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Issue 2776653002: [ESLint] Fix violations when enabling curly rule in eslint. (Closed)
Patch Set: rebase Created 3 years, 8 months ago
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1 <!DOCTYPE html> 1 <!DOCTYPE html>
2 <!-- 2 <!--
3 Copyright 2014 The Chromium Authors. All rights reserved. 3 Copyright 2014 The Chromium Authors. All rights reserved.
4 Use of this source code is governed by a BSD-style license that can be 4 Use of this source code is governed by a BSD-style license that can be
5 found in the LICENSE file. 5 found in the LICENSE file.
6 --> 6 -->
7 7
8 <link rel="import" href="/tracing/base/math/math.html"> 8 <link rel="import" href="/tracing/base/math/math.html">
9 <link rel="import" href="/tracing/base/math/range.html"> 9 <link rel="import" href="/tracing/base/math/range.html">
10 <script src="/mannwhitneyu/mannwhitneyu.js"></script> 10 <script src="/mannwhitneyu/mannwhitneyu.js"></script>
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35 // TODO(charliea): Remove: 35 // TODO(charliea): Remove:
36 /* eslint-disable catapult-camelcase */ 36 /* eslint-disable catapult-camelcase */
37 37
38 tr.exportTo('tr.b.math', function() { 38 tr.exportTo('tr.b.math', function() {
39 var identity = x => x; 39 var identity = x => x;
40 40
41 var Statistics = {}; 41 var Statistics = {};
42 42
43 /* Returns the quotient, or zero if the denominator is zero.*/ 43 /* Returns the quotient, or zero if the denominator is zero.*/
44 Statistics.divideIfPossibleOrZero = function(numerator, denominator) { 44 Statistics.divideIfPossibleOrZero = function(numerator, denominator) {
45 if (denominator === 0) 45 if (denominator === 0) return 0;
46 return 0;
47 return numerator / denominator; 46 return numerator / denominator;
48 }; 47 };
49 48
50 Statistics.sum = function(ary, opt_func, opt_this) { 49 Statistics.sum = function(ary, opt_func, opt_this) {
51 var func = opt_func || identity; 50 var func = opt_func || identity;
52 var ret = 0; 51 var ret = 0;
53 var i = 0; 52 var i = 0;
54 for (var elt of ary) 53 for (var elt of ary) {
55 ret += func.call(opt_this, elt, i++); 54 ret += func.call(opt_this, elt, i++);
55 }
56 return ret; 56 return ret;
57 }; 57 };
58 58
59 Statistics.mean = function(ary, opt_func, opt_this) { 59 Statistics.mean = function(ary, opt_func, opt_this) {
60 var func = opt_func || identity; 60 var func = opt_func || identity;
61 var sum = 0; 61 var sum = 0;
62 var i = 0; 62 var i = 0;
63 63
64 for (var elt of ary) 64 for (var elt of ary) {
65 sum += func.call(opt_this, elt, i++); 65 sum += func.call(opt_this, elt, i++);
66 }
66 67
67 if (i === 0) 68 if (i === 0) return undefined;
68 return undefined;
69 69
70 return sum / i; 70 return sum / i;
71 }; 71 };
72 72
73 Statistics.geometricMean = function(ary, opt_func, opt_this) { 73 Statistics.geometricMean = function(ary, opt_func, opt_this) {
74 var func = opt_func || identity; 74 var func = opt_func || identity;
75 var i = 0; 75 var i = 0;
76 var logsum = 0; 76 var logsum = 0;
77 77
78 // The geometric mean is expressed as the arithmetic mean of logarithms 78 // The geometric mean is expressed as the arithmetic mean of logarithms
79 // in order to prevent overflow. 79 // in order to prevent overflow.
