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How to use generateComparisonSummary method in Best

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instanceComparisonSummarizer.js

Source:instanceComparisonSummarizer.js

1(function () {2    summarizer = {};3    summarizer.instanceMap = {};4    summarizer.featureMap = {};5    summarizer.intercept = null;6    summarizer.globalSummaryMap = {7        "housing-gam-instance-data" : {8            "Linear-positive" : {9                "description" : "For <b>1 feature</b>, the final prediction increases when any feature value increases.",10                "features" : ["CHAS"]11            },12            "Linear-negative" : {13                "description" : "For <b>4 features</b>, the final prediction decreases when any feature value decreases.",14                "features" : ["INDUS","RAD","PTRATIO","LSTAT"]15            },16            "Non-linear" : {17                "description" : "For <b>8 features</b>, the final prediction is not proportional to a change in any feature value.",18                "features" : ["CRIM","ZN","NOX","RM","AGE","DIS","TAX","B"]19            },20            "Flat": {21                "description" : "",22                "features" : []23            }24        },25        "diamonds-gam-instance-data" : {26            "Linear-positive" : {27                "description" : "For <b>5 features</b>, the final prediction increases when any feature value increases.",28                "features" : ["carat","color","clarity","depth","y"]29            },30            "Linear-negative" : {31                "description" : "",32                "features" : []33            },34            "Non-linear" : {35                "description" : "For <b>2 features</b>, the final prediction is not proportional to a change in any feature value.",36                "features" : ["x","z"]37            },38            "Flat": {39                "description" : "For <b>2 features</b>, the final prediction remains constant when any feature value changes.",40                "features" : ["cut","table"]41            }42        },43        "red-wine-gam-instance-data" : {44            "Linear-positive" : {45                "description" : "For <b>2 features</b>, the final prediction increases when any feature value increases.",46                "features" : ["alcohol","residualSugar"]47            },48            "Linear-negative" : {49                "description" : "For <b>4 features</b>, the final prediction decreases when any feature value decreases.",50                "features" : ["volatileAcidity","chlorides","density","pH"]51            },52            "Non-linear" : {53                "description" : "For <b>5 features</b>, the final prediction is not proportional to a change in any feature value.",54                "features" : ["fixedAcidity","citricAcid","freeSulfurDioxide","totalSulfurDioxide","sulphates"]55            },56            "Flat" : {57                "description" : "",58                "features" : []59            }60        },61        "ames-housing-gam-instance-data" : {62            "Linear-positive" : {63                "description" : "For <b>9 features</b>, the final prediction increases when any feature value increases.",64                "features" : ["LotFrontage","LotArea","OverallQual","OverallCond","TotalBsmtSF","FirstFlrSF"65                    ,"SecondFlrSF","GarageCars","ThreeSsnPorch"]66            },67            "Linear-negative" : {68                "description" : "For <b>2 features</b>, the final prediction decreases when any feature value decreases.",69                "features" : ["KitchenAbvGr","EnclosedPorch"]70            },71            "Non-linear" : {72                "description" : "For <b>6 features</b>, the final prediction is not proportional to a change in any feature value.",73                "features" : ["GarageArea","GrLivArea","BsmtFinSFOne","WoodDeckSF","OpenPorchSF","PoolArea"]74            },75            "Flat" : {76                "description" : "For <b>18 features</b>, the final prediction remains constant when any feature value changes.",77                "features" : ["MSSubClass","YearRemodAdd","TotRmsAbvGrd","MasVnrArea","BsmtFinSFTwo","BsmtUnfSF",78                    "LowQualFinSF","BsmtFullBath","BsmtHalfBath","FullBath","HalfBath","BedroomAbvGr",79                    "Fireplaces","ScreenPorch","MiscVal","GarageYrBlt","MoSold","YrSold"]80            }81        }82    };83    summarizer.globalSummaryMap_old = {84        "ames-housing-gam-instance-data" : [85            {86                "description":"Not coded yet",87                "features" : []88            }89        ],90        "housing-gam-instance-data" : [91            {92                "description":"5/13 features (<b>CRIM</b>, <b>ZN</b>, <b>NOX</b>, <b>AGE</b>, <b>RAD</b>) have a varying trend in predictions",93                "features" : ["CRIM", "ZN", "NOX", "AGE", "RAD"]94            },95            {96                "description":"3/13 features (<b>CHAS</b>, <b>RM</b>, <b>B</b>) have an upward trend in predictions (i.e., the prediction increases with an increase in data values)",97                "features" : ["CHAS", "RM", "B"]98            },99            {100                "description":"5/13 features (<b>INDUS</b>, <b>DIS</b>, <b>TAX</b>, <b>PTRATIO</b>, <b>LSTAT</b>) have a downward trend in predictions (i.e., the prediction decreases with an increase in data values)",101                "features" : ["INDUS", "DIS", "TAX", "PTRATIO", "LSTAT"]102            }103        ],104        "diamonds-gam-instance-data" : [105            {106                "description":"6/9 features (<b>carat</b>, <b>cut</b>, <b>color</b>, <b>clarity</b>, <b>depth</b>, <b>y</b>) have a varying trend in predictions",107                "features" : ["carat","cut","color","clarity","depth","y"]108            },109            {110                "description":"2/9 features (<b>x</b>, <b>z</b>) have an upward trend in predictions (i.e., the prediction increases with an increase in data values)",111                "features" : ["x","z"]112            },113            {114                "description":"1/9 features (<b>table</b>) have a downward trend in predictions (i.e., the prediction decreases with an increase in data values)",115                "features" : ["table"]116            }117        ],118        "red-wine-gam-instance-data" : [119            {120                "description":"3/11 features (<b>residualSugar</b>,<b>freeSulfurDioxide</b>, <b>alcohol</b>) have a varying trend in predictions",121                "features" : ["residualSugar", "freeSulfurDioxide","alcohol"]122            },123            {124                "description":"4/11 features (<b>volatileAcidity</b>, <b>chlorides</b>, <b>density</b>, <b>pH</b>) have an upward trend in predictions (i.e., the prediction increases with an increase in data values)",125                "features" : ["volatileAcidity", "chlorides", "density", "pH"]126            },127            {128                "description":"4/11 features (<b>fixedAcidity</b>, <b>citricAcid</b>, <b>totalSulfurDioxide</b>, <b>sulphates</b>) have a downward trend in predictions (i.e., the prediction decreases with an increase in data values)",129                "features" : ["fixedAcidity", "citricAcid", "totalSulfurDioxide", "sulphates"]130            }131        ]132    };133    summarizer.instanceSummaryParams = {};134    summarizer.instanceSummaryParams.contributionThreshold = .2;135    summarizer.instanceSummaryParams.summaryDetailLevel = 1;136    summarizer.comparisonParams = {};137    summarizer.comparisonParams.totalPredictionSimilarityThreshold = .25;138    summarizer.comparisonParams.totalPredictionDifferenceThreshold = .75;139    summarizer.comparisonParams.featurePredictionThreshold = .25;140    summarizer.comparisonParams.featurePredictionCountThreshold = .5;141    summarizer.comparisonParams.summaryDetailLevel = 1;142    summarizer.init = function (data, intercept) {143        summarizer.instanceMap = {};144        summarizer.featureMap = {};145        for(let instanceObj of data){146            let predictionObjs = instanceObj['data'];147            let totalPrediction = intercept;148            summarizer.intercept = intercept;149            summarizer.instanceMap[instanceObj['id']] = instanceObj;150            for(let predictionObj of predictionObjs){151                let feature = predictionObj['name'];152                let predictedValue = +predictionObj['pdep'];153                if(feature in summarizer.featureMap){154                    summarizer.featureMap[feature]['values'].push(predictedValue);155                    if(summarizer.featureMap[feature]['min']>predictedValue){156                        summarizer.featureMap[feature]['min'] = predictedValue;157                    }158                    if(summarizer.featureMap[feature]['max']<predictedValue){159                        summarizer.featureMap[feature]['max'] = predictedValue;160                    }161                }else{162                    summarizer.featureMap[feature] = {};163                    summarizer.featureMap[feature]['values'] = [predictedValue];164                    summarizer.featureMap[feature]['min'] = predictedValue;165                    summarizer.featureMap[feature]['max'] = predictedValue;166                }167                totalPrediction += +(predictionObj['pdep']);168            }169            if('totalPrediction' in summarizer.featureMap){170                summarizer.featureMap['totalPrediction']['values'].push(totalPrediction);171                if(summarizer.featureMap['totalPrediction']['min']>totalPrediction){172                    summarizer.featureMap['totalPrediction']['min'] = totalPrediction;173                }174                if(summarizer.featureMap['totalPrediction']['max']<totalPrediction){175                    summarizer.featureMap['totalPrediction']['max'] = totalPrediction;176                }177            }else{178                summarizer.featureMap['totalPrediction'] = {};179                summarizer.featureMap['totalPrediction']['values'] = [totalPrediction];180                summarizer.featureMap['totalPrediction']['min'] = totalPrediction;181                summarizer.featureMap['totalPrediction']['max'] = totalPrediction;182            }183            summarizer.instanceMap[instanceObj['id']]['totalPrediction'] = totalPrediction;184        }185        for(let feature in summarizer.featureMap){186            let featureMinValue = summarizer.featureMap[feature]['min'];187            let featureMaxValue = summarizer.featureMap[feature]['max'];188            summarizer.featureMap[feature]['scale'] = d3.scaleLinear().domain([featureMinValue,featureMaxValue]).range([0,1]);189        }190        summarizer.featureCount = Object.keys(summarizer.featureMap).length-1;191    };192    summarizer.generateInstanceSummary = function(instanceObj) {193        let summaryObj = {}, instanceObjPredictionObjs = instanceObj['data'];194        let totalIndividualPredictions = 0;195        for(let i=0;i<instanceObjPredictionObjs.length;i++){196            totalIndividualPredictions += Math.abs(instanceObjPredictionObjs[i]['pdep']);197        }198        let featureContributionMap = {}, highlyContributingFeatures = [], highlyContributingFeaturesTotalContribution = 0;199        for(let i=0;i<instanceObjPredictionObjs.length;i++){200            featureContributionMap[instanceObjPredictionObjs[i]['name']] = Math.abs(instanceObjPredictionObjs[i]['pdep'])/totalIndividualPredictions;201            if(featureContributionMap[instanceObjPredictionObjs[i]['name']]>summarizer.instanceSummaryParams.contributionThreshold){202                highlyContributingFeatures.push(instanceObjPredictionObjs[i]['name']);203                highlyContributingFeaturesTotalContribution += featureContributionMap[instanceObjPredictionObjs[i]['name']];204            }205        }206        highlyContributingFeaturesTotalContribution = (highlyContributingFeaturesTotalContribution*100).toFixed(2);207        if(highlyContributingFeatures.length==0){208            summaryObj = {209                "highlyContributingFeatures":[],210                "highlyContributingFeaturesTotalContribution":0,211                "summarySentence":"<b>None</b> of the features individually have a notable impact on the prediction."212            }213        }else {214            summaryObj = {215                "highlyContributingFeatures":highlyContributingFeatures,216                "highlyContributingFeaturesTotalContribution":highlyContributingFeaturesTotalContribution217            };218            if(summarizer.instanceSummaryParams.summaryDetailLevel==1){219                summaryObj["summarySentence"]="<b>Some features</b> <b>have a notable impact</b> on the prediction.";220            }else if(summarizer.instanceSummaryParams.summaryDetailLevel==2){221                if(highlyContributingFeatures.length==1){222                    summaryObj["summarySentence"]="<b>1 feature</b> has a notable impact and <b>individually accounts for over "+summarizer.instanceSummaryParams.contributionThreshold*100+"%</b> of the prediction.";223                }else {224                    summaryObj["summarySentence"]= "<b>"+highlyContributingFeatures.length + " features</b> have a notable impact and <b>individually account for over "+summarizer.instanceSummaryParams.contributionThreshold*100+"%</b> of the prediction.";225                }226            }else if(summarizer.instanceSummaryParams.summaryDetailLevel==3){227                if(highlyContributingFeatures.length==1){228                    summaryObj["summarySentence"]="<b>1 feature</b> individually has a notable impact <b>accounting for " + highlyContributingFeaturesTotalContribution + "%</b> of the prediction.";229                }else {230                    summaryObj["summarySentence"]= "<b>"+highlyContributingFeatures.length + " features</b> individually have a notable impact and <b>account for a total of " + highlyContributingFeaturesTotalContribution + "%</b> of the prediction.";231                }232            }233        }234        return summaryObj;235    };236    summarizer.generateComparisonSummary = function (instanceObj1, instanceObj2, method) {237        let summaryObj;238        if(method=='quartiles'){239        }else {240            summaryObj = getComparisonSummaryUsingThresholds(instanceObj1,instanceObj2);241        }242        return summaryObj;243    };244    function getComparisonSummaryUsingThresholds(instanceObj1,instanceObj2){245        let summaryObj;246        let totalPredictionDifferenceStatus = 'MODERATE', totalPredictionRawDifference;247        let totalPredictionScale = summarizer.featureMap['totalPrediction']['scale'];248        let instanceObj1TotalPrediction = summarizer.instanceMap[instanceObj1.id]['totalPrediction'], instanceObj2TotalPrediction = summarizer.instanceMap[instanceObj2.id]['totalPrediction'];249        let totalPredictionDiff = totalPredictionScale(instanceObj1TotalPrediction) - totalPredictionScale(instanceObj2TotalPrediction);250        totalPredictionRawDifference = Math.abs(instanceObj1TotalPrediction-instanceObj2TotalPrediction);251        if(Math.abs(totalPredictionDiff)<=summarizer.comparisonParams.totalPredictionSimilarityThreshold){252            totalPredictionDifferenceStatus = 'SMALL';253        }else if(Math.abs(totalPredictionDiff)>=summarizer.comparisonParams.totalPredictionDifferenceThreshold){254            totalPredictionDifferenceStatus = 'LARGE';255        }256        let instanceObj1PredictionObjs = instanceObj1['data'], instanceObj2PredictionObjs = instanceObj2['data'];257        let featurePredictionDifferenceStatus, featurePredictionDifferenceObjs = [];258        for(let i in instanceObj1PredictionObjs){259            let instanceObj1PredictionObj = instanceObj1PredictionObjs[i];260            let instanceObj2PredictionObj = instanceObj2PredictionObjs[i];261            // console.log(instanceObj1PredictionObj['name'],instanceObj2PredictionObj['name']);262            let instanceObj1FeaturePrediction = instanceObj1PredictionObj['pdep'];263            let instanceObj2FeaturePrediction = instanceObj2PredictionObj['pdep'];264            let feature = instanceObj1PredictionObj['name'];265            if(feature!='totalPrediction'){266                let featureScale = summarizer.featureMap[feature]['scale'];267                let featurePredictionDiff = featureScale(instanceObj1FeaturePrediction) - featureScale(instanceObj2FeaturePrediction);268                if(Math.abs(featurePredictionDiff)>summarizer.comparisonParams.featurePredictionThreshold){269                    featurePredictionDifferenceObjs.push({270                        'name' : feature,271                        'diff' : Math.abs(instanceObj1FeaturePrediction-instanceObj2FeaturePrediction),272                        'diff_normalized' : Math.abs(featurePredictionDiff)273                    });274                }275            }276        }277        let totalPredictionDifferenceObj = {278            'totalPredictionDifferenceStatus' : totalPredictionDifferenceStatus,279            'totalPredictionRawDifference' : totalPredictionRawDifference,280            'instance1TotalPrediction': instanceObj1TotalPrediction,281            'instance2TotalPrediction': instanceObj2TotalPrediction282        };283        let featurePredictionDifferenceObj;284        if((featurePredictionDifferenceObjs.length/(summarizer.featureCount))<summarizer.comparisonParams.featurePredictionCountThreshold){ // -1 for totalPrediction285            if(featurePredictionDifferenceObjs.length==0){286                featurePredictionDifferenceObj = {287                    'featurePredictionDifferenceStatus': 'CONSISTENT_SIMILAR',288                    'featurePredictionDifferenceObjs' : featurePredictionDifferenceObjs289                }290            }else {291                featurePredictionDifferenceObj = {292                    'featurePredictionDifferenceStatus': 'VARIED',293                    'featurePredictionDifferenceObjs' : featurePredictionDifferenceObjs294                }295            }296            summaryObj = generateComparisonSummaryObj(totalPredictionDifferenceObj,featurePredictionDifferenceObj);297        }else{298            featurePredictionDifferenceObj = {299                'featurePredictionDifferenceStatus': 'CONSISTENT_DIFFERENT',300                'featurePredictionDifferenceObjs' : featurePredictionDifferenceObjs301            };302            summaryObj = generateComparisonSummaryObj(totalPredictionDifferenceObj,featurePredictionDifferenceObj);303        }304        return summaryObj;305    }306    function generateComparisonSummaryObj(totalPredictionDifferenceObj,featurePredictionDifferenceObj){307        let totalPredictionDifferenceStatus = totalPredictionDifferenceObj['totalPredictionDifferenceStatus'];308        let totalPredictionRawDifference = totalPredictionDifferenceObj['totalPredictionRawDifference'];309        let featurePredictionDifferenceStatus = featurePredictionDifferenceObj['featurePredictionDifferenceStatus'];310        let featurePredictionDifferenceObjs = featurePredictionDifferenceObj['featurePredictionDifferenceObjs'];311        let summary;312        if(totalPredictionDifferenceStatus=='SMALL'){313            if(featurePredictionDifferenceStatus=="CONSISTENT_SIMILAR"){314                if(summarizer.comparisonParams.summaryDetailLevel==1){315                    summary = "<b>Overall predictions are similar</b> with <b>all features contributing similarly</b> from both instances";316                }else if(summarizer.comparisonParams.summaryDetailLevel==2){317                    summary = "<b>Overall predictions are similar</b> with <b>all " + (summarizer.featureCount) + " features contributing similarly</b> from both instances";318                }else if(summarizer.comparisonParams.summaryDetailLevel==3){319                    summary = "<b>Overall predictions of "+totalPredictionDifferenceObj['instance1TotalPrediction'].toFixed(2)+" and "+totalPredictionDifferenceObj['instance2TotalPrediction'].toFixed(2)+" are similar</b> with <b>all " + (summarizer.featureCount) + " features contributing similarly</b> from both instances";320                }321            }else if(featurePredictionDifferenceStatus=="CONSISTENT_DIFFERENT"){322                if(summarizer.comparisonParams.summaryDetailLevel==1) {323                    summary = "<b>Overall predictions are similar</b> but <b>most features contribute differently</b> from both instances";324                }else if(summarizer.comparisonParams.summaryDetailLevel==2){325                    summary = "<b>Overall predictions are similar</b> but <b>over "+(summarizer.comparisonParams.featurePredictionCountThreshold*100).toFixed(2)+"% of the features contribute differently</b> from both instances";326                }else if(summarizer.comparisonParams.summaryDetailLevel==3){327                    summary = "<b>Overall predictions of "+totalPredictionDifferenceObj['instance1TotalPrediction'].toFixed(2)+" and "+totalPredictionDifferenceObj['instance2TotalPrediction'].toFixed(2)+" are similar</b> but <b>"+featurePredictionDifferenceObj['featurePredictionDifferenceObjs'].length+" (i.e. over "+(summarizer.comparisonParams.featurePredictionCountThreshold*100).toFixed(2)+"%) features contribute differently</b> from both instances";328                }329            }else if(featurePredictionDifferenceStatus=="VARIED"){330                if(summarizer.comparisonParams.summaryDetailLevel==1) {331                    summary = "<b>Overall predictions are similar</b> but <b>some features contribute differently</b> from both instances";332                }else if(summarizer.comparisonParams.summaryDetailLevel==2){333                    summary = "<b>Overall predictions are similar</b> but <b>"+featurePredictionDifferenceObj['featurePredictionDifferenceObjs'].length+" features contribute differently</b> from both instances";334                }else if(summarizer.comparisonParams.summaryDetailLevel==3){335                    summary = "<b>Overall predictions of "+totalPredictionDifferenceObj['instance1TotalPrediction'].toFixed(2)+" and "+totalPredictionDifferenceObj['instance2TotalPrediction'].toFixed(2)+" are similar</b> but <b>"+featurePredictionDifferenceObj['featurePredictionDifferenceObjs'].length+" features (i.e. "+((featurePredictionDifferenceObjs.length/summarizer.featureCount)*100).toFixed(2)+"%) contribute differently</b> from both instances";336                }337            }338        }else if(totalPredictionDifferenceStatus=='MODERATE'){339            if(featurePredictionDifferenceStatus=="CONSISTENT_SIMILAR"){340                if(summarizer.comparisonParams.summaryDetailLevel==1) {341                    summary = "<b>Overall predictions vary</b> but <b>all features contribute similarly</b> from both instances";342                }else if(summarizer.comparisonParams.summaryDetailLevel==2){343                    summary = "<b>Overall predictions vary</b> but <b>all "+summarizer.featureCount+" features contribute similarly</b> from both instances";344                }else if(summarizer.comparisonParams.summaryDetailLevel==3){345                    summary = "<b>Overall predictions of "+totalPredictionDifferenceObj['instance1TotalPrediction'].toFixed(2)+" and "+totalPredictionDifferenceObj['instance2TotalPrediction'].toFixed(2)+" vary</b> but <b>all "+summarizer.featureCount+" features contribute similarly</b> from both instances";346                }347            }else if(featurePredictionDifferenceStatus=="CONSISTENT_DIFFERENT"){348                if(summarizer.comparisonParams.summaryDetailLevel==1) {349                    summary = "<b>Overall predictions vary</b> and <b>most features contribute differently</b> from both instances";350                }else if(summarizer.comparisonParams.summaryDetailLevel==2){351                    summary = "<b>Overall predictions vary</b> and <b>"+featurePredictionDifferenceObj['featurePredictionDifferenceObjs'].length+" features contribute differently</b> from both instances";352                }else if(summarizer.comparisonParams.summaryDetailLevel==3){353                    summary = "<b>Overall predictions of "+totalPredictionDifferenceObj['instance1TotalPrediction'].toFixed(2)+" and "+totalPredictionDifferenceObj['instance2TotalPrediction'].toFixed(2)+" vary</b> and <b>"+featurePredictionDifferenceObj['featurePredictionDifferenceObjs'].length+" features (i.e. over "+(summarizer.comparisonParams.featurePredictionCountThreshold*100).toFixed(2)+"%) contribute differently</b> from both instances";354                }355            }else if(featurePredictionDifferenceStatus=="VARIED"){356                if(summarizer.comparisonParams.summaryDetailLevel==1) {357                    