  \/\/           later polygons whose bbox overlaps an already-kept polygon are dropped. Reflects how\n  \/\/           modern seeders disable duplicate sowing \u2014 a second pass over the same row doesn't\n  \/\/           plant more seed, so it shouldn't be double-counted in coverage \/ total.\n  \/\/ Uses a uniform-grid spatial index for ~O(n \u00d7 neighbours) instead of O(n\u00b2).\n  function computeKeptMask(strategy){\n    if(!polyData) return null;\n    var n = polyData.length;\n    if(!n) return null;\n    var mask = new Uint8Array(n);\n    if(strategy !== 'first'){\n      for(var i=0;i<n;i++) mask[i] = 1;\n      return { mask: mask, kept: n, strategy: strategy };\n    }\n    \/\/ Compute dataset bbox + average polygon size for grid cell sizing\n    var gMinX = Infinity, gMaxX = -Infinity, gMinY = Infinity, gMaxY = -Infinity;\n    var sumW = 0, sumH = 0;\n    for(var pi=0; pi<n; pi++){\n      var p = polyData[pi];\n      if(p.minX < gMinX) gMinX = p.minX;\n      if(p.maxX > gMaxX) gMaxX = p.maxX;\n      if(p.minY < gMinY) gMinY = p.minY;\n      if(p.maxY > gMaxY) gMaxY = p.maxY;\n      sumW += (p.maxX - p.minX);\n      sumH += (p.maxY - p.minY);\n    }\n    var avgDim = Math.max((sumW + sumH) \/ (2 * n), 1);\n    var cellSize = avgDim * 4;\n    var nCols = Math.max(1, Math.ceil((gMaxX - gMinX) \/ cellSize));\n    var nRows = Math.max(1, Math.ceil((gMaxY - gMinY) \/ cellSize));\n    \/\/ Cap at 200\u00d7200 buckets to avoid runaway memory on degenerate data\n    if(nCols > 200){ cellSize *= (nCols \/ 200); nCols = 200; }\n    if(nRows > 200){ cellSize *= (nRows \/ 200); nRows = 200; }\n    var buckets = new Array(nCols * nRows);\n    for(var bi=0;bi<buckets.length;bi++) buckets[bi] = null;\n    var ord = playback.order;\n    var keptCount = 0;\n    \/\/ Dedup rule: a polygon q is \"duplicate\" only if its CENTROID falls inside an earlier-kept\n    \/\/ polygon's bbox. Bbox-vs-bbox overlap (the previous heuristic) was too aggressive \u2014 adjacent\n    \/\/ parallel seeder passes have touching bboxes but no real spatial overlap, so it dropped\n    \/\/ most of the seeded area (field 006: 8.89 ha shown instead of ~37 ha). The centroid-in-bbox\n    \/\/ check correctly distinguishes \"second pass at the same spot\" from \"next swath over\".\n    for(var oi=0; oi<n; oi++){\n      var idx = ord ? ord[oi] : oi;\n      var q = polyData[idx];\n      var qx = q.cx, qy = q.cy;\n      var ccc = Math.max(0, Math.min(nCols-1, Math.floor((qx - gMinX) \/ cellSize)));\n      var crr = Math.max(0, Math.min(nRows-1, Math.floor((qy - gMinY) \/ cellSize)));\n      var dup = false;\n      \/\/ Search a 3x3 neighbourhood around the centroid cell \u2014 covers polygons whose bbox crosses\n      \/\/ a cell boundary while their centroid sits in the adjacent cell.\n      for(var dc=-1; dc<=1; dc++){\n        if(dup) break;\n        var cc = ccc + dc; if(cc<0 ? true : cc>=nCols) continue;\n        for(var dr=-1; dr<=1; dr++){\n          if(dup) break;\n          var rr = crr + dr; if(rr<0 ? true : rr>=nRows) continue;\n          var bucket = buckets[rr*nCols + cc];\n          if(!bucket) continue;\n          for(var bj=0; bj<bucket.length; bj++){\n            var ek = polyData[bucket[bj]];\n            \/\/ centroid-in-bbox test using ternary form (CLAUDE.md: no ampersand chars in script bodies)\n            var inX = qx >= ek.minX ? qx <= ek.maxX : false;\n            var inY = qy >= ek.minY ? qy <= ek.maxY : false;\n            if(inX ? inY : false){ dup = true; break; }\n          }\n        }\n      }\n      if(!dup){\n        mask[idx] = 1;\n        keptCount++;\n        \/\/ Register in every cell its bbox touches, so a later polygon centroid in any of those cells finds this one.\n        var c0 = Math.max(0, Math.floor((q.minX - gMinX) \/ cellSize));\n        var c1 = Math.min(nCols-1, Math.floor((q.maxX - gMinX) \/ cellSize));\n        var r0 = Math.max(0, Math.floor((q.minY - gMinY) \/ cellSize));\n        var r1 = Math.min(nRows-1, Math.floor((q.maxY - gMinY) \/ cellSize));\n        for(var cc2=c0; cc2<=c1; cc2++){\n          for(var rr2=r0; rr2<=r1; rr2++){\n            var k = rr2*nCols + cc2;\n            if(!buckets[k]) buckets[k] = [];\n            buckets[k].push(idx);\n          }\n        }\n      }\n    }\n    return { mask: mask, kept: keptCount, strategy: strategy };\n  }\n  \/\/ Cumulative distance in real meters along the playback order (center-to-center).\n  \/\/ Centers are in Web-Mercator-meters relative to dataset center; multiply by cos(lat) to get true ground meters.\n  function computeCumulativeDistance(){\n    var n = featCount();\n    if(n < 2) return null;\n    var ord = playback.order;\n    \/\/ Average latitude for the WM\u2192true-meters correction (use first ~100 features for speed).\n    var latSum = 0, latCnt = 0;\n    var sampleMax = Math.min(n, 100);\n    for(var i=0;i<sampleMax;i++){\n      var fi = ord ? ord[i] : i;\n      var g = features[fi] ? features[fi].geometry : null;\n      if(!g) continue;\n      var c = g.coordinates;\n      while(Array.isArray(c) ? Array.isArray(c[0]) : false) c = c[0];\n      if(c ? typeof c[1] === 'number' : false){ latSum += c[1]; latCnt++; }\n    }\n    var cosLat = latCnt > 0 ? Math.cos(latSum \/ latCnt * Math.PI \/ 180) : 1;\n    var cum = new Float32Array(n);\n    cum[0] = 0;\n    for(var i2=1;i2<n;i2++){\n      var ai = ord ? ord[i2-1] : (i2-1);\n      var bi = ord ? ord[i2]   : i2;\n      var dx = featCx(bi) - featCx(ai), dy = featCy(bi) - featCy(ai);\n      var stepM = Math.sqrt(dx*dx + dy*dy) * cosLat;\n      cum[i2] = cum[i2-1] + stepM;\n    }\n    return cum;\n  }\n  function formatDistance(m){\n    if(distanceUnit === 'imperial'){\n      var mi = m \/ 1609.344;\n      if(mi < 1) return Math.round(m * 3.28084) + ' ft';\n      return mi.toFixed(mi < 10 ? 2 : 1) + ' mi';\n    }\n    if(m < 1000) return Math.round(m) + ' m';\n    return (m \/ 1000).toFixed(m < 10000 ? 2 : 1) + ' km';\n  }\n  function formatCost(usd){\n    if(!isFinite(usd) || usd < 0) usd = 0;\n    if(usd < 100) return '$' + usd.toFixed(0);\n    return '$' + Math.round(usd).toLocaleString('en-US');\n  }\n  \/\/ Strip the area denominator from a column unit to get the per-unit-product label.\n  \/\/  \"t\/ha\"  \u2192 \"t\"   (tonnes \u00d7 hectares \u00f7 hectares = tonnes)\n  \/\/  \"bu\/ac\" \u2192 \"bu\"  (bushels \u00d7 acres \u00f7 acres = bushels)\n  \/\/  \"kg\/ha\" \u2192 \"kg\"\n  \/\/  \"L\/ha\"  \u2192 \"L\"   (litres of product)\n  \/\/  \"\"      \u2192 \"unit\"\n  function priceUnitFor(colUnit){\n    if(!colUnit) return 'unit';\n    var u = (''+colUnit).replace(\/\\s*\\\/\\s*(hectares?|ha|acres?|ac)\\s*$\/i, '').trim();\n    return u || 'unit';\n  }\n  \/\/ Convert hectares to the column's area-denominator unit so value \u00d7 area gives a\n  \/\/ number in the column's product units. For \"\/ac\" columns area must be in acres.\n  function areaForUnit(areaHa, colUnit){\n    if(!colUnit) return areaHa;\n    if(\/\\\/\\s*(acres?|ac)\\s*$\/i.test(colUnit)) return areaHa * 2.47105;\n    return areaHa;\n  }\n  \/\/ Label used for the cost\/revenue figure in the playback stats. Harvest = revenue;\n  \/\/ anything else (planting, spraying, fertilizing, application) = cost.\n  function priceFigureLabel(opLabel){\n    return opLabel === 'harvest' ? 'Revenue' : 'Cost';\n  }\n  function updatePlaybackUI(){\n    var n = values.length;\n    var clamped = playback.idx > n ? n : (playback.idx < 0 ? 0 : playback.idx);\n    var pct = n > 0 ? clamped \/ n : 0;\n    var fill = $('#gpy-pb-fill'); if(fill) fill.style.width = (pct*100) + '%';\n    var thumb = $('#gpy-pb-thumb'); if(thumb) thumb.style.left = (pct*100) + '%';\n    var playBtn = $('#gpy-pb-play');\n    var pauseBtn = $('#gpy-pb-pause');\n    if(playBtn) playBtn.disabled = playback.active ? true : false;\n    if(pauseBtn) pauseBtn.disabled = playback.active ? false : true;\n    \/\/ Polygon datasets accumulate covered area + product (value \u00d7 area) as playback walks.\n    \/\/ Points + lines don't have area; we still show distance + turnarounds which are\n    \/\/ meaningful for any geometry.\n    var areaSoFar = 0;\n    var productSoFar = 0;\n    if(mode === 'polygon' ? polyData : false){\n      var upto = clamped < polyData.length ? clamped : polyData.length;\n      for(var i=0;i<upto;i++){\n        var pIdx = playback.order ? playback.order[i] : i;\n        var pd = polyData[pIdx];\n        if(pd){\n          var aHa = pd.areaHa || 0;\n          areaSoFar += aHa;\n          var vRaw = values ? values[pIdx] : NaN;\n          if(isFinite(vRaw)) productSoFar += vRaw * areaForUnit(aHa, currentUnit);\n        }\n      }\n    }\n    var totalDollars = productSoFar * productPrice;\n    var statsEl = $('#gpy-pb-stats');\n    if(statsEl){\n      var pctDone = n > 0 ? (clamped \/ n * 100) : 0;\n      var pctStr = pctDone >= 100 ? '100%' : (pctDone >= 10 ? pctDone.toFixed(0) + '%' : pctDone.toFixed(1) + '%');\n      var parts = ['<b>' + pctStr + '<\/b>', clamped + '\/' + n];\n      if(mode === 'polygon' ? areaSoFar > 0 : false){\n        var areaStr = areaSoFar < 10 ? areaSoFar.toFixed(2) : (areaSoFar < 100 ? areaSoFar.toFixed(1) : Math.round(areaSoFar));\n        parts.push(areaStr + ' ha');\n      }\n      if(mode === 'polygon' ? productSoFar > 0 : false){\n        var prodUnit = priceUnitFor(currentUnit);\n        var prodStr = productSoFar < 10 ? productSoFar.toFixed(2) : (productSoFar < 1000 ? productSoFar.toFixed(1) : Math.round(productSoFar).toLocaleString('en-US'));\n        var line = prodStr + ' ' + prodUnit;\n        if(productPrice > 0){\n          line += ' \u00b7 ' + priceFigureLabel(playback.opLabel) + ' ' + formatCost(totalDollars);\n        }\n        parts.push(line);\n      }\n      if(playback.opLabel){\n        parts.push(playback.opLabel);\n      }\n      \/\/ NOTE: playback.orderSource (e.g. \"snake sweep \u2192 NN walk\") is kept for the\n      \/\/ dev console only \u2014 never surfaced in the UI. Exposing the internal path \/\n      \/\/ interpolation algorithm names is forbidden (see factory CLAUDE.md \"Never\n      \/\/ expose internal algorithm names in user-facing copy\").\n      statsEl.innerHTML = parts.join(' \u00b7 ');\n    }\n    \/\/ Sync the price input + unit display with the current product price + active column unit.\n    var priceInput = $('#gpy-pb-price');\n    if(priceInput ? document.activeElement !== priceInput : false){\n      priceInput.value = productPrice > 0 ? productPrice : '';\n    }\n    var priceUnitEl = $('#gpy-pb-price-unit');\n    if(priceUnitEl) priceUnitEl.textContent = '\/' + priceUnitFor(currentUnit);\n    var priceLblEl = $('#gpy-pb-price-lbl');\n    if(priceLblEl){\n      var isHarv = playback.opLabel === 'harvest';\n      priceLblEl.title = isHarv\n        ? 'Revenue per unit of harvested product (e.g., $\/t, $\/bu). Total revenue updates as playback runs.'\n        : 'Product cost per unit applied (e.g., $\/kg fertilizer, $\/L spray, $\/seed). Total cost updates as playback runs.';\n    }\n  }\n  \/\/ Compute and cache the cubic Bezier that connects the end of the previous pass to the start\n  \/\/ of the next pass at boundary index `bi`. The sprite animates along this curve during the\n  \/\/ turnaround so it never teleports between rows. Returns true on success.\n  \/\/ Check whether a cubic Bezier sampled at `steps` points stays inside\n  \/\/ `hull` (with `bufM` real-meter outward buffer). Returns true if every\n  \/\/ sample passes pointInHull; false on the first violation.\n  function bezierInsideHull(p0x, p0y, p1x, p1y, p2x, p2y, p3x, p3y, hull, bufM, steps){\n    if(!hull) return true;\n    var N = steps > 0 ? steps : 16;\n    for(var s=0; s<=N; s++){\n      var t = s \/ N;\n      var u = 1 - t;\n      var bx = u*u*u*p0x + 3*u*u*t*p1x + 3*u*t*t*p2x + t*t*t*p3x;\n      var by = u*u*u*p0y + 3*u*u*t*p1y + 3*u*t*t*p2y + t*t*t*p3y;\n      if(!pointInHull(bx, by, hull, bufM)) return false;\n    }\n    return true;\n  }\n  function setupTurnaround(bi){\n    var bnd = playback.boundaries;\n    var endX = pathCx(bi - 1), endY = pathCy(bi - 1);\n    var nxtX = pathCx(bi),     nxtY = pathCy(bi);\n    var dx1 = 0, dy1 = 0;\n    if(bi >= 2){\n      if(bnd ? !bnd[bi-1] : true){\n        dx1 = endX - pathCx(bi-2);\n        dy1 = endY - pathCy(bi-2);\n      }\n    }\n    var l1 = Math.sqrt(dx1*dx1 + dy1*dy1);\n    if(l1 < 0.0001){ dx1 = nxtX - endX; dy1 = nxtY - endY; l1 = Math.sqrt(dx1*dx1 + dy1*dy1); }\n    if(l1 < 0.0001){ dx1 = 1; dy1 = 0; l1 = 1; }\n    dx1 \/= l1; dy1 \/= l1;\n    var dx2 = 0, dy2 = 0;\n    if(bi + 1 < values.length){\n      if(bnd ? !bnd[bi+1] : true){\n        dx2 = pathCx(bi+1) - nxtX;\n        dy2 = pathCy(bi+1) - nxtY;\n      }\n    }\n    var l2 = Math.sqrt(dx2*dx2 + dy2*dy2);\n    if(l2 < 0.0001){ dx2 = nxtX - endX; dy2 = nxtY - endY; l2 = Math.sqrt(dx2*dx2 + dy2*dy2); }\n    if(l2 < 0.0001){ dx2 = 1; dy2 = 0; l2 = 1; }\n    dx2 \/= l2; dy2 \/= l2;\n    var gapDx = nxtX - endX, gapDy = nxtY - endY;\n    var gapM = Math.sqrt(gapDx*gapDx + gapDy*gapDy);\n    \/\/ U-TURN (not V-turn). Real ag headland turns are SMOOTH WIDE ARCS, not sharp angles.\n    \/\/ Bezier control distance must be large enough relative to the gap for the curve to\n    \/\/ round out into a U. Empirically, ctrl \u2248 1.5\u20132\u00d7 gap produces a clear U shape; smaller\n    \/\/ values pinch the curve into a V at the midpoint. Floor at wM \u00d7 1.5 ensures small\n    \/\/ gaps still get a usable U; cap at wM \u00d7 2.5 keeps wide-implement arcs from flooding\n    \/\/ past the field too far.\n    var wM = playback.implementWidth ? playback.implementWidth : equipmentWidthM(playback.opLabel);\n    var ctrl = gapM * 1.7;\n    var minCtrl = wM * 1.5;\n    var maxCtrl = wM * 2.5;\n    if(ctrl < minCtrl) ctrl = minCtrl;\n    if(ctrl > maxCtrl) ctrl = maxCtrl;\n    if(ctrl < 10) ctrl = 10;\n    \/\/ Field boundary constraint: the arc MUST stay STRICTLY INSIDE the field hull\n    \/\/ (no past-edge overshoot). Real machines start the headland turn IN ADVANCE of\n    \/\/ reaching the field boundary, so the entire turn happens within the worked area.\n    \/\/ Pick the hull that contains the source pass endpoint \u2014 multi-field datasets have\n    \/\/ multiple disjoint hulls; we only care about the one the current pass lives in.\n    \/\/ Falls back to the legacy bbox cap when neither endpoint sits inside any hull\n    \/\/ (degenerate cases, line-only files).\n    var hulls = playback.fieldHulls;\n    var fieldHull = null;\n    if(hulls ? hulls.length : false){\n      fieldHull = findContainingHull(endX, endY, hulls);\n      if(!fieldHull) fieldHull = findContainingHull(nxtX, nxtY, hulls);\n    }\n    var hullBufM = 0;\n    var ctrlShrinkApplied = false;\n    if(!fieldHull){\n      \/\/ Legacy bbox cap as a safety net for datasets too small for a hull.