utils_sampleData.js - hiro-nyon/cesium-heatbox GitHub Wiki
Source: utils/sampleData.js
日本語 | English
English
See also: Class: sampleData
/**
* Utility helpers for generating sample datasets.
* サンプルデータ生成ユーティリティ群。
*/
import * as Cesium from 'cesium';
/**
* Generate pseudo-random test entities within the specified bounds.
* 指定範囲内にランダムなテストエンティティを生成します。
* @param {Object} viewer - CesiumJS Viewer
* @param {Object} bounds - 生成範囲 {minLon, maxLon, minLat, maxLat, minAlt, maxAlt}
* @param {number} count - 生成数（デフォルト: 500）
* @returns {Array} 生成されたエンティティ配列
*/
export function generateTestEntities(viewer, bounds, count = 500) {
if (!viewer) {
throw new Error('viewer is required');
}
if (!bounds || !('minLon' in bounds) || !('maxLon' in bounds) || !('minLat' in bounds) || !('maxLat' in bounds)) {
throw new Error('bounds must include minLon, maxLon, minLat, maxLat');
}
const entities = [];
// デフォルト高度範囲
const minAlt = bounds.minAlt || 0;
const maxAlt = bounds.maxAlt || 100;
for (let i = 0; i < count; i++) {
const lon = bounds.minLon + (bounds.maxLon - bounds.minLon) * Math.random();
const lat = bounds.minLat + (bounds.maxLat - bounds.minLat) * Math.random();
const alt = minAlt + (maxAlt - minAlt) * Math.random();
const entity = viewer.entities.add({
id: `test-entity-${i}`,
position: Cesium.Cartesian3.fromDegrees(lon, lat, alt),
point: {
pixelSize: 5,
color: Cesium.Color.YELLOW,
outlineColor: Cesium.Color.BLACK,
outlineWidth: 1
},
label: {
text: `Test ${i}`,
font: '10pt sans-serif',
pixelOffset: new Cesium.Cartesian2(0, -30),
fillColor: Cesium.Color.WHITE,
outlineColor: Cesium.Color.BLACK,
outlineWidth: 1,
style: Cesium.LabelStyle.FILL_AND_OUTLINE
}
});
entities.push(entity);
}
return entities;
}
/**
* Retrieve every entity registered on the given viewer.
* 指定された Viewer の全エンティティを取得します。
* @param {Object} viewer - CesiumJS Viewer
* @returns {Array} エンティティ配列
*/
export function getAllEntities(viewer) {
if (!viewer || !viewer.entities) {
throw new Error('Invalid viewer');
}
return viewer.entities.values;
}
/**
* Generate clustered sample entities without adding to a viewer.
* ビューアに追加せず、クラスター状のサンプルエンティティ配列を生成します。
* @param {number} total - 総エンティティ数
* @param {Object} config - { clusters: Array<{ center:[lon,lat,alt], radius:number, density:number, count:number }> }
* @returns {Array<Cesium.Entity>} エンティティ配列
*/
export function generateSampleData(total, config = {}) {
const clusters = Array.isArray(config.clusters) && config.clusters.length > 0
? config.clusters
: [{ center: [139.75, 35.7, 50], radius: 0.02, density: 0.5, count: total }];
const entities = [];
let remaining = total;
clusters.forEach((c, idx) => {
const count = Math.min(remaining, Math.max(0, c.count || Math.floor(total / clusters.length)));
remaining -= count;
const [lon0, lat0, alt0] = c.center || [139.75, 35.7, 50];
const radius = c.radius || 0.02; // degrees
const altRange = 100;
for (let i = 0; i < count; i++) {
// Uniform random within circle (approx in degrees)
const r = Math.sqrt(Math.random()) * radius;
const theta = Math.random() * Math.PI * 2;
const lon = lon0 + r * Math.cos(theta);
const lat = lat0 + r * Math.sin(theta);
const alt = alt0 + (Math.random() - 0.5) * altRange;
const entity = new Cesium.Entity({
id: `sample-${idx}-${i}-${Math.random().toString(36).slice(2, 8)}`,
position: Cesium.Cartesian3.fromDegrees(lon, lat, alt)
});
entities.push(entity);
}
});
// If any remainder, add around the first cluster center
while (remaining-- > 0) {
const [lon0, lat0, alt0] = clusters[0].center;
const lon = lon0 + (Math.random() - 0.5) * 0.02;
const lat = lat0 + (Math.random() - 0.5) * 0.02;
const alt = alt0 + (Math.random() - 0.5) * 100;
entities.push(new Cesium.Entity({
id: `sample-extra-${Math.random().toString(36).slice(2, 8)}`,
position: Cesium.Cartesian3.fromDegrees(lon, lat, alt)
}));
}
return entities;
}
/**
* Return a convenience bounding box covering the Tokyo Station area.
