projects / dygraphs.git / blame
| Commit | Line | Data |
|---|---|---|
| 34bbe78b DV |
1 | <html> |
| 2 | <head> | |
| 3 | <title>Linear Regression</title> | |
| 4 | <!--[if IE]> | |
| 5 | <script type="text/javascript" src="excanvas.js"></script> | |
| 6 | <![endif]--> | |
| 7 | <script type="text/javascript" src="../strftime/strftime-min.js"></script> | |
| 8 | <script type="text/javascript" src="../rgbcolor/rgbcolor.js"></script> | |
| 9 | <script type="text/javascript" src="../dygraph-canvas.js"></script> | |
| 10 | <script type="text/javascript" src="../dygraph.js"></script> | |
| 11 | <style type="text/css"> | |
| 12 | body { max-width: 640 px; } | |
| 13 | </style> | |
| 14 | </head> | |
| 15 | <body> | |
| 16 | <h2>Linear Regression Demo</h2> | |
| 17 | <p>Click the buttons to generate linear regressions over either data | |
| 18 | series. If you zoom in and click the regression button, the regression will | |
| 19 | only be run over visible points. Zoom back out to see what the local | |
| 20 | regression looks like over the full data.</p> | |
| 21 | ||
| 22 | <div id="demodiv" style="width: 480px; height: 320px;"></div> | |
| 23 | ||
| 24 | <script type="text/javascript"> | |
| 25 | var data = []; | |
| 26 | for (var i = 0; i < 120; i++) { | |
| 27 | data.push([i, | |
| 28 | i / 5.0 + 10.0 * Math.sin(i / 3.0), | |
| 29 | 30.0 - i / 5.0 - 10.0 * Math.sin(i / 3.0 + 1.0)]); | |
| 30 | } | |
| 31 | var labels = ['X', 'Y1', 'Y2']; | |
| 32 | var orig_colors = []; | |
| 33 | ||
| 34 | g = new Dygraph( | |
| 35 | document.getElementById("demodiv"), | |
| 36 | data, | |
| 37 | { | |
| 38 | labels: labels, | |
| 39 | drawPoints: true, | |
| 40 | drawCallback: function(g, is_initial) { | |
| 41 | if (!is_initial) return; | |
| 42 | var c = g.getColors(); | |
| 43 | for (var i = 0; i < c.length; i++) orig_colors.push(c[i]); | |
| 44 | } | |
| 45 | } | |
| 46 | ); | |
| 47 | ||
| 48 | // coefficients of regression for each series. | |
| 49 | // if coeffs = [ null, [1, 2], null ] then we draw a regression for series 1 | |
| 50 | // only. The regression line is y = 1 + 2 * x. | |
| 51 | var coeffs = [ null, null, null ]; | |
| 52 | function regression(series) { | |
| 53 | // Only run the regression over visible points. | |
| 54 | var range = g.xAxisRange(); | |
| 55 | ||
| 56 | var sum_xy = 0.0, sum_x = 0.0, sum_y = 0.0, sum_x2 = 0.0, num = 0; | |
| 57 | for (var i = 0; i < data.length; i++) { | |
| 58 | var x = data[i][0]; | |
| 59 | if (x < range[0] || x > range[1]) continue; | |
| 60 | ||
| 61 | var y = data[i][series]; | |
| 62 | if (y == null) continue; | |
| 63 | ||
| 64 | num++; | |
| 65 | sum_x += x; | |
| 66 | sum_y += y; | |
| 67 | sum_xy += x * y; | |
| 68 | sum_x2 += x * x; | |
| 69 | } | |
| 70 | ||
| 71 | var a = (sum_xy - sum_x * sum_y / num) / (sum_x2 - sum_x * sum_x / num); | |
| 72 | var b = (sum_y - a * sum_x) / num; | |
| 73 | ||
| 74 | coeffs[series] = [b, a]; | |
| 75 | if (console) { | |
| 76 | console.log("coeffs(" + series + "): [" + b + ", " + a + "]"); | |
| 77 | } | |
| 78 | ||