\n      var bboxOk = isFinite(mxMin) ? isFinite(mxMax) : false;\n      if(bboxOk){\n        var tx1 = Infinity, ty1 = Infinity;\n        if(dx1 > 0.0001) tx1 = (mxMax - endX) \/ dx1;\n        else if(dx1 < -0.0001) tx1 = (mxMin - endX) \/ dx1;\n        if(dy1 > 0.0001) ty1 = (myMax - endY) \/ dy1;\n        else if(dy1 < -0.0001) ty1 = (myMin - endY) \/ dy1;\n        var distFwd = tx1 < ty1 ? tx1 : ty1;\n        if(distFwd < 0) distFwd = 0;\n        var dxBack = -dx2, dyBack = -dy2;\n        var tx2 = Infinity, ty2 = Infinity;\n        if(dxBack > 0.0001) tx2 = (mxMax - nxtX) \/ dxBack;\n        else if(dxBack < -0.0001) tx2 = (mxMin - nxtX) \/ dxBack;\n        if(dyBack > 0.0001) ty2 = (myMax - nxtY) \/ dyBack;\n        else if(dyBack < -0.0001) ty2 = (myMin - nxtY) \/ dyBack;\n        var distBwd = tx2 < ty2 ? tx2 : ty2;\n        if(distBwd < 0) distBwd = 0;\n        var smaller = distFwd < distBwd ? distFwd : distBwd;\n        var boundaryCap = smaller + wM * 0.5;\n        if(ctrl > boundaryCap){ ctrl = boundaryCap; ctrlShrinkApplied = true; }\n      }\n    }\n    playback.turnAct = true;\n    playback.turnEnd = bi;\n    playback.turnFrac = 0;\n    \/\/ Perpendicular swing: clears the previous pass's swath band. Offset is capped by gap\/2\n    \/\/ so the arc never overshoots the destination row \u2014 for the typical gap = wM case it's\n    \/\/ wM \u00d7 0.4, and for narrow overlapping gaps it scales down with the gap. Without the cap\n    \/\/ the arc would visibly leave the data hull and look disconnected from the polygons.\n    var perpX = -dy1;\n    var perpY = dx1;\n    var perpSign = (gapDx * perpX + gapDy * perpY) >= 0 ? 1 : -1;\n    var perpOff = wM * 0.25;\n    if(perpOff > gapM * 0.4) perpOff = gapM * 0.4;\n    \/\/ Hull-fit retry loop: shrink ONLY ctrl (the forward extension along dx1\/dx2)\n    \/\/ by 0.7\u00d7 per attempt until every sampled point on the Bezier lies strictly\n    \/\/ inside the field hull. Perpendicular swing (perpOff) is preserved so the U\n    \/\/ does NOT collapse into a V \u2014 the forward extent is what pushes the arc past\n    \/\/ the field edge; the perpendicular component keeps the U-shape. Floor at\n    \/\/ wM \u00d7 0.3 so the curve still has a forward tangent and the sprite doesn't\n    \/\/ snap sideways at boundary entry. Eight attempts max (was six \u2014 extra room\n    \/\/ for tight edge passes). No-op when there is no hull.\n    var p1xT, p1yT, p2xT, p2yT;\n    var attempt = 0;\n    var maxAttempt = 8;\n    var ctrlFloor = wM * 0.3;\n    while(true){\n      p1xT = endX + dx1 * ctrl + perpX * perpSign * perpOff;\n      p1yT = endY + dy1 * ctrl + perpY * perpSign * perpOff;\n      p2xT = nxtX - dx2 * ctrl + perpX * perpSign * perpOff;\n      p2yT = nxtY - dy2 * ctrl + perpY * perpSign * perpOff;\n      if(!fieldHull) break;\n      if(bezierInsideHull(endX, endY, p1xT, p1yT, p2xT, p2yT, nxtX, nxtY, fieldHull, hullBufM, 16)) break;\n      attempt++;\n      if(attempt >= maxAttempt) break;\n      if(ctrl <= ctrlFloor) break;\n      ctrl *= 0.7;\n      if(ctrl < ctrlFloor) ctrl = ctrlFloor;\n      ctrlShrinkApplied = true;\n    }\n    if(ctrlShrinkApplied){\n      try { console.warn('[GPY] U-turn hull-clamped at boundary i='+bi+' (ctrl='+ctrl.toFixed(1)+', attempts='+attempt+')'); } catch(_){}\n    }\n    playback.turnBezier = {\n      p0x: endX, p0y: endY,\n      p1x: p1xT, p1y: p1yT,\n      p2x: p2xT, p2y: p2yT,\n      p3x: nxtX, p3y: nxtY\n    };\n    \/\/ Turnaround duration is proportional to arc length (was fixed at 3.5s at 1\u00d7). Real ag\n    \/\/ machines drive the headland turn at ~1.5 m\/s; PLAYBACK_SCALE = 5 compresses that.\n    \/\/ Estimate arc length from control-point distances: cubic Bezier with our typical\n    \/\/ geometry is roughly arc \u2248 ctrl \u00d7 1.8 + gapM \u00d7 0.5. Computed AFTER the hull-fit\n    \/\/ retry loop because ctrl may have shrunk during it.\n    var arcLen = ctrl * 1.8 + gapM * 0.5;\n    var realArcSec = arcLen \/ 1.5;\n    playback.turnDurMs = (realArcSec \/ PLAYBACK_SCALE) * 1000 \/ playback.speed;\n    if(playback.turnDurMs < 600) playback.turnDurMs = 600;  \/\/ minimum 0.6s so turn stays visible\n    if(playback.turnDurMs > 12000) playback.turnDurMs = 12000;  \/\/ cap at 12s so wide arcs don't stall\n  }\n  \/\/ Ease-in-out for turnaround Bezier: machine enters arc slow, peaks at mid, exits slow.\n  \/\/ Smoothstep: t\u00b2 * (3 - 2t). Input\/output both in [0, 1].\n  function easeT(t){\n    var c = t > 1 ? 1 : (t < 0 ? 0 : t);\n    return c * c * (3 - 2 * c);\n  }\n  \/\/ Evaluate cubic Bezier B(t) \u2014 used by both the sprite (during turnaround) and the partial\n  \/\/ trail rendering. `xy` = 'x' or 'y' for which coord to return.\n  function bezierAt(b, t, xy){\n    var u = 1 - t;\n    var a = u*u*u, bcoeff = 3*u*u*t, ccoeff = 3*u*t*t, d = t*t*t;\n    if(xy === 'x') return a*b.p0x + bcoeff*b.p1x + ccoeff*b.p2x + d*b.p3x;\n    return a*b.p0y + bcoeff*b.p1y + ccoeff*b.p2y + d*b.p3y;\n  }\n  \/\/ RAF loop: advances playback.idx proportional to elapsed time \u00d7 speed, draws once per frame.\n  \/\/ Duration at 1\u00d7 is calibrated from field area \u00d7 op throughput in setupPlayback (so a 50ha combine\n  \/\/ job \u2248 100min at 1\u00d7 \/ 20min at default 5\u00d7, while a 50ha sprayer job \u2248 10min \/ 2min at the same\n  \/\/ speeds). Larger fields \u2192 longer playback. Floor of 15s keeps tiny datasets from finishing instantly.\n  function playbackLoop(now){\n    if(!playback.active){ playback.raf = null; return; }\n    if(!playback.lastT) playback.lastT = now;\n    var dt = now - playback.lastT;\n    if(dt > 100) dt = 100;\n    playback.lastT = now;\n    playback.frameDtMs = dt;\n    if(playback.turnAct){\n      \/\/ While in a headland turnaround, idxFloat is parked at the boundary and no new polygons\n      \/\/ fill. The sprite glides along a cached Bezier from end-of-prev-pass to start-of-next.\n      \/\/ Turnaround duration scales inversely with playback.speed so the visual takes proportional\n      \/\/ wall-clock time at any speed (real combines turn at ~25s; we compress to ~1.5s at 1\u00d7).\n      playback.turnFrac = playback.turnFrac + dt \/ playback.turnDurMs;\n      if(playback.turnFrac >= 1){\n        playback.turnAct = false;\n        playback.turnFrac = 1;\n        \/\/ Cross the boundary: bump idxFloat one polygon past so the boundary polygon also fills.\n        playback.idxFloat = playback.turnEnd + 1;\n        if(playback.idxFloat > values.length) playback.idxFloat = values.length;\n        playback.idx = Math.floor(playback.idxFloat);\n        playback.smoothedHeading = null;\n        playback.smoothedX = null;\n        playback.smoothedY = null;\n      }\n      draw();\n      updatePlaybackUI();\n      if(playback.idx >= values.length){\n        playback.active = false;\n        playback.raf = null;\n        var pbEnd1 = $('#gpy-pb-play'); if(pbEnd1) pbEnd1.disabled = false;\n        var pauseEnd1 = $('#gpy-pb-pause'); if(pauseEnd1) pauseEnd1.disabled = true;\n        return;\n      }\n      playback.raf = requestAnimationFrame(playbackLoop);\n      return;\n    }\n    var totalMs = playback.totalSec1x ? playback.totalSec1x * 1000 : (values.length \/ 3 * 1000);\n    \/\/ Accumulate fractional progress so low speeds advance smoothly (was rounding to 1\/frame).\n    var delta = (values.length \/ totalMs) * dt * playback.speed;\n    \/\/ Apply per-index speed factor so the equipment slows down at headland turns \u2014 real combines\n    \/\/ drop to ~30% speed when pivoting at row ends, then accelerate back to full pace.\n    var sf = playback.speedFactor;\n    if(sf){\n      var sfIdx = Math.floor(playback.idxFloat);\n      if(sfIdx < 0) sfIdx = 0;\n      if(sfIdx > sf.length - 1) sfIdx = sf.length - 1;\n      delta = delta * sf[sfIdx];\n    }\n    \/\/ Distance-based pacing \u2014 advance idxFloat slower through sparse regions where consecutive\n    \/\/ polygons are far apart, faster through tightly-packed ones. Without this, idxFloat ticks\n    \/\/ one polygon per beat regardless of how far apart they are in the real world, so the\n    \/\/ equipment appears to \"accelerate\" through sparse zones with no data points. Uses cumM\n    \/\/ (cumulative real meters) which is already computed in setupPlayback.\n    var cm = playback.cumM;\n    if(cm){\n      var idxN = Math.floor(playback.idxFloat);\n      if(idxN < 0) idxN = 0;\n      if(idxN > cm.length - 2) idxN = cm.length - 2;\n      if(idxN >= 0 ? idxN < cm.length - 1 : false){\n        var localStep = cm[idxN + 1] - cm[idxN];\n        var avgStep = cm.length > 1 ? (cm[cm.length - 1] \/ (cm.length - 1)) : 1;\n        if(avgStep > 0.001 ? localStep > 0.001 : false){\n          var rate = avgStep \/ localStep;\n          \/\/ Real-world-speed clamp: rate = avgStep\/localStep makes the sprite cover constant\n          \/\/ ground distance per frame regardless of polygon density. Floor at 0.02 (was 0.08,\n          \/\/ before that 0.2) \u2014 for gaps up to 50\u00d7 the median spacing the sprite slows\n          \/\/ proportionally, matching real machine behaviour. The upper cap of 3 prevents the\n          \/\/ sprite from skipping polygons in very dense pockets.\n          if(rate > 3) rate = 3;\n          if(rate < 0.02) rate = 0.02;\n          delta = delta * rate;\n        }\n      }\n    }\n    \/\/ Realistic equipment-width cap: limit per-frame path advance to \u2248 1 \u00d7 wM\n    \/\/ so the visual leading edge always looks like ONE moving machine, not a\n    \/\/ wide multi-pass swath. Scales slowly with playback.speed so the cap never\n    \/\/ exceeds ~3.7 \u00d7 wM even at the 2000\u00d7 extreme.\n    \/\/   1\u00d7:    1.0 \u00d7 wM\/frame\n    \/\/   20\u00d7:   1.4 \u00d7 wM\/frame\n    \/\/   100\u00d7:  2.2 \u00d7 wM\/frame\n    \/\/   500\u00d7:  3.0 \u00d7 wM\/frame\n    \/\/   2000\u00d7: 3.7 \u00d7 wM\/frame\n    if(cm ? playback.implementWidth > 0 : false){\n      var idxAt = Math.floor(playback.idxFloat);\n      if(idxAt < 0) idxAt = 0;\n      var idxAhead = idxAt + Math.ceil(delta);\n      if(idxAhead > cm.length - 1) idxAhead = cm.length - 1;\n      if(idxAt < idxAhead){\n        var coverM = cm[idxAhead] - cm[idxAt];\n        var logSpeed = Math.log(playback.speed > 1 ? playback.speed : 1) \/ Math.log(2);\n        var maxCoverM = playback.implementWidth * Math.max(1, logSpeed \/ 3);\n        if(coverM > maxCoverM){\n          var capR = maxCoverM \/ coverM;\n          delta = delta * capR;\n        }\n      }\n    }\n    var newIdxFloat = playback.idxFloat + delta;\n    \/\/ Will this delta carry us across a turnaround boundary? If so, park at boundary and start the\n    \/\/ turnaround animation instead of letting the sprite teleport.\n    var bndArr = playback.boundaries;\n    var crossedBoundary = -1;\n    if(bndArr){\n      var floorOld = Math.floor(playback.idxFloat);\n      var floorNew = Math.floor(newIdxFloat);\n      for(var ci = floorOld + 1; ci <= floorNew; ci++){\n        if(ci >= bndArr.length) break;\n        if(bndArr[ci]){ crossedBoundary = ci; break; }\n      }\n    }\n    if(crossedBoundary >= 0 ? showMachinePath : false){\n      \/\/ Turnaround animation is ONLY needed when the sprite + trail are visible.\n      \/\/ Hidden-path mode just advances idxFloat past the boundary \u2014 no Bezier\n      \/\/ animation, no parked-at-boundary delay. Without this gate, playback\n      \/\/ pauses ~600ms per boundary even though nothing's being drawn (a 1805-\n      \/\/ feature dataset with 210 boundaries was adding ~120s of dead wall-clock).\n      \/\/\n      \/\/ A real headland turn moves the machine by at least half a swath. If the\n      \/\/ gap between the two pass endpoints at this boundary is smaller than that,\n      \/\/ the detection is almost certainly a false positive \u2014 skip the turnaround\n      \/\/ animation entirely and let normal playback advance across the boundary.\n      var wMcheck = playback.implementWidth ? playback.implementWidth : equipmentWidthM(playback.opLabel);\n      var bDx = pathCx(crossedBoundary) - pathCx(crossedBoundary - 1);\n      var bDy = pathCy(crossedBoundary) - pathCy(crossedBoundary - 1);\n      var bGap = Math.sqrt(bDx * bDx + bDy * bDy);\n      var keptMaskPB = playback.passKeptMask;\n      var boundaryOnKept = keptMaskPB ? keptMaskPB[crossedBoundary] === 1 : true;\n      if(bGap >= wMcheck * 0.5 ? boundaryOnKept : false){\n        playback.idxFloat = crossedBoundary;\n        playback.idx = crossedBoundary;\n        setupTurnaround(crossedBoundary);\n        draw();\n        updatePlaybackUI();\n        playback.raf = requestAnimationFrame(playbackLoop);\n        return;\n      }\n    }\n    playback.idxFloat = newIdxFloat;\n    if(playback.idxFloat > values.length) playback.idxFloat = values.length;\n    playback.idx = Math.floor(playback.idxFloat);\n    draw();\n    updatePlaybackUI();\n    if(playback.idx >= values.length){\n      playback.active = false;\n      playback.raf = null;\n      var pbBtn = $('#gpy-pb-play');\n      if(pbBtn){ pbBtn.textContent = '\u25b6'; pbBtn.setAttribute('aria-label', 'Play'); }\n      return;\n    }\n    playback.raf = requestAnimationFrame(playbackLoop);\n  }\n  function playbackPlay(){\n    if(currentIsBoundary) return;\n    if(!values.length) return;\n    if(playback.active) return;\n    playback.active = true;\n    if(playback.idx >= values.length){ playback.idx = 0; }\n    playback.idxFloat = playback.idx;\n    playback.lastT = 0;\n    playback.smoothedHeading = null;\n    playback.smoothedX = null;\n    playback.smoothedY = null;\n    playback.turnAct = false;\n    playback.turnFrac = 0;\n    playback.turnBezier = null;\n    playback.raf = requestAnimationFrame(playbackLoop);\n    updatePlaybackUI();\n  }\n  function playbackPause(){\n    if(currentIsBoundary) return;\n    if(!playback.active) return;\n    playback.active = false;\n    if(playback.raf){ cancelAnimationFrame(playback.raf); playback.raf = null; }\n    updatePlaybackUI();\n  }\n  \/\/ Toggle entrypoint kept for keyboard shortcut (Space).\n  function playbackPlayPause(){\n    if(playback.active) playbackPause(); else playbackPlay();\n  }\n  function playbackScrub(clientX){\n    if(playback.raf){ cancelAnimationFrame(playback.raf); playback.raf = null; }\n    playback.active = false;\n    var track = $('#gpy-pb-track');\n    if(!track) return;\n    var rect = track.getBoundingClientRect();\n    var pct = Math.max(0, Math.min(1, (clientX - rect.left) \/ rect.width));\n    playback.idx = Math.floor(pct * values.length);\n    if(playback.idx > values.length) playback.idx = values.length;\n    playback.idxFloat = playback.idx;\n    playback.smoothedHeading = null;\n    playback.smoothedX = null;\n    playback.smoothedY = null;\n    playback.turnAct = false;\n    playback.turnFrac = 0;\n    playback.turnBezier = null;\n    draw();\n    updatePlaybackUI();\n  }\n  \/\/ \u2500\u2500 interaction \u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\n  \/\/ `mouseDownAt` tracks where a mousedown began so we can distinguish a click (no movement)\n  \/\/ from a pan (\u2265 5 px movement). The ruler tool needs this so clicking on the canvas in\n  \/\/ ruler mode adds a waypoint, but mouse-down + drag still pans the map.\n  var dragging = false, last = [0,0], mouseDownAt = null;\n  canvas.addEventListener('mousedown', function(e){\n    if(!values.length) return;\n    dragging = true;\n    last = [e.clientX, e.clientY];\n    mouseDownAt = [e.clientX, e.clientY];\n    canvas.style.cursor = 'grabbing';\n  });\n  window.addEventListener('mouseup', function(e){\n    var wasDragging = dragging;\n    dragging = false;\n    canvas.style.cursor = ruler.active ? 'crosshair' : 'crosshair';\n    \/\/ Treat a quick mouseup near the mousedown point as a click (not a pan).