summary = "<b>Overall predictions vary</b> potentially due to <b>some features contributing differently</b> from both instances";358                }else if(summarizer.comparisonParams.summaryDetailLevel==2){359                    summary = "<b>Overall predictions vary</b> potentially due to <b>"+featurePredictionDifferenceObj['featurePredictionDifferenceObjs'].length+" features contributing differently</b> from both instances";360                }else if(summarizer.comparisonParams.summaryDetailLevel==3){361                    summary = "<b>Overall predictions of "+totalPredictionDifferenceObj['instance1TotalPrediction'].toFixed(2)+" and "+totalPredictionDifferenceObj['instance2TotalPrediction'].toFixed(2)+" vary</b> potentially due to <b>"+featurePredictionDifferenceObj['featurePredictionDifferenceObjs'].length+" features (i.e. "+((featurePredictionDifferenceObj['featurePredictionDifferenceObjs'].length/summarizer.featureCount)*100).toFixed(2)+"%) contributing differently</b> from both instances";362                }363            }364        }else if(totalPredictionDifferenceStatus=='LARGE'){365            if(featurePredictionDifferenceStatus=="CONSISTENT_SIMILAR"){366                if(summarizer.comparisonParams.summaryDetailLevel==1) {367                    summary = "<b>Overall predictions are very different</b> but <b>all features contribute similarly</b> from both instances";368                }else if(summarizer.comparisonParams.summaryDetailLevel==2){369                    summary = "<b>Overall predictions are very different</b> but <b>all "+summarizer.featureCount+" features contribute similarly</b> from both instances";370                }else if(summarizer.comparisonParams.summaryDetailLevel==3){371                    summary = "<b>Overall predictions of "+totalPredictionDifferenceObj['instance1TotalPrediction'].toFixed(2)+" and "+totalPredictionDifferenceObj['instance2TotalPrediction'].toFixed(2)+" are very different</b> but <b>all "+summarizer.featureCount+" features contribute similarly</b> from both instances";372                }373            }else if(featurePredictionDifferenceStatus=="CONSISTENT_DIFFERENT"){374                if(summarizer.comparisonParams.summaryDetailLevel==1) {375                    summary = "<b>Overall predictions are very different</b> with <b>most features contributing differently</b> from both instances";376                }else if(summarizer.comparisonParams.summaryDetailLevel==2){377                    summary = "<b>Overall predictions are very different</b> with <b>"+featurePredictionDifferenceObj['featurePredictionDifferenceObjs'].length+" features contributing differently</b> from both instances";378                }else if(summarizer.comparisonParams.summaryDetailLevel==3){379                    summary = "<b>Overall predictions of "+totalPredictionDifferenceObj['instance1TotalPrediction'].toFixed(2)+" and "+totalPredictionDifferenceObj['instance2TotalPrediction'].toFixed(2)+" are very different</b> with <b>"+featurePredictionDifferenceObj['featurePredictionDifferenceObjs'].length+" features (i.e. over "+(summarizer.comparisonParams.featurePredictionCountThreshold*100).toFixed(2)+"%) contributing differently</b> from both instances";380                }381            }else if(featurePredictionDifferenceStatus=="VARIED"){382                if(summarizer.comparisonParams.summaryDetailLevel==1) {383                    summary = "<b>Overall predictions are very different</b> potentially due to <b>some features that contribute differently</b> from both instances";384                }else if(summarizer.comparisonParams.summaryDetailLevel==2){385                    summary = "<b>Overall predictions are very different</b> potentially due to the <b>"+featurePredictionDifferenceObj['featurePredictionDifferenceObjs'].length+" features that contribute differently</b> from both instances";386                }else if(summarizer.comparisonParams.summaryDetailLevel==3){387                    summary = "<b>Overall predictions of "+totalPredictionDifferenceObj['instance1TotalPrediction'].toFixed(2)+" and "+totalPredictionDifferenceObj['instance2TotalPrediction'].toFixed(2)+" are very different</b> potentially due to the <b>"+featurePredictionDifferenceObj['featurePredictionDifferenceObjs'].length+" features (i.e. "+((featurePredictionDifferenceObj['featurePredictionDifferenceObjs'].length/summarizer.featureCount)*100)+"%) that contribute differently</b> from both instances";388                }389            }390        }391        let summaryObj = {392            "totalPredictionDifferenceStatus" : totalPredictionDifferenceStatus,393            "totalPredictionRawDifference" : totalPredictionRawDifference,394            "featurePredictionDifferenceStatus" : featurePredictionDifferenceStatus,395            "featurePredictionDifferenceObjs" : featurePredictionDifferenceObjs,396            "summarySentence" : summary397        };398        return summaryObj;399    }...

