对于栅格数据,为提升网络的传输效率,通过一定的计算公式将栅格数据压缩成一个灰度图,在通过客户端进行解析渲染是常见的一种手段。本文将结合canvas实现此功能。
测试数据来源于ventusky上的温度图,渲染的色标也用了该网站上面的。
const canvas = document.getElementById('canvas'); canvas.width = window.innerWidth canvas.height = window.innerHeight const ctx = canvas.getContext('2d'); const legends = [{"v":50,"c":"rgb(43, 0, 1)"},{"v":40,"c":"rgb(107, 21, 39)"},{"v":30,"c":"rgba(190, 48, 102, 0.92)"},{"v":25,"c":"rgba(229, 109, 83, 0.92)"},{"v":20,"c":"rgba(234, 164, 62, 0.92)"},{"v":15,"c":"rgba(235, 215, 53, 0.92)"},{"v":10,"c":"rgba(190, 228, 61, 0.92)"},{"v":5,"c":"rgba(89, 208, 73, 0.92)"},{"v":0,"c":"rgba(75, 182, 152, 0.92)"},{"v":-5,"c":"rgba(62, 121, 198, 0.92)"},{"v":-10,"c":"rgba(85, 78, 177, 0.92)"},{"v":-15,"c":"rgba(36, 24, 106, 0.92)"},{"v":-20,"c":"rgba(145, 9, 145, 0.92)"},{"v":-30,"c":"rgba(255, 170, 255, 0.92)"},{"v":-40,"c":"rgba(238, 238, 238, 0.92)"}] class Palette { constructor(legends) { this._init(legends) } _init(legends) { // 创建canvas let canvas = document.createElement("canvas"); canvas.width = 10; canvas.height = 256; let ctx = canvas.getContext("2d"); // 创建线性渐变色 let linearGradient = ctx.createLinearGradient(0, 0, 0, canvas.height); const max = legends[0].v, min = legends[legends.length - 1].v - 10 this.colorStops = {} legends.forEach(legend => { const k = (legend.v - min) / (max - min) linearGradient.addColorStop(k, legend.c); }) // 绘制渐变色条 ctx.fillStyle = linearGradient; ctx.fillRect(0, 0, canvas.width, canvas.height); // 读取像素数据 this.imageData = ctx.getImageData(0, 0, 1, canvas.height).data; this.canvas = canvas; } colorPicker(position) { return this.imageData.slice(position * 4, position * 4 + 3); } } const palette = new Palette(legends) const img = new Image() img.src = './tem.jpg' let imgData = null img.onload = function () { // 离屏 const w = img.width, h = img.height const _canvas = document.createElement('canvas'); _canvas.width = w _canvas.height = h const _ctx = _canvas.getContext('2d'); _ctx.drawImage(img, 0, 0) imgData = _ctx.getImageData(0, 0, w, h) ctx.putImageData(imgData, 0, 0) const data = imgData.data let val = [] for (let i = 0; i < data.length; i+=4) { let pos = data[i]; val.push(pos) } val = val.sort((a, b) => a - b) const min = val[0], max = val[val.length - 1] for (let i = 0; i < data.length; i+=4) { let pos = data[i]; pos = Math.floor(((pos - min) / (max - min)) * 256) let color = palette.colorPicker(pos); data[i] = color[0]; data[i + 1] = color[1]; data[i + 2] = color[2]; data[i + 3] = 255; } // 展示img ctx.putImageData(imgData, w + 10, 0) // 绘制图例 const _w = palette.canvas.width, _h = palette.canvas.height / 2 const x = 25, y = canvas.height - 20 - _h ctx.fillStyle = 'white' ctx.shadowBlur = 10 ctx.shadowColor = '#ccc' ctx.shadowOffsetX = 2 ctx.shadowOffsetY = 2 ctx.textAlign = 'left' ctx.fillRect(x - 10, y - 10, _w + 40, _h + 20) ctx.drawImage(palette.canvas, x, y, _w, _h) // 绘制文字 ctx.fillStyle = '#000' ctx.textBaseline = 'top' ctx.fillText(legends[legends.length - 1].v, x + _w + 6, y) ctx.textBaseline = 'bottom' ctx.fillText(legends[0].v, x + _w + 6, y + _h) }
结合到openlayers中:
const legends = [{"v":50,"c":"rgb(43, 0, 1)"},{"v":40,"c":"rgb(107, 21, 39)"},{"v":30,"c":"rgba(190, 48, 102, 0.92)"},{"v":25,"c":"rgba(229, 109, 83, 0.92)"},{"v":20,"c":"rgba(234, 164, 62, 0.92)"},{"v":15,"c":"rgba(235, 215, 53, 0.92)"},{"v":10,"c":"rgba(190, 228, 61, 0.92)"},{"v":5,"c":"rgba(89, 208, 73, 0.92)"},{"v":0,"c":"rgba(75, 182, 152, 0.92)"},{"v":-5,"c":"rgba(62, 121, 198, 0.92)"},{"v":-10,"c":"rgba(85, 78, 177, 0.92)"},{"v":-15,"c":"rgba(36, 24, 106, 0.92)"},{"v":-20,"c":"rgba(145, 9, 145, 0.92)"},{"v":-30,"c":"rgba(255, 170, 255, 0.92)"},{"v":-40,"c":"rgba(238, 238, 238, 0.92)"}] class Palette { constructor(legends) { this._init(legends) } _init(legends) { // 创建canvas let canvas = document.createElement("canvas"); canvas.width = 10; canvas.height = 256; let ctx = canvas.getContext("2d"); // 创建线性渐变色 let linearGradient = ctx.createLinearGradient(0, 0, 0, canvas.height); const max = legends[0].v, min = legends[legends.length - 1].v - 10 this.colorStops = {} legends.forEach(legend => { const k = (legend.v - min) / (max - min) linearGradient.addColorStop(k, legend.c); }) // 绘制渐变色条 ctx.fillStyle = linearGradient; ctx.fillRect(0, 0, canvas.width, canvas.height); // 读取像素数据 this.imageData = ctx.getImageData(0, 0, 1, canvas.height).data; this.canvas = canvas; } colorPicker(position) { return this.imageData.slice(position * 4, position * 4 + 3); } } const palette = new Palette(legends) const img = new Image() img.src = './data/tem.jpg' img.onload = function () { // 离屏 const w = img.width, h = img.height const _canvas = document.createElement('canvas'); _canvas.width = w _canvas.height = h const _ctx = _canvas.getContext('2d'); _ctx.drawImage(img, 0, 0) const imgData = _ctx.getImageData(0, 0, w, h) const data = imgData.data let val = [] for (let i = 0; i < data.length; i+=4) { let pos = data[i]; val.push(pos) } val = val.sort((a, b) => a - b) const min = val[0], max = val[val.length - 1] for (let i = 0; i < data.length; i+=4) { let pos = data[i]; pos = Math.floor(((pos - min) / (max - min)) * 256) let color = palette.colorPicker(pos); data[i] = color[0]; data[i + 1] = color[1]; data[i + 2] = color[2]; data[i + 3] = 150; } // 展示img _ctx.putImageData(imgData, 0, 0) const imgLayer = new ol.layer.Image({ source: new ol.source.ImageStatic({ url: _canvas.toDataURL(), imageExtent: [-180, -90, 180, 90] }) }) map.addLayer(imgLayer); }