cabal sandbox init --sandbox=.cabal-sandbox
cabal install
# run benchmark: 'x' * n + quotes
cabal run slen
# run benchmark: quote * n
cabal run qlen
# run benchmark: 'x' * N with randomly inserted quotes * n
cabal run qcount
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January 25, 2016 19:58
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benchmarks for elm-format PRs #121 and #122
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| /dist/ | |
| /cabal.sandbox.config | |
| /.cabal-sandbox/ |
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| module Benchmarks where | |
| import Criterion (bench, nf, bgroup, Benchmark) | |
| import Criterion.Main (defaultConfig, defaultMainWith) | |
| import Criterion.Types (Config(..)) | |
| import Data.List (subsequences) | |
| import Control.DeepSeq (deepseq) | |
| import System.Random (mkStdGen, randomR) | |
| import qualified Text.Regex.Applicative as Regex | |
| import qualified Data.List.Split as Split | |
| import qualified Data.List as List | |
| sLenMain = defaultMainWith | |
| (defaultConfig { reportFile = Just "escape-slen.html" }) | |
| [ bgroup "quotes-at-end" | |
| [ bgroup "regex" $ benchSimple escapeMultiQuotesRegex | |
| , bgroup "split" $ benchSimple escapeMultiQuotesSplit | |
| ] | |
| ] | |
| qLenMain = defaultMainWith | |
| (defaultConfig { reportFile = Just "escape-qlen.html" }) | |
| [ bgroup "quotes-length" | |
| [ bgroup "regex" $ benchQuoteLength escapeMultiQuotesRegex | |
| , bgroup "split" $ benchQuoteLength escapeMultiQuotesSplit | |
| ] | |
| ] | |
| qCountMain = defaultMainWith | |
| (defaultConfig { reportFile = Just "escape-qcount.html" }) | |
| [ bgroup "quotes-count" | |
| [ bgroup "regex" $ benchQuoteCount escapeMultiQuotesRegex | |
| , bgroup "split" $ benchQuoteCount escapeMultiQuotesSplit | |
| ] | |
| ] | |
| benchSimple :: (String -> String) -> [Benchmark] | |
| benchSimple f = | |
| (map createBenchmark [0, 1000 .. 10000]) | |
| where | |
| createBenchmark n = | |
| let | |
| xs = (replicate n 'x') ++ "\"\"\"" | |
| in | |
| xs `deepseq` (bench (show n) $ nf f xs) | |
| benchQuoteLength :: (String -> String) -> [Benchmark] | |
| benchQuoteLength f = | |
| (map createBenchmark [0, 1 .. 10]) | |
| where | |
| createBenchmark n = | |
| let | |
| xs = (replicate n '"') | |
| in | |
| xs `deepseq` (bench (show n) $ nf f xs) | |
| benchQuoteCount :: (String -> String) -> [Benchmark] | |
| benchQuoteCount f = | |
| (map createBenchmark [0, 100 .. 1000]) | |
| where | |
| createBenchmark n = | |
| let | |
| (_, xs) = | |
| foldl insertQuote ((mkStdGen 1), (replicate 10000 '"')) [0..n] | |
| insertQuote (rgen, memo) _ = | |
| let | |
| (i, newgen) = randomR (0, (length memo)) rgen | |
| (pre, post) = splitAt i memo | |
| in | |
| (newgen, concat [pre, "\"\"\"", post]) | |
| in | |
| xs `deepseq` (bench (show n) $ nf f xs) | |
| showN :: String -> Int -> String | |
| showN prefix n = | |
| prefix ++ "-" ++ (show n) | |
| escapeMultiQuotesRegex = | |
| let | |
| quote = | |
| Regex.sym '"' | |
| oneOrMoreQuotes = | |
| Regex.some quote | |
| escape = | |
| ("\\\"\\\"\\" ++) . (List.intersperse '\\') | |
| in | |
| Regex.replace $ escape <$> oneOrMoreQuotes <* quote <* quote | |
| escapeMultiQuotesSplit multi = | |
| let | |
| isQuote = | |
| ('"' ==) | |
| escape :: Int -> String -> String | |
| escape i quotes@('"':'"':'"':xs) | |
| | odd i && (all isQuote xs) = | |