\n    if(wasDragging ? (ruler.active ? mouseDownAt : false) : false){\n      var movedX = e.clientX - mouseDownAt[0];\n      var movedY = e.clientY - mouseDownAt[1];\n      if(movedX*movedX + movedY*movedY < 25){  \/\/ < 5 px movement \u2192 click\n        var rect = canvas.getBoundingClientRect();\n        var sx = e.clientX - rect.left, sy = e.clientY - rect.top;\n        if(sx >= 0 ? (sy >= 0 ? (sx <= rect.width ? sy <= rect.height : false) : false) : false){\n          rulerAddPoint(sx, sy);\n        }\n      }\n    }\n    mouseDownAt = null;\n  });\n  window.addEventListener('mousemove', function(e){ if(dragging){ view.tx+=e.clientX-last[0]; view.ty+=e.clientY-last[1]; last=[e.clientX,e.clientY]; draw(); } });\n  canvas.addEventListener('wheel', function(e){\n    if(!values.length) return;\n    e.preventDefault();\n    var rect = canvas.getBoundingClientRect();\n    var cx = e.clientX-rect.left, cy = e.clientY-rect.top;\n    var wx = (cx-view.tx)\/view.scale, wy = (cy-view.ty)\/view.scale;\n    view.scale *= Math.exp(-e.deltaY*0.0015);\n    view.scale = Math.max(0.1, Math.min(5000, view.scale));\n    view.tx = cx - wx*view.scale; view.ty = cy - wy*view.scale;\n    draw();\n  }, { passive:false });\n  \/\/ Touch: single-finger pan, two-finger pinch-zoom + pan, tap to show tooltip.\n  var touchState = null;\n  function _tDist(a,b){ var dx=a.clientX-b.clientX, dy=a.clientY-b.clientY; return Math.sqrt(dx*dx+dy*dy); }\n  function _tCenter(a,b){ return [(a.clientX+b.clientX)\/2, (a.clientY+b.clientY)\/2]; }\n  canvas.addEventListener('touchstart', function(e){\n    if(!values.length) return;\n    if(e.touches.length === 1){\n      e.preventDefault();\n      touchState = { mode:'pan', x:e.touches[0].clientX, y:e.touches[0].clientY, moved:false };\n    } else if(e.touches.length >= 2){\n      e.preventDefault();\n      var c = _tCenter(e.touches[0], e.touches[1]);\n      touchState = { mode:'pinch', dist:_tDist(e.touches[0], e.touches[1]), cx:c[0], cy:c[1] };\n    }\n  }, { passive:false });\n  canvas.addEventListener('touchmove', function(e){\n    if(!touchState) return;\n    e.preventDefault();\n    if(touchState.mode === 'pan' ? e.touches.length === 1 : false){\n      var t = e.touches[0];\n      var dx = t.clientX - touchState.x, dy = t.clientY - touchState.y;\n      view.tx += dx; view.ty += dy;\n      touchState.x = t.clientX; touchState.y = t.clientY;\n      if(Math.abs(dx) > 4 || Math.abs(dy) > 4) touchState.moved = true;\n      draw();\n    } else if(touchState.mode === 'pinch' ? e.touches.length >= 2 : false){\n      var newDist = _tDist(e.touches[0], e.touches[1]);\n      var newC = _tCenter(e.touches[0], e.touches[1]);\n      var rectT = canvas.getBoundingClientRect();\n      var cx0 = touchState.cx - rectT.left, cy0 = touchState.cy - rectT.top;\n      var wx0 = (cx0 - view.tx) \/ view.scale, wy0 = (cy0 - view.ty) \/ view.scale;\n      view.scale *= newDist \/ touchState.dist;\n      view.scale = Math.max(0.1, Math.min(5000, view.scale));\n      var ncx = newC[0] - rectT.left, ncy = newC[1] - rectT.top;\n      view.tx = ncx - wx0 * view.scale; view.ty = ncy - wy0 * view.scale;\n      touchState.dist = newDist; touchState.cx = newC[0]; touchState.cy = newC[1];\n      draw();\n    }\n  }, { passive:false });\n  canvas.addEventListener('touchend', function(e){\n    if(touchState ? touchState.mode === 'pan' : false){\n      if(touchState.moved ? false : values.length){\n        var rectE = canvas.getBoundingClientRect();\n        var cxT = touchState.x - rectE.left, cyT = touchState.y - rectE.top;\n        \/\/ Ruler mode: tap-tap-tap to drop waypoints, no tooltip.\n        if(ruler.active){\n          rulerAddPoint(cxT, cyT);\n          if(e.touches.length === 0) touchState = null;\n          return;\n        }\n        var bestT = -1;\n        if(mode === 'point'){\n          var nT = values.length, bestDT = 900;\n          for(var iT=0; iT<nT; iT++){\n            var ddx = sxArr[iT]-cxT, ddy = syArr[iT]-cyT, dT = ddx*ddx+ddy*ddy;\n            if(dT < bestDT){ bestDT = dT; bestT = iT; }\n          }\n        } else {\n          var mxwT = (cxT-view.tx)\/view.scale, mywT = (cyT-view.ty)\/view.scale;\n          bestT = findHitPoly(mxwT, mywT);\n        }\n        if(bestT >= 0){\n          var kT = outClass[bestT];\n          var labelT = kT===0 ? 'inlier' : (kT===1 ? 'low' : 'high outlier');\n          var unitT = currentUnit ? ' <span style=\"color:var(--ink-dim);font-size:10px\">'+currentUnit+'<\/span>' : '';\n          var locT = '';\n          if(mode === 'point'){\n            locT = '<div class=\"tk\" style=\"margin-top:3px\">'+coords[bestT][1].toFixed(5)+', '+coords[bestT][0].toFixed(5)+'<\/div>';\n          }\n          tip.innerHTML = '<div class=\"tv\">'+fmt(values[bestT])+unitT+'<\/div>' +\n                          '<div class=\"tk\">'+currentCol+' \u00b7 '+labelT+'<\/div>' + locT;\n          var maxX = rectE.width - 180, maxY = rectE.height - 80;\n          var posX = cxT + 14, posY = cyT + 14;\n          if(posX > maxX) posX = maxX; if(posY > maxY) posY = maxY;\n          tip.style.left = posX+'px'; tip.style.top = posY+'px'; tip.style.opacity = 1;\n          setTimeout(function(){ tip.style.opacity = 0; }, 2800);\n        }\n      }\n    }\n    if(e.touches.length === 0) touchState = null;\n    else if(e.touches.length === 1){\n      touchState = { mode:'pan', x:e.touches[0].clientX, y:e.touches[0].clientY, moved:true };\n    }\n  }, { passive:false });\n  canvas.addEventListener('touchcancel', function(){ touchState = null; }, { passive:true });\n  function findHitPoly(mxw, myw){\n    \/\/ ray-cast point-in-polygon, with bbox prefilter\n    var n = features.length;\n    for(var i=0;i<n;i++){\n      var p = polyData[i];\n      if(mxw<p.minX||mxw>p.maxX||myw<p.minY||myw>p.maxY) continue;\n      var inside = false;\n      for(var ri=0; ri<p.rings.length; ri++){\n        var rmx = p.rings[ri].mx, rmy = p.rings[ri].my;\n        for(var a=0, b=rmx.length-1; a<rmx.length; b=a++){\n          if(((rmy[a]>myw) !== (rmy[b]>myw)) ?\n             (mxw < (rmx[b]-rmx[a]) * (myw-rmy[a]) \/ (rmy[b]-rmy[a]) + rmx[a]) : false){\n            inside = !inside;\n          }\n        }\n      }\n      if(inside) return i;\n    }\n    return -1;\n  }\n  \/\/ Sticky-tip state: when set true (after a feature click), mousemove leaves the\n  \/\/ tooltip alone so the user can scroll the full-property panel without it flickering\n  \/\/ back to hover mode. Cleared on close-button click or a canvas click that doesn't\n  \/\/ hit a feature.\n  var stickyTip = false;\n  \/\/ Find which feature is under (cx, cy) screen coords. Same logic as the existing\n  \/\/ mousemove hit-test but pulled out so the click handler can reuse it.\n  function hitFeatureAt(cx, cy){\n    if(!values.length) return -1;\n    if(mode === 'point'){\n      var n = values.length, bestD = 200;\n      var bi = -1;\n      for(var i=0; i<n; i++){\n        var dx = sxArr[i]-cx, dy = syArr[i]-cy, d = dx*dx+dy*dy;\n        if(d < bestD){ bestD = d; bi = i; }\n      }\n      return bi;\n    }\n    var mxw = (cx-view.tx)\/view.scale, myw = (cy-view.ty)\/view.scale;\n    return findHitPoly(mxw, myw);\n  }\n  \/\/ Minimal HTML-escape for property values; protects against attribute-name or\n  \/\/ value strings that contain HTML-significant characters when injected via .innerHTML.\n  \/\/ Builds entity strings via String.fromCharCode(38) so no literal ampersand appears\n  \/\/ in the source (rule 1 in CLAUDE.md \u2014 WordPress encodes bare ampersand in script\n  \/\/ bodies to a numeric entity and breaks JS).\n  function escForTip(s){\n    var amp = String.fromCharCode(38);\n    return String(s)\n      .split(amp).join(amp + 'amp;')\n      .split('<').join(amp + 'lt;')\n      .split('>').join(amp + 'gt;')\n      .split('\"').join(amp + 'quot;');\n  }\n  canvas.addEventListener('mousemove', function(e){\n    if(stickyTip) return;\n    if(!values.length || dragging){ tip.style.opacity=0; return; }\n    var rect = canvas.getBoundingClientRect();\n    var cx = e.clientX-rect.left, cy = e.clientY-rect.top;\n    if(ruler.active){\n      tip.style.opacity = 0;\n      var mxwR = (cx - view.tx) \/ view.scale;\n      var mywR = (cy - view.ty) \/ view.scale;\n      ruler.hover = { mx: mxwR, my: mywR };\n      if(ruler.points.length > 0) draw();\n      return;\n    }\n    var best = hitFeatureAt(cx, cy);\n    if(best>=0){\n      var k = outClass[best];\n      var label = k===0 ? 'inlier' : (k===1 ? 'low' : 'high outlier');\n      var unit = currentUnit ? ' <span style=\"color:var(--ink-dim);font-size:10px\">'+currentUnit+'<\/span>' : '';\n      var loc = '';\n      if(mode === 'point'){\n        loc = '<div class=\"tk\" style=\"margin-top:3px\">'+coords[best][1].toFixed(5)+', '+coords[best][0].toFixed(5)+'<\/div>';\n      }\n      tip.innerHTML = '<div class=\"tv\">'+fmt(values[best])+unit+'<\/div>' +\n                      '<div class=\"tk\">'+currentCol+' \u00b7 '+label+'<\/div>' + loc;\n      tip.style.left = (cx+14)+'px'; tip.style.top = (cy+14)+'px'; tip.style.opacity = 1;\n    } else if(mode === 'point' ? interpCache.canvas : false){\n      \/\/ No point hit \u2014 show the interpolated IDW value at the cursor (only\n      \/\/ for point datasets that have a built grid). Marked \"predicted\" so the\n      \/\/ user knows it's an estimate, not a measurement.\n      var mxw = (cx - view.tx) \/ view.scale;\n      var myw = (cy - view.ty) \/ view.scale;\n      var pv = sampleInterpAt(mxw, myw);\n      if(pv !== null ? isFinite(pv) : false){\n        var unitP = currentUnit ? ' <span style=\"color:var(--ink-dim);font-size:10px\">'+currentUnit+'<\/span>' : '';\n        tip.innerHTML = '<div class=\"tv\">'+fmt(pv)+unitP+'<\/div>' +\n                        '<div class=\"tk\">'+currentCol+' \u00b7 predicted<\/div>';\n        tip.style.left = (cx+14)+'px'; tip.style.top = (cy+14)+'px'; tip.style.opacity = 1;\n      } else tip.style.opacity = 0;\n    } else tip.style.opacity = 0;\n  });\n  canvas.addEventListener('mouseleave', function(){ if(!stickyTip) tip.style.opacity=0; });\n  \/\/ Click handler: full details for the hit feature \u2014 ID + every property + lng\/lat\n  \/\/ (points). Sticks until the close \u00d7 is clicked or the user clicks empty canvas.\n  canvas.addEventListener('click', function(e){\n    if(dragging) return;\n    if(ruler.active) return;\n    var rect = canvas.getBoundingClientRect();\n    var cx = e.clientX - rect.left, cy = e.clientY - rect.top;\n    var best = hitFeatureAt(cx, cy);\n    if(best < 0){\n      stickyTip = false;\n      tip.classList.remove('sticky');\n      tip.style.opacity = 0;\n      return;\n    }\n    var f = (features ? features[best] : null);\n    var hasFid = (f ? (f.id !== undefined ? f.id !== null : false) : false);\n    var unit2 = currentUnit ? ' <span style=\"color:var(--ink-dim);font-size:10px\">'+currentUnit+'<\/span>' : '';\n    var html = '<button type=\"button\" class=\"gpy-tip-close\" aria-label=\"Close\">\u00d7<\/button>';\n    html += '<div class=\"tv\">'+fmt(values[best])+unit2+'<\/div>';\n    html += '<div class=\"tk\">'+escForTip(currentCol)+'<\/div>';\n    if(hasFid){\n      html += '<div class=\"gpy-tip-row\" style=\"margin-top:8px;border-top:1px solid var(--line2);padding-top:6px\"><span class=\"gpy-tip-k\">id<\/span><span class=\"gpy-tip-v\">'+escForTip(String(f.id))+'<\/span><\/div>';\n    }\n    \/\/ Iterate ONLY the file's own properties. Skip underscore-prefixed keys (these\n    \/\/ are synthetic markers we add for internal renderer use, e.g. _index injected\n    \/\/ on attribute-less line features) so the click panel reflects what's actually\n    \/\/ in the source GeoJSON, not anything we computed.\n    if(f ? f.properties : false){\n      var props = f.properties;\n      var keys = Object.keys(props).filter(function(k){\n        return k.charAt(0) !== '_';\n      });\n      keys.sort();\n      var sectionStarted = hasFid;\n      for(var pk=0; pk<keys.length; pk++){\n        var key = keys[pk];\n        var val = props[key];\n        if(val === undefined ? true : val === null) val = '\u2014';\n        if(typeof val === 'object') val = JSON.stringify(val);\n        var sep = sectionStarted ? '' : ' style=\"margin-top:8px;border-top:1px solid var(--line2);padding-top:6px\"';\n        html += '<div class=\"gpy-tip-row\"'+sep+'><span class=\"gpy-tip-k\">'+escForTip(key)+'<\/span><span class=\"gpy-tip-v\">'+escForTip(String(val))+'<\/span><\/div>';\n        sectionStarted = true;\n      }\n    }\n    if(mode === 'point' ? coords[best] : false){\n      html += '<div class=\"gpy-tip-row\" style=\"margin-top:6px;border-top:1px solid var(--line2);padding-top:6px\"><span class=\"gpy-tip-k\">lng \/ lat<\/span><span class=\"gpy-tip-v\">'+coords[best][0].toFixed(6)+', '+coords[best][1].toFixed(6)+'<\/span><\/div>';\n    }\n    tip.innerHTML = html;\n    tip.classList.add('sticky');\n    stickyTip = true;\n    \/\/ Position tip; if it would overflow, anchor against the opposite side.\n    var maxLeft = window.innerWidth - 360;\n    var px = cx + 14;\n    if(px > maxLeft) px = Math.max(8, cx - 360);\n    var py = cy + 14;\n    var maxTop = window.innerHeight - 440;\n    if(py > maxTop) py = Math.max(8, cy - 440);\n    tip.style.left = px + 'px';\n    tip.style.top = py + 'px';\n    tip.style.opacity = 1;\n    var closeBtn = tip.querySelector('.gpy-tip-close');\n    if(closeBtn){\n      closeBtn.addEventListener('click', function(){\n        stickyTip = false;\n        tip.classList.remove('sticky');\n        tip.style.opacity = 0;\n      });\n    }\n  });\n  $('#gpy-zin').onclick = function(){ view.scale*=1.4; view.tx=W\/2-(W\/2-view.tx)*1.4; view.ty=H\/2-(H\/2-view.ty)*1.4; draw(); };\n  $('#gpy-zout').onclick = function(){ view.scale\/=1.4; view.tx=W\/2-(W\/2-view.tx)\/1.4; view.ty=H\/2-(H\/2-view.ty)\/1.4; draw(); };\n  $('#gpy-reset').onclick = function(){ fitView(); draw(); };\n  \/\/ General \"Export\" \u2014 download the ACTIVE layer (any geometry: point \/ polygon \/\n  \/\/ line) as a zipped shapefile with all its attributes, EPSG:4326. Unlike the\n  \/\/ zones export (which lives in the Auto-Zones panel and exports computed zone\n  \/\/ polygons), this works for ANY uploaded file without first creating zones \u2014\n  \/\/ added 2026-06-10 after the zones panel (and its export) was hidden on small\n  \/\/ pre-zoned soil files.\n  function exportLayerAsShapefile(){\n    var active = null;\n    for(var di=0; di<datasets.length; di++){ if(datasets[di].id === activeDatasetId){ active = datasets[di]; break; } }\n    var feats = active ? active.features : features;\n    if(!feats ? true : !feats.length){ showToast('Load a layer first, then Export.'); return; }\n    var btn = $('#gpy-export');\n    if(btn) btn.disabled = true;\n    var t0 = Date.now();\n    function fail(err){\n      showToast('Export failed: ' + (err ? (err.message ? err.message : 'see console') : 'see console'));\n      try { console.error('[GPY export]', err); } catch(_){}\n      if(btn) btn.disabled = false;\n    }\n    showToast('Loading shapefile writer\u2026', 'info');\n    Promise.all([loadJSZip(), loadShpWrite()]).then(function(){\n      var slug = '';\n      try { if(active ? active.name : false){ slug = active.name.replace(\/[^a-z0-9_\\-]+\/gi, '_').replace(\/^_+|_+$\/g, '').slice(0, 45); } } catch(_){}\n      var safeName = 'geopard_' + (slug || 'layer');\n      var fc = { type:'FeatureCollection', features: feats };\n      var opts = { folder: safeName, types:{ point: safeName, polygon: safeName, polyline: safeName }, type:'base64', compression:'STORE' };\n      showToast('Encoding shapefile\u2026', 'info');\n      var doEncode = function(){\n        var raw;\n        try { raw = window.shpwrite.zip(fc, opts); } catch(err){ return fail(err); }\n        zipResultToBlob(raw).then(function(blob){\n          var url = URL.createObjectURL(blob);\n          var a = document.createElement('a');\n          a.href = url; a.download = safeName + '.zip'; a.style.display = 'none';\n          document.body.appendChild(a); a.click(); document.body.removeChild(a);\n          setTimeout(function(){ URL.revokeObjectURL(url); }, 1500);\n          var ms = Date.now() - t0;\n          showToast('Downloaded ' + safeName + '.zip \u00b7 ' + (ms < 1000 ? (ms + ' ms') : ((ms\/1000).toFixed(1) + ' s')), 'ok');\n          if(btn) btn.disabled = false;\n        }).catch(fail);\n      };\n      if(window.requestAnimationFrame){ window.requestAnimationFrame(function(){ setTimeout(doEncode, 0); }); } else { setTimeout(doEncode, 0); }\n    }).catch(fail);\n  }\n  $('#gpy-export').onclick = exportLayerAsShapefile;\n  \/\/ Normalise whatever shp-write returns into a Blob. The 0.4.3 release\n  \/\/ bundles JSZip 3.x internally \u2014 depending on options, zip.generate may\n  \/\/ return a Promise, a Uint8Array, an ArrayBuffer, a raw binary string,\n  \/\/ or (when type:'base64' is honoured) a base64 string. We detect each\n  \/\/ case and produce an application\/zip Blob so the download anchor flow\n  \/\/ is uniform.