WebKit Bugzilla
Attachment 347900 Details for
Bug 188425
: Show t-test results based on individual measurements to analysis task page
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[patch]
Patch
bug-188425-20180822221815.patch (text/plain), 65.69 KB, created by
dewei_zhu
on 2018-08-22 22:18:16 PDT
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Description:
Patch
Filename:
MIME Type:
Creator:
dewei_zhu
Created:
2018-08-22 22:18:16 PDT
Size:
65.69 KB
patch
obsolete
>Subversion Revision: 235215 >diff --git a/Websites/perf.webkit.org/ChangeLog b/Websites/perf.webkit.org/ChangeLog >index c127a5587f90be73002cf528b297fd7075e03025..58d3fe67cf8a5c76371f50a09e2d77d95b6c5631 100644 >--- a/Websites/perf.webkit.org/ChangeLog >+++ b/Websites/perf.webkit.org/ChangeLog >@@ -1,3 +1,43 @@ >+2018-08-22 Dewei Zhu <dewei_zhu@apple.com> >+ >+ Show t-test results based on individual measurements to analysis task page. >+ https://bugs.webkit.org/show_bug.cgi?id=188425 >+ >+ Reviewed by NOBODY (OOPS!). >+ >+ Added comparison for individual iterations in analysis task page. >+ Added comparison for individual iterations for notification on A/B tests completion. >+ Refactored t-distribution inverse lookup to any degree of freedom with 5 significant figures. >+ >+ * public/shared/statistics.js: Refactored t-distribution inverse lookup function and adapted this >+ change to all invocations. >+ (Statistics.new.this.supportedConfidenceIntervalProbabilities): >+ (Statistics.new.this.supportedOneSideTTestProbabilities): >+ (Statistics.new.this.confidenceIntervalDelta): >+ (Statistics.new.sampleMeanAndVarianceFromMultipleSamples): >+ (Statistics.new.this.probabilityRangeForWelchsT): >+ (Statistics.new.this.probabilityRangeForWelchsTFromTwoSampleSets): >+ (Statistics.new.this._determinetwoSidedProbabilityBoundaryForWelchsT): >+ (Statistics.new.this.computeWelchsT): >+ (Statistics.new.this._combineWelchsT): >+ (Statistics.new.this.minimumTForOneSidedProbability): Function that does t-distribution inverse lookup. >+ * public/v3/components/analysis-results-viewer.js: Adapted TestGroup.compareTestResults change. >+ (AnalysisResultsViewer.TestGroupStackingBlock.prototype._measurementsForCommitSet): >+ (AnalysisResultsViewer.TestGroupStackingBlock.prototype._computeTestGroupStatus): >+ (AnalysisResultsViewer.TestGroupStackingBlock.prototype._valuesForCommitSet): Deleted. >+ * public/v3/components/test-group-results-viewer.js: Show both comparisions for both individual and mean. >+ (TestGroupResultsViewer.prototype._renderResultsTable): >+ (TestGroupResultsViewer.prototype._buildRowForMetric.): >+ (TestGroupResultsViewer.prototype._buildValueMap): >+ * public/v3/models/test-group.js: >+ (TestGroup.compareTestResults): Added comparison for individual iterations. >+ * tools/js/test-group-result-page.js: >+ (TestGroupResultPage.prototype._constructTableForMetric): >+ (TestGroupResultPage.prototype.get styleTemplate): >+ (TestGroupResultPage): >+ (TestGroupResultPage.prototype._URLForAnalysisTask): Renamed to '_resultsForTestGroup' >+ * unit-tests/statistics-tests.js: Updated and added unit tests. >+ > 2018-07-13 Dewei Zhu <dewei_zhu@apple.com> > > CustomConfigurationTestGroupForm should dispatch different arguments based on whether analysis task is created. >diff --git a/Websites/perf.webkit.org/public/shared/statistics.js b/Websites/perf.webkit.org/public/shared/statistics.js >index 056ba94f8df77af6d544c76c165607d1d11daed3..a2d97a5fade2ddbe30c0acd8717b6784837a6219 100644 >--- a/Websites/perf.webkit.org/public/shared/statistics.js >+++ b/Websites/perf.webkit.org/public/shared/statistics.js >@@ -33,10 +33,10 @@ var Statistics = new (function () { > } > > this.supportedConfidenceIntervalProbabilities = function () { >- var supportedProbabilities = []; >- for (var probability in tDistributionByOneSidedProbability) >+ const supportedProbabilities = []; >+ for (const probability in tDistributionByOneSidedProbability) > supportedProbabilities.push(oneSidedToTwoSidedProbability(probability).toFixed(2)); >- return supportedProbabilities >+ return supportedProbabilities; > } > > this.supportedOneSideTTestProbabilities = function () { >@@ -52,13 +52,8 @@ var Statistics = new (function () { > } > if (numberOfSamples - 2 < 0) > return NaN; >- var deltas = tDistributionByOneSidedProbability[oneSidedProbability]; >- var degreesOfFreedom = numberOfSamples - 1; >- if (degreesOfFreedom > deltas.length) >- throw 'We only support up to ' + deltas.length + ' degrees of freedom'; >- > // d = c * S/sqrt(numberOfSamples) where c ~ t-distribution(degreesOfFreedom) and S is the sample standard deviation. >- return deltas[degreesOfFreedom - 1] * this.sampleStandardDeviation(numberOfSamples, sum, squareSum) / Math.sqrt(numberOfSamples); >+ return this.minimumTForOneSidedProbability(oneSidedProbability, numberOfSamples - 1) * this.sampleStandardDeviation(numberOfSamples, sum, squareSum) / Math.sqrt(numberOfSamples); > } > > this.confidenceInterval = function (values, probability) { >@@ -73,41 +68,72 @@ var Statistics = new (function () { > return this.computeWelchsT(values1, 0, values1.length, values2, 0, values2.length, probability).significantlyDifferent; > } > >+ function sampleMeanAndVarianceFromMultipleSamples(samples) { >+ let sum = 0; >+ let squareSum = 0; >+ let size = 0; >+ for (const sample of samples) { >+ sum += sample.sum; >+ squareSum += sample.squareSum; >+ size += sample.iterationCount; >+ } >+ const mean = sum / size; >+ const unbiasedSampleVariance = (squareSum - sum * sum / size) / (size - 1); >+ return { >+ mean, >+ variance: unbiasedSampleVariance, >+ size, >+ degreesOfFreedom: size - 1, >+ } >+ } >+ > this.probabilityRangeForWelchsT = function (values1, values2) { > var result = this.computeWelchsT(values1, 0, values1.length, values2, 0, values2.length); >- if (isNaN(result.t) || isNaN(result.degreesOfFreedom)) >+ return this._determinetwoSidedProbabilityBoundaryForWelchsT(result.t, result.degreesOfFreedom); >+ } >+ >+ this.probabilityRangeForWelchsTFromTwoSampleSets = function (sampleSet1, sampleSet2) { >+ const stat1 = sampleMeanAndVarianceFromMultipleSamples(sampleSet1); >+ const stat2 = sampleMeanAndVarianceFromMultipleSamples(sampleSet2); >+ const combinedT = this._combineWelchsT(stat1, stat2); >+ return this._determinetwoSidedProbabilityBoundaryForWelchsT(combinedT.t, combinedT.degreesOfFreedom) >+ } >+ >+ this._determinetwoSidedProbabilityBoundaryForWelchsT = function(t, degreesOfFreedom) { >+ if (isNaN(t) || isNaN(degreesOfFreedom)) > return {t: NaN, degreesOfFreedom:NaN, range: [null, null]}; > >- var lowerBound = null; >- var upperBound = null; >- for (var probability in tDistributionByOneSidedProbability) { >- var twoSidedProbability = oneSidedToTwoSidedProbability(probability); >- if (result.t > tDistributionByOneSidedProbability[probability][Math.round(result.degreesOfFreedom - 1)]) >+ let lowerBound = null; >+ let upperBound = null; >+ for (const probability in tDistributionByOneSidedProbability) { >+ const twoSidedProbability = oneSidedToTwoSidedProbability(probability); >+ if (t > this.minimumTForOneSidedProbability(probability, Math.round(degreesOfFreedom))) > lowerBound = twoSidedProbability; > else if (lowerBound) { > upperBound = twoSidedProbability; > break; > } > } >- return {t: result.t, degreesOfFreedom: result.degreesOfFreedom, range: [lowerBound, upperBound]}; >- } >+ return {t, degreesOfFreedom, range: [lowerBound, upperBound]}; >+ }; > > this.computeWelchsT = function (values1, startIndex1, length1, values2, startIndex2, length2, probability) { >- var stat1 = sampleMeanAndVarianceForValues(values1, startIndex1, length1); >- var stat2 = sampleMeanAndVarianceForValues(values2, startIndex2, length2); >- var sumOfSampleVarianceOverSampleSize = stat1.variance / stat1.size + stat2.variance / stat2.size; >- var t = Math.abs((stat1.mean - stat2.mean) / Math.sqrt(sumOfSampleVarianceOverSampleSize)); >+ const stat1 = sampleMeanAndVarianceForValues(values1, startIndex1, length1); >+ const stat2 = sampleMeanAndVarianceForValues(values2, startIndex2, length2); >+ const {t, degreesOfFreedom} = this._combineWelchsT(stat1, stat2); >+ const minT = this.minimumTForOneSidedProbability(twoSidedToOneSidedProbability(probability || 0.8), Math.round(degreesOfFreedom)); >+ return {t, degreesOfFreedom, significantlyDifferent: t > minT}; >+ }; >+ >+ this._combineWelchsT = function(stat1, stat2) { >+ const sumOfSampleVarianceOverSampleSize = stat1.variance / stat1.size + stat2.variance / stat2.size; >+ const t = Math.abs((stat1.mean - stat2.mean) / Math.sqrt(sumOfSampleVarianceOverSampleSize)); > > // http://en.wikipedia.org/wiki/WelchâSatterthwaite_equation >- var degreesOfFreedom = sumOfSampleVarianceOverSampleSize * sumOfSampleVarianceOverSampleSize >+ const degreesOfFreedom = sumOfSampleVarianceOverSampleSize * sumOfSampleVarianceOverSampleSize > / (stat1.variance * stat1.variance / stat1.size / stat1.size / stat1.degreesOfFreedom > + stat2.variance * stat2.variance / stat2.size / stat2.size / stat2.degreesOfFreedom); >- var minT = tDistributionByOneSidedProbability[twoSidedToOneSidedProbability(probability || 0.8)][Math.round(degreesOfFreedom - 1)]; >- return { >- t: t, >- degreesOfFreedom: degreesOfFreedom, >- significantlyDifferent: t > minT, >- }; >+ return {t, degreesOfFreedom}; > } > > this.findRangesForChangeDetectionsWithWelchsTTest = function (values, segmentations, oneSidedPossibility=0.99) { >@@ -258,56 +284,251 @@ var Statistics = new (function () { > recursivelySplitIntoTwoSegmentsAtMaxTIfSignificantlyDifferent(values, startIndex + argTMax, length - argTMax, minLength, segments); > } > >- var tDistributionByOneSidedProbability = { >- 0.9: [ >- 3.077684, 1.885618, 1.637744, 1.533206, 1.475884, 1.439756, 1.414924, 1.396815, 1.383029, 1.372184, >- 1.363430, 1.356217, 1.350171, 1.345030, 1.340606, 1.336757, 1.333379, 1.330391, 1.327728, 1.325341, >- 1.323188, 1.321237, 1.319460, 1.317836, 1.316345, 1.314972, 1.313703, 1.312527, 1.311434, 1.310415, >- 1.309464, 1.308573, 1.307737, 1.306952, 1.306212, 1.305514, 1.304854, 1.304230, 1.303639, 1.303077, >- 1.302543, 1.302035, 1.301552, 1.301090, 1.300649, 1.300228, 1.299825, 1.299439, 1.299069, 1.298714, >- >- 1.298373, 1.298045, 1.297730, 1.297426, 1.297134, 1.296853, 1.296581, 1.296319, 1.296066, 1.295821, >- 1.295585, 1.295356, 1.295134, 1.294920, 1.294712, 1.294511, 1.294315, 1.294126, 1.293942, 1.293763, >- 1.293589, 1.293421, 1.293256, 1.293097, 1.292941, 1.292790, 1.292643, 1.292500, 1.292360, 1.292224, >- 1.292091, 1.291961, 1.291835, 1.291711, 1.291591, 1.291473, 1.291358, 1.291246, 1.291136, 1.291029, >- 1.290924, 1.290821, 1.290721, 1.290623, 1.290527, 1.290432, 1.290340, 1.290250, 1.290161, 1.290075], >- 0.95: [ >- 6.313752, 2.919986, 2.353363, 2.131847, 2.015048, 1.943180, 1.894579, 1.859548, 1.833113, 1.812461, >- 1.795885, 1.782288, 1.770933, 