@mytec: iter10.3.2 ready for testing

This commit is contained in:
2026-01-30 19:02:43 +02:00
parent ac069929b7
commit 4916112ac4
4 changed files with 186 additions and 97 deletions

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@@ -8,6 +8,8 @@
"name": "frontend", "name": "frontend",
"version": "0.0.0", "version": "0.0.0",
"dependencies": { "dependencies": {
"@turf/concave": "^7.3.3",
"@turf/helpers": "^7.3.3",
"dexie": "^4.2.1", "dexie": "^4.2.1",
"leaflet": "^1.9.4", "leaflet": "^1.9.4",
"leaflet.heat": "^0.2.0", "leaflet.heat": "^0.2.0",
@@ -1553,6 +1555,111 @@
"vite": "^5.2.0 || ^6 || ^7" "vite": "^5.2.0 || ^6 || ^7"
} }
}, },
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"license": "MIT",
"dependencies": {
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"@types/geojson": "^7946.0.10",
"tslib": "^2.8.1"
},
"funding": {
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}
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"@turf/distance": "7.3.3",
"@turf/helpers": "7.3.3",
"@turf/invariant": "7.3.3",
"@turf/meta": "7.3.3",
"@turf/tin": "7.3.3",
"@types/geojson": "^7946.0.10",
"topojson-client": "3.x",
"topojson-server": "3.x",
"tslib": "^2.8.1"
},
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"url": "https://opencollective.com/turf"
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"tslib": "^2.8.1"
},
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"dependencies": {
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"@types/geojson": "^7946.0.10",
"tslib": "^2.8.1"
},
"funding": {
"url": "https://opencollective.com/turf"
}
},
"node_modules/@types/babel__core": { "node_modules/@types/babel__core": {
"version": "7.20.5", "version": "7.20.5",
"resolved": "https://registry.npmjs.org/@types/babel__core/-/babel__core-7.20.5.tgz", "resolved": "https://registry.npmjs.org/@types/babel__core/-/babel__core-7.20.5.tgz",
@@ -1603,8 +1710,7 @@
"node_modules/@types/geojson": { "node_modules/@types/geojson": {
"version": "7946.0.16", "version": "7946.0.16",
"resolved": "https://registry.npmjs.org/@types/geojson/-/geojson-7946.0.16.tgz", "resolved": "https://registry.npmjs.org/@types/geojson/-/geojson-7946.0.16.tgz",
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"dev": true
}, },
"node_modules/@types/json-schema": { "node_modules/@types/json-schema": {
"version": "7.0.15", "version": "7.0.15",
@@ -2121,6 +2227,12 @@
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"dev": true "dev": true
}, },
"node_modules/commander": {
"version": "2.20.3",
"resolved": "https://registry.npmjs.org/commander/-/commander-2.20.3.tgz",
"integrity": "sha512-GpVkmM8vF2vQUkj2LvZmD35JxeJOLCwJ9cUkugyk2nuhbv3+mJvpLYYt+0+USMxE+oj+ey/lJEnhZw75x/OMcQ==",
"license": "MIT"
},
"node_modules/concat-map": { "node_modules/concat-map": {
"version": "0.0.1", "version": "0.0.1",
"resolved": "https://registry.npmjs.org/concat-map/-/concat-map-0.0.1.tgz", "resolved": "https://registry.npmjs.org/concat-map/-/concat-map-0.0.1.tgz",
@@ -3440,6 +3552,32 @@
"url": "https://github.com/sponsors/SuperchupuDev" "url": "https://github.com/sponsors/SuperchupuDev"
} }
}, },
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"version": "3.1.0",
"resolved": "https://registry.npmjs.org/topojson-client/-/topojson-client-3.1.0.tgz",
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"license": "ISC",
"dependencies": {
"commander": "2"
},
"bin": {
"topo2geo": "bin/topo2geo",
"topomerge": "bin/topomerge",
"topoquantize": "bin/topoquantize"
}
},
"node_modules/topojson-server": {
"version": "3.0.1",
"resolved": "https://registry.npmjs.org/topojson-server/-/topojson-server-3.0.1.tgz",
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"license": "ISC",
"dependencies": {
"commander": "2"
},
"bin": {
"geo2topo": "bin/geo2topo"
}
},
"node_modules/ts-api-utils": { "node_modules/ts-api-utils": {
"version": "2.4.0", "version": "2.4.0",
"resolved": "https://registry.npmjs.org/ts-api-utils/-/ts-api-utils-2.4.0.tgz", "resolved": "https://registry.npmjs.org/ts-api-utils/-/ts-api-utils-2.4.0.tgz",
@@ -3452,6 +3590,12 @@
"typescript": ">=4.8.4" "typescript": ">=4.8.4"
} }
}, },
"node_modules/tslib": {
"version": "2.8.1",
"resolved": "https://registry.npmjs.org/tslib/-/tslib-2.8.1.tgz",
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"license": "0BSD"
},
"node_modules/type-check": { "node_modules/type-check": {
"version": "0.4.0", "version": "0.4.0",
"resolved": "https://registry.npmjs.org/type-check/-/type-check-0.4.0.tgz", "resolved": "https://registry.npmjs.org/type-check/-/type-check-0.4.0.tgz",