| 79 | updateChart(); | |
| 80 | } | |
| 81 | ||
| 82 | function updateChart() { | |
| 83 | // Generate a new data set with the regression lines. | |
| 84 | var new_labels = []; | |
| 85 | var new_colors = []; | |
| 86 | for (var i = 0; i < labels.length; i++) { | |
| 87 | new_labels.push(labels[i]); | |
| 88 | if (i) new_colors.push(orig_colors[i - 1]); | |
| 89 | if (coeffs[i]) { | |
| 90 | // Darken the series by 50% to generate its regression. | |
| 91 | new_labels.push(labels[i] + " Regression"); | |
| 92 | var c = new RGBColor(orig_colors[i - 1]); | |
| 93 | c.r = Math.floor(255 - 0.5 * (255 - c.r)); | |
| 94 | c.g = Math.floor(255 - 0.5 * (255 - c.g)); | |
| 95 | c.b = Math.floor(255 - 0.5 * (255 - c.b)); | |
| 96 | new_colors.push(c.toHex()); | |
| 97 | } | |
| 98 | } | |
| 99 | ||
| 100 | var new_data = []; | |
| 101 | for (var i = 0; i < data.length; i++) { | |
| 102 | new_data.push([]); | |
| 103 | for (var j = 0; j < data[i].length; j++) { | |
| 104 | new_data[i].push(data[i][j]); | |
| 105 | if (coeffs[j]) { | |
| 106 | new_data[i].push(coeffs[j][0] + coeffs[j][1] * data[i][0]); | |
| 107 | } | |
| 108 | } | |
| 109 | } | |
| 110 | ||
| 111 | // TODO(danvk): set colors intelligently. | |
| 112 | ||
| 113 | g.updateOptions({ | |
| 114 | file: new_data, | |
| 115 | labels: new_labels, | |
| 116 | colors: new_colors | |
| 117 | }); | |
| 118 | } | |
| 119 | ||
| 120 | function clearLines() { | |
| 121 | for (var i = 0; i < coeffs.length; i++) coeffs[i] = null; | |
| 122 | updateChart(); | |
| 123 | } | |
| 124 | ||
| 125 | // function drawLines(ctx, area, layout) { | |
| 126 | // if (typeof(g) == 'undefined') return; // won't be set on the initial draw. | |
| 127 | ||
| 128 | // var range = g.xAxisRange(); | |
| 129 | // for (var i = 0; i < coeffs.length; i++) { | |
| 130 | // if (!coeffs[i]) continue; | |
| 131 | // var a = coeffs[i][1]; | |
| 132 | // var b = coeffs[i][0]; | |
| 133 | ||
| 134 | // var x1 = range[0]; | |
| 135 | // var y1 = a * x1 + b; | |
| 136 | // var x2 = range[1]; | |
| 137 | // var y2 = a * x2 + b; | |
| 138 | ||
| 139 | // var p1 = g.toDomCoords(x1, y1); | |
| 140 | // var p2 = g.toDomCoords(x2, y2); | |
| 141 | ||
| 142 | // var color = g.getColors()[i - 1]; | |
| 143 | // ctx.save(); | |
| 144 | // ctx.strokeStyle = color; | |
| 145 | // ctx.lineWidth = 1.0; | |
| 146 | // ctx.beginPath(); | |
| 147 | // ctx.moveTo(p1[0], p1[1]); | |
| 148 | // ctx.lineTo(p2[0], p2[1]); | |
| 149 | // ctx.closePath(); | |
| 150 | // ctx.stroke(); | |
| 151 | // ctx.restore(); | |
| 152 | // } | |
| 153 | // } | |
| 154 | ||
| 155 | </script> | |
| 156 | ||
| 157 | <div style="position: absolute; left: 500px; top: 150px;"> | |
| 158 | <input type=button style="color: green;" value="Regression (Y1)" onClick="regression(1)" /> | |
| 159 | <br/><br/> | |
| 160 | <input type=button style="color: blue;" value="Regression (Y2)" onClick="regression(2)" /> | |
| 161 | <br/><br/> | |
| 162 | <input type=button value="Clear Lines" onClick="clearLines()" /> | |
| 163 | </div> | |
| 164 | </body> | |
| 165 | </html> |