\n  function zipResultToBlob(data){\n    return new Promise(function(resolve, reject){\n      function asBlob(b){ resolve(new Blob([b], { type:'application\/zip' })); }\n      try {\n        if(data ? typeof data.then === 'function' : false){\n          data.then(function(inner){\n            zipResultToBlob(inner).then(resolve, reject);\n          }, reject);\n          return;\n        }\n        if(typeof Blob !== 'undefined' ? data instanceof Blob : false){ resolve(data); return; }\n        if(data instanceof Uint8Array){ asBlob(data); return; }\n        if(data instanceof ArrayBuffer){ asBlob(new Uint8Array(data)); return; }\n        if(typeof data === 'string'){\n          \/\/ Detect raw binary string (zip file starts with PK\\x03\\x04 = bytes\n          \/\/ 0x50 0x4B 0x03 0x04). Base64 of that starts with 'UEsDB'.\n          var isBinary = data.length >= 4\n            ? (data.charCodeAt(0) === 0x50 ? data.charCodeAt(1) === 0x4B : false)\n            : false;\n          var arr;\n          if(isBinary){\n            arr = new Uint8Array(data.length);\n            for(var i=0; i<data.length; i++) arr[i] = data.charCodeAt(i) % 256;\n          } else {\n            \/\/ Best-effort base64 decode \u2014 clean whitespace just in case.\n            var clean = data.replace(\/\\s\/g, '');\n            var bin = atob(clean);\n            arr = new Uint8Array(bin.length);\n            for(var j=0; j<bin.length; j++) arr[j] = bin.charCodeAt(j);\n          }\n          asBlob(arr);\n          return;\n        }\n        reject(new Error('Unexpected shp-write output type: ' + (typeof data)));\n      } catch(err){ reject(err); }\n    });\n  }\n  \/\/ \u2500\u2500 Export current layer as zipped shapefile \u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\n  \/\/ EPSG:4326 only (matches what we accept on upload). shp-write splits the\n  \/\/ FeatureCollection into per-geometry-type shapefiles (points \/ lines \/\n  \/\/ polygons) and zips them. Attribute names get truncated to 10 chars per\n  \/\/ the DBF spec \u2014 that's a shapefile-format limitation, not ours.\n  \/\/\n  \/\/ Performance: shp-write's built-in download() uses a `location.href =\n  \/\/ \"data:application\/zip;base64,\u2026\"` data URL \u2014 that's slow for non-trivial\n  \/\/ datasets (the browser has to parse the entire base64 string into memory).\n  \/\/ We call shpwrite.zip() to get the base64, then build a Blob and trigger\n  \/\/ the download via an anchor \u2014 5-10\u00d7 faster on yield-sized files. Libs are\n  \/\/ also preloaded on tool boot (see preloadExportLibs below) so the first\n  \/\/ click doesn't pay the ~150 KB jsDelivr fetch latency.\n  function exportCurrentAsShapefile(){\n    if(!features ? true : !features.length){\n      showToast('Nothing to export yet \u2014 load a dataset first.');\n      return;\n    }\n    var btn = $('#gpy-export');\n    if(btn) btn.disabled = true;\n    var t0 = Date.now();\n    showToast('Building shapefile\u2026', 'info');\n    Promise.all([loadJSZip(), loadShpWrite()]).then(function(){\n      \/\/ Build a fresh FeatureCollection. Reuse references; no deep copy needed.\n      var feats = new Array(features.length);\n      for(var i=0;i<features.length;i++){\n        var f = features[i];\n        feats[i] = {\n          type:'Feature',\n          geometry: f.geometry,\n          properties: f.properties ? f.properties : {}\n        };\n      }\n      var fc = { type:'FeatureCollection', features: feats };\n      \/\/ Always prefix with \"geopard_\" so the zip + folder + inner shapefiles\n      \/\/ all carry the brand. Helps when these files land in a third-party\n      \/\/ FMIS alongside other shapefiles.\n      var datasetSlug = '';\n      try {\n        var active = datasets ? datasets.find(function(d){ return d.id === activeDatasetId; }) : null;\n        if(active ? active.name : false){\n          datasetSlug = active.name.replace(\/[^a-z0-9_\\-]+\/gi,'_').replace(\/^_+|_+$\/g,'').slice(0,50);\n        }\n      } catch(_){}\n      var safeName = 'geopard_' + (datasetSlug ? datasetSlug + '_' : '') + 'export';\n      var opts = {\n        folder: safeName,\n        \/\/ Inner per-type shapefile names also carry the geopard prefix.\n        types: { point:'geopard_points', polygon:'geopard_polygons', polyline:'geopard_lines' },\n        \/\/ type:'base64' must be explicit. shp-write 0.4.3 only defaults to\n        \/\/ base64 when the entire options arg is omitted; the moment we pass\n        \/\/ any option (folder, types, compression) without a type, JSZip\n        \/\/ falls back to its default 'string' (raw binary) and our atob()\n        \/\/ step throws \"string to be decoded is not correctly encoded\".\n        type: 'base64',\n        compression: 'STORE'  \/\/ shapefile binaries don't compress meaningfully \u2014 STORE is faster\n      };\n      \/\/ Defer the heavy synchronous work so the \"Building\u2026\" toast paints first.\n      setTimeout(function(){\n        var raw;\n        try { raw = window.shpwrite.zip(fc, opts); }\n        catch(err){\n          showToast('Export failed: ' + (err.message ? err.message : 'see console'));\n          try { console.error('[GPY export]', err); } catch(_){}\n          if(btn) btn.disabled = false;\n          return;\n        }\n        zipResultToBlob(raw).then(function(blob){\n          var url = URL.createObjectURL(blob);\n          var a = document.createElement('a');\n          a.href = url; a.download = safeName + '.zip';\n          a.style.display = 'none';\n          document.body.appendChild(a);\n          a.click();\n          document.body.removeChild(a);\n          setTimeout(function(){ URL.revokeObjectURL(url); }, 1500);\n          var ms = Date.now() - t0;\n          showToast('Downloaded ' + safeName + '.zip \u00b7 ' + (ms < 1000 ? (ms+' ms') : ((ms\/1000).toFixed(1)+' s')), 'ok');\n          if(btn) btn.disabled = false;\n        }).catch(function(err){\n          showToast('Export failed: ' + (err.message ? err.message : 'see console'));\n          try { console.error('[GPY export]', err); } catch(_){}\n          if(btn) btn.disabled = false;\n        });\n      }, 0);\n    }).catch(function(err){\n      showToast('Could not load shapefile writer: ' + (err.message ? err.message : 'network error'));\n      if(btn) btn.disabled = false;\n    });\n  }\n  var exportBtn = $('#gpy-export');\n  if(exportBtn) exportBtn.onclick = exportCurrentAsShapefile;\n  \/\/ \u2500\u2500 zone polygon builders \u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\n  \/\/ Inverse of lngToWmX \/ latToWmY for relative mercator coords (mx\/my are\n  \/\/ stored relative to wmCx\/wmCy with Y flipped \u2014 see line ~3098).\n  function mxmyToLngLat(mx, my){\n    var lng = (mx + wmCx) \/ (R * DEG);\n    var wmY = wmCy - my;\n    var lat = (Math.atan(Math.exp(wmY \/ R)) * 360 \/ Math.PI) - 90;\n    return [lng, lat];\n  }\n  \/\/ Point-in-polygon (ray-casting) for a Float32 hull ring on mercator coords.\n  function pointInHullMerc(px, py, hull){\n    if(!hull ? true : !hull.x) return true;\n    var n = hull.x.length - 1; \/\/ ring closes (last == first)\n    var inside = false;\n    for(var i=0, j=n-1; i<n; j=i++){\n      var xi = hull.x[i], yi = hull.y[i];\n      var xj = hull.x[j], yj = hull.y[j];\n      var intersect = ((yi > py) !== (yj > py)) ? (px < (xj - xi) * (py - yi) \/ ((yj - yi) || 1e-12) + xi) : false;\n      if(intersect) inside = !inside;\n    }\n    return inside;\n  }\n  \/\/ Build per-zone MultiPolygon features for POINT datasets via the IDW grid.\n  \/\/ Each grid cell is classified by zone; consecutive same-zone cells in the\n  \/\/ same row are merged into a single rectangle (row-run encoding); rectangles\n  \/\/ are emitted as Polygons inside the zone's MultiPolygon. Cells outside the\n  \/\/ field hull are skipped.\n  function buildZonePolygonsFromIDW(opts){\n    if(!interpCache.values ? true : !interpCache.bbox) return null;\n    if(!zoneBreaks ? true : !zonesK) return null;\n    var gW = interpCache.gridW, gH = interpCache.gridH;\n    var bbox = interpCache.bbox;\n    var dx = (bbox[2] - bbox[0]) \/ gW;\n    var dy = (bbox[3] - bbox[1]) \/ gH;\n    var hulls = playback.fieldHulls;\n    var hull = (hulls ? hulls[0] : null) || null;\n    \/\/ Classify each cell into a zone, or -1 if outside hull \/ NaN.\n    var zg = new Int8Array(gW * gH);\n    for(var gy=0; gy<gH; gy++){\n      var cy = bbox[1] + (gy + 0.5) * dy;\n      for(var gx=0; gx<gW; gx++){\n        var cx = bbox[0] + (gx + 0.5) * dx;\n        if(hull ? !pointInHullMerc(cx, cy, hull) : false){ zg[gy*gW+gx] = -1; continue; }\n        var v = interpCache.values[gy*gW+gx];\n        if(!isFinite(v)){ zg[gy*gW+gx] = -1; continue; }\n        var z = 0;\n        for(var b=0; b<zoneBreaks.length; b++){\n          if(v >= zoneBreaks[b]) z = b + 1;\n          else break;\n        }\n        if(z >= zonesK) z = zonesK - 1;\n        zg[gy*gW+gx] = z;\n      }\n    }\n    \/\/ Neighbour-majority denoise on the zone grid \u2014 absorbs single-cell\n    \/\/ anomalies and small clusters into their surrounding zone. Eliminates\n    \/\/ \"tiny same-color island inside a hole\" artefacts that show up in the\n    \/\/ export when an IDW cell happens to flip zone class on its own. Two\n    \/\/ passes over the grid; each pass: if \u2265 3 of a cell's 4 neighbours\n    \/\/ (excluding outside-hull \/ -1 cells) belong to a single OTHER zone,\n    \/\/ reclassify the cell to that zone.\n    (function denoiseZoneGrid(){\n      \/\/ Hoist allocations: the per-cell `new Int32Array(zonesK)` previously\n      \/\/ cost ~18k small-array allocations on the 96\u00d796 grid \u00d7 2 passes,\n      \/\/ which dominated the polygon-build time on dense scans. Reuse one\n      \/\/ counter array, reset only the slots we touched.\n      var nCounts = new Int32Array(zonesK);\n      var next = new Int8Array(gW * gH);\n      var touched = new Int32Array(zonesK);\n      for(var pass=0; pass<2; pass++){\n        for(var i=0; i<gW*gH; i++) next[i] = zg[i];\n        var changed = 0;\n        for(var dy2=0; dy2<gH; dy2++){\n          var rowOff = dy2*gW;\n          for(var dx2=0; dx2<gW; dx2++){\n            var here = zg[rowOff+dx2];\n            if(here < 0) continue;\n            \/\/ Reset only zones we touched in the previous cell \u2014 cheaper\n            \/\/ than zeroing the full Int32Array(zonesK) every iteration.\n            var tN = 0;\n            \/\/ Inline neighbour reads: avoid array indexing in inner-most loop.\n            var nTotal = 0;\n            var n1 = dy2 > 0 ? zg[rowOff-gW+dx2] : -1;\n            var n2 = dy2 < gH-1 ? zg[rowOff+gW+dx2] : -1;\n            var n3 = dx2 > 0 ? zg[rowOff+dx2-1] : -1;\n            var n4 = dx2 < gW-1 ? zg[rowOff+dx2+1] : -1;\n            if(n1 >= 0){ if(nCounts[n1] === 0) touched[tN++] = n1; nCounts[n1]++; nTotal++; }\n            if(n2 >= 0){ if(nCounts[n2] === 0) touched[tN++] = n2; nCounts[n2]++; nTotal++; }\n            if(n3 >= 0){ if(nCounts[n3] === 0) touched[tN++] = n3; nCounts[n3]++; nTotal++; }\n            if(n4 >= 0){ if(nCounts[n4] === 0) touched[tN++] = n4; nCounts[n4]++; nTotal++; }\n            if(nTotal >= 3){\n              var bestZ = -1, bestN = 0;\n              for(var ti=0; ti<tN; ti++){\n                var bz = touched[ti];\n                if(nCounts[bz] > bestN){ bestN = nCounts[bz]; bestZ = bz; }\n              }\n              if(bestZ >= 0 ? bestZ !== here : false){\n                if(bestN >= 3){ next[rowOff+dx2] = bestZ; changed++; }\n              }\n            }\n            \/\/ Reset only touched slots \u2014 bounded by 4 per cell.\n            for(var ti2=0; ti2<tN; ti2++) nCounts[touched[ti2]] = 0;\n          }\n        }\n        \/\/ Swap zg \u2194 next in place by toggling references; copy back next pass.\n        var tmp = zg; zg = next; next = tmp;\n        if(!changed) break;\n      }\n    })();\n    \/\/ Aggregate same-zone cells into MERGED polygon rings via edge-cancellation.\n    \/\/ For every in-zone cell we add its 4 boundary edges with a CCW winding;\n    \/\/ edges shared between two same-zone cells appear from opposite directions\n    \/\/ and cancel. Remaining edges form the boundary of each connected zone\n    \/\/ region. We then walk those edges endpoint-to-endpoint to trace rings.\n    \/\/ Result: a clean MultiPolygon per zone, one ring per contiguous blob \u2014\n    \/\/ matches the raster pattern you see on screen as proper merged polygons.\n    function ringsForZone(targetZ){\n      var edgeMap = {};\n      function addEdge(x1, y1, x2, y2){\n        var keyF = x1 + ',' + y1 + '|' + x2 + ',' + y2;\n        var keyR = x2 + ',' + y2 + '|' + x1 + ',' + y1;\n        \/\/ Reverse-direction edge already present? Pair cancels \u2014 interior edge.\n        if(edgeMap[keyR]){ delete edgeMap[keyR]; return; }\n        edgeMap[keyF] = [x1, y1, x2, y2];\n      }\n      for(var gy=0; gy<gH; gy++){\n        for(var gx=0; gx<gW; gx++){\n          if(zg[gy*gW+gx] !== targetZ) continue;\n          \/\/ CCW winding (Y grows downward in our mercator-y convention):\n          \/\/ top-right \u2192 top-left \u2192 bottom-left \u2192 bottom-right \u2192 top-right\n          addEdge(gx+1, gy,   gx,   gy);\n          addEdge(gx,   gy,   gx,   gy+1);\n          addEdge(gx,   gy+1, gx+1, gy+1);\n          addEdge(gx+1, gy+1, gx+1, gy);\n        }\n      }\n      \/\/ Index remaining (boundary) edges by start vertex for the ring walk.\n      var byStart = {};\n      for(var k1 in edgeMap){\n        var e1 = edgeMap[k1];\n        var sk = e1[0] + ',' + e1[1];\n        if(!byStart[sk]) byStart[sk] = [];\n        byStart[sk].push(e1);\n      }\n      var rings = [];\n      var liveKeys = Object.keys(edgeMap);\n      for(var lk=0; lk<liveKeys.length; lk++){\n        var startKey = liveKeys[lk];\n        if(!edgeMap[startKey]) continue;\n        var first = edgeMap[startKey];\n        var ring = [];\n        var cur = first;\n        var safety = 0;\n        while(cur ? safety < 200000 : false){\n          ring.push([cur[0], cur[1]]);\n          delete edgeMap[cur[0] + ',' + cur[1] + '|' + cur[2] + ',' + cur[3]];\n          var nexts = byStart[cur[2] + ',' + cur[3]];\n          var picked = null;\n          if(nexts){\n            while(nexts.length){\n              var cand = nexts.shift();\n              var ck = cand[0] + ',' + cand[1] + '|' + cand[2] + ',' + cand[3];\n              if(edgeMap[ck]){ picked = cand; break; }\n            }\n          }\n          if(!picked) break;\n          if(picked[0] === first[0] ? picked[1] === first[1] : false){\n            ring.push([picked[0], picked[1]]);\n            cur = null;\n          } else {\n            cur = picked;\n          }\n          safety++;\n        }\n        if(ring.length >= 4) rings.push(ring);\n      }\n      return rings;\n    }\n    \/\/ Real-time geometry validator + self-intersection fixer. Edge-cancellation\n    \/\/ tracing on a grid normally produces clean rings, but a \"pinch point\" \u2014\n    \/\/ where two regions of the same zone touch at a single grid vertex (4-cell\n    \/\/ checkerboard) \u2014 gives a ring that visits one vertex TWICE, forming a\n    \/\/ bowtie \/ figure-8 self-intersection. The fix is to split the ring at\n    \/\/ the duplicate vertex into two independent rings, then recurse.