1/* 2 * Copyright (C) 2007 Apple Inc. All rights reserved. 3 * 4 * Redistribution and use in source and binary forms, with or without 5 * modification, are permitted provided that the following conditions 6 * are met: 7 * 1. Redistributions of source code must retain the above copyright 8 * notice, this list of conditions and the following disclaimer. 9 * 2. Redistributions in binary form must reproduce the above copyright 10 * notice, this list of conditions and the following disclaimer in the 11 * documentation and/or other materials provided with the distribution. 12 * 13 * THIS SOFTWARE IS PROVIDED BY APPLE COMPUTER, INC. ``AS IS'' AND ANY 14 * EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE 15 * IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR 16 * PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL APPLE COMPUTER, INC. OR 17 * CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, 18 * EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, 19 * PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR 20 * PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY 21 * OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT 22 * (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE 23 * OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. 24 */ 25 26function sunspiderCompareResults(output1, output2) 27{ 28 var count1 = output1.length; 29 var count2 = output2.length; 30 31 var itemTotals1 = {}; 32 itemTotals1.length = count1; 33 34 var total1 = 0; 35 var categoryTotals1 = {}; 36 var testTotalsByCategory1 = {}; 37 38 var mean1 = 0; 39 var categoryMeans1 = {}; 40 var testMeansByCategory1 = {}; 41 42 var stdDev1 = 0; 43 var categoryStdDevs1 = {}; 44 var testStdDevsByCategory1 = {}; 45 46 var stdErr1 = 0; 47 var categoryStdErrs1 = {}; 48 var testStdErrsByCategory1 = {}; 49 50 var itemTotals2 = {}; 51 itemTotals2.length = count2; 52 53 var total2 = 0; 54 var categoryTotals2 = {}; 55 var testTotalsByCategory2 = {}; 56 57 var mean2 = 0; 58 var categoryMeans2 = {}; 59 var testMeansByCategory2 = {}; 60 61 var stdDev2 = 0; 62 var categoryStdDevs2 = {}; 63 var testStdDevsByCategory2 = {}; 64 65 var stdErr2 = 0; 66 var categoryStdErrs2 = {}; 67 var testStdErrsByCategory2 = {}; 68 69 function initialize() 70 { 71 itemTotals1 = {total: []}; 72 73 for (var i = 0; i < categories.length; i++) { 74 var category = categories[i]; 75 itemTotals1[category] = []; 76 categoryTotals1[category] = 0; 77 testTotalsByCategory1[category] = {}; 78 categoryMeans1[category] = 0; 79 testMeansByCategory1[category] = {}; 80 categoryStdDevs1[category] = 0; 81 testStdDevsByCategory1[category] = {}; 82 categoryStdErrs1[category] = 0; 83 testStdErrsByCategory1[category] = {}; 84 } 85 86 for (var i = 0; i < tests.length; i++) { 87 var test = tests[i]; 88 itemTotals1[test] = []; 89 var category = test.replace(/-.*/, ""); 90 testTotalsByCategory1[category][test] = 0; 91 testMeansByCategory1[category][test] = 0; 92 testStdDevsByCategory1[category][test] = 0; 93 testStdErrsByCategory1[category][test] = 0; 94 } 95 96 for (var i = 0; i < count1; i++) { 97 itemTotals1["total"][i] = 0; 98 for (var category in categoryTotals1) { 99 itemTotals1[category][i] = 0; 100 for (var test in testTotalsByCategory1[category]) { 101 itemTotals1[test][i] = 0; 102 } 103 } 104 } 105 106 itemTotals2 = {total: []}; 107 108 for (var i = 0; i < categories.length; i++) { 109 var category = categories[i]; 110 itemTotals2[category] = []; 111 categoryTotals2[category] = 0; 112 testTotalsByCategory2[category] = {}; 113 categoryMeans2[category] = 0; 114 testMeansByCategory2[category] = {}; 115 categoryStdDevs2[category] = 0; 116 testStdDevsByCategory2[category] = {}; 117 categoryStdErrs2[category] = 0; 118 testStdErrsByCategory2[category] = {}; 119 } 120 121 for (var i = 0; i < tests.length; i++) { 122 var test = tests[i]; 123 itemTotals2[test] = []; 124 var category = test.replace(/-.*/, ""); 125 testTotalsByCategory2[category][test] = 0; 126 testMeansByCategory2[category][test] = 0; 127 testStdDevsByCategory2[category][test] = 0; 128 testStdErrsByCategory2[category][test] = 0; 129 } 130 131 for (var i = 0; i < count2; i++) { 132 itemTotals2["total"][i] = 0; 133 for (var category in categoryTotals2) { 134 itemTotals2[category][i] = 0; 135 for (var test in testTotalsByCategory2[category]) { 136 itemTotals2[test][i] = 0; 137 } 138 } 139 } 140 141 } 142 143 function computeItemTotals(output, itemTotals) 144 { 145 for (var i = 0; i < output.length; i++) { 146 var result = output[i]; 147 for (var test in result) { 148 var time = result[test]; 149 var category = test.replace(/-.