* 東京駅周辺の境界情報を返します。
* @returns {Object} 東京駅周辺の境界情報
*/
export function getTokyoStationBounds() {
return {
minLon: 139.7640,
maxLon: 139.7680,
minLat: 35.6790,
maxLat: 35.6820,
minAlt: 0,
maxAlt: 100,
centerLon: 139.7660,
centerLat: 35.6805,
centerAlt: 50
};
}
/**
* Create an axis-aligned bounding box from a centre point and edge length.
* 指定された中心点とサイズから境界を生成します。
* @param {number} centerLon - 中心経度
* @param {number} centerLat - 中心緯度
* @param {number} centerAlt - 中心高度
* @param {number} sizeMeters - 一辺のサイズ（メートル）
* @returns {Object} 境界情報
*/
export function createBoundsFromCenter(centerLon, centerLat, centerAlt, sizeMeters) {
// 度からメートルへの概算変換
const latDelta = sizeMeters / 111000 / 2;
const lonDelta = sizeMeters / (111000 * Math.cos(centerLat * Math.PI / 180)) / 2;
const altDelta = sizeMeters / 2;
return {
minLon: centerLon - lonDelta,
maxLon: centerLon + lonDelta,
minLat: centerLat - latDelta,
maxLat: centerLat + latDelta,
minAlt: centerAlt - altDelta,
maxAlt: centerAlt + altDelta,
centerLon,
centerLat,
centerAlt
};
}
/**
* v0.1.15 Phase 1: Density pattern generators for parameter optimization (ADR-0011)
* パラメータ最適化用の密度パターン生成関数
*/
/**
* Generate a clustered density pattern.
* 高密度クラスターの分布を生成します。
* @param {Object} bounds - Bounding box
* @param {number} count - Total entity count
* @param {number} clusterCount - Number of clusters (default: 3)
* @returns {Array<Cesium.Entity>} Generated entities
*/
function generateClusteredPattern(bounds, count, clusterCount = 3) {
const entities = [];
if (!Number.isFinite(count) || count <= 0) {
return entities;
}
const clusters = Math.max(1, Math.min(Math.floor(clusterCount) || 1, count));
const basePerCluster = Math.floor(count / clusters);
const remainder = count - basePerCluster * clusters;
const centerLon = (bounds.minLon + bounds.maxLon) / 2;
const centerLat = (bounds.minLat + bounds.maxLat) / 2;
const centerAlt = (bounds.minAlt + bounds.maxAlt) / 2;
let globalIndex = 0;
for (let c = 0; c < clusters; c++) {
const clusterSize = basePerCluster + (c < remainder ? 1 : 0);
if (clusterSize <= 0) {
continue;
}
// クラスター中心をランダムに配置
const clusterLon = centerLon + (Math.random() - 0.5) * (bounds.maxLon - bounds.minLon) * 0.6;
const clusterLat = centerLat + (Math.random() - 0.5) * (bounds.maxLat - bounds.minLat) * 0.6;
const clusterAlt = centerAlt + (Math.random() - 0.5) * (bounds.maxAlt - bounds.minAlt) * 0.6;
// 各クラスター内にエンティティを密集配置
const clusterRadius = Math.min(
(bounds.maxLon - bounds.minLon),
(bounds.maxLat - bounds.minLat)
) * 0.1;
for (let i = 0; i < clusterSize; i++) {
const r = Math.sqrt(Math.random()) * clusterRadius;
const theta = Math.random() * Math.PI * 2;
const lon = clusterLon + r * Math.cos(theta);
const lat = clusterLat + r * Math.sin(theta);
const alt = clusterAlt + (Math.random() - 0.5) * (bounds.maxAlt - bounds.minAlt) * 0.2;
entities.push(new Cesium.Entity({
id: `clustered-${c}-${i}-${globalIndex}-${Math.random().toString(36).slice(2, 8)}`,
position: Cesium.Cartesian3.fromDegrees(lon, lat, alt)
}));
globalIndex++;
}
}
return entities;
}
/**
* Generate a scattered density pattern.