\n    \/\/\n    \/\/ Also drops degenerate rings (< 4 vertices, zero area, collinear).\n    function splitRingAtPinches(ring){\n      \/\/ ring: array of [x,y], closed (last === first). Returns one OR MORE\n      \/\/ sub-rings, each split at any pinch point.\n      var out = [];\n      var stack = [ring];\n      while(stack.length){\n        var r = stack.pop();\n        if(!r ? true : r.length < 4) continue;\n        \/\/ Skip collapsed rings (all vertices identical).\n        var n = r.length - 1;\n        \/\/ Detect first pinch: a vertex (other than the closing duplicate)\n        \/\/ that appears twice in the ring.\n        var seen = {};\n        var pinchI = -1, pinchJ = -1;\n        for(var i=0; i<n; i++){\n          var key = r[i][0] + ',' + r[i][1];\n          if(seen[key] !== undefined){\n            pinchI = seen[key]; pinchJ = i; break;\n          }\n          seen[key] = i;\n        }\n        if(pinchI < 0){\n          \/\/ No pinch. Make sure ring is closed and emit.\n          if(r[0][0] !== r[r.length-1][0] ? true : r[0][1] !== r[r.length-1][1]){\n            r.push([r[0][0], r[0][1]]);\n          }\n          out.push(r);\n          continue;\n        }\n        \/\/ Split into two rings at the pinch:\n        \/\/   inner = r[pinchI .. pinchJ] + back to r[pinchI]\n        \/\/   outer = r[0 .. pinchI]      + r[pinchJ+1 .. end-1] + r[0]  (skip duplicate close)\n        var inner = r.slice(pinchI, pinchJ + 1);\n        inner.push([r[pinchI][0], r[pinchI][1]]);\n        var outer = r.slice(0, pinchI + 1).concat(r.slice(pinchJ + 1, n));\n        outer.push([outer[0][0], outer[0][1]]);\n        if(inner.length >= 4) stack.push(inner);\n        if(outer.length >= 4) stack.push(outer);\n      }\n      return out;\n    }\n    \/\/ Validate a single ring \u2014 returns true if it has non-zero signed area and\n    \/\/ \u2265 3 unique vertices. Used to drop degenerate \/ collinear rings that would\n    \/\/ produce invalid shapefile geometry.\n    function isValidRingGrid(ring){\n      if(!ring ? true : ring.length < 4) return false;\n      \/\/ Need at least 3 distinct vertices.\n      var distinct = {};\n      var distinctN = 0;\n      for(var i=0; i<ring.length-1; i++){\n        var k = ring[i][0] + ',' + ring[i][1];\n        if(!distinct[k]){ distinct[k] = 1; distinctN++; if(distinctN >= 3) break; }\n      }\n      if(distinctN < 3) return false;\n      \/\/ Non-zero signed area.\n      var s = 0;\n      for(var j=0; j<ring.length-1; j++){\n        s += ring[j][0] * ring[j+1][1] - ring[j+1][0] * ring[j][1];\n      }\n      return Math.abs(s) > 0.5;  \/\/ grid coords are integer-spaced, anything < 0.5 is degenerate\n    }\n    \/\/ Shoelace signed area in grid coords. With the CCW edge winding the\n    \/\/ ring tracer uses (Y grows downward), OUTER rings come out negative and\n    \/\/ HOLE rings positive \u2014 opposite signs make the classification obvious.\n    function ringSignedAreaGrid(ring){\n      var s = 0;\n      for(var i=0; i<ring.length-1; i++){\n        s += ring[i][0] * ring[i+1][1] - ring[i+1][0] * ring[i][1];\n      }\n      return s * 0.5;\n    }\n    function ringCentroidGrid(ring){\n      \/\/ Simple vertex centroid \u2014 robust enough for the convex-ish zone blobs\n      \/\/ we get from raster aggregation. Good interior test point.\n      var cx = 0, cy = 0, n = ring.length - 1;\n      for(var i=0; i<n; i++){ cx += ring[i][0]; cy += ring[i][1]; }\n      return [cx \/ n, cy \/ n];\n    }\n    function pointInRingGrid(px, py, ring){\n      var inside = false;\n      var n = ring.length - 1;  \/\/ closed ring (last == first)\n      for(var i=0, j=n-1; i<n; j=i++){\n        var xi = ring[i][0], yi = ring[i][1];\n        var xj = ring[j][0], yj = ring[j][1];\n        var crosses = (yi > py) !== (yj > py);\n        if(crosses ? (px < (xj - xi) * (py - yi) \/ ((yj - yi) || 1e-12) + xi) : false) inside = !inside;\n      }\n      return inside;\n    }\n    function reverseRing(ring){\n      var out = new Array(ring.length);\n      for(var i=0; i<ring.length; i++) out[i] = ring[ring.length - 1 - i];\n      return out;\n    }\n    var feats = [];\n    \/\/ Sanity-check counters surfaced to the console \u2014 helps diagnose any\n    \/\/ future topology regressions without polluting the user UI.\n    var diag = { orphanHoles:0, totalHoles:0, totalOuters:0, pinchSplits:0, droppedRings:0 };\n    \/\/ Per-zone body extracted so both the synchronous loop AND the async\n    \/\/ chunked driver can call it. Pushes a Feature into `feats` on success.\n    function _processZone(zz){\n      var ringsRaw = ringsForZone(zz);\n      if(!ringsRaw.length) return;\n      \/\/ \u2500\u2500 Validation + self-intersection fix pass \u2500\u2500\n      \/\/ Each traced ring goes through splitRingAtPinches() to bust any\n      \/\/ figure-8 \/ bowtie. Then isValidRingGrid drops collinear \/ zero-area\n      \/\/ residues. Net: every ring that reaches the classifier is a valid,\n      \/\/ simple closed polygon ring in grid coords.\n      var ringsG = [];\n      for(var rri=0; rri<ringsRaw.length; rri++){\n        var rraw = ringsRaw[rri];\n        if(!rraw ? true : rraw.length < 4){ diag.droppedRings++; continue; }\n        var splits = splitRingAtPinches(rraw);\n        if(splits.length > 1) diag.pinchSplits += (splits.length - 1);\n        for(var rsi=0; rsi<splits.length; rsi++){\n          if(isValidRingGrid(splits[rsi])) ringsG.push(splits[rsi]);\n          else diag.droppedRings++;\n        }\n      }\n      if(!ringsG.length) return;\n      \/\/ Classify rings into outers vs holes by signed-area sign.\n      var outers = [], holes = [];\n      for(var ri=0; ri<ringsG.length; ri++){\n        var rg = ringsG[ri];\n        if(rg.length < 4) continue;\n        var sa = ringSignedAreaGrid(rg);\n        if(sa < 0) outers.push({ ring: rg, area: -sa });\n        else if(sa > 0) holes.push({ ring: rg, area: sa, centroid: ringCentroidGrid(rg) });\n      }\n      diag.totalOuters += outers.length;\n      diag.totalHoles += holes.length;\n      if(!outers.length){\n        \/\/ No outer rings? Fall back to treating every hole-classified ring as\n        \/\/ its own outer (reversed so winding is consistent). Prevents gaps\n        \/\/ when sign classification fails for unusual edge cases.\n        var fallbackPolys = [];\n        for(var fh=0; fh<holes.length; fh++) fallbackPolys.push([reverseRing(holes[fh].ring)]);\n        if(!fallbackPolys.length) return;\n        outers = []; for(var fp=0; fp<fallbackPolys.length; fp++) outers.push({ ring: fallbackPolys[fp][0], area: holes[fp].area });\n        holes = [];\n      }\n      \/\/ For each hole, find its smallest enclosing outer \u2014 that's its parent.\n      \/\/ Use the hole CENTROID for the inside test (more robust than the first\n      \/\/ vertex, which can lie exactly on the outer's boundary).\n      var polyRings = new Array(outers.length);\n      for(var o=0; o<outers.length; o++) polyRings[o] = [outers[o].ring];\n      for(var h=0; h<holes.length; h++){\n        var hole = holes[h];\n        var bestO = -1, bestArea = Infinity;\n        for(var o2=0; o2<outers.length; o2++){\n          var outer = outers[o2];\n          if(outer.area >= bestArea) continue;\n          if(pointInRingGrid(hole.centroid[0], hole.centroid[1], outer.ring)){\n            bestO = o2; bestArea = outer.area;\n          }\n        }\n        if(bestO >= 0){\n          polyRings[bestO].push(hole.ring);\n        } else {\n          \/\/ Orphan hole \u2014 couldn't be matched to any outer in this zone.\n          \/\/ Emit it as its own outer polygon (reversed to be CCW) so the\n          \/\/ area is still represented; better than dropping \u2192 no gap.\n          polyRings.push([reverseRing(hole.ring)]);\n          diag.orphanHoles++;\n        }\n      }\n      \/\/ Convert each Polygon's rings (outer + holes) to lng\/lat.\n      var polys = [];\n      for(var pp=0; pp<polyRings.length; pp++){\n        var rings = polyRings[pp];\n        var llPoly = [];\n        for(var rr=0; rr<rings.length; rr++){\n          var rgr = rings[rr];\n          if(rgr.length < 4) continue;\n          var llR = new Array(rgr.length);\n          for(var p=0; p<rgr.length; p++){\n            var mxC = bbox[0] + rgr[p][0] * dx;\n            var myC = bbox[1] + rgr[p][1] * dy;\n            llR[p] = mxmyToLngLat(mxC, myC);\n          }\n          llPoly.push(llR);\n        }\n        if(llPoly.length) polys.push(llPoly);\n      }\n      if(!polys.length) return;\n      \/\/ DBF column order = property key order. Rate columns FIRST after the\n      \/\/ auto-FID so the prescription value is immediately visible in QGIS \/\n      \/\/ any FMIS that opens the .shp.\n      var props = {};\n      if(zoneRates ? isFinite(zoneRates[zz]) : false){\n        var rateVal = zoneRates[zz];\n        var rateUnitS = zoneRateUnit || 'kg\/ha';\n        var aHa = zoneStats.areas ? zoneStats.areas[zz] : 0;\n        var perAc = \/\\\/ac\/i.test(rateUnitS);\n        var aForUnit = perAc ? aHa * 2.47105 : aHa;\n        props.rate = rateVal;\n        props.rate_unit = rateUnitS;\n        props.total_pd = Math.round(rateVal * aForUnit * 100) \/ 100;\n      }\n      props.zone = zz + 1;\n      props.zone_min = zoneStats.mins[zz];\n      props.zone_max = zoneStats.maxs[zz];\n      props.zone_mean = zoneStats.means[zz];\n      props.n_points = zoneStats.counts[zz];\n      props.attribute = currentCol;\n      props.source = 'GeoPard';\n      feats.push({\n        type:'Feature',\n        geometry:{ type:'MultiPolygon', coordinates: polys },\n        properties: props\n      });\n    }\n    \/\/ Fast row-run rectangle assembly. For each row of the IDW grid, emit\n    \/\/ each maximal run of same-zone cells as one axis-aligned rectangle.\n    \/\/ O(cells) total \u2014 no edge tracing, no ring walking, no hole topology,\n    \/\/ no pinch detection, no O(holes \u00d7 outers) classification pass. The\n    \/\/ visual outline is \"blocky\" instead of contour-following, but coverage\n    \/\/ is identical to the IDW classification and the data this exports goes\n    \/\/ into FMIS \/ QGIS for VRA prescription \u2014 outline smoothness is purely\n    \/\/ aesthetic, not load-bearing.\n    \/\/\n    \/\/ Always on. The edge-tracing path (kept as _processZone for tests +\n    \/\/ historical reference) over-engineers the export use case: smooth\n    \/\/ contour-following outlines look nicer in some viewers but never\n    \/\/ change zone coverage, and the O(holes \u00d7 outers \u00d7 ring length) hole-\n    \/\/ classification can spend tens of seconds per zone on any dataset\n    \/\/ with a noisy IDW raster (reported on soil-scanner 17k pts, yield\n    \/\/ 1.8k pts \u2014 both produce noisy rasters). Row-run rectangles cover\n    \/\/ the exact same area, O(cells), and the FMIS \/ QGIS user can't tell\n    \/\/ the difference once the shapefile is loaded.\n    var _useFastRowRun = true;\n    function _processZoneFast(zz){\n      var polys = [];\n      for(var gy=0; gy<gH; gy++){\n        var rowOff = gy*gW;\n        var gx = 0;\n        while(gx < gW){\n          if(zg[rowOff+gx] !== zz){ gx++; continue; }\n          var startX = gx;\n          while(gx < gW ? zg[rowOff+gx] === zz : false) gx++;\n          var ax = bbox[0] + startX*dx, bxx = bbox[0] + gx*dx;\n          var ay = bbox[1] + gy*dy,     byy = bbox[1] + (gy+1)*dy;\n          var ll = [\n            mxmyToLngLat(ax, ay),\n            mxmyToLngLat(bxx, ay),\n            mxmyToLngLat(bxx, byy),\n            mxmyToLngLat(ax, byy)\n          ];\n          ll.push([ll[0][0], ll[0][1]]);\n          polys.push([ll]);\n        }\n      }\n      if(!polys.length) return;\n      var props = {};\n      if(zoneRates ? isFinite(zoneRates[zz]) : false){\n        var rateVal = zoneRates[zz];\n        var rateUnitS = zoneRateUnit || 'kg\/ha';\n        var aHa = zoneStats.areas ? zoneStats.areas[zz] : 0;\n        var perAc = \/\\\/ac\/i.test(rateUnitS);\n        var aForUnit = perAc ? aHa * 2.47105 : aHa;\n        props.rate = rateVal;\n        props.rate_unit = rateUnitS;\n        props.total_pd = Math.round(rateVal * aForUnit * 100) \/ 100;\n      }\n      props.zone = zz + 1;\n      props.zone_min = zoneStats.mins[zz];\n      props.zone_max = zoneStats.maxs[zz];\n      props.zone_mean = zoneStats.means[zz];\n      props.n_points = zoneStats.counts[zz];\n      props.attribute = currentCol;\n      props.source = 'GeoPard';\n      feats.push({\n        type:'Feature',\n        geometry:{ type:'MultiPolygon', coordinates: polys },\n        properties: props\n      });\n    }\n    function _runZone(zz){\n      return _useFastRowRun ? _processZoneFast(zz) : _processZone(zz);\n    }\n    function _finish(){\n      try {\n        var msg = '[GPY zones] ' + diag.totalOuters + ' outers + ' + diag.totalHoles + ' holes across ' + zonesK + ' zones';\n        var notes = [];\n        if(diag.pinchSplits > 0) notes.push(diag.pinchSplits + ' pinch self-intersection(s) split');\n        if(diag.droppedRings > 0) notes.push(diag.droppedRings + ' degenerate ring(s) dropped');\n        if(diag.orphanHoles > 0) notes.push(diag.orphanHoles + ' orphan hole(s) emitted as fallback');\n        if(notes.length){\n          console.warn(msg + ' \u00b7 ' + notes.join(' \u00b7 ') + '. Geometry sanitised.');\n        } else {\n          console.info(msg + ' classified cleanly.');\n        }\n      } catch(_){}\n    }\n    \/\/ Async driver: process one zone per setTimeout tick so the page stays\n    \/\/ responsive. With 17k-point soil-scanner data the per-zone polygon\n    \/\/ assembly can take ~0.5-1 s; running 4 zones synchronously freezes the\n    \/\/ tab for 2-4 s. Yielding between zones surfaces phase-by-phase progress\n    \/\/ via opts.progress() and lets the browser repaint the toast \/ accept\n    \/\/ input. Sync path is preserved for tests + any future caller that\n    \/\/ doesn't need yielding.\n    if(opts ? opts.async : false){\n      var zAsync = 0;\n      function _next(){\n        if(zAsync >= zonesK){ _finish(); opts.done(feats); return; }\n        if(opts.progress) opts.progress(zAsync, zonesK, _useFastRowRun);\n        setTimeout(function(){\n          try { _runZone(zAsync); }\n          catch(err){ if(opts.fail) opts.fail(err); else console.error(err); return; }\n          zAsync++;\n          _next();\n        }, 0);\n      }\n      _next();\n      return null;\n    }\n    for(var zz=0; zz<zonesK; zz++) _runZone(zz);\n    _finish();\n    return feats;\n  }\n  \/\/ For POLYGON-mode datasets, group the existing polygons by zone \u2014 no IDW\n  \/\/ raster needed. Each input polygon is copied into the per-zone MultiPolygon\n  \/\/ as-is, preserving its real geometry. Adjacent zones don't dissolve here\n  \/\/ (a QGIS \"dissolve by zone\" pass cleans that up); but the result is\n  \/\/ already a valid categorical zones layer.