analyze.ts

Source:analyze.ts

...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({...

index.ts

Source:index.ts

...76}77export async function completeBenchmarkComparisonCheck(gitHubInstallation: Octokit, check: Octokit.ChecksCreateResponse, comparison: BenchmarkComparison, globalConfig: FrozenGlobalConfig) {78    const { repo: { repo, owner }  } = globalConfig.gitInfo;79    const comparisonComment = generateComparisonComment(comparison);80    const comparisonSummary = generateComparisonSummary(comparison, globalConfig.commentThreshold);81    const now = (new Date()).toISOString();82    const { baseCommit, targetCommit } = comparison;83    const summary = `Base commit: \`${baseCommit}\` | Target commit: \`${targetCommit}\`\n\n${comparisonSummary}`;84    await gitHubInstallation.checks.update({85        owner,86        repo,87        check_run_id: check.id,88        completed_at: now,89        conclusion: 'success',90        output: {91            title: 'Best Summary',92            summary,93            text: comparisonComment94        }...

Using AI Code Generation

1var BestPractices = require('./BestPractices.js');2var bestPractices = new BestPractices();3var comparisonSummary = bestPractices.generateComparisonSummary();4console.log(comparisonSummary);5var BestPractices = function() {6  this.generateComparisonSummary = function() {7    return "This is a comparison summary";8  }9}10module.exports = BestPractices;

Using AI Code Generation

1var BestPractices = require('./BestPractices.js');2var bestPractices = new BestPractices();3var comparisonSummary = bestPractices.generateComparisonSummary();4console.log(comparisonSummary);5var BestPractices = function() {6  this.generateComparisonSummary = function() {7    return "This is a comparison summary";8  }9}10module.exports = BestPractices;

Using AI Code Generation

1var bestBuyComparison = new BestBuyComparison();2var comparisonSummary = bestBuyComparison.generateComparisonSummary();3console.log("Comparison Summary: " + comparisonSummary);4var bestBuyComparison = new BestBuyComparison();5var comparisonSummary = bestBuyComparison.generateComparisonSummary();6console.log("Comparison Summary: " + comparisonSummary);7var bestBuyComparison = new BestBuyComparison();8var comparisonSummary = bestBuyComparison.generateComparisonSummary();9console.log("Comparison Summary: " + comparisonSummary);10var bestBuyComparison = new BestBuyComparison();11var comparisonSummary = bestBuyComparison.generateComparisonSummary();12console.log("Comparison Summary: " + comparisonSummary);13var bestBuyComparison = new BestBuyComparison();14var comparisonSummary = bestBuyComparison.generateComparisonSummary();15console.log("Comparison Summary: " + comparisonSummary);16var bestBuyComparison = new BestBuyComparison();17var comparisonSummary = bestBuyComparison.generateComparisonSummary();18console.log("Comparison Summary: " + comparisonSummary);19var bestBuyComparison = new BestBuyComparison();20var comparisonSummary = bestBuyComparison.generateComparisonSummary();21console.log("Comparison Summary: " + comparisonSummary);22var bestBuyComparison = new BestBuyComparison();23var comparisonSummary = bestBuyComparison.generateComparisonSummary();24console.log("Comparison Summary: " + comparisonSummary);25var bestBuyComparison = new BestBuyComparison();26var comparisonSummary = bestBuyComparison.generateComparisonSummary();27console.log("Comparison Summary: " + comparisonSummary);28var bestBuyComparison = new BestBuyComparison();

Using AI Code Generation

1var bestBuyComparison = require('./bestBuyComparison.js');2var bestBuyComparisonObj = new bestBuyComparison();3var productComparisonSummary = bestBuyComparisonObj.generateComparisonSummary('product1','product2','product3','product4','product5');4console.log(productComparisonSummary);5var BestBuyComparison = function () {6    this.generateComparisonSummary = function (product1, product2, product3, product4, product5) {7        var product1 = product1 || 'product1';8        var product2 = product2 || 'product2';9        var product3 = product3 || 'product3';10        var product4 = product4 || 'product4';11        var product5 = product5 || 'product5';12        var comparisonSummary = 'The best product is ' + product1 + ' followed by ' + product2 + ' and ' + product3 + ' and ' + product4 + ' and ' + product5;13        return comparisonSummary;14    };15};16module.exports = BestBuyComparison;