80 for (var elt of ary) { 80 for (var elt of ary) {
81 var x = func.call(opt_this, elt, i++); 81 var x = func.call(opt_this, elt, i++);
82 if (x <= 0) 82 if (x <= 0) return 0;
83 return 0;
84 logsum += Math.log(Math.abs(x)); 83 logsum += Math.log(Math.abs(x));
85 } 84 }
86 85
87 if (i === 0) 86 if (i === 0) return 1;
88 return 1;
89 87
90 return Math.exp(logsum / i); 88 return Math.exp(logsum / i);
91 }; 89 };
92 90
93 // Returns undefined if the sum of the weights is zero. 91 // Returns undefined if the sum of the weights is zero.
94 Statistics.weightedMean = function( 92 Statistics.weightedMean = function(
95 ary, weightCallback, opt_valueCallback, opt_this) { 93 ary, weightCallback, opt_valueCallback, opt_this) {
96 var valueCallback = opt_valueCallback || identity; 94 var valueCallback = opt_valueCallback || identity;
97 var numerator = 0; 95 var numerator = 0;
98 var denominator = 0; 96 var denominator = 0;
99 var i = -1; 97 var i = -1;
100 98
101 for (var elt of ary) { 99 for (var elt of ary) {
102 i++; 100 i++;
103 var value = valueCallback.call(opt_this, elt, i); 101 var value = valueCallback.call(opt_this, elt, i);
104 if (value === undefined) 102 if (value === undefined) continue;
105 continue;
106 var weight = weightCallback.call(opt_this, elt, i, value); 103 var weight = weightCallback.call(opt_this, elt, i, value);
107 numerator += weight * value; 104 numerator += weight * value;
108 denominator += weight; 105 denominator += weight;
109 } 106 }
110 107
111 if (denominator === 0) 108 if (denominator === 0) return undefined;
112 return undefined;
113 109
114 return numerator / denominator; 110 return numerator / denominator;
115 }; 111 };
116 112
117 Statistics.variance = function(ary, opt_func, opt_this) { 113 Statistics.variance = function(ary, opt_func, opt_this) {
118 if (ary.length === 0) 114 if (ary.length === 0) return undefined;
119 return undefined; 115 if (ary.length === 1) return 0;
120 if (ary.length === 1)
121 return 0;
122 var func = opt_func || identity; 116 var func = opt_func || identity;
123 var mean = Statistics.mean(ary, func, opt_this); 117 var mean = Statistics.mean(ary, func, opt_this);
124 var sumOfSquaredDistances = Statistics.sum( 118 var sumOfSquaredDistances = Statistics.sum(
125 ary, 119 ary,
126 function(d, i) { 120 function(d, i) {
127 var v = func.call(this, d, i) - mean; 121 var v = func.call(this, d, i) - mean;
128 return v * v; 122 return v * v;
129 }, 123 },
130 opt_this); 124 opt_this);
131 return sumOfSquaredDistances / (ary.length - 1); 125 return sumOfSquaredDistances / (ary.length - 1);
132 }; 126 };
133 127
134 Statistics.stddev = function(ary, opt_func, opt_this) { 128 Statistics.stddev = function(ary, opt_func, opt_this) {
135 if (ary.length === 0) 129 if (ary.length === 0) return undefined;
136 return undefined;
137 return Math.sqrt( 130 return Math.sqrt(
138 Statistics.variance(ary, opt_func, opt_this)); 131 Statistics.variance(ary, opt_func, opt_this));
139 }; 132 };
140 133
141 Statistics.max = function(ary, opt_func, opt_this) { 134 Statistics.max = function(ary, opt_func, opt_this) {
142 var func = opt_func || identity; 135 var func = opt_func || identity;
143 var ret = -Infinity; 136 var ret = -Infinity;
144 var i = 0; 137 var i = 0;
145 for (var elt of ary) 138 for (var elt of ary) {
146 ret = Math.max(ret, func.call(opt_this, elt, i++)); 139 ret = Math.max(ret, func.call(opt_this, elt, i++));
140 }
147 return ret; 141 return ret;
148 }; 142 };
149 143