\n  function buildZonePolygonsFromInputPolygons(){\n    if(!zonesK ? true : !zoneClass) return null;\n    var perZone = new Array(zonesK);\n    for(var z=0; z<zonesK; z++) perZone[z] = [];\n    for(var i=0; i<features.length; i++){\n      var zc = zoneClass[i];\n      if(zc === 255) continue;\n      if(zc >= zonesK) continue;\n      var f = features[i];\n      if(!f ? true : !f.geometry) continue;\n      var g = f.geometry;\n      if(g.type === 'Polygon'){\n        perZone[zc].push(g.coordinates);\n      } else if(g.type === 'MultiPolygon'){\n        for(var pi=0; pi<g.coordinates.length; pi++) perZone[zc].push(g.coordinates[pi]);\n      }\n    }\n    var feats = [];\n    for(var z2=0; z2<zonesK; z2++){\n      if(!perZone[z2].length) continue;\n      \/\/ Same column-order convention as the IDW-raster path: rate first.\n      var props2 = {};\n      if(zoneRates ? isFinite(zoneRates[z2]) : false){\n        var rateVal2 = zoneRates[z2];\n        var rateUnitS2 = zoneRateUnit || 'kg\/ha';\n        var aHa2 = zoneStats.areas ? zoneStats.areas[z2] : 0;\n        var perAc2 = \/\\\/ac\/i.test(rateUnitS2);\n        var aForUnit2 = perAc2 ? aHa2 * 2.47105 : aHa2;\n        props2.rate = rateVal2;\n        props2.rate_unit = rateUnitS2;\n        props2.total_pd = Math.round(rateVal2 * aForUnit2 * 100) \/ 100;\n      }\n      props2.zone = z2 + 1;\n      props2.zone_min = zoneStats.mins[z2];\n      props2.zone_max = zoneStats.maxs[z2];\n      props2.zone_mean = zoneStats.means[z2];\n      props2.n_points = zoneStats.counts[z2];\n      props2.attribute = currentCol;\n      props2.source = 'GeoPard';\n      feats.push({\n        type:'Feature',\n        geometry:{ type:'MultiPolygon', coordinates: perZone[z2] },\n        properties: props2\n      });\n    }\n    return feats;\n  }\n  \/\/ Get a representative lng\/lat point per feature \u2014 used to group features\n  \/\/ by zone and build per-zone convex hull polygons.\n  function featLngLat(idx){\n    var f = features[idx];\n    if(!f ? true : !f.geometry) return null;\n    var g = f.geometry;\n    if(g.type === 'Point') return g.coordinates;\n    \/\/ Polygon \/ MultiPolygon: average outer ring vertices.\n    var ring = null;\n    if(g.type === 'MultiPolygon' ? g.coordinates[0] : false) ring = g.coordinates[0][0];\n    else if(g.type === 'Polygon') ring = g.coordinates[0];\n    else if(g.type === 'LineString') ring = g.coordinates;\n    else if(g.type === 'MultiLineString' ? g.coordinates[0] : false) ring = g.coordinates[0];\n    if(!ring ? true : ring.length < 1) return null;\n    var sx=0, sy=0, n=0;\n    var until = (ring.length > 1 ? (ring[0][0] === ring[ring.length-1][0] ? (ring[0][1] === ring[ring.length-1][1] ? ring.length - 1 : ring.length) : ring.length) : ring.length);\n    for(var i=0; i<until; i++){ sx += ring[i][0]; sy += ring[i][1]; n++; }\n    if(!n) return null;\n    return [sx \/ n, sy \/ n];\n  }\n  \/\/ Export PER-ZONE POLYGONS. Algorithm picks the right strategy per mode:\n  \/\/   - Point datasets (soil sample, yield) \u2192 rasterize the IDW interpolated\n  \/\/     surface into a 96\u00d796 grid, classify each cell into a zone using the\n  \/\/     same break points as the dots, mask to the field hull, then row-run\n  \/\/     merge consecutive same-zone cells into rectangles. Emits one\n  \/\/     MultiPolygon per zone. Result reflects the spatial pattern visible\n  \/\/     on screen (zones follow the IDW surface, not abstract hulls), and\n  \/\/     polygons of different zones don't overlap.\n  \/\/   - Polygon datasets (zones shapefile, as-applied) \u2192 group the existing\n  \/\/     polygons by zone class and emit per-zone MultiPolygons containing\n  \/\/     the original geometries. A QGIS \"dissolve by zone\" pass merges\n  \/\/     adjacent polygons within each zone for a clean field map.\n  function exportZonesAsShapefile(){\n    if(!zonesK){ showToast('Pick 3, 4, or 5 zones first.'); return; }\n    if(!zoneClass ? true : !zoneStats){ showToast('Zones not ready yet \u2014 try again in a moment.'); return; }\n    if(!features ? true : !features.length){ showToast('Nothing to export.'); return; }\n    var btn = $('#gpy-zones-export');\n    if(btn) btn.disabled = true;\n    var t0 = Date.now();\n    \/\/ Chain each heavy phase behind a setTimeout(0) yield so the toast\n    \/\/ re-paints between phases. On a 17k-point soil-scanner the previous\n    \/\/ synchronous pipeline froze the browser for ~2 s with no feedback;\n    \/\/ users reported \"hangs\". Now they see a phase-by-phase progress\n    \/\/ toast and the UI stays interactive between steps.\n    function yieldNext(fn){\n      if(window.requestAnimationFrame){ window.requestAnimationFrame(function(){ setTimeout(fn, 0); }); }\n      else { setTimeout(fn, 0); }\n    }\n    function fail(err, label){\n      showToast((label || 'Export failed') + ': ' + (err ? (err.message ? err.message : 'see console') : 'see console'));\n      try { console.error('[GPY zones export]', err); } catch(_){}\n      if(btn) btn.disabled = false;\n    }\n    showToast('Loading shapefile writer\u2026', 'info');\n    Promise.all([loadJSZip(), loadShpWrite()]).then(function(){\n      \/\/ Phase 1: IDW grid build (cached if warm \u2014 fast path).\n      showToast('Computing IDW raster\u2026', 'info');\n      yieldNext(function(){\n        try {\n          if(mode !== 'line' ? !interpCache.values : false) buildPointInterp();\n          if(interpCache.col !== currentCol) buildPointInterp();\n        } catch(err){ return fail(err, 'IDW build failed'); }\n        \/\/ Phase 2: zone polygon assembly off the IDW grid. The IDW path is\n        \/\/ driven asynchronously \u2014 one zone per setTimeout tick \u2014 so the\n        \/\/ browser stays responsive on dense (17k-point) soil-scanner data\n        \/\/ where each zone takes ~0.5-1 s to trace + classify + reproject.\n        showToast('Building zone polygons (1 of ' + zonesK + ')\u2026', 'info');\n        function _afterPolygons(feats){\n          if(!feats ? true : !feats.length){\n            showToast('No zones to export \u2014 try a different attribute or zone count.');\n            if(btn) btn.disabled = false;\n            return;\n          }\n          _phaseEncode(feats);\n        }\n        function _phaseEncode(feats){\n          var fc = { type:'FeatureCollection', features: feats };\n          var datasetSlug = '';\n          try {\n            var active = datasets ? datasets.find(function(d){ return d.id === activeDatasetId; }) : null;\n            if(active ? active.name : false){\n              datasetSlug = active.name.replace(\/[^a-z0-9_\\-]+\/gi,'_').replace(\/^_+|_+$\/g,'').slice(0,45);\n            }\n          } catch(_){}\n          var safeName = 'geopard_zones_' + (datasetSlug ? datasetSlug + '_' : '') + 'k' + zonesK;\n          var opts = {\n            folder: safeName,\n            types: { point:'geopard_zones', polygon:'geopard_zones', polyline:'geopard_zones' },\n            type: 'base64',\n            compression: 'STORE'\n          };\n          \/\/ Phase 3: shp-write encoding (the heaviest synchronous step on\n          \/\/ large polygons \u2014 1-2 s on the dense soil-scan grid).\n          showToast('Encoding shapefile\u2026', 'info');\n          yieldNext(function(){\n            var raw;\n            try { raw = window.shpwrite.zip(fc, opts); }\n            catch(err){ return fail(err); }\n            \/\/ Phase 4: blob conversion + browser download.\n            zipResultToBlob(raw).then(function(blob){\n              var url = URL.createObjectURL(blob);\n              var a = document.createElement('a');\n              a.href = url; a.download = safeName + '.zip';\n              a.style.display = 'none';\n              document.body.appendChild(a);\n              a.click();\n              document.body.removeChild(a);\n              setTimeout(function(){ URL.revokeObjectURL(url); }, 1500);\n              var ms = Date.now() - t0;\n              showToast('Downloaded ' + safeName + '.zip \u00b7 ' + (ms < 1000 ? (ms+' ms') : ((ms\/1000).toFixed(1)+' s')), 'ok');\n              if(btn) btn.disabled = false;\n            }).catch(function(err){ fail(err); });\n          });\n        }\n        \/\/ Kick off the polygon build. IDW path runs asynchronously (one\n        \/\/ zone per setTimeout tick); the polygon-mode fallback is fast\n        \/\/ enough to keep synchronous.\n        if(mode !== 'line' ? interpCache.values : false){\n          buildZonePolygonsFromIDW({\n            async: true,\n            progress: function(zi, total){\n              showToast('Building zone polygons (' + (zi+1) + ' of ' + total + ')\u2026', 'info');\n            },\n            fail: function(err){ fail(err, 'Polygon build failed'); },\n            done: _afterPolygons\n          });\n        } else if(mode === 'polygon'){\n          try { _afterPolygons(buildZonePolygonsFromInputPolygons()); }\n          catch(err){ fail(err, 'Polygon build failed'); }\n        } else {\n          _afterPolygons(null);\n        }\n      });\n    }).catch(function(err){\n      showToast('Could not load shapefile writer: ' + (err.message ? err.message : 'network error'));\n      if(btn) btn.disabled = false;\n    });\n  }\n  var zonesExportBtn = $('#gpy-zones-export');\n  if(zonesExportBtn) zonesExportBtn.onclick = exportZonesAsShapefile;\n  \/\/ Preload the export libs after the tool is interactive so the first\n  \/\/ Export click doesn't pay the ~150 KB jsDelivr fetch latency.\n  \/\/ Wire the floating CTA dismiss button. Hidden state persists for the\n  \/\/ Floating CTA is intentionally non-dismissable \u2014 it's the primary\n  \/\/ \"Smarter zones in GeoPard\" hook beside the canvas. Clear any legacy\n  \/\/ sessionStorage flag from previous builds so returning visitors still see it.\n  try { sessionStorage.removeItem('gpy-cta-hidden'); } catch(_){}\n  function preloadExportLibs(){\n    try { loadJSZip(); loadShpWrite(); } catch(_){}\n  }\n  if(window.requestIdleCallback){\n    window.requestIdleCallback(preloadExportLibs, { timeout: 4000 });\n  } else {\n    setTimeout(preloadExportLibs, 2500);\n  }\n  \/\/ \u2500\u2500 Ruler tool \u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\n  \/\/ Append a waypoint at canvas pixel coords (sx, sy). Called from mouse-click and touch-tap.\n  function rulerAddPoint(sx, sy){\n    if(!ruler.active) return;\n    var mxR = (sx - view.tx) \/ view.scale;\n    var myR = (sy - view.ty) \/ view.scale;\n    ruler.points.push({ mx: mxR, my: myR });\n    draw();\n  }\n  function rulerToggle(){\n    if(ruler.active){\n      \/\/ Toggle off: clear and exit\n      ruler.active = false;\n      ruler.points = [];\n      ruler.hover = null;\n      var btnA = $('#gpy-ruler');\n      if(btnA) btnA.classList.remove('is-active');\n      draw();\n      return;\n    }\n    ruler.active = true;\n    ruler.points = [];\n    ruler.hover = null;\n    var btnB = $('#gpy-ruler');\n    if(btnB) btnB.classList.add('is-active');\n    if(tip) tip.style.opacity = 0;\n    draw();\n  }\n  $('#gpy-ruler').onclick = rulerToggle;\n  \/\/ Double-click finalizes the line: stops the preview segment but keeps the measurement visible.\n  \/\/ A subsequent click starts a new measurement (clears + adds first point).\n  canvas.addEventListener('dblclick', function(e){\n    if(!ruler.active) return;\n    e.preventDefault();\n    if(ruler.points.length > 0){\n      \/\/ Drop the last point if it was added by the first click of the dblclick burst\n      \/\/ (otherwise the user gets a tiny zero-length segment at the dblclick location).\n      if(ruler.points.length >= 2){\n        var pl1 = ruler.points[ruler.points.length - 1];\n        var pl2 = ruler.points[ruler.points.length - 2];\n        var ddx = pl1.mx - pl2.mx, ddy = pl1.my - pl2.my;\n        if(Math.sqrt(ddx*ddx + ddy*ddy) * view.scale < 5) ruler.points.pop();\n      }\n      ruler.hover = null;\n    }\n    draw();\n  });\n  window.addEventListener('keydown', function(e){\n    if((e.key==='r'||e.key==='R') ? (values.length ? !ruler.active : false) : false){ fitView(); draw(); }\n    if(e.key === 'Escape' ? ruler.active : false){ rulerToggle(); }\n  });\n  var sigBtns = root.querySelectorAll('#gpy-sig button');\n  for(var i=0;i<sigBtns.length;i++){\n    sigBtns[i].onclick = function(){\n      for(var j=0;j<sigBtns.length;j++) sigBtns[j].classList.remove('on');\n      this.classList.add('on');\n      sigmaK = +this.dataset.k;\n      \/\/ \u03c3 click \u2192 back to auto mode for the HIGH cutoff. Also clear stop 4's override so\n      \/\/ the legend's top thumb follows the \u03c3-derived value (otherwise a previously-dragged\n      \/\/ thumb would stick at the old position).\n      hiCutoff = null;\n      stopValueOverrides[4] = null;\n      recompute(); draw();\n    };\n  }\n  $('#gpy-lo-r').oninput = function(e){ loCutoff = +e.target.value; $('#gpy-lo').textContent = fmt(loCutoff); recompute(); draw(); };\n  $('#gpy-hi-r').oninput = function(e){ hiCutoff = +e.target.value; $('#gpy-hi').textContent = fmt(hiCutoff); recompute(); draw(); };\n  \/\/ Editable legend min\/max \u2014 visible inputs + steppers + draggable thumbs on the gradient bar.\n  \/\/ Visible inputs make it discoverable that the values are editable (previous click-to-edit spans\n  \/\/ were not obvious). Steppers nudge by a magnitude-aware step. Thumbs let the user drag visually.\n  \/\/ Set ONE stop's override while preserving the other stops' current visible positions.\n  \/\/ Without this, changing e.g. Min would also shift Low-mid\/Mid\/High-mid because they auto-derive\n  \/\/ from min and max. Locking the other stops' current effective values as explicit overrides keeps\n  \/\/ the rest of the gradient stable \u2014 the user changes only the class they touched.\n  \/\/ Stop 0 + 4 are merged with the Lo\/Hi outlier cutoffs: dragging them also updates\n  \/\/ loCutoff \/ hiCutoff so the outlier classification stays consistent with the colour range.\n  function setStopOverride(idx, val){\n    if(val === null){\n      stopValueOverrides[idx] = null;\n      if(idx === 4) hiCutoff = null;  \/\/ back to auto (\u03c3-based) high cutoff\n      return;\n    }\n    for(var i=0; i<stopValueOverrides.length; i++){\n      if(i !== idx ? stopValueOverrides[i] === null : false){\n        stopValueOverrides[i] = effStops[i];\n      }\n    }\n    stopValueOverrides[idx] = val;\n    if(idx === 0) loCutoff = val;\n    else if(idx === 4) hiCutoff = val;\n  }\n  function wireLegendInput(inputId, wrapId, stopIdx){\n    var input = $('#' + inputId);\n    var wrap = $('#' + wrapId);\n    if(!input ? true : !wrap) return;\n    var commit = function(){\n      if(!values.length) return;\n      var v = parseFloat(input.value);\n      setStopOverride(stopIdx, isFinite(v) ? v : null);\n      recompute(); draw();\n    };\n    input.addEventListener('change', commit);\n    input.addEventListener('keydown', function(ev){\n      if(ev.key === 'Enter'){ ev.preventDefault(); commit(); input.blur(); }\n      else if(ev.key === 'Escape'){\n        setStopOverride(stopIdx, null);\n        recompute(); draw();\n        input.blur();\n      }\n    });\n    input.addEventListener('focus', function(){ wrap.classList.add('is-focus'); });\n    input.addEventListener('blur', function(){ wrap.classList.remove('is-focus'); });\n  }\n  \/\/ Stepper buttons (\u25b2\/\u25bc) \u2014 nudge a stop by ~1% of data range, snapped to a \"nice\" step.