| concat (map (\_ -> "\\\"") quotes) | |
| escape _ x = x | |
| in | |
| Split.split (Split.condense $ Split.whenElt isQuote) multi | |
| |> zipWith escape [0..] | |
| |> concat | |
| (|>) :: a -> (a -> b) -> b | |
| x |> f = f x |
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| <!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN" "http://www.w3.org/TR/html4/loose.dtd"> | |
| <html> | |
| <head> | |
| <meta http-equiv="Content-Type" content="text/html; charset=utf-8"> | |
| <title>criterion report</title> | |
| <script language="javascript" type="text/javascript"> | |
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i=0,position;position=positions[i];i++){if(position.x==x&&position.y==y){position.active=true;return}}position={active:true,rendered:false,element:positions.length?info.element.clone():info.element,x:x,y:y};positions.push(position);position.element.css({top:Math.round(y),left:Math.round(x),"text-align":halign})};Canvas.prototype.removeText=function(layer,x,y,text,font,angle){if(text==null){var layerCache=this._textCache[layer];if(layerCache!=null){for(var styleKey in layerCache){if(hasOwnProperty.call(layerCache,styleKey)){var styleCache=layerCache[styleKey];for(var key in styleCache){if(hasOwnProperty.call(styleCache,key)){var positions=styleCache[key].positions;for(var i=0,position;position=positions[i];i++){position.active=false}}}}}}}else{var positions=this.getTextInfo(layer,text,font,angle).positions;for(var i=0,position;position=positions[i];i++){if(position.x==x&&position.y==y){position.active=false}}}};function Plot(placeholder,data_,options_,plugins){var series=[],options={colors:["#edc240","#afd8f8","#cb4b4b","#4da74d","#9440ed"],legend:{show:true,noColumns:1,labelFormatter:null,labelBoxBorderColor:"#ccc",container:null,position:"ne",margin:5,backgroundColor:null,backgroundOpacity:.85,sorted:null},xaxis:{show:null,position:"bottom",mode:null,font:null,color:null,tickColor:null,transform:null,inverseTransform:null,min:null,max:null,autoscaleMargin:null,ticks:null,tickFormatter:null,labelWidth:null,labelHeight:null,reserveSpace:null,tickLength:null,alignTicksWithAxis:null,tickDecimals:null,tickSize:null,minTickSize:null},yaxis:{autoscaleMargin:.02,position:"left"},xaxes:[],yaxes:[],series:{points:{show:false,radius:3,lineWidth:2,fill:true,fillColor:"#ffffff",symbol:"circle"},lines:{lineWidth:2,fill:false,fillColor:null,steps:false},bars:{show:false,lineWidth:2,barWidth:1,fill:true,fillColor:null,align:"left",horizontal:false,zero:true},shadowSize:3,highlightColor:null},grid:{show:true,aboveData:false,color:"#545454",backgroundColor:null,borderColor:null,tickColor:null,margin:0,labelMargin:5,axisMargin:8,borderWidth:2,minBorderMargin:null,markings:null,markingsColor:"#f4f4f4",markingsLineWidth:2,clickable:false,hoverable:false,autoHighlight:true,mouseActiveRadius:10},interaction:{redrawOverlayInterval:1e3/60},hooks:{}},surface=null,overlay=null,eventHolder=null,ctx=null,octx=null,xaxes=[],yaxes=[],plotOffset={left:0,right:0,top:0,bottom:0},plotWidth=0,plotHeight=0,hooks={processOptions:[],processRawData:[],processDatapoints:[],processOffset:[],drawBackground:[],drawSeries:[],draw:[],bindEvents:[],drawOverlay:[],shutdown:[]},plot=this;plot.setData=setData;plot.setupGrid=setupGrid;plot.draw=draw;plot.getPlaceholder=function(){return placeholder};plot.getCanvas=function(){return surface.element};plot.getPlotOffset=function(){return plotOffset};plot.width=function(){return plotWidth};plot.height=function(){return plotHeight};plot.offset=function(){var o=eventHolder.offset();o.left+=plotOffset.left;o.top+=plotOffset.top;return o};plot.getData=function(){return series};plot.getAxes=function(){var res={},i;$.each(xaxes.concat(yaxes),function(_,axis){if(axis)res[axis.direction+(axis.n!