150 Statistics.min = function(ary, opt_func, opt_this) { 144 Statistics.min = function(ary, opt_func, opt_this) {
151 var func = opt_func || identity; 145 var func = opt_func || identity;
152 var ret = Infinity; 146 var ret = Infinity;
153 var i = 0; 147 var i = 0;
154 for (var elt of ary) 148 for (var elt of ary) {
155 ret = Math.min(ret, func.call(opt_this, elt, i++)); 149 ret = Math.min(ret, func.call(opt_this, elt, i++));
150 }
156 return ret; 151 return ret;
157 }; 152 };
158 153
159 Statistics.range = function(ary, opt_func, opt_this) { 154 Statistics.range = function(ary, opt_func, opt_this) {
160 var func = opt_func || identity; 155 var func = opt_func || identity;
161 var ret = new tr.b.math.Range(); 156 var ret = new tr.b.math.Range();
162 var i = 0; 157 var i = 0;
163 for (var elt of ary) 158 for (var elt of ary) {
164 ret.addValue(func.call(opt_this, elt, i++)); 159 ret.addValue(func.call(opt_this, elt, i++));
160 }
165 return ret; 161 return ret;
166 }; 162 };
167 163
168 Statistics.percentile = function(ary, percent, opt_func, opt_this) { 164 Statistics.percentile = function(ary, percent, opt_func, opt_this) {
169 if (!(percent >= 0 && percent <= 1)) 165 if (!(percent >= 0 && percent <= 1)) {
170 throw new Error('percent must be [0,1]'); 166 throw new Error('percent must be [0,1]');
167 }
171 168
172 var func = opt_func || identity; 169 var func = opt_func || identity;
173 var tmp = new Array(ary.length); 170 var tmp = new Array(ary.length);
174 var i = 0; 171 var i = 0;
175 for (var elt of ary) 172 for (var elt of ary) {
176 tmp[i] = func.call(opt_this, elt, i++); 173 tmp[i] = func.call(opt_this, elt, i++);
174 }
177 tmp.sort((a, b) => a - b); 175 tmp.sort((a, b) => a - b);
178 var idx = Math.floor((ary.length - 1) * percent); 176 var idx = Math.floor((ary.length - 1) * percent);
179 return tmp[idx]; 177 return tmp[idx];
180 }; 178 };
181 179
182 /** 180 /**
183 * Sorts the samples, and map them linearly to the range [0,1]. 181 * Sorts the samples, and map them linearly to the range [0,1].
184 * 182 *
185 * They're mapped such that for the N samples, the first sample is 0.5/N and 183 * They're mapped such that for the N samples, the first sample is 0.5/N and
186 * the last sample is (N-0.5)/N. 184 * the last sample is (N-0.5)/N.
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230 /** 228 /**
231 * Computes the discrepancy of a set of 1D samples from the interval [0,1]. 229 * Computes the discrepancy of a set of 1D samples from the interval [0,1].
232 * 230 *
233 * The samples must be sorted. We define the discrepancy of an empty set 231 * The samples must be sorted. We define the discrepancy of an empty set
234 * of samples to be zero. 232 * of samples to be zero.
235 * 233 *
236 * http://en.wikipedia.org/wiki/Low-discrepancy_sequence 234 * http://en.wikipedia.org/wiki/Low-discrepancy_sequence
237 * http://mathworld.wolfram.com/Discrepancy.html 235 * http://mathworld.wolfram.com/Discrepancy.html
238 */ 236 */
239 Statistics.discrepancy = function(samples, opt_locationCount) { 237 Statistics.discrepancy = function(samples, opt_locationCount) {
240 if (samples.length === 0) 238 if (samples.length === 0) return 0.0;
241 return 0.0;
242 239
243 var maxLocalDiscrepancy = 0; 240 var maxLocalDiscrepancy = 0;
244 var invSampleCount = 1.0 / samples.length; 241 var invSampleCount = 1.0 / samples.length;
245 var locations = []; 242 var locations = [];
246 // For each location, stores the number of samples less than that location. 243 // For each location, stores the number of samples less than that location.