* 疎分布のデータセットを生成します。
* @param {Object} bounds - Bounding box
* @param {number} count - Total entity count
* @returns {Array<Cesium.Entity>} Generated entities
*/
function generateScatteredPattern(bounds, count) {
const entities = [];
for (let i = 0; i < count; i++) {
const lon = bounds.minLon + Math.random() * (bounds.maxLon - bounds.minLon);
const lat = bounds.minLat + Math.random() * (bounds.maxLat - bounds.minLat);
const alt = bounds.minAlt + Math.random() * (bounds.maxAlt - bounds.minAlt);
entities.push(new Cesium.Entity({
id: `scattered-${i}-${Math.random().toString(36).slice(2, 8)}`,
position: Cesium.Cartesian3.fromDegrees(lon, lat, alt)
}));
}
return entities;
}
/**
* Generate a gradient-based density pattern.
* グラデーション分布のデータセットを生成します。
* @param {Object} bounds - Bounding box
* @param {number} count - Total entity count
* @returns {Array<Cesium.Entity>} Generated entities
*/
function generateGradientPattern(bounds, count) {
const entities = [];
for (let i = 0; i < count; i++) {
// X軸方向に密度が増加するグラデーション
const x = Math.random();
const densityWeight = x * x; // 二乗で密度を増加
const lon = bounds.minLon + x * (bounds.maxLon - bounds.minLon);
const lat = bounds.minLat + Math.random() * (bounds.maxLat - bounds.minLat);
const alt = bounds.minAlt + Math.random() * (bounds.maxAlt - bounds.minAlt);
// 密度の高いエリアでは複数のエンティティを近接配置
if (densityWeight > 0.7 && Math.random() > 0.5) {
const offset = 0.0001; // 約10m
entities.push(new Cesium.Entity({
id: `gradient-${i}-extra-${Math.random().toString(36).slice(2, 8)}`,
position: Cesium.Cartesian3.fromDegrees(
lon + (Math.random() - 0.5) * offset,
lat + (Math.random() - 0.5) * offset,
alt
)
}));
}
entities.push(new Cesium.Entity({
id: `gradient-${i}-${Math.random().toString(36).slice(2, 8)}`,
position: Cesium.Cartesian3.fromDegrees(lon, lat, alt)
}));
}
return entities;
}
/**
* Generate a mixed density pattern.
* 混在分布のデータセットを生成します。
* @param {Object} bounds - Bounding box
* @param {number} count - Total entity count
* @returns {Array<Cesium.Entity>} Generated entities
*/
function generateMixedPattern(bounds, count) {
const entities = [];
// 30%を高密度クラスター、70%を疎分布として配置
const clusteredCount = Math.floor(count * 0.3);
const scatteredCount = count - clusteredCount;
// 高密度クラスター部分
const clusteredEntities = generateClusteredPattern(bounds, clusteredCount, 2);
entities.push(...clusteredEntities);
// 疎分布部分
const scatteredEntities = generateScatteredPattern(bounds, scatteredCount);
entities.push(...scatteredEntities);
return entities;
}
/**
* Density pattern generators map (ADR-0011 Phase 1)
* パラメータ最適化用密度パターンマップ
*/
export const DENSITY_PATTERNS = {
clustered: generateClusteredPattern,
scattered: generateScatteredPattern,
gradient: generateGradientPattern,
mixed: generateMixedPattern
};
/**
* Generate test dataset with specified pattern
* 指定したパターンでテストデータセットを生成
* @param {string} pattern - Pattern name ('clustered', 'scattered', 'gradient', 'mixed')
* @param {Object} bounds - Bounding box
* @param {number} count - Total entity count
* @returns {Array<Cesium.Entity>} Generated entities
*/
export function generatePatternData(pattern, bounds, count) {
const generator = DENSITY_PATTERNS[pattern];
if (!generator) {
throw new Error(`Unknown pattern: ${pattern}. Available: ${Object.keys(DENSITY_PATTERNS).join(', ')}`);
}
return generator(bounds, count);
}
日本語
関連: sampleDataクラス
/**
* Utility helpers for generating sample datasets.
