How to use samplesComparison method in Best

Best JavaScript code snippet using best

analyze.ts

Source:analyze.ts

1/*2 * Copyright (c) 2019, salesforce.com, inc.3 * All rights reserved.4 * SPDX-License-Identifier: MIT5 * For full license text, see the LICENSE file in the repo root or https://opensource.org/licenses/MIT6*/7import json2md from 'json2md';8import { BenchmarkComparison, ResultComparison, BenchmarkMetricNames, BenchmarkStats, ResultComparisonBenchmark, ResultComparisonGroup, ResultComparisonProject } from '@best/types';9interface MarkdownTable {10    table: {11        headers: string[];12        rows: string[][];13    }14}15interface SignificantlyChangedSummary {16    improved: string[][]17    regressed: string[][]18}19type GroupedTables = { [projectName: string]: MarkdownTable[] }20function padding(n: number) {21    return n > 022        ? Array.apply(null, Array((n - 1) * 3))23            .map(() => ' ')24            .join('') + 'ââ '25        : '';26}27function generateMarkdownFromGroupedTables(tables: GroupedTables) {28    const flattenedTables = Object.keys(tables).reduce((groups, projectName): json2md.DataObject[] => {29        groups.push({ h2: `*${projectName}*` });30        groups.push(...tables[projectName]);31        return groups;32    }, <json2md.DataObject[]>[])33    return json2md(flattenedTables);34}35function generateRow(36    name: string,37    metrics: {38        baseStats: BenchmarkStats;39        targetStats: BenchmarkStats;40        samplesComparison: 0 | 1 | -1;41    },42    includeEmojiTrend: boolean43): string[] {44    const baseStats = metrics.baseStats;45    const targetStats = metrics.targetStats;46    const samplesComparison = metrics.samplesComparison;47    const percentage = (Math.abs(baseStats.median - targetStats.median) / baseStats.median) * 100;48    const relativeTrend = targetStats.median - baseStats.median;49    const sign = Math.sign(relativeTrend) === 1 ? '+' : '';50    const comparisonEmoji = (samplesComparison === 0 ? 'ð' : samplesComparison === 1 ? 'ð' : 'ð');51    return [52        name,53        `${baseStats.median.toFixed(2)} (Â± ${baseStats.medianAbsoluteDeviation.toFixed(2)}ms)`,54        `${targetStats.median.toFixed(2)} (Â± ${targetStats.medianAbsoluteDeviation.toFixed(2)}ms)`,55        sign + relativeTrend.toFixed(1) + 'ms (' + percentage.toFixed(1) + '%)' + (includeEmojiTrend ? ` ${comparisonEmoji}` : '')56    ]57}58function generateRowsFromComparison<RowType>(stats: ResultComparison, handler: (node: ResultComparisonBenchmark, parentName: string) => RowType[], name: string = '', initialRows: RowType[] = []) {59    if (stats.type === "project" || stats.type === "group") {60        return stats.comparisons.reduce((rows, node): RowType[] => {61            if (node.type === "project" || node.type === "group") {62                return generateRowsFromComparison(node, handler, node.name, rows);63            } else if (node.type === "benchmark") {64                rows.push(...handler(node, name));65            }66            return rows;67        }, initialRows);68    } else {69        return initialRows;70    }71}72function significantlyChangedRows(stats: ResultComparison, threshold: number, name: string = '', initialRows: SignificantlyChangedSummary = { improved: [], regressed: [] }) {73    const highThreshold = Math.abs(threshold); // handle whether the threshold is positive or negative74    const lowThreshold = -1 * highThreshold;75    if (stats.type === "project" || stats.type === "group") {76        return stats.comparisons.reduce((rows, node): SignificantlyChangedSummary => {77            if (node.type === "project" || node.type === "group") {78                return significantlyChangedRows(node, threshold, node.name, rows);79            } else if (node.type === "benchmark") {80                // for the significantly changed summary, we only check for aggregate81                const metrics = node.metrics.aggregate;82                if (metrics) {83                    const { baseStats, targetStats, samplesComparison } = metrics;84                    85                    if (samplesComparison !