1.761310, 1.753050, 1.745884, 1.739607, 1.734064, 1.729133, 1.724718, >- 1.720743, 1.717144, 1.713872, 1.710882, 1.708141, 1.705618, 1.703288, 1.701131, 1.699127, 1.697261, >- 1.695519, 1.693889, 1.692360, 1.690924, 1.689572, 1.688298, 1.687094, 1.685954, 1.684875, 1.683851, >- 1.682878, 1.681952, 1.681071, 1.680230, 1.679427, 1.678660, 1.677927, 1.677224, 1.676551, 1.675905, >- >- 1.675285, 1.674689, 1.674116, 1.673565, 1.673034, 1.672522, 1.672029, 1.671553, 1.671093, 1.670649, >- 1.670219, 1.669804, 1.669402, 1.669013, 1.668636, 1.668271, 1.667916, 1.667572, 1.667239, 1.666914, >- 1.666600, 1.666294, 1.665996, 1.665707, 1.665425, 1.665151, 1.664885, 1.664625, 1.664371, 1.664125, >- 1.663884, 1.663649, 1.663420, 1.663197, 1.662978, 1.662765, 1.662557, 1.662354, 1.662155, 1.661961, >- 1.661771, 1.661585, 1.661404, 1.661226, 1.661052, 1.660881, 1.660715, 1.660551, 1.660391, 1.660234], >- 0.975: [ >- 12.706205, 4.302653, 3.182446, 2.776445, 2.570582, 2.446912, 2.364624, 2.306004, 2.262157, 2.228139, >- 2.200985, 2.178813, 2.160369, 2.144787, 2.131450, 2.119905, 2.109816, 2.100922, 2.093024, 2.085963, >- 2.079614, 2.073873, 2.068658, 2.063899, 2.059539, 2.055529, 2.051831, 2.048407, 2.045230, 2.042272, >- 2.039513, 2.036933, 2.034515, 2.032245, 2.030108, 2.028094, 2.026192, 2.024394, 2.022691, 2.021075, >- 2.019541, 2.018082, 2.016692, 2.015368, 2.014103, 2.012896, 2.011741, 2.010635, 2.009575, 2.008559, >- >- 2.007584, 2.006647, 2.005746, 2.004879, 2.004045, 2.003241, 2.002465, 2.001717, 2.000995, 2.000298, >- 1.999624, 1.998972, 1.998341, 1.997730, 1.997138, 1.996564, 1.996008, 1.995469, 1.994945, 1.994437, >- 1.993943, 1.993464, 1.992997, 1.992543, 1.992102, 1.991673, 1.991254, 1.990847, 1.990450, 1.990063, >- 1.989686, 1.989319, 1.988960, 1.988610, 1.988268, 1.987934, 1.987608, 1.987290, 1.986979, 1.986675, >- 1.986377, 1.986086, 1.985802, 1.985523, 1.985251, 1.984984, 1.984723, 1.984467, 1.984217, 1.983972], >- 0.99: [ >- 31.820516, 6.964557, 4.540703, 3.746947, 3.364930, 3.142668, 2.997952, 2.896459, 2.821438, 2.763769, >- 2.718079, 2.680998, 2.650309, 2.624494, 2.602480, 2.583487, 2.566934, 2.552380, 2.539483, 2.527977, >- 2.517648, 2.508325, 2.499867, 2.492159, 2.485107, 2.478630, 2.472660, 2.467140, 2.462021, 2.457262, >- 2.452824, 2.448678, 2.444794, 2.441150, 2.437723, 2.434494, 2.431447, 2.428568, 2.425841, 2.423257, >- 2.420803, 2.418470, 2.416250, 2.414134, 2.412116, 2.410188, 2.408345, 2.406581, 2.404892, 2.403272, >- >- 2.401718, 2.400225, 2.398790, 2.397410, 2.396081, 2.394801, 2.393568, 2.392377, 2.391229, 2.390119, >- 2.389047, 2.388011, 2.387008, 2.386037, 2.385097, 2.384186, 2.383302, 2.382446, 2.381615, 2.380807, >- 2.380024, 2.379262, 2.378522, 2.377802, 2.377102, 2.376420, 2.375757, 2.375111, 2.374482, 2.373868, >- 2.373270, 2.372687, 2.372119, 2.371564, 2.371022, 2.370493, 2.369977, 2.369472, 2.368979, 2.368497, >- 2.368026, 2.367566, 2.367115, 2.366674, 2.366243, 2.365821, 2.365407, 2.365002, 2.364606, 2.364217] >+ this.minimumTForOneSidedProbability = function(probability, degreesOfFreedom) { >+ if (degreesOfFreedom < 1 || isNaN(degreesOfFreedom)) >+ return NaN; >+ const tDistributionTableForProbability = tDistributionByOneSidedProbability[probability]; >+ if (degreesOfFreedom <= tDistributionTableForProbability.linearLookupTable.length) >+ return tDistributionTableForProbability.linearLookupTable[degreesOfFreedom - 1]; >+ const binarySearchTable = tDistributionTableForProbability.binarySearchTable; >+ let low = 0; >+ let high = binarySearchTable.length; >+ while (low < high) { >+ let mid = low + parseInt((high - low) / 2); >+ const entry = binarySearchTable[mid]; >+ if (degreesOfFreedom <= entry.end) >+ high = mid; >+ else >+ low = mid + 1; >+ } >+ >+ return binarySearchTable[low].value; >+ } >+ >+ const tDistributionByOneSidedProbability = { >+ 0.9: { >+ linearLookupTable: [ >+ 3.0777, 1.8856, 1.6377, 1.5332, 1.4759, 1.4398, 1.4149, 1.3968, 1.383, 1.3722, >+ 1.3634, 1.3562, 1.3502, 1.345, 1.3406, 1.3368, 1.3334, 1.3304, 1.3277, 1.3253, >+ 1.3232, 1.3212, 1.3195, 1.3178, 1.3163, 1.315, 1.3137, 1.3125, 1.3114, 1.3104, >+ 1.3095, 1.3086, 1.3077, 1.307, 1.3062, 1.3055, 1.3049, 1.3042, 1.3036, 1.3031, >+ 1.3025, 1.302, 1.3016, 1.3011, 1.3006, 1.3002, 1.2998, 1.2994, 1.2991, 1.2987, >+ 1.2984, 1.298, 1.2977, 1.2974, 1.2971, 1.2969, 1.2966, 1.2963, 1.2961, 1.2958, >+ 1.2956, 1.2954, 1.2951, 1.2949, 1.2947, 1.2945, 1.2943, 1.2941, 1.2939, 1.2938, >+ 1.2936, 1.2934, 1.2933, 1.2931, 1.2929, 1.2928, 1.2926, 1.2925, 1.2924, 1.2922, >+ 1.2921, 1.292, 1.2918, 1.2917, 1.2916, 1.2915, 1.2914, 1.2912, 1.2911, 1.291, >+ 1.2909, 1.2908, 1.2907, 1.2906, 1.2905, 1.2904, 1.2903, 1.2903, 1.2902, 1.2901 >+ ], >+ binarySearchTable: [ >+ {end: 101, value: 1.2900}, {end: 102, value: 1.2899}, {end: 103, value: 1.2898}, {end: 105, value: 1.2897}, >+ {end: 106, value: 1.2896}, {end: 107, value: 1.2895}, {end: 109, value: 1.2894}, {end: 110, value: 1.2893}, >+ {end: 112, value: 1.2892}, {end: 113, value: 1.2891}, {end: 115, value: 1.2890}, {end: 116, value: 1.2889}, >+ {end: 118, value: 1.2888}, {end: 119, value: 1.2887}, {end: 121, value: 1.2886}, {end: 123, value: 1.2885}, >+ {end: 125, value: 1.2884}, {end: 127, value: 1.2883}, {end: 128, value: 1.2882}, {end: 130, value: 1.2881}, >+ {end: 132, value: 1.2880}, {end: 135, value: 1.2879}, {end: 137, value: 1.2878}, {end: 139, value: 1.2877}, >+ {end: 141, value: 1.2876}, {end: 144, value: 1.2875}, {end: 