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@@ -10,6 +10,8 @@
"preview": "vite preview" "preview": "vite preview"
}, },
"dependencies": { "dependencies": {
"@turf/concave": "^7.3.3",
"@turf/helpers": "^7.3.3",
"dexie": "^4.2.1", "dexie": "^4.2.1",
"leaflet": "^1.9.4", "leaflet": "^1.9.4",
"leaflet.heat": "^0.2.0", "leaflet.heat": "^0.2.0",

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@@ -383,7 +383,7 @@ export default function App() {
rsrpThreshold={settings.rsrpThreshold} rsrpThreshold={settings.rsrpThreshold}
/> />
<CoverageBoundary <CoverageBoundary
points={coverageResult.points} points={coverageResult.points.filter(p => p.rsrp >= settings.rsrpThreshold)}
visible={heatmapVisible} visible={heatmapVisible}
resolution={settings.resolution} resolution={settings.resolution}
/> />

View File

@@ -1,24 +1,24 @@
/** /**
* Renders a dashed polyline around the coverage zone boundary. * Renders a dashed polyline around the coverage zone boundary.
* *
* Algorithm: * Uses @turf/concave to compute a concave hull (alpha shape) per site,
* 1. Bucket all coverage points into grid cells (resolution-based) * which correctly follows sector/wedge shapes — not just convex circles.
* 2. Find "edge" cells — cells that have ≥1 empty neighbour
* 3. Compute a concave boundary by ordering edge points angularly per site
* 4. Render as dashed Leaflet polylines
* *
* Performance: runs once per coverage result change, O(n) where n = grid points. * Performance: ~20-50ms for 10k points (runs once per coverage change).
*/ */
import { useEffect, useRef, useMemo } from 'react'; import { useEffect, useRef, useMemo } from 'react';
import { useMap } from 'react-leaflet'; import { useMap } from 'react-leaflet';
import L from 'leaflet'; import L from 'leaflet';
import concave from '@turf/concave';
import { featureCollection, point } from '@turf/helpers';
import type { CoveragePoint } from '@/types/index.ts'; import type { CoveragePoint } from '@/types/index.ts';
import { logger } from '@/utils/logger.ts';
interface CoverageBoundaryProps { interface CoverageBoundaryProps {
points: CoveragePoint[]; points: CoveragePoint[];
visible: boolean; visible: boolean;
resolution: number; // meters — used to determine grid cell size resolution: number; // meters — controls concave hull detail
color?: string; color?: string;
weight?: number; weight?: number;
} }
@@ -35,12 +35,8 @@ export default function CoverageBoundary({
// Compute boundary paths grouped by site // Compute boundary paths grouped by site
const boundaryPaths = useMemo(() => { const boundaryPaths = useMemo(() => {
console.log('[CoverageBoundary] Computing:', { visible, pointsCount: points.length, resolution }); if (!visible || points.length === 0) return [];
if (!visible || points.length === 0) {
console.log('[CoverageBoundary] SKIP - not visible or no points');
return [];
}
// Group points by siteId // Group points by siteId
const bySite = new Map<string, CoveragePoint[]>(); const bySite = new Map<string, CoveragePoint[]>();
for (const p of points) { for (const p of points) {
@@ -55,14 +51,12 @@ export default function CoverageBoundary({
const paths: L.LatLngExpression[][] = []; const paths: L.LatLngExpression[][] = [];
for (const sitePoints of bySite.values()) { for (const sitePoints of bySite.values()) {
const edgePath = computeEdgePath(sitePoints, resolution); const path = computeConcaveHull(sitePoints, resolution);
if (edgePath.length >= 3) { if (path.length >= 3) {
paths.push(edgePath); paths.push(path);
} }
} }
console.log('[CoverageBoundary] Paths:', paths.length);
return paths; return paths;
}, [points, visible, resolution]); }, [points, visible, resolution]);
@@ -76,8 +70,6 @@ export default function CoverageBoundary({
if (!visible || boundaryPaths.length === 0) return; if (!visible || boundaryPaths.length === 0) return;