== 0 && baseStats.median > 1 && targetStats.median > 1) { // ensures passes Mann-Whiteney U test and results are more than 1ms86                        const percentage = (Math.abs(baseStats.median - targetStats.median) / baseStats.median) * 100;87                        const relativeTrend = targetStats.median - baseStats.median;88                        const relativePercentage = Math.sign(relativeTrend) * percentage;89                        const row = generateRow(`${name}/${node.name}`, metrics, false);90                        if (relativePercentage < lowThreshold) { // less than a negative is GOOD (things got faster)91                            rows.improved.push(row);92                        } else if (relativePercentage > highThreshold) { // more than a positive is WORSE (things got slower)93                            rows.regressed.push(row);94                        }95                    }96                }97            }98            return rows;99        }, initialRows)100    } else {101        return initialRows;102    }103}104function generateAllRows(stats: ResultComparison) {105    return generateRowsFromComparison(stats, (node, parentName) => {106        const rows: string[][] = [];107        const emptyFields = Array.apply(null, Array(3)).map(() => '-');108        rows.push([`${parentName}/${node.name}`, ...emptyFields]);109        Object.keys(node.metrics).forEach(metric => {110            const metrics = node.metrics[metric as BenchmarkMetricNames];111            if (metrics) {112                rows.push(generateRow(padding(1) + metric, metrics, true));113            }114        })115        return rows;116    })117}118function generateCommentWithTables(result: BenchmarkComparison, handler: (node: ResultComparisonProject | ResultComparisonGroup, baseCommit: string, targetCommit: string) => MarkdownTable[]) {119    const { baseCommit, targetCommit, comparisons } = result;120    const grouped: GroupedTables = comparisons.reduce((tables, node): GroupedTables => {121        if (node.type === "project" || node.type === "group") {122            const markdownTables = handler(node, baseCommit, targetCommit);123            if (markdownTables.length) {124                return {125                    ...tables,126                    [node.name]: markdownTables127                }128            }129            return tables;130        }131        return tables;132    }, <GroupedTables>{});133    return generateMarkdownFromGroupedTables(grouped);134}135export function generateComparisonSummary(result: BenchmarkComparison, threshold: number) {136    return generateCommentWithTables(result, (node, base, target) => {137        const changes = significantlyChangedRows(node, threshold);138        const tables: MarkdownTable[] = [];139        140        if (changes.improved.length) {141            tables.push({142                table: {143                    headers: [`â Improvements`, `base (\`${base}\`)`, `target (\`${target}\`)`, 'trend'],144                    rows: changes.improved145                }146            })147        }148        if (changes.regressed.length) {149            tables.push({150                table: {151                    headers: [`â Regressions`, `base (\`${base}\`)`, `target (\`${target}\`)`, 'trend'],152                    rows: changes.regressed153                }154            });155        }156        return tables;157    })158}159function generateAllRowsTable(baseCommit: string, targetCommit: string, stats: ResultComparison): MarkdownTable {160    const { name: benchmarkName } = stats;161    const mdName = benchmarkName.replace('.benchmark', '');162    return {163        table: {164            headers: [`${mdName}`, `base (\`${baseCommit}\`)`, `target (\`${targetCommit}\`)`, 'trend'],165            rows: generateAllRows(stats)166        }167    }168}169export function generateComparisonComment(result: BenchmarkComparison) {170    const tablesMarkdown = generateCommentWithTables(result, (node, base, target) => {171        const tables = node.comparisons.map(child => {172            return generateAllRowsTable(base, target, child);173        })174        return tables;175    });176    return `# Full Results\n\n${tablesMarkdown}`;177}178// this takes all the results and recursively goes through them179// then it creates a flat list of all of the percentages of change180export function generatePercentages(stats: ResultComparison): number[] {181    return generateRowsFromComparison(stats, (node, parentName) => {182        const rows: number[] = [];183        Object.keys(node.metrics).map(metricName => {184            const metrics = node.metrics[metricName as BenchmarkMetricNames];185            if (metrics) {186                const { baseStats, targetStats, samplesComparison } = metrics;187                const baseMed = baseStats.median;188                const targetMed = targetStats.median;189    190                const percentage = Math.abs((baseMed - targetMed) / baseMed * 100);191                const relativeTrend = targetMed - baseMed;192                // ensures passes Mann-Whiteney U test and results are more than 1ms193                if (samplesComparison !== 0 && baseMed > 1 && targetMed > 1) {194                    rows.push(Math.sign(relativeTrend) * percentage);195                } else {196                    rows.push(0); // otherwise we count it as zero197                }198            }199        })200        return rows;201    })...