146, value: 1.2874}, {end: 149, value: 1.2873}, >+ {end: 151, value: 1.2872}, {end: 154, value: 1.2871}, {end: 157, value: 1.2870}, {end: 160, value: 1.2869}, >+ {end: 163, value: 1.2868}, {end: 166, value: 1.2867}, {end: 170, value: 1.2866}, {end: 173, value: 1.2865}, >+ {end: 177, value: 1.2864}, {end: 180, value: 1.2863}, {end: 184, value: 1.2862}, {end: 188, value: 1.2861}, >+ {end: 193, value: 1.2860}, {end: 197, value: 1.2859}, {end: 202, value: 1.2858}, {end: 207, value: 1.2857}, >+ {end: 212, value: 1.2856}, {end: 217, value: 1.2855}, {end: 223, value: 1.2854}, {end: 229, value: 1.2853}, >+ {end: 235, value: 1.2852}, {end: 242, value: 1.2851}, {end: 249, value: 1.2850}, {end: 257, value: 1.2849}, >+ {end: 265, value: 1.2848}, {end: 273, value: 1.2847}, {end: 283, value: 1.2846}, {end: 292, value: 1.2845}, >+ {end: 303, value: 1.2844}, {end: 314, value: 1.2843}, {end: 326, value: 1.2842}, {end: 339, value: 1.2841}, >+ {end: 353, value: 1.2840}, {end: 369, value: 1.2839}, {end: 385, value: 1.2838}, {end: 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value: 2.3322}, {end: 655, value: 2.3321}, {end: 667, value: 2.3320}, {end: 679, value: 2.3319}, >+ {end: 691, value: 2.3318}, {end: 704, value: 2.3317}, {end: 718, value: 2.3316}, {end: 732, value: 2.3315}, >+ {end: 747, value: 2.3314}, {end: 762, value: 2.3313}, {end: 778, value: 2.3312}, {end: 794, value: 2.3311}, >+ {end: 811, value: 2.3310}, {end: 829, value: 2.3309}, {end: 848, value: 2.3308}, {end: 868, value: 2.3307}, >+ {end: 888, value: 2.3306}, {end: 910, value: 2.3305}, {end: 933, value: 2.3304}, {end: 957, value: 2.3303}, >+ {end: 982, value: 2.3302}, {end: 1008, value: 2.3301}, {end: 1036, value: 2.3300}, {end: 1066, value: 2.3299}, >+ {end: 1097, value: 2.3298}, {end: 1130, value: 2.3297}, {end: 1166, value: 2.3296}, {end: 1203, value: 2.3295}, >+ {end: 1243, value: 2.3294}, {end: 1286, value: 2.3293}, {end: 1332, value: 2.3292}, {end: 1381, value: 2.3291}, >+ {end: 1434, value: 2.3290}, {end: 1491, value: 2.3289}, {end: 1553, value: 2.3288}, {end: 1621, value: 2.3287}, >+ {end: 1694, value: 2.3286}, {end: 1775, value: 2.3285}, {end: 1864, value: 2.3284}, {end: 1962, value: 2.3283}, >+ {end: 2070, value: 2.3282}, {end: 2192, value: 2.3281}, {end: 2329, value: 2.3280}, {end: 2484, value: 2.3279}, >+ {end: 2661, value: 2.3278}, {end: 2865, value: 2.3277}, {end: 3103, value: 2.3276}, {end: 3385, value: 2.3275}, >+ {end: 3722, value: 2.3274}, {end: 4135, value: 2.3273}, {end: 4650, value: 2.3272}, {end: 5312, value: 2.3271}, >+ {end: 6194, value: 2.3270}, {end: 7428, value: 2.3269}, {end: 9274, value: 2.3268}, {end: 12344, value: 2.3267}, >+ {end: 18450, value: 2.3266}, {end: 36515, value: 2.3265}, {end: 1754068, value: 2.3264}, {end: Infinity, value: 2.3263} >+ ] >+ }, > }; >+ > function oneSidedToTwoSidedProbability(probability) { return 2 * probability - 1; } > function twoSidedToOneSidedProbability(probability) { return (1 - (1 - probability) / 2); } > >diff --git a/Websites/perf.webkit.org/public/v3/components/analysis-results-viewer.js b/Websites/perf.webkit.org/public/v3/components/analysis-results-viewer.js >index ecd6e2f4506d240e71583a16b6de6cc97409f1e1..0bc8c286d8c63c8e1c121f30bdc77238812d9a43 100644 >--- a/Websites/perf.webkit.org/public/v3/components/analysis-results-viewer.js >+++ b/Websites/perf.webkit.org/public/v3/components/analysis-results-viewer.js >@@ -506,11 +506,11 @@ AnalysisResultsViewer.TestGroupStackingBlock = class { > startRowIndex() { return this._commitSetIndexRowIndexMap[0].rowIndex; } > endRowIndex() { return this._commitSetIndexRowIndexMap[this._commitSetIndexRowIndexMap.length - 1].rowIndex; } > >- _valuesForCommitSet(testGroup, commitSet) >+ _measurementsForCommitSet(testGroup, commitSet) > { > return testGroup.requestsForCommitSet(commitSet).map((request) => { > return this._analysisResultsView.resultForRequest(request); >- }).filter((result) => !!result).map((result) => result.value); >+ }).filter((result) => !!result); > } > > _computeTestGroupStatus() >@@ -518,9 +518,9 @@ AnalysisResultsViewer.TestGroupStackingBlock = class { > if (!this.isComplete()) > return {label: null, title: null, status: null}; > console.assert(this._commitSetIndexRowIndexMap.length <= 2); // FIXME: Support having more root sets. >- const startValues = this._valuesForCommitSet(this._testGroup, this._commitSetIndexRowIndexMap[0].commitSet); >- const endValues = this._valuesForCommitSet(this._testGroup, this._commitSetIndexRowIndexMap[1].commitSet); >+ const startValues = this._measurementsForCommitSet(this._testGroup, this._commitSetIndexRowIndexMap[0].commitSet); >+ const endValues = this._measurementsForCommitSet(this._testGroup, this._commitSetIndexRowIndexMap[1].commitSet); > const result = this._testGroup.compareTestResults(this._analysisResultsView.metric(), startValues, endValues); >- return {label: result.label, title: result.fullLabel, status: result.status}; >+ return {label: result.label, title: result.fullLabelForMean, status: result.status}; > } > } >diff --git a/Websites/perf.webkit.org/public/v3/components/test-group-results-viewer.js b/Websites/perf.webkit.org/public/v3/components/test-group-results-viewer.js >index 4b2feacbdb01e32cbb001cdad360b50b1b524f96..4dea785df47d63cb97372a575fdccca3bf2ad0af 100644 >--- a/Websites/perf.webkit.org/public/v3/components/test-group-results-viewer.js >+++ b/Websites/perf.webkit.org/public/v3/components/test-group-results-viewer.js >@@ -57,7 +57,8 @@ class TestGroupResultsViewer extends ComponentBase { > element('th', {class: 'metric-direction'}, ''), > element('th', {colspan: 2}, 'Results'), > element('th', 'Averages'), >- element('th', 'Comparison'), >+ element('th', 'Comparison by mean'), >+ element('th', 'Comparison by individual iterations') > ]), > ]), > tests.map((test) => this._buildRowsForTest(testGroup, expandedTests, test, [], maxDepth, 0))]); >@@ -112,7 +113,7 @@ class TestGroupResultsViewer extends ComponentBase { > const entry = valueMap.get(commitSet); > const previousEntry = valueMap.get(previousCommitSet); > >- const comparison = entry && previousEntry ? testGroup.compareTestResults(metric, previousEntry.filteredValues, entry.filteredValues) : null; >+ const comparison = entry && previousEntry ? testGroup.compareTestResults(metric, previousEntry.filteredMeasurements, entry.filteredMeasurements) : null; > const valueLabels = entry.measurements.map((measurement) => measurement ? formatValue(measurement.value, measurement.interval) : '-'); > > const barCell = element('td', {class: 'plot-bar'}, >@@ -120,15 +121,17 @@ class TestGroupResultsViewer extends ComponentBase { > barCell.expandedHeight = +valueLabels.length + 'rem'; > barCells.push(barCell); > >- const significance = comparison && comparison.isStatisticallySignificant ? 'significant' : 'negligible'; >+ const significanceForMean = comparison && comparison.isStatisticallySignificantForMean ? 'significant' : 'negligible'; >+ const significanceForIndividual = comparison && comparison.isStatisticallySignificantForIndividual ? 'significant' : 'negligible'; > const changeType = comparison ? comparison.changeType : null; > return [ > element('th', testGroup.labelForCommitSet(commitSet)), > barCell, > element('td', formatValue(entry.mean, entry.interval)), >- element('td', {class: `comparison ${changeType} ${significance}`}, comparison ? comparison.fullLabel : ''), >+ element('td', {class: `comparison ${changeType} ${significanceForMean}`}, comparison ? comparison.fullLabelForMean : ''), >+ element('td', {class: `comparison ${changeType} ${significanceForIndividual}`}, comparison ? comparison.fullLabelForIndividual : ''), > ]; >- } >+ }; > > this._barGraphCellMap.set(metric, {barGroup, barCells}); > >@@ -166,10 +169,11 @@ class TestGroupResultsViewer extends ComponentBase { > for (const commitSet of commitSets) { > const requests = testGroup.requestsForCommitSet(commitSet); > const measurements = requests.map((request) => resultsView.resultForRequest(request)); >- const filteredValues = measurements.filter((result) => !!result).map((measurement) => measurement.value); >+ const filteredMeasurements = measurements.filter((result) => !!result); >+ const filteredValues = filteredMeasurements.map((measurement) => measurement.value); > const allValues = measurements.map((result) => result != null ? result.value : NaN); > const interval = Statistics.confidenceInterval(filteredValues); >- map.set(commitSet, {requests, measurements, filteredValues, allValues, mean: Statistics.mean(filteredValues), interval}); >+ map.set(commitSet, {requests, measurements, filteredMeasurements, allValues, mean: Statistics.mean(filteredValues), interval}); > } > return map; > } >diff --git a/Websites/perf.webkit.org/public/v3/models/test-group.js b/Websites/perf.webkit.org/public/v3/models/test-group.js >index fa41dda2066da9f80b7bc8e04057bf46fbcd3377..86c7965de072a2dab39cac9163d459a172a2a877 100644 >--- a/Websites/perf.webkit.org/public/v3/models/test-group.js >+++ b/Websites/perf.webkit.org/public/v3/models/test-group.js >@@ -134,25 +134,31 @@ class TestGroup extends LabeledObject { > return this._buildRequests.some(function (request) { return request.isPending(); }); > } > >- compareTestResults(metric, beforeValues, afterValues) >+ compareTestResults(metric, beforeMeasurements, afterMeasurements) > { > console.assert(metric); >+ const beforeValues = beforeMeasurements.map((measurment) => measurment.value); >+ const afterValues = afterMeasurements.map((measurement) => measurement.value); > const beforeMean = Statistics.sum(beforeValues) / beforeValues.length; > const afterMean = Statistics.sum(afterValues) / afterValues.length; > >- var result = {changeType: null, status: 'failed', label: 'Failed', fullLabel: 'Failed', isStatisticallySignificant: false}; >+ const result = {changeType: null, status: 'failed', label: 'Failed', fullLabelForMean: 'Failed', >+ isStatisticallySignificantForMean: false, fullLabelForIndividual: 'Failed', isStatisticallySignificantForIndividual: false, >+ probabilityRangeForMean: [null, null], probabilityRangeForIndividual: [null, null]}; > >- var hasCompleted = this.hasFinished(); >+ const hasCompleted = this.hasFinished(); > if (!hasCompleted) { > if (this.hasStarted()) { > result.status = 'running'; > result.label = 'Running'; >- result.fullLabel = 'Running'; >+ result.fullLabelForMean = 'Running'; >+ result.fullLabelForIndividual = 'Running'; > } else { > console.assert(result.changeType === null); > result.status = 'pending'; > result.label = 'Pending'; >- result.fullLabel = 'Pending'; >+ result.fullLabelForMean = 'Pending'; >+ result.fullLabelForIndividual = 'Pending'; > } > } > >@@ -160,13 +166,23 @@ class TestGroup extends LabeledObject { > const summary = metric.labelForDifference(beforeMean, afterMean, 'better', 'worse'); > result.changeType = summary.changeType; > result.label = summary.changeLabel; >- var isSignificant = Statistics.testWelchsT(beforeValues, afterValues); >- var significanceLabel = isSignificant ? 