\n  \/\/ Uses setStopOverride so other stops stay put.\n  function legendStep(stopIdx, dir){\n    if(!values.length) return;\n    var range = (sorted.length ? sorted[sorted.length-1] : 1) - (sorted.length ? sorted[0] : 0);\n    if(!isFinite(range) ? true : range <= 0) range = 1;\n    var raw = range * 0.01;\n    var step = raw < 0.05 ? 0.01 : (raw < 0.5 ? 0.1 : (raw < 5 ? 1 : (raw < 50 ? 10 : 100)));\n    var cur = stopValueOverrides[stopIdx] !== null ? stopValueOverrides[stopIdx] : effStops[stopIdx];\n    var next = cur + dir * step;\n    next = Math.round(next \/ step) * step;\n    setStopOverride(stopIdx, next);\n    recompute(); draw();\n  }\n  \/\/ Drag a thumb on the gradient bar to set a stop's data value visually. Uses setStopOverride so\n  \/\/ dragging one thumb doesn't move the others (they get locked at their current values).\n  function wireLegendThumb(thumbId, stopIdx){\n    var thumb = $('#' + thumbId);\n    var bar = $('#gpy-legend-bar');\n    if(!thumb ? true : !bar) return;\n    var dragging = false;\n    function setFromX(clientX){\n      if(!values.length) return;\n      var rect = bar.getBoundingClientRect();\n      var t = (clientX - rect.left) \/ Math.max(1, rect.width);\n      if(t < 0) t = 0; if(t > 1) t = 1;\n      var dataMin = sorted[0], dataMax = sorted[sorted.length-1];\n      var v = dataMin + (dataMax - dataMin) * t;\n      v = Math.round(v * 100) \/ 100;\n      setStopOverride(stopIdx, v);\n      thumb.style.left = (t*100) + '%';\n      recompute(); draw();\n    }\n    function getX(e){ return e.touches ? (e.touches.length ? e.touches[0].clientX : 0) : e.clientX; }\n    thumb.addEventListener('mousedown', function(e){ dragging = true; thumb.classList.add('is-drag'); e.preventDefault(); });\n    thumb.addEventListener('touchstart', function(e){ dragging = true; thumb.classList.add('is-drag'); e.preventDefault(); }, { passive:false });\n    window.addEventListener('mousemove', function(e){ if(dragging) setFromX(e.clientX); });\n    window.addEventListener('touchmove', function(e){ if(dragging) { setFromX(getX(e)); e.preventDefault(); } }, { passive:false });\n    var end = function(){ if(!dragging) return; dragging = false; thumb.classList.remove('is-drag'); };\n    window.addEventListener('mouseup', end);\n    window.addEventListener('touchend', end);\n  }\n  \/\/ Build the 5 per-class rows inside the legend, wire up inputs \/ steppers \/ thumbs for each.\n  (function buildLegendStops(){\n    var container = $('#gpy-legend-stops');\n    if(!container) return;\n    var html = '';\n    for(var si=0; si<5; si++){\n      var c = STOP_COLORS[si];\n      var swColor = 'rgb('+c[0]+','+c[1]+','+c[2]+')';\n      html += '<div class=\"gpy-legend-tickrow\" data-stop=\"'+si+'\">';\n      html += '<span class=\"gpy-l-sw\" style=\"background:'+swColor+'\"><\/span>';\n      html += '<span class=\"gpy-l-lbl\">'+STOP_LABELS[si]+'<\/span>';\n      html += '<div class=\"gpy-l-num\" id=\"gpy-l-stop-wrap-'+si+'\">';\n      html += '<input type=\"number\" step=\"any\" id=\"gpy-l-stop-'+si+'\" placeholder=\"auto\" aria-label=\"'+STOP_LABELS[si]+' threshold\">';\n      html += '<span class=\"gpy-l-unit\" id=\"gpy-l-stop-unit-'+si+'\"><\/span>';\n      html += '<span class=\"gpy-l-step\"><button type=\"button\" id=\"gpy-l-stop-up-'+si+'\" aria-label=\"Increase\">\u25b2<\/button><button type=\"button\" id=\"gpy-l-stop-down-'+si+'\" aria-label=\"Decrease\">\u25bc<\/button><\/span>';\n      html += '<\/div><\/div>';\n    }\n    container.innerHTML = html;\n    for(var si2=0; si2<5; si2++){\n      (function(s){\n        wireLegendInput('gpy-l-stop-'+s, 'gpy-l-stop-wrap-'+s, s);\n        wireLegendThumb('gpy-l-thumb-'+s, s);\n        var up = $('#gpy-l-stop-up-'+s);\n        var dn = $('#gpy-l-stop-down-'+s);\n        if(up) up.addEventListener('click', function(){ legendStep(s, 1); });\n        if(dn) dn.addEventListener('click', function(){ legendStep(s, -1); });\n      })(si2);\n    }\n  })();\n  var legResetBtn = $('#gpy-l-reset');\n  if(legResetBtn){\n    legResetBtn.addEventListener('click', function(){\n      for(var ro=0; ro<stopValueOverrides.length; ro++) stopValueOverrides[ro] = null;\n      \/\/ Also reset the merged outlier cutoffs back to auto. hiCutoff = null lets \u03c3 drive it;\n      \/\/ loCutoff resets to its slider default (which gets re-adapted in setColumn anyway).\n      hiCutoff = null;\n      legResetBtn.classList.remove('show');\n      recompute(); draw();\n    });\n  }\n  \/\/ Equipment width input \u2014 user can override the auto-detected \/ table value. Triggers a\n  \/\/ re-run of setupPlayback (current dataset) so the path \/ sprite \/ swath \/ Bezier all\n  \/\/ rebuild with the new width.\n  function applyUserWidth(){\n    var inp = $('#gpy-wm-in');\n    if(!inp) return;\n    var raw = parseFloat(inp.value);\n    if(isFinite(raw) ? raw >= 0.5 : false){\n      playback.userWidth = raw;\n    } else {\n      playback.userWidth = null;\n    }\n    var activeDs = null;\n    for(var d=0; d<datasets.length; d++){\n      if(datasets[d].id === activeDatasetId){ activeDs = datasets[d]; break; }\n    }\n    if(activeDs) setupPlayback(activeDs);\n    draw();\n  }\n  var widthInEl = $('#gpy-wm-in');\n  if(widthInEl){\n    widthInEl.addEventListener('change', applyUserWidth);\n    widthInEl.addEventListener('keydown', function(ev){\n      if(ev.key === 'Enter'){ ev.preventDefault(); applyUserWidth(); widthInEl.blur(); }\n      else if(ev.key === 'Escape'){ widthInEl.value = ''; applyUserWidth(); widthInEl.blur(); }\n    });\n  }\n  var widthResetEl = $('#gpy-wm-reset');\n  if(widthResetEl){\n    widthResetEl.addEventListener('click', function(){\n      var inp = $('#gpy-wm-in');\n      if(inp) inp.value = '';\n      playback.userWidth = null;\n      applyUserWidth();\n    });\n  }\n  \/\/ AB-line heading override \u2014 same pattern as the equipment-width input. Converts\n  \/\/ standard ag heading (deg from north, clockwise) to the internal mercator angle\n  \/\/ used by detectFieldAxis. Empty input = revert to auto-detection (sibling AB line\n  \/\/ or longest hull edge).\n  function applyUserHeading(){\n    var inp = $('#gpy-hd-in');\n    if(!inp){ return; }\n    var raw = parseFloat(inp.value);\n    if(isFinite(raw)){\n      var norm = raw % 360;\n      if(norm < 0) norm += 360;\n      playback.userHeadingRad = norm * Math.PI \/ 180;\n    } else {\n      playback.userHeadingRad = null;\n    }\n    var activeDsH = null;\n    for(var dH=0; dH<datasets.length; dH++){\n      if(datasets[dH].id === activeDatasetId){ activeDsH = datasets[dH]; break; }\n    }\n    if(activeDsH) setupPlayback(activeDsH);\n    syncHeadingHint();\n    draw();\n  }\n  \/\/ After setupPlayback runs, update the hint line under the heading input so the user\n  \/\/ sees both the auto-detected heading (placeholder) and the active source.\n  function syncHeadingHint(){\n    var hintEl = $('#gpy-hd-hint');\n    var inpEl = $('#gpy-hd-in');\n    if(!hintEl ? true : !inpEl) return;\n    var axes = playback.fieldAxes;\n    if(!axes ? true : axes.length === 0){\n      hintEl.textContent = '\u2014';\n      inpEl.placeholder = 'auto';\n      return;\n    }\n    \/\/ Use cluster-0 heading as the displayed value; multi-field datasets share heading\n    \/\/ in practice (parallel fields) \u2014 the manual override applies to all anyway.\n    var ax = axes[0];\n    if(!ax){ hintEl.textContent = '\u2014'; inpEl.placeholder = 'auto'; return; }\n    \/\/ polyData stores Y flipped (canvas-Y = south-positive). Real heading-from-north\n    \/\/ = atan2(east_real, north_real) = atan2(ux_stored, -uy_stored). Axis is\n    \/\/ direction-agnostic so normalize to [0, 180).\n    var hN = Math.atan2(ax.ux, -ax.uy) * 180 \/ Math.PI;\n    if(hN < 0) hN += 360;\n    if(hN >= 180) hN -= 180;\n    inpEl.placeholder = hN.toFixed(0);\n    hintEl.textContent = hN.toFixed(0) + '\u00b0 \u00b7 ' + ax.source;\n  }\n  var hdInEl = $('#gpy-hd-in');\n  if(hdInEl){\n    hdInEl.addEventListener('change', applyUserHeading);\n    hdInEl.addEventListener('keydown', function(ev){\n      if(ev.key === 'Enter'){ ev.preventDefault(); applyUserHeading(); hdInEl.blur(); }\n      else if(ev.key === 'Escape'){ hdInEl.value = ''; applyUserHeading(); hdInEl.blur(); }\n    });\n  }\n  var hdResetEl = $('#gpy-hd-reset');\n  if(hdResetEl){\n    hdResetEl.addEventListener('click', function(){\n      var inp2 = $('#gpy-hd-in');\n      if(inp2) inp2.value = '';\n      playback.userHeadingRad = null;\n      applyUserHeading();\n    });\n  }\n  \/\/ Both attribute-picker handlers re-fit after zones recompute so any\n  \/\/ sidebar-panel growth (zones list appearing) doesn't leave the canvas\n  \/\/ showing only a corner of the dataset.\n  function attrChangeRefit(){\n    if(zonesK > 0){ computeZones(); updateZonesPanel(); }\n    if(window.requestAnimationFrame){\n      window.requestAnimationFrame(function(){\n        if(typeof resize === 'function') resize();\n        fitView();\n        draw();\n      });\n    } else { fitView(); draw(); }\n  }\n  $('#gpy-col').onchange = function(e){\n    setColumn(e.target.value);\n    var ov = $('#gpy-col-overlay'); if(ov) ov.value = e.target.value;\n    attrChangeRefit();\n  };\n  var attrOv = $('#gpy-col-overlay');\n  if(attrOv){\n    attrOv.onchange = function(e){\n      setColumn(e.target.value);\n      $('#gpy-col').value = e.target.value;\n      attrChangeRefit();\n    };\n  }\n  \/\/ Wire the Auto Zones segmented control.\n  var zoneBtns = root.querySelectorAll('#gpy-zones-seg button');\n  for(var zi2=0; zi2<zoneBtns.length; zi2++){\n    zoneBtns[zi2].onclick = function(){ setZonesK(+this.dataset.z); };\n  }\n  $('#gpy-upload').onclick = function(){ $('#gpy-upload-modal').classList.add('show'); };\n  $('#gpy-modal-x').onclick = function(){ $('#gpy-upload-modal').classList.remove('show'); };\n  $('#gpy-upload-modal').onclick = function(e){\n    if(e.target === this) this.classList.remove('show');\n  };\n  \/\/ SHP export removed from UI per user request. Binary writer + DBF helper\n  \/\/ functions (buildShapefile, buildAttrSpecsFromDataset, sanitizeDbfFieldName,\n  \/\/ formatDbfField, downloadBlob) remain in this file for future use \u2014 they\n  \/\/ have no callers, but are small and harmless dormant.\n  \/\/ Modern dropzone \u2014 click anywhere inside to open the file picker, drag-and-drop to load.\n  \/\/ Supports multi-file selection (routes through processFolder if > 1) plus folder drops via\n  \/\/ webkitGetAsEntry. Single point of UX for uploads.\n  var dropzone = $('#gpy-dropzone');\n  if(dropzone){\n    \/\/ Ignore clicks \/ keys that originate inside the \"Which file types?\" info\n    \/\/ hint \u2014 tapping it (mobile) or focusing it (keyboard) must show its tooltip,\n    \/\/ not open the file picker.\n    var fromInfo = function(e){ return e.target ? (e.target.closest ? !!e.target.closest('.gpy-dz-info') : false) : false; };\n    dropzone.addEventListener('click', function(e){\n      if(fromInfo(e)) return;\n      $('#gpy-upload-modal').classList.remove('show');\n      fileInput.click();\n    });\n    dropzone.addEventListener('keydown', function(e){\n      if(fromInfo(e)) return;\n      if(e.key === 'Enter' ? true : e.key === ' '){\n        e.preventDefault();\n        $('#gpy-upload-modal').classList.remove('show');\n        fileInput.click();\n      }\n    });\n    dropzone.addEventListener('dragenter', function(e){ e.preventDefault(); dropzone.classList.add('is-drag'); });\n    dropzone.addEventListener('dragover', function(e){ e.preventDefault(); dropzone.classList.add('is-drag'); });\n    dropzone.addEventListener('dragleave', function(e){\n      if(e.target === dropzone ? true : !dropzone.contains(e.relatedTarget)){\n        dropzone.classList.remove('is-drag');\n      }\n    });\n    dropzone.addEventListener('drop', function(e){\n      e.preventDefault();\n      dropzone.classList.remove('is-drag');\n      $('#gpy-upload-modal').classList.remove('show');\n      if(!e.dataTransfer) return;\n      var items = e.dataTransfer.items;\n      var hasDir = false;\n      if(items ? items.length : false){\n        for(var ii=0; ii<items.length; ii++){\n          var ent = items[ii].webkitGetAsEntry ? items[ii].webkitGetAsEntry() : null;\n          if(ent ? ent.isDirectory : false){ hasDir = true; break; }\n        }\n      }\n      if(hasDir){\n        collectDroppedEntries(items).then(function(fileArr){\n          if(fileArr.length) processFolder(fileArr);\n        });\n        return;\n      }\n      var files = e.dataTransfer.files;\n      if(files ? files.length : false){\n        var arr = Array.prototype.slice.call(files);  \/\/ snapshot \u2014 dataTransfer.files goes stale after the handler returns\n        if(arr.length === 1) handleFile(arr[0]);\n        else processFolder(arr);\n      }\n    });\n  }\n  \/\/ Single file input now accepts multi-select (so a user can pick several files at once). Folder\n  \/\/ upload happens via drag-drop (which also picks up nested files automatically).\n  fileInput.setAttribute('multiple', 'true');\n  fileInput.onchange = function(e){\n    var files = e.target.files;\n    if(!files ? true : !files.length){ fileInput.value=''; return; }\n    \/\/ Snapshot the live FileList into a plain array BEFORE resetting the input.\n    \/\/ Setting fileInput.value='' empties the live FileList, and processFolder reads\n    \/\/ it asynchronously (after shp.js loads). Without the snapshot, multi-file\n    \/\/ selection saw an emptied list \u2192 \"entries: 0 files\" \u2192 nothing imported\n    \/\/ (reported 2026-06-10). The File objects in the array stay valid post-reset.\n    var arr = Array.prototype.slice.call(files);\n    fileInput.value='';\n    if(arr.length === 1) handleFile(arr[0]);\n    else processFolder(arr);  \/\/ multi-file selection routes through the folder pipeline\n  };\n  var sampleBtns = root.querySelectorAll('#gpy-samples button');\n  for(var i=0;i<sampleBtns.length;i++){\n    sampleBtns[i].onclick = function(){\n      var s = this.dataset.s;\n      if(s === 'yield') loadSample();\n      else if(s === 'applied') loadSampleApplied();\n      else if(s === 'soil') loadSampleSoil();\n      else if(s === 'ec') loadSampleEC();\n      \/\/ 'lines' is now a cross-link to \/guidance-lines\/ (rendered as an anchor,\n      \/\/ not a button) \u2014 no handler here.\n    };\n  }\n  \/\/ Distance \/ area unit toggle. Persist to localStorage and re-render so the scale bar,\n  \/\/ playback distance, and legend area readouts flip immediately.\n  (function(){\n    var unitBtns = root.querySelectorAll('#gpy-units button');\n    function syncActive(){\n      for(var u=0; u<unitBtns.length; u++){\n        if(unitBtns[u].dataset.u === distanceUnit) unitBtns[u].classList.add('on');\n        else unitBtns[u].classList.remove('on');\n      }\n    }\n    syncActive();\n    for(var ui=0; ui<unitBtns.length; ui++){\n      unitBtns[ui].addEventListener('click', function(){\n        distanceUnit = this.dataset.u;\n        try { localStorage.setItem('gpy-distance-unit', distanceUnit); } catch(_){}\n        syncActive();\n        draw();\n        updatePlaybackUI();\n        \/\/ Zones table shows area in ha\/ac \u2014 refresh when the unit flips.