106 lines
2.8 KiB
JavaScript
106 lines
2.8 KiB
JavaScript
import DataTileSource from '../src/ol/source/DataTile.js';
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import Map from '../src/ol/Map.js';
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import TileLayer from '../src/ol/layer/WebGLTile.js';
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import View from '../src/ol/View.js';
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import {fromLonLat} from '../src/ol/proj.js';
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// 16-bit COG
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// Which will be served as NumpyTiles.
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const COG =
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'https://storage.googleapis.com/open-cogs/stac-examples/20201211_223832_CS2_analytic.tif';
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function numpyTileLoader(z, x, y) {
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const url = `https://api.cogeo.xyz/cog/tiles/WebMercatorQuad/${z}/${x}/${y}@1x?format=npy&url=${encodeURIComponent(
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COG
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)}`;
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return fetch(url)
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.then((r) => r.arrayBuffer())
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.then((buffer) => NumpyLoader.fromArrayBuffer(buffer))
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.then((numpyData) => {
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// flatten the numpy data
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const dataTile = new Float32Array(256 * 256 * 5);
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const bandSize = 256 * 256;
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for (let x = 0; x < 256; x++) {
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for (let y = 0; y < 256; y++) {
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const px = x + y * 256;
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dataTile[px * 5 + 0] = numpyData.data[y * 256 + x];
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dataTile[px * 5 + 1] = numpyData.data[bandSize + y * 256 + x];
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dataTile[px * 5 + 2] = numpyData.data[bandSize * 2 + y * 256 + x];
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dataTile[px * 5 + 3] = numpyData.data[bandSize * 3 + y * 256 + x];
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dataTile[px * 5 + 4] =
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numpyData.data[bandSize * 4 + y * 256 + x] > 0 ? 1.0 : 0;
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}
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}
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return dataTile;
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});
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}
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const interpolateBand = (bandIdx) => [
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'interpolate',
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['linear'],
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['band', bandIdx],
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['var', 'bMin'],
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0,
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['var', 'bMax'],
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1,
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];
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const initialMin = 3000;
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const initialMax = 18000;
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const numpyLayer = new TileLayer({
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style: {
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color: [
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'array',
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interpolateBand(3),
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interpolateBand(2),
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interpolateBand(1),
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['band', 5],
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],
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variables: {
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'bMin': initialMin,
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'bMax': initialMax,
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},
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},
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source: new DataTileSource({
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loader: numpyTileLoader,
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bandCount: 5,
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}),
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});
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const map = new Map({
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target: 'map',
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layers: [numpyLayer],
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view: new View({
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center: fromLonLat([172.933, 1.3567]),
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zoom: 15,
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}),
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});
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const inputMin = document.getElementById('input-min');
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const inputMax = document.getElementById('input-max');
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const outputMin = document.getElementById('output-min');
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const outputMax = document.getElementById('output-max');
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inputMin.addEventListener('input', (evt) => {
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numpyLayer.updateStyleVariables({
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'bMin': parseFloat(evt.target.value),
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'bMax': parseFloat(inputMax.value),
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});
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outputMin.innerText = evt.target.value;
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});
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inputMax.addEventListener('input', (evt) => {
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numpyLayer.updateStyleVariables({
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'bMin': parseFloat(inputMin.value),
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'bMax': parseFloat(evt.target.value),
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});
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outputMax.innerText = evt.target.value;
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});
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inputMin.value = initialMin;
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inputMax.value = initialMax;
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outputMin.innerText = initialMin;
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outputMax.innerText = initialMax;
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