|
101 | 101 | tempgeo *= tagged_data[i][j]; |
102 | 102 | } |
103 | 103 | tempgeo = Math.pow(tempgeo, 1/tagged_data[i].length); |
| 104 | + tempgeo = 1/tempgeo; |
104 | 105 | geomeans.push(tempgeo); |
105 | 106 | } |
106 | | - geomeans.push(trunk_geomean); |
| 107 | + geomeans.push(1/trunk_geomean); |
107 | 108 | var ticks = [data['baseline']]; |
108 | 109 | for (var i in data['tagged_revs']) { |
109 | 110 | ticks.push(data['tagged_revs'][i]); |
110 | 111 | } |
111 | 112 | ticks.push('PyPy trunk'); |
112 | 113 | var geolabels = new Array(); |
113 | | - for (var i in geomeans) { |
114 | | - geolabels.push(geomeans[i].toFixed(2) + " (" + (1/geomeans[i]).toFixed(1) + "x)"); |
| 114 | + for (var i in geomeans) { |
| 115 | +// geolabels.push(geomeans[i].toFixed(2) + " (" + (1/geomeans[i]).toFixed(1) + "x)"); |
| 116 | + geolabels.push(geomeans[i].toFixed(2) + "x"); |
115 | 117 | } |
116 | 118 | $('#num_of_benchs').html(num_of_benchs) |
117 | 119 |
|
|
131 | 133 | ticks: ticks |
132 | 134 | }, |
133 | 135 | yaxis:{ |
134 | | - ticks: [0.0, 0.25, 0.5, 0.75, 1.0, 1.25], |
| 136 | +// ticks: [0.0, 0.25, 0.5, 0.75, 1.0, 1.25], |
| 137 | + min: 0, |
135 | 138 | tickOptions:{formatString:'%.2f'} |
136 | 139 | } |
137 | 140 | } |
@@ -196,7 +199,7 @@ <h3>How fast is PyPy?</h3> |
196 | 199 | <h3>How has PyPy performance evolved over time?</h3> |
197 | 200 |
|
198 | 201 | <div id="cpythonplot2" style="width:600px;height:400px;margin: 0 auto;"></div> |
199 | | - <p style="font-size:smaller;">Plot 2: Geometric averages of normalized times, out of <span id="num_of_benchs"></span> benchmarks. Smaller is better. "times faster" inside parenthesis</p> |
| 202 | + <p style="font-size:smaller;">Plot 2: Speedup compared to CPython, using the inverse of the geometric average of normalized times, out of <span id="num_of_benchs"></span> benchmarks.</p> |
200 | 203 | </div> |
201 | 204 | </div> |
202 | 205 | {% endblock body %} |
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