* サンプルデータ生成ユーティリティ群。
*/
import * as Cesium from 'cesium';
/**
* Generate pseudo-random test entities within the specified bounds.
* 指定範囲内にランダムなテストエンティティを生成します。
* @param {Object} viewer - CesiumJS Viewer
* @param {Object} bounds - 生成範囲 {minLon, maxLon, minLat, maxLat, minAlt, maxAlt}
* @param {number} count - 生成数（デフォルト: 500）
* @returns {Array} 生成されたエンティティ配列
*/
export function generateTestEntities(viewer, bounds, count = 500) {
if (!viewer) {
throw new Error('viewer is required');
}
if (!bounds || !('minLon' in bounds) || !('maxLon' in bounds) || !('minLat' in bounds) || !('maxLat' in bounds)) {
throw new Error('bounds must include minLon, maxLon, minLat, maxLat');
}
const entities = [];
// デフォルト高度範囲
const minAlt = bounds.minAlt || 0;
const maxAlt = bounds.maxAlt || 100;
for (let i = 0; i < count; i++) {
const lon = bounds.minLon + (bounds.maxLon - bounds.minLon) * Math.random();
const lat = bounds.minLat + (bounds.maxLat - bounds.minLat) * Math.random();
const alt = minAlt + (maxAlt - minAlt) * Math.random();
const entity = viewer.entities.add({
id: `test-entity-${i}`,
position: Cesium.Cartesian3.fromDegrees(lon, lat, alt),
point: {
pixelSize: 5,
color: Cesium.Color.YELLOW,
outlineColor: Cesium.Color.BLACK,
outlineWidth: 1
},
label: {
text: `Test ${i}`,
font: '10pt sans-serif',
pixelOffset: new Cesium.Cartesian2(0, -30),
fillColor: Cesium.Color.WHITE,
outlineColor: Cesium.Color.BLACK,
outlineWidth: 1,
style: Cesium.LabelStyle.FILL_AND_OUTLINE
}
});
entities.push(entity);
}
return entities;
}
/**
* Retrieve every entity registered on the given viewer.
* 指定された Viewer の全エンティティを取得します。
* @param {Object} viewer - CesiumJS Viewer
* @returns {Array} エンティティ配列
*/
export function getAllEntities(viewer) {
if (!viewer || !viewer.entities) {
throw new Error('Invalid viewer');
}
return viewer.entities.values;
}
/**
* Generate clustered sample entities without adding to a viewer.
* ビューアに追加せず、クラスター状のサンプルエンティティ配列を生成します。
* @param {number} total - 総エンティティ数
* @param {Object} config - { clusters: Array<{ center:[lon,lat,alt], radius:number, density:number, count:number }> }
* @returns {Array<Cesium.Entity>} エンティティ配列
*/
export function generateSampleData(total, config = {}) {
const clusters = Array.isArray(config.clusters) && config.clusters.length > 0
? config.clusters
: [{ center: [139.75, 35.7, 50], radius: 0.02, density: 0.5, count: total }];
const entities = [];
let remaining = total;
clusters.forEach((c, idx) => {
const count = Math.min(remaining, Math.max(0, c.count || Math.floor(total / clusters.length)));
remaining -= count;
const [lon0, lat0, alt0] = c.center || [139.75, 35.7, 50];
const radius = c.radius || 0.02; // degrees
const altRange = 100;
for (let i = 0; i < count; i++) {
// Uniform random within circle (approx in degrees)
const r = Math.sqrt(Math.random()) * radius;
const theta = Math.random() * Math.PI * 2;
const lon = lon0 + r * Math.cos(theta);
const lat = lat0 + r * Math.sin(theta);
const alt = alt0 + (Math.random() - 0.5) * altRange;
const entity = new Cesium.Entity({
id: `sample-${idx}-${i}-${Math.random().toString(36).slice(2, 8)}`,
position: Cesium.Cartesian3.fromDegrees(lon, lat, alt)
});
entities.push(entity);
}
});
// If any remainder, add around the first cluster center
while (remaining-- > 0) {
const [lon0, lat0, alt0] = clusters[0].center;
const lon = lon0 + (Math.random() - 0.5) * 0.02;
const lat = lat0 + (Math.random() - 0.5) * 0.02;
const alt = alt0 + (Math.random() - 0.5) * 100;
entities.push(new Cesium.Entity({
id: `sample-extra-${Math.random().toString(36).slice(2, 8)}`,
position: Cesium.Cartesian3.fromDegrees(lon, lat, alt)
}));
}
return entities;
}
/**
* Return a convenience bounding box covering the Tokyo Station area.