=1?axis.n:"")+"axis"]=axis});return res};plot.getXAxes=function(){return xaxes};plot.getYAxes=function(){return yaxes};plot.c2p=canvasToAxisCoords;plot.p2c=axisToCanvasCoords;plot.getOptions=function(){return options};plot.highlight=highlight;plot.unhighlight=unhighlight;plot.triggerRedrawOverlay=triggerRedrawOverlay;plot.pointOffset=function(point){return{left:parseInt(xaxes[axisNumber(point,"x")-1].p2c(+point.x)+plotOffset.left,10),top:parseInt(yaxes[axisNumber(point,"y")-1].p2c(+point.y)+plotOffset.top,10)}};plot.shutdown=shutdown;plot.destroy=function(){shutdown();placeholder.removeData("plot").empty();series=[];options=null;surface=null;overlay=null;eventHolder=null;ctx=null;octx=null;xaxes=[];yaxes=[];hooks=null;highlights=[];plot=null};plot.resize=function(){var width=placeholder.width(),height=placeholder.height();surface.resize(width,height);overlay.resize(width,height)};plot.hooks=hooks;initPlugins(plot);parseOptions(options_);setupCanvases();setData(data_);setupGrid();draw();bindEvents();function executeHooks(hook,args){args=[plot].concat(args);for(var i=0;i<hook.length;++i)hook[i].apply(this,args)}function initPlugins(){var classes={Canvas:Canvas};for(var i=0;i<plugins.length;++i){var p=plugins[i];p.init(plot,classes);if(p.options)$.extend(true,options,p.options)}}function parseOptions(opts){$.extend(true,options,opts);if(opts&&opts.colors){options.colors=opts.colors}if(options.xaxis.color==null)options.xaxis.color=$.color.parse(options.grid.color).scale("a",.22).toString();if(options.yaxis.color==null)options.yaxis.color=$.color.parse(options.grid.color).scale("a",.22).toString();if(options.xaxis.tickColor==null)options.xaxis.tickColor=options.grid.tickColor||options.xaxis.color;if(options.yaxis.tickColor==null)options.yaxis.tickColor=options.grid.tickColor||options.yaxis.color;if(options.grid.borderColor==null)options.grid.borderColor=options.grid.color;if(options.grid.tickColor==null)options.grid.tickColor=$.color.parse(options.grid.color).scale("a",.22).toString();var i,axisOptions,axisCount,fontSize=placeholder.css("font-size"),fontSizeDefault=fontSize?+fontSize.replace("px",""):13,fontDefaults={style:placeholder.css("font-style"),size:Math.round(.8*fontSizeDefault),variant:placeholder.css("font-variant"),weight:placeholder.css("font-weight"),family:placeholder.css("font-family")};axisCount=options.xaxes.length||1;for(i=0;i<axisCount;++i){axisOptions=options.xaxes[i];if(axisOptions&&!axisOptions.tickColor){axisOptions.tickColor=axisOptions.color}axisOptions=$.extend(true,{},options.xaxis,axisOptions);options.xaxes[i]=axisOptions;if(axisOptions.font){axisOptions.font=$.extend({},fontDefaults,axisOptions.font);if(!axisOptions.font.color){axisOptions.font.color=axisOptions.color}if(!axisOptions.font.lineHeight){axisOptions.font.lineHeight=Math.round(axisOptions.font.size*1.15)}}}axisCount=options.yaxes.length||1;for(i=0;i<axisCount;++i){axisOptions=options.yaxes[i];if(axisOptions&&!axisOptions.tickColor){axisOptions.tickColor=axisOptions.color}axisOptions=$.extend(true,{},options.yaxis,