247 var countLess = []; 244 var countLess = [];
248 // For each location, stores the number of samples less than or equal to 245 // For each location, stores the number of samples less than or equal to
249 // that location. 246 // that location.
250 var countLessEqual = []; 247 var countLessEqual = [];
251 248
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353 * 350 *
354 * The time stamp series C = [0,2,3,4] and D = [0,2,3,4,5] have the same 351 * The time stamp series C = [0,2,3,4] and D = [0,2,3,4,5] have the same
355 * absolute discrepancy, but D has lower relative discrepancy than C. 352 * absolute discrepancy, but D has lower relative discrepancy than C.
356 * 353 *
357 * |timestamps| may be a list of lists S = [S_1, S_2, ..., S_N], where each 354 * |timestamps| may be a list of lists S = [S_1, S_2, ..., S_N], where each
358 * S_i is a time stamp series. In that case, the discrepancy D(S) is: 355 * S_i is a time stamp series. In that case, the discrepancy D(S) is:
359 * D(S) = max(D(S_1), D(S_2), ..., D(S_N)) 356 * D(S) = max(D(S_1), D(S_2), ..., D(S_N))
360 **/ 357 **/
361 Statistics.timestampsDiscrepancy = function(timestamps, opt_absolute, 358 Statistics.timestampsDiscrepancy = function(timestamps, opt_absolute,
362 opt_locationCount) { 359 opt_locationCount) {
363 if (timestamps.length === 0) 360 if (timestamps.length === 0) return 0.0;
364 return 0.0;
365 361
366 if (opt_absolute === undefined) 362 if (opt_absolute === undefined) opt_absolute = true;
367 opt_absolute = true;
368 363
369 if (Array.isArray(timestamps[0])) { 364 if (Array.isArray(timestamps[0])) {
370 var rangeDiscrepancies = timestamps.map(function(r) { 365 var rangeDiscrepancies = timestamps.map(function(r) {
371 return Statistics.timestampsDiscrepancy(r); 366 return Statistics.timestampsDiscrepancy(r);
372 }); 367 });
373 return Math.max.apply(null, rangeDiscrepancies); 368 return Math.max.apply(null, rangeDiscrepancies);
374 } 369 }
375 370
376 var s = Statistics.normalizeSamples(timestamps); 371 var s = Statistics.normalizeSamples(timestamps);
377 var samples = s.normalized_samples; 372 var samples = s.normalized_samples;
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401 * Because timestamp discrepancy is defined in terms of timestamps, we first 396 * Because timestamp discrepancy is defined in terms of timestamps, we first
402 * convert the list of durations to monotonically increasing timestamps. 397 * convert the list of durations to monotonically increasing timestamps.
403 * 398 *
404 * Args: 399 * Args:
405 * durations: List of interval lengths in milliseconds. 400 * durations: List of interval lengths in milliseconds.
406 * absolute: See TimestampsDiscrepancy. 401 * absolute: See TimestampsDiscrepancy.
407 * opt_locationCount: See TimestampsDiscrepancy. 402 * opt_locationCount: See TimestampsDiscrepancy.
408 **/ 403 **/
409 Statistics.durationsDiscrepancy = function( 404 Statistics.durationsDiscrepancy = function(
410 durations, opt_absolute, opt_locationCount) { 405 durations, opt_absolute, opt_locationCount) {
411 if (durations.length === 0) 406 if (durations.length === 0) return 0.0;
412 return 0.0;
413 407
414 var timestamps = durations.reduce(function(prev, curr, index, array) { 408 var timestamps = durations.reduce(function(prev, curr, index, array) {
415 prev.push(prev[prev.length - 1] + curr); 409 prev.push(prev[prev.length - 1] + curr);
416 return prev; 410 return prev;
417 }, [0]); 411 }, [0]);
418 return Statistics.timestampsDiscrepancy( 412 return Statistics.timestampsDiscrepancy(
419 timestamps, opt_absolute, opt_locationCount); 413 timestamps, opt_absolute, opt_locationCount);
420 }; 414 };
421 415
422 /** 416 /**
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455 * 449 *
456 * Args: 450 * Args:
457 * samples: Array of elements that have already been selected. Start with []. 451 * samples: Array of elements that have already been selected. Start with [].
