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pverseer rambling at 430am

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legop3
2026-05-02 04:35:20 -04:00
parent 0f97382f42
commit e8f6fb9654
4 changed files with 86 additions and 23 deletions
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webui/src/components/vip/VipNeatoCard.jsx
+41 -13
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@@ -45,21 +45,49 @@ function buildLidarRenderPoints(points = []) {
(point) => point && point.valid && Number.isFinite(point.angleDeg) && Number.isFinite(point.distanceMm),
);
const sortedPoints = [...validPoints].sort((a, b) => Number(a.angleDeg) - Number(b.angleDeg));
const filteredPoints = sortedPoints.filter((point, index, list) => {
if (list.length < 3) return true;
const distanceMm = Math.max(0, Number(point.distanceMm));
const prev = list[(index - 1 + list.length) % list.length];
const next = list[(index + 1) % list.length];
const prevDistanceMm = Math.max(0, Number(prev.distanceMm));
const nextDistanceMm = Math.max(0, Number(next.distanceMm));
const neighborDistanceMm = Math.max(prevDistanceMm, nextDistanceMm);
const groups = [];
let currentGroup = [];
// Drop single-point radial spikes that sit far beyond both adjacent angle samples.
if (neighborDistanceMm <= 0) return true;
const muchFartherThanNeighbors = distanceMm > neighborDistanceMm * 1.85;
const largeAbsoluteGap = distanceMm - neighborDistanceMm > 1400;
return !(muchFartherThanNeighbors && largeAbsoluteGap);
for (const point of sortedPoints) {
if (!currentGroup.length) {
currentGroup.push(point);
continue;
}
const previousPoint = currentGroup[currentGroup.length - 1];
const angleGap = Math.abs(Number(point.angleDeg) - Number(previousPoint.angleDeg));
const prevDistanceMm = Math.max(0, Number(previousPoint.distanceMm));
const distanceMm = Math.max(0, Number(point.distanceMm));
const distanceGap = Math.abs(distanceMm - prevDistanceMm);
if (angleGap <= 2 && distanceGap <= 900) {
currentGroup.push(point);
continue;
}
groups.push(currentGroup);
currentGroup = [point];
}
if (currentGroup.length) groups.push(currentGroup);
const groupStats = groups.map((group) => {
const distances = group.map((point) => Math.max(0, Number(point.distanceMm)));
const avgDistanceMm = distances.reduce((sum, value) => sum + value, 0) / Math.max(1, distances.length);
return {
points: group,
size: group.length,
avgDistanceMm,
};
});
const largestGroup = groupStats.reduce((best, group) => (group.size > (best?.size || 0) ? group : best), null);
const referenceDistanceMm = largestGroup?.avgDistanceMm || 1000;
const filteredPoints = groupStats
.filter((group) => {
const tinyCluster = group.size <= 3;
const farFromMainBody =
group.avgDistanceMm > referenceDistanceMm * 1.8 && group.avgDistanceMm - referenceDistanceMm > 1400;
return !(tinyCluster && farFromMainBody);
})
.flatMap((group) => group.points);
const scaleDistances = filteredPoints.map((point) => Math.max(0, Number(point.distanceMm))).sort((a, b) => a - b);
const percentileIndex = Math.max(0, Math.floor((scaleDistances.length - 1) * 0.95));
const maxDistanceMm = Math.max(1000, scaleDistances[percentileIndex] || 1000);