CN-1563 feat: 轨迹地图基础逻辑

src/utils/api.js

@@ -351,6 +351,11 @@ export const api = {
       entityNew: apiVersion + '/entity/explorer/overview/new', // entity首页new数据概览
       entityTotal: apiVersion + '/entity/explorer/overview/total' // entity首页total数据概览
     }
+  },
+  location: {
+    map: apiVersion + '/locationIntelligence/map',
+    density: apiVersion + '/locationIntelligence/population/density',
+    trend: apiVersion + '/locationIntelligence/active/subscribers'
   }
 }
 

src/utils/hexbinDataConverter.js

@@ -0,0 +1,51 @@
+import turf from 'turf'
+import { propEach, featureReduce } from '@turf/meta'
+import simpleStats from 'simple-statistics'
+import { extent } from 'd3-array'
+
+// cellSize: 六角网格每一边的大小（公里）
+export default function hexbinDataConverter (data, cellSize = 0.5) {
+  // 纽约的粗略地理边界框
+  const bbox = [-74.24939, 40.50394, -73.701195, 40.90995]
+  // const bbox = [74, 18, 136, 42]
+  // const bbox = [74, 18, 136, 54]
+
+  // 为给定的 bbox 和cellSize创建 hexbin（六边形） 几何形状
+  const hexGrid = turf.hexGrid(bbox, cellSize)
+
+  // 对我们的六边形几何体和数据点执行“空间连接”
+  const collected = turf.collect(hexGrid, data, 'data', 'data')
+
+  // 为每个六边形设置一个唯一id
+  collected.features.forEach((feature, i) => {
+    feature.id = i
+  })
+  // 过滤掉没有连接数据的多边形
+  collected.features = collected.features.filter(d => d.properties.data.length)
+
+  // 计算每个六边形里点的总数 count
+  propEach(collected, props => {
+    props.count = props.data.reduce((acc, cur) => acc += 1, 0)
+  })
+
+  // 将 count 拎出来
+  const reduced = featureReduce(collected, (acc, cur) => {
+    acc.push(cur.properties.count)
+    return acc
+  }, [])
+
+  // 用 ckmeans 算法将值按大小分成3（设计图中的颜色数量）层
+  const levels = simpleStats.ckmeans(reduced, 3)
+
+  // 将六边形层级和该层的范围添加到数据中
+  propEach(collected, props => {
+    levels.forEach((level, index) => {
+      if (level.indexOf(props.count) > -1) {
+        props.level = index
+        props.levelRange = extent(level)
+      }
+    })
+  })
+
+  return collected
+}