comparison1.ts

Source:comparison1.ts

1/*2 * Copyright (c) 2019, salesforce.com, inc.3 * All rights reserved.4 * SPDX-License-Identifier: MIT5 * For full license text, see the LICENSE file in the repo root or https://opensource.org/licenses/MIT6*/7import { BenchmarkComparison } from '@best/types';8const comparison: BenchmarkComparison = {9  "baseCommit": "abcdef0",10  "targetCommit": "1234567",11  "comparisons": [12    {13      "type": "project",14      "name": "project-foo",15      "comparisons": [16        {17          "type": "group",18          "name": "bar.benchmark",19          "comparisons": [20            {21              "type": "group",22              "name": "bar 1",23              "comparisons": [24                {25                  "type": "benchmark",26                  "name": "fibonacci 15",27                  "metrics": {28                    "script": {29                      "baseStats": {30                        "samples": [31                          0.195,32                          0.135,33                          0.14,34                          0.345,35                          0.13536                        ],37                        "sampleSize": 5,38                        "samplesQuantileThreshold": 0.8,39                        "mean": 0.19,40                        "median": 0.14,41                        "variance": 0.007,42                        "medianAbsoluteDeviation": 0.00543                      },44                      "targetStats": {45                        "samples": [46                          0.225,47                          0.125,48                          0.17,49                          0.23,50                          0.14551                        ],52                        "sampleSize": 5,53                        "samplesQuantileThreshold": 0.8,54                        "mean": 0.179,55                        "median": 0.17,56                        "variance": 0.002,57                        "medianAbsoluteDeviation": 0.04558                      },59                      "samplesComparison": 060                    },61                    "aggregate": {62                      "baseStats": {63                        "samples": [64                          1.27,65                          0.28,66                          0.305,67                          0.775,68                          0.5669                        ],70                        "sampleSize": 5,71                        "samplesQuantileThreshold": 0.8,72                        "mean": 0.638,73                        "median": 0.56,74                        "variance": 0.133,75                        "medianAbsoluteDeviation": 0.25576                      },77                      "targetStats": {78                        "samples": [79                          1.505,80                          0.575,81                          0.78,82                          0.475,83                          0.73584                        ],85                        "sampleSize": 5,86                        "samplesQuantileThreshold": 0.8,87                        "mean": 0.814,88                        "median": 0.735,89                        "variance": 0.131384,90                        "medianAbsoluteDeviation": 0.16091                      },92                      "samplesComparison": 093                    }94                  }95                },96                {97                  "type": "benchmark",98                  "name": "fibonacci 38",99                  "metrics": {100                    "script": {101                      "baseStats": {102                        "samples": [103                          498.465,104                          475.37,105                          473.74,106                          478.11,107                          471.91108                        ],109                        "sampleSize": 5,110                        "samplesQuantileThreshold": 0.8,111                        "mean": 479.519,112                        "median": 475.37,113                        "variance": 93.889,114                        "medianAbsoluteDeviation": 2.740115                      },116                      "targetStats": {117                        "samples": [118                          478.37,119                          476.67,120                          471.725,121                          482.67,122                          479.44123                        ],124                        "sampleSize": 5,125                        "samplesQuantileThreshold": 0.8,126                        "mean": 477.775,127                        "median": 478.37,128                        "variance": 12.982,129                        "medianAbsoluteDeviation": 1.7130                      },131                      "samplesComparison": 0132                    },133                    "aggregate": {134                      "baseStats": {135                        "samples": [136                          498.735,137                          475.635,138                          473.955,139                          478.305,140                          472.14141                        ],142                        "sampleSize": 5,143                        "samplesQuantileThreshold": 0.8,144                        "mean": 479.754,145                        "median": 475.635,146                        "variance": 94.189,147                        "medianAbsoluteDeviation": 2.670148                      },149                      "targetStats": {150                        "samples": [151                          478.61,152                          477.005,153                          471.93,154                          482.89,155                          479.71156                        ],157                        "sampleSize": 5,158                        "samplesQuantileThreshold": 0.8,159                        "mean": 478.029,160                        "median": 478.61,161                        "variance": 13.008,162                        "medianAbsoluteDeviation": 1.605163                      },164                      "samplesComparison": 0165                    }166                  }167                }168              ]169            }170          ]171        },172        {173          "type": "group",174          "name": "baz.benchmark",175          "comparisons": [176            {177              "type": "group",178              "name": "baz 1",179              "comparisons": [180                {181                  "type": "benchmark",182                  "name": "fibonacci",183                  "metrics": {184                    "script": {185                      "baseStats": {186                        "samples": [187                          0.215,188                          0.25,189                          0.355,190                          0.325,191                          0.355192                        ],193                        "sampleSize": 5,194                        "samplesQuantileThreshold": 0.8,195                        "mean": 0.3,196                        "median": 0.325,197                        "variance": 0.003,198                        "medianAbsoluteDeviation": 0.03199                      },200                      "targetStats": {201                        "samples": [202                          0.185,203                          0.2,204                          0.16,205                          0.19,206                          0.375207                        ],208                        "sampleSize": 5,209                        "samplesQuantileThreshold": 0.8,210                        "mean": 0.222,211                        "median": 0.19,212                        "variance": 0.006,213                        "medianAbsoluteDeviation": 0.01214                      },215                      "samplesComparison": 0216                    },217                    "aggregate": {218                      "baseStats": {219                        "samples": [220                          1.29,221                          1.02,222                          0.735,223                          0.585,224                          0.615225                        ],226                        "sampleSize": 5,227                        "samplesQuantileThreshold": 0.8,228                        "mean": 0.849,229                        "median": 0.735,230                        "variance": 0.072,231                        "medianAbsoluteDeviation": 0.15232                      },233                      "targetStats": {234                        "samples": [235                          1.22,236                          0.885,237                          0.335,238                          0.675,239                          0.705240                        ],241                        "sampleSize": 5,242                        "samplesQuantileThreshold": 0.8,243                        "mean": 0.764,244                        "median": 0.705,245                        "variance": 0.084,246                        "medianAbsoluteDeviation": 0.180247                      },248                      "samplesComparison": 0249                    }250                  }251                }252              ]253            }254          ]255        }256      ]257    }258  ]259}...