Using AI Code Generation

1var BestBuy = require('./BestBuy.js');2var bestBuy = new BestBuy();3var result = bestBuy.generateComparisonSummary('Guitar', 'Acoustic Guitar');4console.log(result);5var BestBuy = require('./BestBuy.js');6var bestBuy = new BestBuy();7var result = bestBuy.generateComparisonSummary('Guitar', 'Acoustic Guitar');8console.log(result);9var BestBuy = require('./BestBuy.js');10var bestBuy = new BestBuy();11var result = bestBuy.generateComparisonSummary('Guitar', 'Acoustic Guitar');12console.log(result);13var BestBuy = require('./BestBuy.js');14var bestBuy = new BestBuy();15var result = bestBuy.generateComparisonSummary('Guitar', 'Acoustic Guitar');16console.log(result);17var BestBuy = require('./BestBuy.js');18var bestBuy = new BestBuy();19var result = bestBuy.generateComparisonSummary('Guitar', 'Acoustic Guitar');20console.log(result);21var BestBuy = require('./BestBuy.js');22var bestBuy = new BestBuy();23var result = bestBuy.generateComparisonSummary('Guitar', 'Acoustic Guitar');24console.log(result);25var BestBuy = require('./BestBuy.js');26var bestBuy = new BestBuy();27var result = bestBuy.generateComparisonSummary('Guitar', 'Acoustic Guitar');28console.log(result);e

Using AI Code Generation

1var bestMatchFinder = require('./bestMatchFinder.js');2var data = require('./data.js');3var reference = require('./reference.js');4var bestMatchFinder = new bestMatchFinder.BestMatchFinder();5var summary = bestMatchFinder.generateComparisonSummary(data, reference, 'name');6console.log(summary);7var fs = require('fs');8var stream = fs.createWriteStream("test4_output.txt");9stream.once('open', function(fd) {10  stream.write(summary);11  stream.end();12});13var bestMatchFinder = require('./bestMatchFinder.js');14var data = require('./data.js');15var reference = require('./reference.js');16var bestMatchFinder = new bestMatchFinder.BestMatchFinder();17var summary = bestMatchFinder.generateComparisonSummary(data, reference, 'name', 0.7);18console.log(summary);19var fs = require('fs');20var stream = fs.createWriteStream("test5_output.txt");21stream.once('open', function(fd) {22  stream.write(summary);23  stream.end();24});25var bestMatchFinder = require('./bestMatchFinder.js');26var data = require('./data.js');27var reference = require('./reference.js');28var BestBuy = require('./BestBuy.js');29var bestBuy = new BestBuy();30var result = bestBuy.generateComparisonSummary('Guitar', 'Acoustic Guitar');31console.log(result);32var BestBuy = require('./BestBuy.js');33var bestBuy = new BestBuy();

Using AI Code Generation

1var bestMatchFinder = require('./bestMatchFinder.js');2var data = require('./data.js');3var reference = require('./reference.js');4var bestMatchFinder = new bestMatchFinder.BestMatchFinder();5var summary = bestMatchFinder.generateComparisonSummary(data, reference, 'name');6console.log(summary);7var fs = require('fs');8var stream = fs.createWriteStream("test4_output.txt");9stream.once('open', function(fd) {10  stream.write(summary);11  stream.end();12});13var bestMatchFinder = require('./bestMatchFinder.js');14var data = require('./data.js');15var reference = require('./reference.js');16var bestMatchFinder = new bestMatchFinder.BestMatchFinder();17var summary = bestMatchFinder.generateComparisonSummary(data, reference, 'name', 0.7);18console.log(summary);19var fs = require('fs');20var stream = fs.createWriteStream("test5_output.txt");21stream.once('open', function(fd) {22  stream.write(summary);23  stream.end();24});25var bestMatchFinder = require('./bestMatchFinder.js');26var data = require('./data.js');27var reference = require('./reference.js');

Automation Testing Tutorials

Learn to execute automation testing from scratch with LambdaTest Learning Hub. Right from setting up the prerequisites to run your first automation test, to following best practices and diving deeper into advanced test scenarios. LambdaTest Learning Hubs compile a list of step-by-step guides to help you be proficient with different test automation frameworks i.e. Selenium, Cypress, TestNG etc.