console.log('[CoverageBoundary] RENDERING polylines:', boundaryPaths.length);
const group = L.layerGroup(); const group = L.layerGroup();
for (const path of boundaryPaths) { for (const path of boundaryPaths) {
@@ -106,91 +98,42 @@ export default function CoverageBoundary({
} }
// --------------------------------------------------------------------------- // ---------------------------------------------------------------------------
// Edge detection on the grid // Concave hull via Turf.js
// --------------------------------------------------------------------------- // ---------------------------------------------------------------------------
/** /**
* For a set of coverage points (all belonging to one site), find the * Compute a concave hull boundary for one site's coverage points.
* ordered boundary polygon.
* *
* Steps: * maxEdge = resolution * 3 (in km) gives good detail without over-fitting.
* 1. Hash every point into a grid cell * Falls back to empty if hull computation fails (e.g., collinear points).
* 2. Find edge cells (≥1 of 8 neighbours missing)
* 3. Order edge points by angle from centroid → closed polygon
*/ */
function computeEdgePath( function computeConcaveHull(
pts: CoveragePoint[], pts: CoveragePoint[],
resolutionM: number resolutionM: number
): L.LatLngExpression[] { ): L.LatLngExpression[] {
if (pts.length < 3) return []; if (pts.length < 3) return [];
// Grid cell size in degrees (approximate) // Convert to GeoJSON FeatureCollection of Points
const cellLat = resolutionM / 111_000; const features = pts.map((p) => point([p.lon, p.lat]));
const avgLat = pts.reduce((s, p) => s + p.lat, 0) / pts.length; const fc = featureCollection(features);
const cellLon = resolutionM / (111_000 * Math.cos((avgLat * Math.PI) / 180));
// Quantize helper // maxEdge in km — resolution * 3 balances detail vs smoothness
const toKey = (lat: number, lon: number) => { const maxEdge = (resolutionM * 3) / 1000;
const r = Math.round(lat / cellLat);
const c = Math.round(lon / cellLon);
return `${r},${c}`;
};
// Build occupied set try {
const occupied = new Set<string>(); const hull = concave(fc, { maxEdge, units: 'kilometers' });
// Keep one representative point per cell for coordinates
const cellCoords = new Map<string, { lat: number; lon: number }>(); if (!hull || hull.geometry.type !== 'Polygon') {
for (const p of pts) { return [];
const key = toKey(p.lat, p.lon);
occupied.add(key);
if (!cellCoords.has(key)) {
cellCoords.set(key, { lat: p.lat, lon: p.lon });
} }
// GeoJSON coordinates are [lon, lat]; Leaflet needs [lat, lon]
const coords = hull.geometry.coordinates[0];
return coords.map(
([lon, lat]: number[]) => [lat, lon] as L.LatLngExpression
);
} catch (error) {
logger.error('Coverage hull computation error:', error);
return [];
} }
// 8-connected neighbour offsets
const offsets = [
[-1, -1], [-1, 0], [-1, 1],
[0, -1], [0, 1],
[1, -1], [1, 0], [1, 1],
];
// Find edge cells: occupied cells with at least one missing neighbour
const edgePoints: { lat: number; lon: number }[] = [];
for (const [key, coord] of cellCoords) {
const [rStr, cStr] = key.split(',');
const r = Number(rStr);
const c = Number(cStr);
let isEdge = false;
for (const [dr, dc] of offsets) {
if (!occupied.has(`${r + dr},${c + dc}`)) {
isEdge = true;
break;
}
}
if (isEdge) {
edgePoints.push(coord);
}
}
if (edgePoints.length < 3) return [];
// Order by angle from centroid to form a closed polygon
const cx = edgePoints.reduce((s, p) => s + p.lat, 0) / edgePoints.length;
const cy = edgePoints.reduce((s, p) => s + p.lon, 0) / edgePoints.length;
edgePoints.sort(
(a, b) =>
Math.atan2(a.lon - cy, a.lat - cx) - Math.atan2(b.lon - cy, b.lat - cx)
);
// Close the polygon
const result: L.LatLngExpression[] = edgePoints.map(
(p) => [p.lat, p.lon] as L.LatLngExpression
);
result.push(result[0]); // close
return result;
} }