Using AI Code Generation

1var BestPractice = require('./bestPractice.js');2var bp = new BestPractice();3var sample1 = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10];4var sample2 = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10];5var result = bp.samplesComparison(sample1, sample2);6console.log(result);

Using AI Code Generation

1var BestMatch = require('./BestMatch');2var fs = require('fs');3var samples = fs.readFileSync('samples.txt').toString().split("4");5var test = fs.readFileSync('test.txt').toString().split("6");7var bestMatch = new BestMatch();8var result = bestMatch.samplesComparison(samples, test);9console.log(result);10var BestMatch = function(){};11BestMatch.prototype.samplesComparison = function(samples, test){12    var result = [];13    var sample = [];14    var sampleName = "";15    var sampleData = "";16    var sampleLength = 0;17    var testLength = test.length;18    var i = 0;19    var j = 0;20    var k = 0;21    var l = 0;22    var count = 0;23    var percent = 0;24    var temp = 0;25    var tempName = "";26    var tempData = "";27    var tempLength = 0;28    for(i=0; i<samples.length; i++){29        if(samples[i] == ""){30            continue;31        }32        sample = samples[i].split(" ");33        sampleName = sample[0];34        sampleData = sample[1];35        sampleLength = sampleData.length;36        count = 0;37        percent = 0;38        for(j=0; j<testLength; j++){39            if(test[j] == ""){40                continue;41            }42            for(k=0; k<sampleLength; k++){43                if(test[j] == sampleData[k]){44                    count++;45                }46            }47        }48        percent = (count/sampleLength)*100;49        result.push({"name":sampleName, "percent":percent});50    }51    for(l=0; l<result.length; l++){52        for(m=l+1; m<result.length; m++){53            if(result[l].percent < result[m].percent){54                temp = result[l].percent;55                tempName = result[l].name;56                result[l].percent = result[m].percent;57                result[l].name = result[m].name;58                result[m].percent = temp;59                result[m].name = tempName;60            }61        }62    }63    return result;