axisOptions);options.yaxes[i]=axisOptions;if(axisOptions.font){axisOptions.font=$.extend({},fontDefaults,axisOptions.font);if(!axisOptions.font.color){axisOptions.font.color=axisOptions.color}if(!axisOptions.font.lineHeight){axisOptions.font.lineHeight=Math.round(axisOptions.font.size*1.15)}}}if(options.xaxis.noTicks&&options.xaxis.ticks==null)options.xaxis.ticks=options.xaxis.noTicks;if(options.yaxis.noTicks&&options.yaxis.ticks==null)options.yaxis.ticks=options.yaxis.noTicks;if(options.x2axis){options.xaxes[1]=$.extend(true,{},options.xaxis,options.x2axis);options.xaxes[1].position="top";if(options.x2axis.min==null){options.xaxes[1].min=null}if(options.x2axis.max==null){options.xaxes[1].max=null}}if(options.y2axis){options.yaxes[1]=$.extend(true,{},options.yaxis,options.y2axis);options.yaxes[1].position="right";if(options.y2axis.min==null){options.yaxes[1].min=null}if(options.y2axis.max==null){options.yaxes[1].max=null}}if(options.grid.coloredAreas)options.grid.markings=options.grid.coloredAreas;if(options.grid.coloredAreasColor)options.grid.markingsColor=options.grid.coloredAreasColor;if(options.lines)$.extend(true,options.series.lines,options.lines);if(options.points)$.extend(true,options.series.points,options.points);if(options.bars)$.extend(true,options.series.bars,options.bars);if(options.shadowSize!=null)options.series.shadowSize=options.shadowSize;if(options.highlightColor!=null)options.series.highlightColor=options.highlightColor;for(i=0;i<options.xaxes.length;++i)getOrCreateAxis(xaxes,i+1).options=options.xaxes[i];for(i=0;i<options.yaxes.length;++i)getOrCreateAxis(yaxes,i+1).options=options.yaxes[i];for(var n in hooks)if(options.hooks[n]&&options.hooks[n].length)hooks[n]=hooks[n].concat(options.hooks[n]);executeHooks(hooks.processOptions,[options])}function setData(d){series=parseData(d);fillInSeriesOptions();processData()}function parseData(d){var res=[];for(var i=0;i<d.length;++i){var s=$.extend(true,{},options.series);if(d[i].data!=null){s.data=d[i].data;delete d[i].data;$.extend(true,s,d[i]);d[i].data=s.data}else s.data=d[i];res.push(s)}return res}function axisNumber(obj,coord){var a=obj[coord+"axis"];if(typeof a=="object")a=a.n;if(typeof a!="number")a=1;return a}function allAxes(){return $.grep(xaxes.concat(yaxes),function(a){return a})}function canvasToAxisCoords(pos){var res={},i,axis;for(i=0;i<xaxes.length;++i){axis=xaxes[i];if(axis&&axis.used)res["x"+axis.n]=axis.c2p(pos.left)}for(i=0;i<yaxes.length;++i){axis=yaxes[i];if(axis&&axis.used)res["y"+axis.n]=axis.c2p(pos.top)}if(res.x1!==undefined)res.x=res.x1;if(res.y1!==undefined)res.y=res.y1;return res}function axisToCanvasCoords(pos){var res={},i,axis,key;for(i=0;i<xaxes.length;++i){axis=xaxes[i];if(axis&&axis.used){key="x"+axis.n;if(pos[key]==null&&axis.n==1)key="x";if(pos[key]!=null){res.left=axis.p2c(pos[key]);break}}}for(i=0;i<yaxes.length;++i){axis=yaxes[i];if(axis&&axis.used){key="y"+axis.n;if(pos[key]==null&&axis.n==1)key="y";if(pos[key]!=null){res.top=axis.p2c(pos[key]);break}}}return res}function getOrCreateAxis(axes,number){if(!axes[number-1])axes[number-1]={n:number,direction:axes==xaxes?"x":"y",options:$.extend(true,{},axes==xaxes?options.xaxis:options.yaxis)};return axes[number-1]}function fillInSeriesOptions(){var neededColors=series.length,maxIndex=-1,i;for(i=0;i<series.length;++i){var sc=series[i].color;if(sc!