458 * streamLength: The current length of the stream, up to |newElement|. 452 * streamLength: The current length of the stream, up to |newElement|.
459 * newElement: The element that was just extracted from the stream. 453 * newElement: The element that was just extracted from the stream.
460 * numSamples: The total number of samples desired. 454 * numSamples: The total number of samples desired.
461 **/ 455 **/
462 Statistics.uniformlySampleStream = function(samples, streamLength, newElement, 456 Statistics.uniformlySampleStream = function(samples, streamLength, newElement,
463 numSamples) { 457 numSamples) {
464 if (streamLength <= numSamples) { 458 if (streamLength <= numSamples) {
465 if (samples.length >= streamLength) 459 if (samples.length >= streamLength) {
466 samples[streamLength - 1] = newElement; 460 samples[streamLength - 1] = newElement;
467 else 461 } else {
468 samples.push(newElement); 462 samples.push(newElement);
463 }
469 return; 464 return;
470 } 465 }
471 466
472 var probToKeep = numSamples / streamLength; 467 var probToKeep = numSamples / streamLength;
473 if (Math.random() > probToKeep) 468 if (Math.random() > probToKeep) return; // New sample was rejected.
474 return; // New sample was rejected.
475 469
476 // Keeping it, replace an alement randomly. 470 // Keeping it, replace an alement randomly.
477 var index = Math.floor(Math.random() * numSamples); 471 var index = Math.floor(Math.random() * numSamples);
478 samples[index] = newElement; 472 samples[index] = newElement;
479 }; 473 };
480 474
481 /** 475 /**
482 * A mechanism to merge two arrays of uniformly sampled elements in a way that 476 * A mechanism to merge two arrays of uniformly sampled elements in a way that
483 * ensures elements in the final array are still sampled uniformly. 477 * ensures elements in the final array are still sampled uniformly.
484 * 478 *
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626 /* An alternative measure of how spread out the distribution is, 620 /* An alternative measure of how spread out the distribution is,
627 * the variance is the square of the standard deviation. 621 * the variance is the square of the standard deviation.
628 * @return {number} variance. 622 * @return {number} variance.
629 */ 623 */
630 get variance() { 624 get variance() {
631 throw Error('Not implemented'); 625 throw Error('Not implemented');
632 } 626 }
633 }; 627 };
634 628
635 Statistics.UniformDistribution = function(opt_range) { 629 Statistics.UniformDistribution = function(opt_range) {
636 if (!opt_range) 630 if (!opt_range) opt_range = tr.b.math.Range.fromExplicitRange(0, 1);
637 opt_range = tr.b.math.Range.fromExplicitRange(0, 1);
638 this.range = opt_range; 631 this.range = opt_range;
639 }; 632 };
640 633
641 Statistics.UniformDistribution.prototype = { 634 Statistics.UniformDistribution.prototype = {
642 __proto__: Distribution.prototype, 635 __proto__: Distribution.prototype,
643 636
644 computeDensity: function(x) { 637 computeDensity: function(x) {
645 return 1 / this.range.range; 638 return 1 / this.range.range;
646 }, 639 },
647 640
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839 result.significance = Statistics.Significance.INSIGNIFICANT; 832 result.significance = Statistics.Significance.INSIGNIFICANT;
840 } 833 }
841 return result; 834 return result;
842 }; 835 };
843 836
844 return { 837 return {
845 Statistics, 838 Statistics,
846 }; 839 };
847 }); 840 });
848 </script> 841 </script>
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