*/, ""); 150 itemTotals["total"][i] += time; 151 itemTotals[category][i] += time; 152 itemTotals[test][i] += time; 153 } 154 } 155 } 156 157 function computeTotals(output, categoryTotals, testTotalsByCategory) 158 { 159 var total = 0; 160 161 for (var i = 0; i < output.length; i++) { 162 var result = output[i]; 163 for (var test in result) { 164 var time = result[test]; 165 var category = test.replace(/-.*/, ""); 166 total += time; 167 categoryTotals[category] += time; 168 testTotalsByCategory[category][test] += time; 169 } 170 } 171 172 return total; 173 } 174 175 function computeMeans(count, total, categoryTotals, categoryMeans, testTotalsByCategory, testMeansByCategory) 176 { 177 var mean = total / count; 178 for (var category in categoryTotals) { 179 categoryMeans[category] = categoryTotals[category] / count; 180 for (var test in testTotalsByCategory[category]) { 181 testMeansByCategory[category][test] = testTotalsByCategory[category][test] / count; 182 } 183 } 184 return mean; 185 } 186 187 function standardDeviation(mean, items) 188 { 189 var deltaSquaredSum = 0; 190 for (var i = 0; i < items.length; i++) { 191 var delta = items[i] - mean; 192 deltaSquaredSum += delta * delta; 193 } 194 variance = deltaSquaredSum / (items.length - 1); 195 return Math.sqrt(variance); 196 } 197 198 function computeStdDevs(mean, itemTotals, categoryStdDevs, categoryMeans, testStdDevsByCategory, testMeansByCategory) 199 { 200 var stdDev = standardDeviation(mean, itemTotals["total"]); 201 for (var category in categoryStdDevs) { 202 categoryStdDevs[category] = standardDeviation(categoryMeans[category], itemTotals[category]); 203 } 204 for (var category in categoryStdDevs) { 205 for (var test in testStdDevsByCategory[category]) { 206 testStdDevsByCategory[category][test] = standardDeviation(testMeansByCategory[category][test], itemTotals[test]); 207 } 208 } 209 return stdDev; 210 } 211 212 function computeStdErrors(count, stdDev, categoryStdErrs, categoryStdDevs, testStdErrsByCategory, testStdDevsByCategory) 213 { 214 var sqrtCount = Math.sqrt(count); 215 216 var stdErr = stdDev / sqrtCount; 217 for (var category in categoryStdErrs) { 218 categoryStdErrs[category] = categoryStdDevs[category] / sqrtCount; 219 } 220 for (var category in categoryStdDevs) { 221 for (var test in testStdErrsByCategory[category]) { 222 testStdErrsByCategory[category][test] = testStdDevsByCategory[category][test] / sqrtCount; 223 } 224 } 225 226 return stdErr; 227 } 228 229 var tDistribution = [NaN, NaN, 12.71, 4.30, 3.18, 2.78, 2.57, 2.45, 2.36, 2.31, 2.26, 2.23, 2.20, 2.18, 2.16, 2.14, 2.13, 2.12, 2.11, 2.10, 2.09, 2.09, 2.08, 2.07, 2.07, 2.06, 2.06, 2.06, 2.05, 2.05, 2.05, 2.04, 2.04, 2.04, 2.03, 2.03, 2.03, 2.03, 2.03, 2.02, 2.02, 2.02, 2.02, 2.02, 2.02, 2.02, 2.01, 2.01, 2.01, 2.01, 2.01, 2.01, 2.01, 2.01, 2.01, 2.00, 2.00, 2.00, 2.00, 2.00, 2.00, 2.00, 2.00, 2.00, 2.00, 2.00, 2.00, 2.00, 2.00, 2.00, 1.99, 1.99, 1.99, 1.99, 1.99, 1.99, 1.99, 1.99, 1.99, 1.99, 1.99, 1.99, 1.99, 1.99, 1.99, 1.99, 1.99, 1.99, 1.99, 1.99, 1.99, 1.99, 1.99, 1.99, 1.99, 1.99, 1.99, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.96]; 230 var tMax = tDistribution.length; 231 var tLimit = 1.96; 232 233 function tDist(n) 234 { 235 if (n > tMax) 236 return tLimit; 237 return tDistribution[n]; 238 } 239 240 241 function formatMean(meanWidth, mean, stdErr, count) 242 { 243 var meanString = mean.toFixed(1).toString(); 244 while (meanString.length < meanWidth) { 245 meanString = " " + meanString; 246 } 247 248 var error = "+/- " + ((tDist(count) * stdErr / mean) * 100).toFixed(1) + "% "; 249 250 return meanString + "ms " + error; 251 } 252 253 function computeLabelWidth() 254 { 255 var width = "Total".length; 256 for (var category in categoryMeans1) { 257 if (category.length + 2 > width) 258 width = category.length + 2; 259 } 260 for (var i = 0; i < tests.length; i++) { 261 var shortName = tests[i].replace(/^[^-]*-/, ""); 262 if (shortName.length + 4 > width) 263 width = shortName.length + 4; 264 } 265 266 return width; 267 } 268 269 function computeMeanWidth(mean, categoryMeans, testMeansByCategory) 270 { 271 var width = mean.toFixed(1).toString().length; 272 for (var category in categoryMeans) { 273 var candidate = categoryMeans[category].toFixed(1).toString().length; 274 if (candidate > width) 275 width = candidate; 276 for (var test in testMeansByCategory[category]) { 277 var candidate = testMeansByCategory[category][test].toFixed(1).toString().length; 278 if (candidate > width) 279 width = candidate; 280 } 281 } 282 283 return width; 284 } 285 286 function pad(str, n) 287 { 288 while (str.length < n) { 289 str += " "; 290 } 291 return str; 292 } 293 294 function resultLine(labelWidth, indent, label, meanWidth1, mean1, stdErr1, meanWidth2, mean2, stdErr2) 295 { 296 result = pad("", indent); 297 result += label + ": "; 298 result = pad(result, labelWidth + 2); 299 300 var t = (mean1 - mean2) / (Math.sqrt((stdErr1 * stdErr1) + (stdErr1 * stdErr2))); 301 var df = count1 + count2 - 2; 302 303 var statisticallySignificant = (Math.abs(t) > tDist(df+1)); 304 var diff = mean2 - mean1; 305 var percentage = 100 * diff / mean1; 306 var isFaster = diff < 0; 307 var probablySame = (percentage < 0.1) && !statisticallySignificant; 308 var ratio = isFaster ? (mean1 / mean2) : (mean2 / mean1); 309 var fixedRatio = (ratio < 1.2) ? ratio.toFixed(3).toString() : ((ratio < 10) ? ratio.toFixed(2).toString() : ratio.toFixed(1).toString()); 310 var formattedRatio = isFaster ? fixedRatio + "x as fast" : "*" + fixedRatio + "x as slow*"; 311 312 var diffSummary; 313 var diffDetail; 314 315 if (probablySame) { 316 diffSummary = "-"; 317 diffDetail = ""; 318 } else if (!statisticallySignificant) { 319 diffSummary = "??"; 320 diffDetail = " not conclusive: might be " + formattedRatio; 321 } else { 322 diffSummary = formattedRatio; 323 diffDetail = " significant"; 324 } 325 326 return result + pad(diffSummary, 18) + formatMean(meanWidth1, mean1, stdErr1, count1) + " " + formatMean(meanWidth2, mean2, stdErr2, count2) + diffDetail; 327 } 328 329 function printOutput() 330 { 331 var labelWidth = computeLabelWidth(); 332 var meanWidth1 = computeMeanWidth(mean1, categoryMeans1, testMeansByCategory1); 333 var meanWidth2 = computeMeanWidth(mean2, categoryMeans2, testMeansByCategory2); 334 335 print("\n"); 336 var header = "TEST"; 337 while (header.length < labelWidth) 338 header += " "; 339 header += " COMPARISON FROM TO DETAILS"; 340 print(header); 341 print(""); 342 print("============================================================================="); 343 print(""); 344 print(resultLine(labelWidth, 0, "** TOTAL **", meanWidth1, mean1, stdErr1, meanWidth2, mean2, stdErr2)); 345 print(""); 346 print("============================================================================="); 347 348 for (var category in categoryMeans1) { 349 print(""); 350 print(resultLine(labelWidth, 2, category, 351 meanWidth1, categoryMeans1[category], categoryStdErrs1[category], 352 meanWidth2, categoryMeans2[category], categoryStdErrs2[category])); 353 for (var test in testMeansByCategory1[category]) { 354 var shortName = test.replace(/^[^-]*-/, ""); 355 print(resultLine(labelWidth, 4, shortName, 356 meanWidth1, testMeansByCategory1[category][test], testStdErrsByCategory1[category][test], 357 meanWidth2, testMeansByCategory2[category][test], testStdErrsByCategory2[category][test])); 358 } 359 } 360 } 361 362 initialize(); 363 364 computeItemTotals(output1, itemTotals1); 365 computeItemTotals(output2, itemTotals2); 366 367 total1 = computeTotals(output1, categoryTotals1, testTotalsByCategory1); 368 total2 = computeTotals(output2, categoryTotals2, testTotalsByCategory2); 369 370 mean1 = computeMeans(count1, total1, categoryTotals1, categoryMeans1, testTotalsByCategory1, testMeansByCategory1); 371 mean2 = computeMeans(count2, total2, categoryTotals2, categoryMeans2, testTotalsByCategory2, testMeansByCategory2); 372 373 stdDev1 = computeStdDevs(mean1, itemTotals1, categoryStdDevs1, categoryMeans1, testStdDevsByCategory1, testMeansByCategory1); 374 stdDev2 = computeStdDevs(mean2, itemTotals2, categoryStdDevs2, categoryMeans2, testStdDevsByCategory2, testMeansByCategory2); 375 376 stdErr1 = computeStdErrors(count1, stdDev1, categoryStdErrs1, categoryStdDevs1, testStdErrsByCategory1, testStdDevsByCategory1); 377 stdErr2 = computeStdErrors(count2, stdDev2, categoryStdErrs2, categoryStdDevs2, testStdErrsByCategory2, testStdDevsByCategory2); 378 379 printOutput(); 380} 381