Using AI Code Generation

1var samplesComparison = require('./BestMatch.js').samplesComparison;2var sample1 = [1, 2, 3, 4, 5];3var sample2 = [1, 3, 5, 7, 9, 11];4var sample3 = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10];5var sample4 = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11];6var bestMatch = new samplesComparison(sample1, sample2, sample3, sample4);7var result = bestMatch.getBestMatch();8console.log(result);9var samplesComparison = require('./BestMatch.js').samplesComparison;10var sample1 = [1, 2, 3, 4, 5];11var sample2 = [1, 3, 5, 7, 9, 11];12var sample3 = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10];13var sample4 = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11];14var bestMatch = new samplesComparison(sample1, sample2, sample3, sample4);15var result = bestMatch.getBestMatch();16console.log(result);17var samplesComparison = require('./BestMatch.js').samplesComparison;18var sample1 = [1, 2, 3, 4, 5];19var sample2 = [1, 3, 5, 7, 9, 11];20var sample3 = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10];

Using AI Code Generation

1console.log(BestMatch.samplesComparison("string1", "string2"));2console.log(BestMatch.samplesComparison("string1", "string2"));3console.log(BestMatch.samplesComparison("string1", "string2"));4console.log(BestMatch.samplesComparison("string1", "string2"));5console.log(BestMatch.samplesComparison("string1", "string2"));6console.log(BestMatch.samplesComparison("string1", "string2"));7console.log(BestMatch.samplesComparison("string1", "string2"));8console.log(BestMatch.samplesComparison("string1", "string2"));9console.log(BestMatch.samplesComparison("string1", "string2"));10console.log(BestMatch.samplesComparison("string1", "string2"));11console.log(BestMatch.samplesComparison("string1", "string2"));12console.log(BestMatch.samplesComparison("string1", "string2"));

Using AI Code Generation

1var BestMatch = require("./bestMatch");2var bestMatch = new BestMatch();3var sampleTexts = ["The quick brown fox jumps over the lazy dog", "The quick brown fox jumped over the lazy dog", "The quick brown fox jumps over the lazy dog."];4var targetTexts = ["The quick brown fox jumps over the lazy dog", "The quick brown fox jumped over the lazy dog", "The quick brown fox jumps over the lazy dog."];5var result = bestMatch.samplesComparison(sampleTexts, targetTexts);6console.log(result);

Using AI Code Generation

1import BestMatch from './BestMatch.js';2let bm = new BestMatch();3let sample1 = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10];4let sample2 = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10];5let match = bm.samplesComparison(sample1, sample2);6console.log(`The match percentage is: ${match}`);

Using AI Code Generation

1var BestMatch = require('./bestMatch');2var fs = require('fs');3var bm = new BestMatch();4var sampleImage = fs.readFileSync('sample.jpg');5bm.samplesComparison(sampleImage, function(err, result) {6    if (err) {7        console.log(err);8    } else {9        console.log(result);10    }11});12var BestMatch = require('./bestMatch');13var fs = require('fs');14var bm = new BestMatch();15var sampleImage = fs.readFileSync('sample.jpg');16bm.samplesComparison(sampleImage, function(err, result) {17    if (err) {18        console.log(err);19    } else {20        console.log(result);21    }22});

Using AI Code Generation

1var BestPath = require('best-path');2var path1 = {3        {4        },5        {6        },7        {8        }9};10var path2 = {11        {12        },13        {14        },15        {16        }17};18var bestPath = new BestPath();19var bestPaths = bestPath.samplesComparison([path1, path2]);20console.log(bestPaths);21[ { name: 'path1', sample: [ [Object], [Object], [Object] ] },22  { name: 'path2', sample: [ [Object], [Object], [Object] ] } ]

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