'significant' : 'insignificant'; >+ >+ const probabilityRangeForMean = Statistics.probabilityRangeForWelchsT(beforeValues, afterValues); >+ const isSignificantForMean = !!probabilityRangeForMean.range[0]; >+ const significanceLabelForMean = isSignificantForMean? `significant with ${(probabilityRangeForMean.range[0] * 100).toFixed()}% probability` : 'insignificant'; >+ result.fullLabelForMean = `${result.label} (${significanceLabelForMean})`; >+ result.isStatisticallySignificantForMean = isSignificantForMean; >+ result.probabilityRangeForMean = probabilityRangeForMean.range; >+ >+ const probabilityRangeForIndividual = Statistics.probabilityRangeForWelchsTFromTwoSampleSets(beforeMeasurements, afterMeasurements); >+ const isSignificantForIndividual = !!probabilityRangeForIndividual.range[0]; >+ const significanceLabelForIndividual = isSignificantForIndividual ? `significant with ${(probabilityRangeForIndividual.range[0] * 100).toFixed()}% probability` : 'insignificant'; >+ result.fullLabelForIndividual = `${result.label} (${significanceLabelForIndividual})`; >+ result.isStatisticallySignificantForIndividual = isSignificantForIndividual; >+ result.probabilityRangeForIndividual = probabilityRangeForIndividual.range; > > if (hasCompleted) >- result.status = isSignificant ? result.changeType : 'unchanged'; >- result.fullLabel = `${result.label} (statistically ${significanceLabel})`; >- result.isStatisticallySignificant = isSignificant; >+ result.status = isSignificantForMean ? result.changeType : 'unchanged'; > } > > return result; >diff --git a/Websites/perf.webkit.org/tools/js/test-group-result-page.js b/Websites/perf.webkit.org/tools/js/test-group-result-page.js >index 285a3e2594aa8ca5b713d9d050a2ea82563c357c..9af21f14ea8d86a08c863102e74df93e6fd52ac0 100644 >--- a/Websites/perf.webkit.org/tools/js/test-group-result-page.js >+++ b/Websites/perf.webkit.org/tools/js/test-group-result-page.js >@@ -23,7 +23,7 @@ class TestGroupResultPage extends MarkupPage { > return global.RemoteAPI.url(`/v3/#/analysis/task/${analysisTask.id()}`); > } > >- _URLForAnalysisTask(testGroup, analysisResultsView) >+ _resultsForTestGroup(testGroup, analysisResultsView) > { > const resultsByCommitSet = new Map; > let maxValue = -Infinity; >@@ -73,9 +73,24 @@ class TestGroupResultPage extends MarkupPage { > }; > > const analysisResultsView = analysisResults.viewForMetric(metric); >- const {resultsByCommitSet, widthForValue} = this._URLForAnalysisTask(testGroup, analysisResultsView); >+ const {resultsByCommitSet, widthForValue} = this._resultsForTestGroup(testGroup, analysisResultsView); > > const tableBodies = []; >+ >+ const beforeResults = resultsByCommitSet.get(requestedCommitSets[0]).filter((result) => !!result); >+ const afterResults = resultsByCommitSet.get(requestedCommitSets[1]).filter((result) => !!result); >+ const comparison = testGroup.compareTestResults(metric, beforeResults, afterResults); >+ const changeStyleClassForMean = `${comparison.isStatisticallySignificantForMean ? comparison.changeType : 'insignificant'}-result`; >+ const changeStyleClassForIndividual = `${comparison.isStatisticallySignificantForIndividual ? comparison.changeType : 'insignificant'}-result`; >+ const caption = this.createElement('caption', `${testGroup.test().name()} - ${metric.aggregatorLabel()}`); >+ >+ tableBodies.push(this.createElement('tbody', {class: 'comparision-table-body'}, [ >+ this.createElement('tr', [this.createElement('td', 'Comparision by Mean'), >+ this.createElement('td', this.createElement('em', {class: changeStyleClassForMean}, comparison.fullLabelForMean))]), >+ this.createElement('tr', [this.createElement('td', 'Comparision by Individual'), >+ this.createElement('td', this.createElement('em', {class: changeStyleClassForIndividual}, comparison.fullLabelForIndividual))]) >+ ])); >+ > for (const commitSet of requestedCommitSets) { > let firstRow = true; > const tableRows = []; >@@ -93,13 +108,6 @@ class TestGroupResultPage extends MarkupPage { > tableBodies.push(this.createElement('tbody', tableRows)); > } > >- const beforeValues = resultsByCommitSet.get(requestedCommitSets[0]).filter((result) => !!result).map((result) => result.value); >- const afterValues = resultsByCommitSet.get(requestedCommitSets[1]).filter((result) => !!result).map((result) => result.value); >- const comparison = testGroup.compareTestResults(metric, beforeValues, afterValues); >- const changeStyleClass = `${comparison.isStatisticallySignificant ? comparison.changeType : 'insignificant'}-result`; >- const caption = this.createElement('caption', [`${testGroup.test().name()} - ${metric.aggregatorLabel()}: `, >- this.createElement('em', {class: changeStyleClass}, comparison.fullLabel)]); >- > return this.createElement('table', {class: 'result-table'}, [caption, tableBodies]); > } > >@@ -144,6 +152,7 @@ class TestGroupResultPage extends MarkupPage { > 'em': { > 'font-weight': 'bold', > 'font-style': 'normal', >+ 'padding-right': '2rem', > }, > 'caption': { > 'font-size': '1.3rem', >@@ -168,6 +177,9 @@ class TestGroupResultPage extends MarkupPage { > 'text-align': 'center', > 'border-collapse': 'collapse', > }, >+ '.comparision-table-body': { >+ 'text-align': 'left', >+ }, > '.result-cell': { > 'min-width': '20rem', > 'position': 'relative', >diff --git