* 東京駅周辺の境界情報を返します。
* @returns {Object} 東京駅周辺の境界情報
*/
export function getTokyoStationBounds() {
return {
minLon: 139.7640,
maxLon: 139.7680,
minLat: 35.6790,
maxLat: 35.6820,
minAlt: 0,
maxAlt: 100,
centerLon: 139.7660,
centerLat: 35.6805,
centerAlt: 50
};
}
/**
* Create an axis-aligned bounding box from a centre point and edge length.
* 指定された中心点とサイズから境界を生成します。
* @param {number} centerLon - 中心経度
* @param {number} centerLat - 中心緯度
* @param {number} centerAlt - 中心高度
* @param {number} sizeMeters - 一辺のサイズ（メートル）
* @returns {Object} 境界情報
*/
export function createBoundsFromCenter(centerLon, centerLat, centerAlt, sizeMeters) {
// 度からメートルへの概算変換
const latDelta = sizeMeters / 111000 / 2;
const lonDelta = sizeMeters / (111000 * Math.cos(centerLat * Math.PI / 180)) / 2;
const altDelta = sizeMeters / 2;
return {
minLon: centerLon - lonDelta,
maxLon: centerLon + lonDelta,
minLat: centerLat - latDelta,
maxLat: centerLat + latDelta,
minAlt: centerAlt - altDelta,
maxAlt: centerAlt + altDelta,
centerLon,
centerLat,
centerAlt
};
}
/**
* v0.1.15 Phase 1: Density pattern generators for parameter optimization (ADR-0011)
* パラメータ最適化用の密度パターン生成関数
*/
/**
* Generate a clustered density pattern.
* 高密度クラスターの分布を生成します。
* @param {Object} bounds - Bounding box
* @param {number} count - Total entity count
* @param {number} clusterCount - Number of clusters (default: 3)
* @returns {Array<Cesium.Entity>} Generated entities
*/
function generateClusteredPattern(bounds, count, clusterCount = 3) {
const entities = [];
if (!Number.isFinite(count) || count <= 0) {
return entities;
}
const clusters = Math.max(1, Math.min(Math.floor(clusterCount) || 1, count));
const basePerCluster = Math.floor(count / clusters);
const remainder = count - basePerCluster * clusters;
const centerLon = (bounds.minLon + bounds.maxLon) / 2;
const centerLat = (bounds.minLat + bounds.maxLat) / 2;
const centerAlt = (bounds.minAlt + bounds.maxAlt) / 2;
let globalIndex = 0;
for (let c = 0; c < clusters; c++) {
const clusterSize = basePerCluster + (c < remainder ? 1 : 0);
if (clusterSize <= 0) {
continue;
}
// クラスター中心をランダムに配置
const clusterLon = centerLon + (Math.random() - 0.5) * (bounds.maxLon - bounds.minLon) * 0.6;
const clusterLat = centerLat + (Math.random() - 0.5) * (bounds.maxLat - bounds.minLat) * 0.6;
const clusterAlt = centerAlt + (Math.random() - 0.5) * (bounds.maxAlt - bounds.minAlt) * 0.6;
// 各クラスター内にエンティティを密集配置
const clusterRadius = Math.min(
(bounds.maxLon - bounds.minLon),
(bounds.maxLat - bounds.minLat)
) * 0.1;
for (let i = 0; i < clusterSize; i++) {
const r = Math.sqrt(Math.random()) * clusterRadius;
const theta = Math.random() * Math.PI * 2;
const lon = clusterLon + r * Math.cos(theta);
const lat = clusterLat + r * Math.sin(theta);
const alt = clusterAlt + (Math.random() - 0.5) * (bounds.maxAlt - bounds.minAlt) * 0.2;
entities.push(new Cesium.Entity({
id: `clustered-${c}-${i}-${globalIndex}-${Math.random().toString(36).slice(2, 8)}`,
position: Cesium.Cartesian3.fromDegrees(lon, lat, alt)
}));
globalIndex++;
}
}
return entities;
}
/**
* Generate a scattered density pattern.
