Build and parse examples from examples_src/

examples/image-filter.js

@@ -1,146 +0,0 @@
-goog.require('ol.Map');
-goog.require('ol.View');
-goog.require('ol.layer.Tile');
-goog.require('ol.proj');
-goog.require('ol.source.BingMaps');
-
-var key = 'Ak-dzM4wZjSqTlzveKz5u0d4IQ4bRzVI309GxmkgSVr1ewS6iPSrOvOKhA-CJlm3';
-
-var imagery = new ol.layer.Tile({
-  source: new ol.source.BingMaps({key: key, imagerySet: 'Aerial'})
-});
-
-var map = new ol.Map({
-  layers: [imagery],
-  target: 'map',
-  view: new ol.View({
-    center: ol.proj.fromLonLat([-120, 50]),
-    zoom: 6
-  })
-});
-
-var kernels = {
-  none: [
-    0, 0, 0,
-    0, 1, 0,
-    0, 0, 0
-  ],
-  sharpen: [
-    0, -1, 0,
-    -1, 5, -1,
-    0, -1, 0
-  ],
-  sharpenless: [
-    0, -1, 0,
-    -1, 10, -1,
-    0, -1, 0
-  ],
-  blur: [
-    1, 1, 1,
-    1, 1, 1,
-    1, 1, 1
-  ],
-  shadow: [
-    1, 2, 1,
-    0, 1, 0,
-    -1, -2, -1
-  ],
-  emboss: [
-    -2, 1, 0,
-    -1, 1, 1,
-    0, 1, 2
-  ],
-  edge: [
-    0, 1, 0,
-    1, -4, 1,
-    0, 1, 0
-  ]
-};
-
-function normalize(kernel) {
-  var len = kernel.length;
-  var normal = new Array(len);
-  var i, sum = 0;
-  for (i = 0; i < len; ++i) {
-    sum += kernel[i];
-  }
-  if (sum <= 0) {
-    normal.normalized = false;
-    sum = 1;
-  } else {
-    normal.normalized = true;
-  }
-  for (i = 0; i < len; ++i) {
-    normal[i] = kernel[i] / sum;
-  }
-  return normal;
-}
-
-var select = document.getElementById('kernel');
-var selectedKernel = normalize(kernels[select.value]);
-
-
-/**
- * Update the kernel and re-render on change.
- */
-select.onchange = function() {
-  selectedKernel = normalize(kernels[select.value]);
-  map.render();
-};
-
-
-/**
- * Apply a filter on "postcompose" events.
- * @param {ol.render.Event} event Render event.
- */
-imagery.on('postcompose', function(event) {
-  convolve(event.context, selectedKernel);
-});
-
-
-/**
- * Apply a convolution kernel to canvas.  This works for any size kernel, but
- * performance starts degrading above 3 x 3.
- * @param {CanvasRenderingContext2D} context Canvas 2d context.
- * @param {Array.<number>} kernel Kernel.
- */
-function convolve(context, kernel) {
-  var canvas = context.canvas;
-  var width = canvas.width;
-  var height = canvas.height;
-
-  var size = Math.sqrt(kernel.length);
-  var half = Math.floor(size / 2);
-
-  var inputData = context.getImageData(0, 0, width, height).data;
-
-  var output = context.createImageData(width, height);
-  var outputData = output.data;
-
-  for (var pixelY = 0; pixelY < height; ++pixelY) {
-    var pixelsAbove = pixelY * width;
-    for (var pixelX = 0; pixelX < width; ++pixelX) {
-      var r = 0, g = 0, b = 0, a = 0;
-      for (var kernelY = 0; kernelY < size; ++kernelY) {
-        for (var kernelX = 0; kernelX < size; ++kernelX) {
-          var weight = kernel[kernelY * size + kernelX];
-          var neighborY = Math.min(
-              height - 1, Math.max(0, pixelY + kernelY - half));
-          var neighborX = Math.min(
-              width - 1, Math.max(0, pixelX + kernelX - half));
-          var inputIndex = (neighborY * width + neighborX) * 4;
-          r += inputData[inputIndex] * weight;
-          g += inputData[inputIndex + 1] * weight;
-          b += inputData[inputIndex + 2] * weight;
-          a += inputData[inputIndex + 3] * weight;
-        }
-      }
-      var outputIndex = (pixelsAbove + pixelX) * 4;
-      outputData[outputIndex] = r;
-      outputData[outputIndex + 1] = g;
-      outputData[outputIndex + 2] = b;
-      outputData[outputIndex + 3] = kernel.normalized ? a : 255;
-    }
-  }
-  context.putImageData(output, 0, 0);
-}