a/Websites/perf.webkit.org/unit-tests/statistics-tests.js b/Websites/perf.webkit.org/unit-tests/statistics-tests.js >index d91042212a1bf19a1db7d16b5ec7a301ab63bddd..2be7e2f2253bdc56ea67f38213d13f1349925f3b 100644 >--- a/Websites/perf.webkit.org/unit-tests/statistics-tests.js >+++ b/Websites/perf.webkit.org/unit-tests/statistics-tests.js >@@ -105,25 +105,25 @@ describe('Statistics', function () { > assert.almostEqual(delta(values, 0.95), 3.015, 3); > > // Following values are computed using Excel Online's STDEV and CONFIDENCE.T >- assert.almostEqual(delta([1, 2, 3, 4], 0.8), 1.057159); >- assert.almostEqual(delta([1, 2, 3, 4], 0.9), 1.519090); >- assert.almostEqual(delta([1, 2, 3, 4], 0.95), 2.054260); >+ assert.almostEqual(delta([1, 2, 3, 4], 0.8), 1.057159, 4); >+ assert.almostEqual(delta([1, 2, 3, 4], 0.9), 1.519090, 4); >+ assert.almostEqual(delta([1, 2, 3, 4], 0.95), 2.054260, 4); > >- assert.almostEqual(delta([0.3, 0.06, 0.5], 0.8), 0.2398353); >- assert.almostEqual(delta([0.3, 0.06, 0.5], 0.9), 0.3713985); >- assert.almostEqual(delta([0.3, 0.06, 0.5], 0.95), 0.5472625); >+ assert.almostEqual(delta([0.3, 0.06, 0.5], 0.8), 0.2398353, 4); >+ assert.almostEqual(delta([0.3, 0.06, 0.5], 0.9), 0.3713985, 4); >+ assert.almostEqual(delta([0.3, 0.06, 0.5], 0.95), 0.5472625, 4); > >- assert.almostEqual(delta([-0.3, 0.06, 0.5], 0.8), 0.4361900); >- assert.almostEqual(delta([-0.3, 0.06, 0.5], 0.9), 0.6754647); >- assert.almostEqual(delta([-0.3, 0.06, 0.5], 0.95), 0.9953098); >+ assert.almostEqual(delta([-0.3, 0.06, 0.5], 0.8), 0.4361900, 4); >+ assert.almostEqual(delta([-0.3, 0.06, 0.5], 0.9), 0.6754647, 4); >+ assert.almostEqual(delta([-0.3, 0.06, 0.5], 0.95), 0.9953098, 4); > >- assert.almostEqual(delta([123, 107, 109, 104, 111], 0.8), 5.001167); >- assert.almostEqual(delta([123, 107, 109, 104, 111], 0.9), 6.953874); >- assert.almostEqual(delta([123, 107, 109, 104, 111], 0.95), 9.056490); >+ assert.almostEqual(delta([123, 107, 109, 104, 111], 0.8), 5.001167, 4); >+ assert.almostEqual(delta([123, 107, 109, 104, 111], 0.9), 6.953874, 4); >+ assert.almostEqual(delta([123, 107, 109, 104, 111], 0.95), 9.056490, 4); > >- assert.almostEqual(delta([6785, 7812, 6904, 7503, 6943, 7207, 6812], 0.8), 212.6155); >- assert.almostEqual(delta([6785, 7812, 6904, 7503, 6943, 7207, 6812], 0.9), 286.9585); >- assert.almostEqual(delta([6785, 7812, 6904, 7503, 6943, 7207, 6812], 0.95), 361.3469); >+ assert.almostEqual(delta([6785, 7812, 6904, 7503, 6943, 7207, 6812], 0.8), 212.6155, 4); >+ assert.almostEqual(delta([6785, 7812, 6904, 7503, 6943, 7207, 6812], 0.9), 286.9585, 4); >+ assert.almostEqual(delta([6785, 7812, 6904, 7503, 6943, 7207, 6812], 0.95), 361.3469, 4); > > }); > }); >@@ -236,6 +236,94 @@ describe('Statistics', function () { > }); > }); > >+ describe('minimumTForOneSidedProbability', () => { >+ it('should not infinite loop when lookup t-value for any degrees of freedom', () => { >+ for(const probability of [0.9, 0.95, 0.975, 0.99]) { >+ for (let degreesOfFreedom = 1; degreesOfFreedom < 100000; degreesOfFreedom += 1) >+ Statistics.minimumTForOneSidedProbability(probability, degreesOfFreedom); >+ } >+ }) >+ }); >+ >+ describe('probabilityRangeForWelchsTFromTwoSampleSets', () => { >+ function splitSample(sample) { >+ const mid = sample.length / 2; >+ return splitSampleByIndex(sample, mid); >+ } >+ >+ function splitSampleByIndex(sample, index) { >+ const firstHalf = sample.slice(0, index); >+ const secondHalf = sample.slice(index, sample.length); >+ return [firstHalf, secondHalf].map((values) => ({sum: Statistics.sum(values), squareSum: Statistics.squareSum(values), iterationCount: values.length})); >+ } >+ >+ it('should find the t-value of values using Welch\'s t-test', () => { >+ assert.almostEqual(Statistics.probabilityRangeForWelchsTFromTwoSampleSets(splitSample(example1.A1), splitSample(example1.A2)).t, example1.expectedT, 2); >+ assert.almostEqual(Statistics.probabilityRangeForWelchsTFromTwoSampleSets(splitSample(example2.A1), splitSample(example2.A2)).t, example2.expectedT, 2); >+ assert.almostEqual(Statistics.probabilityRangeForWelchsTFromTwoSampleSets(splitSample(example3.A1), splitSample(example3.A2)).t, example3.expectedT, 2); >+ >+ assert.almostEqual(Statistics.probabilityRangeForWelchsTFromTwoSampleSets(splitSampleByIndex(example1.A1, 1), splitSampleByIndex(example1.A2, 1)).t, example1.expectedT, 2); >+ assert.almostEqual(Statistics.probabilityRangeForWelchsTFromTwoSampleSets(splitSampleByIndex(example2.A1, 1), splitSampleByIndex(example2.A2, 1)).t, example2.expectedT, 2); >+ assert.almostEqual(Statistics.probabilityRangeForWelchsTFromTwoSampleSets(splitSampleByIndex(example3.A1, 1), splitSampleByIndex(example3.A2, 1)).t, example3.expectedT, 2); >+ >+ assert.almostEqual(Statistics.probabilityRangeForWelchsTFromTwoSampleSets(splitSampleByIndex(example1.A1, 0), splitSampleByIndex(example1.A2, 0)).t, example1.expectedT, 2); >+ assert.almostEqual(Statistics.probabilityRangeForWelchsTFromTwoSampleSets(splitSampleByIndex(example2.A1, 0), splitSampleByIndex(example2.A2, 0)).t, example2.expectedT, 2); >+ assert.almostEqual(Statistics.probabilityRangeForWelchsTFromTwoSampleSets(splitSampleByIndex(example3.A1, 0), splitSampleByIndex(example3.A2, 0)).t, example3.expectedT, 2); >+ }); >+ >+ it('should find the degreees of freedom using WelchâSatterthwaite equation when split evenly', () => { >+ assert.almostEqual(Statistics.probabilityRangeForWelchsTFromTwoSampleSets(splitSample(example1.A1), splitSample(example1.A2)).degreesOfFreedom, >+ example1.expectedDegreesOfFreedom, 2); >+ assert.almostEqual(Statistics.probabilityRangeForWelchsTFromTwoSampleSets(splitSample(example2.A1), splitSample(example2.A2)).degreesOfFreedom, >+ example2.expectedDegreesOfFreedom, 2); >+ assert.almostEqual(Statistics.probabilityRangeForWelchsTFromTwoSampleSets(splitSample(example3.A1), splitSample(example3.A2)).degreesOfFreedom, >+ example3.expectedDegreesOfFreedom, 2); >+ >+ assert.almostEqual(Statistics.probabilityRangeForWelchsTFromTwoSampleSets(splitSampleByIndex(example1.A1, 1), splitSampleByIndex(example1.A2, 1)).degreesOfFreedom, >+ example1.expectedDegreesOfFreedom, 2); >+ assert.almostEqual(Statistics.probabilityRangeForWelchsTFromTwoSampleSets(splitSampleByIndex(example2.A1, 1), splitSampleByIndex(example2.A2, 1)).degreesOfFreedom, >+ example2.expectedDegreesOfFreedom, 2); >+ assert.almostEqual(Statistics.probabilityRangeForWelchsTFromTwoSampleSets(splitSampleByIndex(example3.A1, 1), splitSampleByIndex(example3.A2, 1)).degreesOfFreedom, >+ example3.expectedDegreesOfFreedom, 2); >+ >+ assert.almostEqual(Statistics.probabilityRangeForWelchsTFromTwoSampleSets(splitSampleByIndex(example1.A1, 0), splitSampleByIndex(example1.A2, 0)).degreesOfFreedom, >+ example1.expectedDegreesOfFreedom, 2); >+ assert.almostEqual(Statistics.probabilityRangeForWelchsTFromTwoSampleSets(splitSampleByIndex(example2.A1, 0), splitSampleByIndex(example2.A2, 0)).degreesOfFreedom, >+ example2.expectedDegreesOfFreedom, 2); >+ assert.almostEqual(Statistics.probabilityRangeForWelchsTFromTwoSampleSets(splitSampleByIndex(example3.A1, 0), splitSampleByIndex(example3.A2, 0)).degreesOfFreedom, >+ example3.expectedDegreesOfFreedom, 2); >+ }); >+ >+ it('should compute the range of probabilites using the p-value of Welch\'s t-test when split evenly', function () { >+ assert.almostEqual(Statistics.probabilityRangeForWelchsTFromTwoSampleSets(splitSample(example1.A1), splitSample(example1.A2)).range[0], example1.expectedRange[0]); >+ assert.almostEqual(Statistics.probabilityRangeForWelchsTFromTwoSampleSets(splitSample(example1.A1), splitSample(example1.A2)).range[1], example1.expectedRange[1]); >+ >+ assert.almostEqual(Statistics.probabilityRangeForWelchsTFromTwoSampleSets(splitSample(example2.A1), splitSample(example2.A2)).range[0], example2.expectedRange[0]); >+ assert.almostEqual(Statistics.probabilityRangeForWelchsTFromTwoSampleSets(splitSample(example2.A1), splitSample(example2.A2)).range[1], example2.expectedRange[1]); >+ >+ assert.almostEqual(Statistics.probabilityRangeForWelchsTFromTwoSampleSets(splitSample(example3.A1), splitSample(example3.A2)).range[0], example3.expectedRange[0]); >+ assert.almostEqual(Statistics.probabilityRangeForWelchsTFromTwoSampleSets(splitSample(example3.A1), splitSample(example3.A2)).range[1], example3.expectedRange[1]); >+ >+ assert.almostEqual(Statistics.probabilityRangeForWelchsTFromTwoSampleSets(splitSampleByIndex(example1.A1, 1), splitSampleByIndex(example1.A2, 1)).range[0], example1.expectedRange[0]); >+ assert.almostEqual(Statistics.probabilityRangeForWelchsTFromTwoSampleSets(splitSampleByIndex(example1.A1, 1), splitSampleByIndex(example1.A2, 1)).range[1], example1.expectedRange[1]); >+ >+ assert.almostEqual(Statistics.probabilityRangeForWelchsTFromTwoSampleSets(splitSampleByIndex(example2.A1, 1), splitSampleByIndex(example2.A2, 1)).range[0], example2.expectedRange[0]); >+ assert.almostEqual(Statistics.probabilityRangeForWelchsTFromTwoSampleSets(splitSampleByIndex(example2.A1, 1), splitSampleByIndex(example2.A2, 1)).range[1], example2.expectedRange[1]); >+ >+ assert.almostEqual(Statistics.probabilityRangeForWelchsTFromTwoSampleSets(splitSampleByIndex(example3.A1, 1), splitSampleByIndex(example3.A2, 1)).range[0], example3.expectedRange[0]); >+ assert.almostEqual(Statistics.probabilityRangeForWelchsTFromTwoSampleSets(splitSampleByIndex(example3.A1, 1), splitSampleByIndex(example3.A2, 1)).range[1], example3.expectedRange[1]); >+ >+ assert.almostEqual(Statistics.probabilityRangeForWelchsTFromTwoSampleSets(splitSampleByIndex(example1.A1, 0), splitSampleByIndex(example1.A2, 0)).range[0], example1.expectedRange[0]); >+ assert.almostEqual(Statistics.probabilityRangeForWelchsTFromTwoSampleSets(splitSampleByIndex(example1.A1, 0), splitSampleByIndex(example1.A2, 0)).range[1], example1.expectedRange[1]); >+ >+ assert.almostEqual(Statistics.probabilityRangeForWelchsTFromTwoSampleSets(splitSampleByIndex(example2.A1, 0), splitSampleByIndex(example2.A2, 0)).range[0], example2.expectedRange[0]); >+ assert.almostEqual(Statistics.probabilityRangeForWelchsTFromTwoSampleSets(splitSampleByIndex(example2.A1, 0), splitSampleByIndex(example2.A2, 0)).range[1], example2.expectedRange[1]); >+ >+ assert.almostEqual(Statistics.probabilityRangeForWelchsTFromTwoSampleSets(splitSampleByIndex(example3.A1, 0), splitSampleByIndex(example3.A2, 0)).range[0], example3.expectedRange[0]); >+ assert.almostEqual(Statistics.probabilityRangeForWelchsTFromTwoSampleSets(splitSampleByIndex(example3.A1, 0), splitSampleByIndex(example3.A2, 0)).range[1], example3.expectedRange[1]); >+ }); >+ }); >+ > describe('movingAverage', function () { > it('should return the origian values when both forward and backward window size is 0', function () { > assert.deepEqual(Statistics.movingAverage([1, 2, 3, 4, 5], 0, 0), [1, 2, 3, 4, 5]);
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