* 疎分布のデータセットを生成します。
* @param {Object} bounds - Bounding box
* @param {number} count - Total entity count
* @returns {Array<Cesium.Entity>} Generated entities
*/
function generateScatteredPattern(bounds, count) {
const entities = [];
for (let i = 0; i < count; i++) {
const lon = bounds.minLon + Math.random() * (bounds.maxLon - bounds.minLon);
const lat = bounds.minLat + Math.random() * (bounds.maxLat - bounds.minLat);
const alt = bounds.minAlt + Math.random() * (bounds.maxAlt - bounds.minAlt);
entities.push(new Cesium.Entity({
id: `scattered-${i}-${Math.random().toString(36).slice(2, 8)}`,
position: Cesium.Cartesian3.fromDegrees(lon, lat, alt)
}));
}
return entities;
}
/**
* Generate a gradient-based density pattern.
* グラデーション分布のデータセットを生成します。
* @param {Object} bounds - Bounding box
* @param {number} count - Total entity count
* @returns {Array<Cesium.Entity>} Generated entities
*/
function generateGradientPattern(bounds, count) {
const entities = [];
for (let i = 0; i < count; i++) {
// X軸方向に密度が増加するグラデーション
const x = Math.random();
const densityWeight = x * x; // 二乗で密度を増加
const lon = bounds.minLon + x * (bounds.maxLon - bounds.minLon);
const lat = bounds.minLat + Math.random() * (bounds.maxLat - bounds.minLat);
const alt = bounds.minAlt + Math.random() * (bounds.maxAlt - bounds.minAlt);
// 密度の高いエリアでは複数のエンティティを近接配置
if (densityWeight > 0.7 && Math.random() > 0.5) {
const offset = 0.0001; // 約10m
entities.push(new Cesium.Entity({
id: `gradient-${i}-extra-${Math.random().toString(36).slice(2, 8)}`,
position: Cesium.Cartesian3.fromDegrees(
lon + (Math.random() - 0.5) * offset,
lat + (Math.random() - 0.5) * offset,
alt
)
}));
}
entities.push(new Cesium.Entity({
id: `gradient-${i}-${Math.random().toString(36).slice(2, 8)}`,
position: Cesium.Cartesian3.fromDegrees(lon, lat, alt)
}));
}
return entities;
}
/**
* Generate a mixed density pattern.
* 混在分布のデータセットを生成します。
* @param {Object} bounds - Bounding box
* @param {number} count - Total entity count
* @returns {Array<Cesium.Entity>} Generated entities
*/
function generateMixedPattern(bounds, count) {
const entities = [];
// 30%を高密度クラスター、70%を疎分布として配置
const clusteredCount = Math.floor(count * 0.3);
const scatteredCount = count - clusteredCount;
// 高密度クラスター部分
const clusteredEntities = generateClusteredPattern(bounds, clusteredCount, 2);
entities.push(...clusteredEntities);
// 疎分布部分
const scatteredEntities = generateScatteredPattern(bounds, scatteredCount);
entities.push(...scatteredEntities);
return entities;
}
/**
* Density pattern generators map (ADR-0011 Phase 1)
* パラメータ最適化用密度パターンマップ
*/
export const DENSITY_PATTERNS = {
clustered: generateClusteredPattern,
scattered: generateScatteredPattern,
gradient: generateGradientPattern,
mixed: generateMixedPattern
};
/**
* Generate test dataset with specified pattern
* 指定したパターンでテストデータセットを生成
* @param {string} pattern - Pattern name ('clustered', 'scattered', 'gradient', 'mixed')
* @param {Object} bounds - Bounding box
* @param {number} count - Total entity count
* @returns {Array<Cesium.Entity>} Generated entities
*/
export function generatePatternData(pattern, bounds, count) {
const generator = DENSITY_PATTERNS[pattern];
if (!generator) {
throw new Error(`Unknown pattern: ${pattern}. Available: ${Object.keys(DENSITY_PATTERNS).join(', ')}`);
}
return generator(bounds, count);
}