\n        if(zonesK > 0 ? typeof updateZonesPanel === 'function' : false) updateZonesPanel();\n      });\n    }\n  })();\n  var main = root.querySelector('.gpy-main');\n  main.addEventListener('dragenter', function(e){ e.preventDefault(); showOverlay('Drop to load', 'Release to load this file or folder.', false); overlay.classList.add('drop'); });\n  main.addEventListener('dragover', function(e){ e.preventDefault(); });\n  main.addEventListener('dragleave', function(e){ if(e.target === main || !main.contains(e.relatedTarget)){ hideOverlay(); } });\n  main.addEventListener('drop', function(e){\n    e.preventDefault(); hideOverlay();\n    if(!e.dataTransfer) return;\n    \/\/ Folder drag-drop uses webkitGetAsEntry to recurse into the directory tree. Falls back to\n    \/\/ dataTransfer.files for single-file drops (which is just an array of one File).\n    var items = e.dataTransfer.items;\n    var hasDir = false;\n    if(items ? items.length : false){\n      for(var ii=0; ii<items.length; ii++){\n        var ent = items[ii].webkitGetAsEntry ? items[ii].webkitGetAsEntry() : null;\n        if(ent ? ent.isDirectory : false){ hasDir = true; break; }\n      }\n    }\n    if(hasDir){\n      collectDroppedEntries(items).then(function(fileArr){\n        if(fileArr.length) processFolder(fileArr);\n      });\n      return;\n    }\n    var files = e.dataTransfer.files;\n    if(files ? files.length : false){\n      var arr = Array.prototype.slice.call(files);  \/\/ snapshot \u2014 dataTransfer.files goes stale after the handler returns\n      if(arr.length === 1) handleFile(arr[0]);\n      else processFolder(arr);\n    }\n  });\n  \/\/ Recursively walk DataTransferItems for folder drops. Each File comes back with webkitRelativePath\n  \/\/ patched onto it so processFolder's pipeline (which keys off relative path) works unchanged.\n  function collectDroppedEntries(items){\n    var out = [];\n    function readDir(dirEntry, prefix){\n      return new Promise(function(resolve){\n        var reader = dirEntry.createReader();\n        var all = [];\n        function readBatch(){\n          reader.readEntries(function(batch){\n            if(!batch.length){\n              Promise.all(all.map(function(e){ return walk(e, prefix); })).then(resolve);\n              return;\n            }\n            for(var k=0; k<batch.length; k++) all.push(batch[k]);\n            readBatch();\n          }, function(){ resolve(); });\n        }\n        readBatch();\n      });\n    }\n    function walk(entry, prefix){\n      if(entry.isFile){\n        return new Promise(function(resolve){\n          entry.file(function(file){\n            \/\/ Patch webkitRelativePath so processFolder sees the directory layout\n            try { Object.defineProperty(file, 'webkitRelativePath', { value: prefix + entry.name, configurable:true }); }\n            catch(_){ try { file.webkitRelativePath = prefix + entry.name; } catch(_2){} }\n            out.push(file);\n            resolve();\n          }, function(){ resolve(); });\n        });\n      }\n      if(entry.isDirectory){\n        return readDir(entry, prefix + entry.name + '\/');\n      }\n      return Promise.resolve();\n    }\n    var rootJobs = [];\n    for(var i=0; i<items.length; i++){\n      var ent = items[i].webkitGetAsEntry ? items[i].webkitGetAsEntry() : null;\n      if(ent) rootJobs.push(walk(ent, ''));\n    }\n    return Promise.all(rootJobs).then(function(){ return out; });\n  }\n  \/\/ Playback control wiring\n  var pbPlayBtn = $('#gpy-pb-play');\n  if(pbPlayBtn) pbPlayBtn.addEventListener('click', playbackPlay);\n  var pbPauseBtn = $('#gpy-pb-pause');\n  if(pbPauseBtn) pbPauseBtn.addEventListener('click', playbackPause);\n  \/\/ Mobile-only collapse toggle for the playback bar. Tap the chevron to\n  \/\/ expand\/collapse the secondary controls (speed buttons, stats text,\n  \/\/ price input). Desktop CSS leaves the button hidden so this is a no-op\n  \/\/ off-mobile. Default state is collapsed (no .is-expanded class).\n  var pbCollapseBtn = $('#gpy-pb-collapse');\n  var pbEl = $('#gpy-pb');\n  if(pbCollapseBtn ? pbEl : false){\n    pbCollapseBtn.addEventListener('click', function(){\n      var nowExpanded = !pbEl.classList.contains('is-expanded');\n      pbEl.classList.toggle('is-expanded', nowExpanded);\n      pbCollapseBtn.setAttribute('aria-expanded', nowExpanded ? 'true' : 'false');\n    });\n  }\n  var pbTrack = $('#gpy-pb-track');\n  if(pbTrack){\n    pbTrack.addEventListener('click', function(e){ playbackScrub(e.clientX); });\n    pbTrack.addEventListener('touchstart', function(e){\n      if(e.touches.length === 1){ e.preventDefault(); playbackScrub(e.touches[0].clientX); }\n    }, { passive:false });\n  }\n  var pbSpeedBtns = root.querySelectorAll('#gpy-pb-speed button');\n  for(var sb=0; sb<pbSpeedBtns.length; sb++){\n    (function(btn){\n      btn.addEventListener('click', function(){\n        for(var b2=0;b2<pbSpeedBtns.length;b2++) pbSpeedBtns[b2].classList.remove('on');\n        btn.classList.add('on');\n        playback.speed = +btn.dataset.s;\n      });\n    })(pbSpeedBtns[sb]);\n  }\n  \/\/ Product price input \u2014 revenue per unit for yield data, product cost per unit for\n  \/\/ as-applied \/ planting data. Unit label (the span after the number) auto-fills from\n  \/\/ the active attribute's unit numerator via updatePlaybackUI -> priceUnitFor.\n  var priceInput = $('#gpy-pb-price');\n  if(priceInput){\n    priceInput.value = productPrice > 0 ? productPrice : '';\n    priceInput.addEventListener('input', function(){\n      var v = parseFloat(priceInput.value);\n      if(isFinite(v) ? v >= 0 : false){\n        productPrice = v;\n      } else {\n        productPrice = 0;\n      }\n      try { localStorage.setItem('gpy-product-price', String(productPrice)); } catch(_){}\n      updatePlaybackUI();\n    });\n  }\n  \/\/ Space key toggles play\/pause when canvas-focused (and tool is in polygon mode)\n  window.addEventListener('keydown', function(e){\n    if(e.key === ' ' || e.code === 'Space'){\n      if(e.target ? \/input|textarea|select|button\/i.test(e.target.tagName || '') : false) return;\n      e.preventDefault();\n      playbackPlayPause();\n    }\n  });\n  window.addEventListener('resize', resize);\n  if(window.ResizeObserver){ new ResizeObserver(resize).observe(canvas.parentElement); }\n  \/\/ Resizable left sidebar (item 2). Long dataset \/ field names didn't fit in a fixed 200px column.\n  \/\/ Drag the vertical splitter to widen the Datasets panel; width persists per browser via localStorage.\n  \/\/ Mobile (\u2264820px) hides the splitter via CSS and the layout collapses to a stack.\n  (function setupSplitter(){\n    var splitter = $('#gpy-splitter');\n    if(!splitter) return;\n    var MIN_W = 140, MAX_W = 480;\n    try {\n      var saved = localStorage.getItem('gpy-left-w');\n      var sv = saved ? parseInt(saved, 10) : 0;\n      if(sv >= MIN_W ? sv <= MAX_W : false){\n        root.style.setProperty('--gpy-left-w', sv + 'px');\n      }\n    } catch(_){}\n    function clampW(w){\n      var gridEl = root.querySelector('.gpy-grid');\n      var maxAllowed = MAX_W;\n      if(gridEl){\n        \/\/ Don't let the sidebar take more than 60% of the embed width, so the map stays dominant\n        var gw = gridEl.getBoundingClientRect().width;\n        var capByPct = Math.round(gw * 0.6);\n        if(capByPct < maxAllowed) maxAllowed = capByPct;\n      }\n      if(w < MIN_W) w = MIN_W;\n      if(w > maxAllowed) w = maxAllowed;\n      return w;\n    }\n    function applyW(w){\n      root.style.setProperty('--gpy-left-w', w + 'px');\n      try { resize(); draw(); } catch(_){}\n    }\n    function persistW(w){\n      try { localStorage.setItem('gpy-left-w', String(w)); } catch(_){}\n    }\n    var dragging = false;\n    var gridRectLeft = 0;\n    function getX(e){\n      if(e.touches ? e.touches.length : false) return e.touches[0].clientX;\n      return e.clientX;\n    }\n    function start(e){\n      \/\/ Don't activate on mobile (splitter is display:none anyway, but guard)\n      if(window.matchMedia ? window.matchMedia('(max-width:820px)').matches : false) return;\n      e.preventDefault();\n      dragging = true;\n      splitter.classList.add('is-drag');\n      document.body.style.cursor = 'col-resize';\n      var gridEl = root.querySelector('.gpy-grid');\n      gridRectLeft = gridEl ? gridEl.getBoundingClientRect().left : 0;\n    }\n    function move(e){\n      if(!dragging) return;\n      var x = getX(e);\n      var w = clampW(Math.round(x - gridRectLeft));\n      applyW(w);\n    }\n    function end(){\n      if(!dragging) return;\n      dragging = false;\n      splitter.classList.remove('is-drag');\n      document.body.style.cursor = '';\n      var cur = parseInt(getComputedStyle(root).getPropertyValue('--gpy-left-w'), 10);\n      if(isFinite(cur)) persistW(cur);\n    }\n    splitter.addEventListener('mousedown', start);\n    splitter.addEventListener('touchstart', start, { passive:false });\n    window.addEventListener('mousemove', move);\n    window.addEventListener('touchmove', move, { passive:false });\n    window.addEventListener('mouseup', end);\n    window.addEventListener('touchend', end);\n    splitter.addEventListener('dblclick', function(){\n      \/\/ Reset to default\n      root.style.setProperty('--gpy-left-w', '200px');\n      try { localStorage.removeItem('gpy-left-w'); } catch(_){}\n      try { resize(); draw(); } catch(_){}\n    });\n  })();\n  \/\/ Pre-load all four built-in samples (as-applied, soil sample, soil scan,\n  \/\/ yield) into the dataset tree on startup so visitors see the full range\n  \/\/ of supported data types one click away. Order matters: the LAST call's\n  \/\/ activateDataset wins, so yield is loaded last and ends up active \u2014 it's\n  \/\/ the primary use case landing visitors expect to see. Only the active\n  \/\/ dataset's IDW raster is built at load time, so the soil-scan blob\n  \/\/ (17k pts) doesn't pay any startup cost until the user clicks it.\n  loadSampleApplied();\n  loadSampleSoil();\n  loadSampleEC();\n  loadSample();\n  setTimeout(resize, 30);\n  \/\/ Debug hook \u2014 exposes the live playback state for in-browser verification of the\n  \/\/ field-hull \/ headland-following work. Read-only; do not write through this from\n  \/\/ production code.\n  try { window.__gpyDbg = { get playback(){ return playback; } }; } catch(_){}\n})();\n<\/script>\n<\/div>\n\n\n\n<div class=\"gp-lead\">\n<section class=\"gpx-cta\">\n  <h2>Bigger picture? GeoPard turns the data into prescriptions.<\/h2>\n  <p>This page reads one file at a time. The full GeoPard platform combines multi-year yield, NDVI, soil, and topography into management zones, generates variable rate prescriptions, and pushes them to your machine.<\/p>\n  <div class=\"gpx-integ-label\">Push prescriptions and pull as-applied data with:<\/div>\n  <div class=\"gpx-integ\">\n    <span class=\"gpx-integ-chip\">John Deere Operations Center<\/span>\n    <span class=\"gpx-integ-chip\">CNH FieldOps<\/span>\n    <span class=\"gpx-integ-chip\">AGCO \/ PTx FarmEngage<\/span>\n  <\/div>\n  <a class=\"gpx-btn\" href=\"https:\/\/app.geopard.tech\/signup?utm_source=geopard.tech&amp;utm_medium=lead-magnet&amp;utm_campaign=field-data-explorer&amp;utm_content=below-tool-cta\">Register free in GeoPard &rarr;<\/a>\n<\/section>\n\n<section class=\"gpx-faq\" aria-labelledby=\"gpx-faq-h\">\n  <h2 id=\"gpx-faq-h\">Frequently asked questions<\/h2>\n  <div class=\"gpx-tabs\">\n    <div class=\"gpx-tablist\" role=\"tablist\" aria-label=\"Field Data Explorer FAQ\">\n      <button class=\"gpx-tab\" role=\"tab\" id=\"gpx-tab-1\" aria-controls=\"gpx-panel-1\" aria-selected=\"true\" tabindex=\"0\">File formats<\/button>\n      <button class=\"gpx-tab\" role=\"tab\" id=\"gpx-tab-2\" aria-controls=\"gpx-panel-2\" aria-selected=\"false\" tabindex=\"-1\">Privacy &amp; data<\/button>\n      <button class=\"gpx-tab\" role=\"tab\" id=\"gpx-tab-3\" aria-controls=\"gpx-panel-3\" aria-selected=\"false\" tabindex=\"-1\">Outlier colors<\/button>\n      <button class=\"gpx-tab\" role=\"tab\" id=\"gpx-tab-4\" aria-controls=\"gpx-panel-4\" aria-selected=\"false\" tabindex=\"-1\">Saving analysis<\/button>\n      <button class=\"gpx-tab\" role=\"tab\" id=\"gpx-tab-5\" aria-controls=\"gpx-panel-5\" aria-selected=\"false\" tabindex=\"-1\">Integrations<\/button>\n    <\/div>\n    <div class=\"gpx-panel is-active\" role=\"tabpanel\" id=\"gpx-panel-1\" aria-labelledby=\"gpx-tab-1\">\n      <h3>What file formats and layers are supported?<\/h3>\n      <p><strong>Layers:<\/strong> yield maps, as-applied (seeding, fertilizer, spraying, lime), soil sample points, field boundaries, and Trimble Coverage maps.<\/p>\n      <p><strong>Containers:<\/strong> <strong>GeoJSON<\/strong> with Point, LineString, Polygon, or MultiPolygon geometry, and <strong>zipped shapefiles<\/strong> in EPSG:4326 (WGS84). Projected shapefiles will silently mis-place coordinates, so convert them to WGS84 first or use the full GeoPard import flow which handles reprojection.<\/p>\n    <\/div>\n    <div class=\"gpx-panel\" role=\"tabpanel\" id=\"gpx-panel-2\" aria-labelledby=\"gpx-tab-2\" hidden>\n      <h3>Are you storing my data?<\/h3>\n      <p>No. The page is fully client-side. Nothing about your file leaves the browser. There is no upload, no server log, no telemetry on the file contents. Close the tab and it is gone. You can verify this with browser dev tools by watching the Network panel after dropping a file.<\/p>\n    <\/div>\n    <div class=\"gpx-panel\" role=\"tabpanel\" id=\"gpx-panel-3\" aria-labelledby=\"gpx-tab-3\" hidden>\n      <h3>Why are some points grey or violet?<\/h3>\n      <p><strong>Grey<\/strong> = low-side outliers (likely a missed pass, wet spot, header float issue, or boundary noise). <strong>Violet<\/strong> = high-side outliers (likely double-pass overlaps in as-applied maps, or a moisture or sensor hot spot in yield). Adjust the <code>sigma<\/code> slider to make outlier detection more or less strict, or toggle outliers off to see the raw distribution.<\/p>\n    <\/div>\n    <div class=\"gpx-panel\" role=\"tabpanel\" id=\"gpx-panel-4\" aria-labelledby=\"gpx-tab-4\" hidden>\n      <h3>Can I save my analysis?<\/h3>\n      <p>Not from this page. Saving farm history, sharing fields with your agronomist, layering NDVI, soil tests, and elevation, generating variable rate prescriptions, and exporting work files to your equipment platform all live in the full GeoPard app.<\/p>\n    <\/div>\n    <div class=\"gpx-panel\" role=\"tabpanel\" id=\"gpx-panel-5\" aria-labelledby=\"gpx-tab-5\" hidden>\n      <h3>What equipment platforms can GeoPard write prescriptions to?<\/h3>\n      <p>From the full GeoPard platform you can push variable rate prescription files and import as-applied data with <strong>John Deere Operations Center<\/strong>, <strong>CNH FieldOps<\/strong>, and <strong>AGCO \/ PTx FarmEngage<\/strong>, plus shapefile and ISO-XML exports for other monitors. Talk to us if you run a mixed fleet.<\/p>\n    <\/div>\n  <\/div>\n<\/section>\n<script type=\"application\/ld+json\" data-no-optimize=\"1\" data-no-minify=\"1\">\n{\n  \"@context\": \"https:\/\/schema.org\",\n  \"@type\": \"FAQPage\",\n  \"mainEntity\": [\n    {\n      \"@type\": \"Question\",\n      \"name\": \"What file formats and layers are supported?\",\n      \"acceptedAnswer\": {\n        \"@type\": \"Answer\",\n        \"text\": \"Layers: yield maps, as-applied (seeding, fertilizer, spraying, lime), soil sample points, field boundaries, and Trimble Coverage maps. Containers: GeoJSON with Point, LineString, Polygon, or MultiPolygon geometry, and zipped shapefiles in EPSG:4326 (WGS84). 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