=null){neededColors--;if(typeof sc=="number"&&sc>maxIndex){maxIndex=sc}}}if(neededColors<=maxIndex){neededColors=maxIndex+1}var c,colors=[],colorPool=options.colors,colorPoolSize=colorPool.length,variation=0;for(i=0;i<neededColors;i++){c=$.color.parse(colorPool[i%colorPoolSize]||"#666");if(i%colorPoolSize==0&&i){if(variation>=0){if(variation<.5){variation=-variation-.2}else variation=0}else variation=-variation}colors[i]=c.scale("rgb",1+variation)}var colori=0,s;for(i=0;i<series.length;++i){s=series[i];if(s.color==null){s.color=colors[colori].toString();++colori}else if(typeof s.color=="number")s.color=colors[s.color].toString();if(s.lines.show==null){var v,show=true;for(v in s)if(s[v]&&s[v].show){show=false;break}if(show)s.lines.show=true}if(s.lines.zero==null){s.lines.zero=!!s.lines.fill}s.xaxis=getOrCreateAxis(xaxes,axisNumber(s,"x"));s.yaxis=getOrCreateAxis(yaxes,axisNumber(s,"y"))}}function processData(){var topSentry=Number.POSITIVE_INFINITY,bottomSentry=Number.NEGATIVE_INFINITY,fakeInfinity=Number.MAX_VALUE,i,j,k,m,length,s,points,ps,x,y,axis,val,f,p,data,format;function updateAxis(axis,min,max){if(min<axis.datamin&&min!=-fakeInfinity)axis.datamin=min;if(max>axis.datamax&&max!=fakeInfinity)axis.datamax=max}$.each(allAxes(),function(_,axis){axis.datamin=topSentry;axis.datamax=bottomSentry;axis.used=false});for(i=0;i<series.length;++i){s=series[i];s.datapoints={points:[]};executeHooks(hooks.processRawData,[s,s.data,s.datapoints])}for(i=0;i<series.length;++i){s=series[i];data=s.data;format=s.datapoints.format;if(!format){format=[];format.push({x:true,number:true,required:true});format.push({y:true,number:true,required:true});if(s.bars.show||s.lines.show&&s.lines.fill){var autoscale=!!(s.bars.show&&s.bars.zero||s.lines.show&&s.lines.zero);format.push({y:true,number:true,required:false,defaultValue:0,autoscale:autoscale});if(s.bars.horizontal){delete format[format.length-1].y;format[format.length-1].x=true}}s.datapoints.format=format}if(s.datapoints.pointsize!=null)continue;s.datapoints.pointsize=format.length;ps=s.datapoints.pointsize;points=s.datapoints.points;var insertSteps=s.lines.show&&s.lines.steps;s.xaxis.used=s.yaxis.used=true;for(j=k=0;j<data.length;++j,k+=ps){p=data[j];var nullify=p==null;if(!nullify){for(m=0;m<ps;++m){val=p[m];f=format[m];if(f){if(f.number&&val!=null){val=+val;if(isNaN(val))val=null;else if(val==Infinity)val=fakeInfinity;else if(val==-Infinity)val=-fakeInfinity}if(val==null){if(f.required)nullify=true;if(f.defaultValue!=null)val=f.defaultValue}}points[k+m]=val}}if(nullify){for(m=0;m<ps;++m){val=points[k+m];if(val!=null){f=format[m];if(f.autoscale!==false){if(f.x){updateAxis(s.xaxis,val,val)}if(f.y){updateAxis(s.yaxis,val,val)}}}points[k+m]=null}}else{if(insertSteps&&k>0&&points[k-ps]!=null&&points[k-ps]!=points[k]&&points[k-ps+1]!=points[k+1]){for(m=0;m<ps;++m)points[k+ps+m]=points[k+m];points[k+1]=points[k-ps+1];k+=ps}}}}for(i=0;i<series.length;++i){s=series[i];executeHooks(hooks.processDatapoints,[s,s.datapoints])}for(i=0;i<series.length;++i){s=series[i];points=s.datapoints.points;ps=s.datapoints.pointsize;format=s.datapoints.format;var xmin=topSentry,ymin=topSentry,xmax=bottomSentry,ymax=bottomSentry;for(j=0;j<points.length;j+=ps){if(points[j]==null)continue;for(m=0;m<ps;++m){val=points[j+m];f=format[m];if(!f||f.autoscale===false||val==fakeInfinity||val==-fakeInfinity)continue;if(f.x){if(val<xmin)xmin=val;if(val>xmax)xmax=val}if(f.y){if(val<ymin)ymin=val;if(val>ymax)ymax=val}}}if(s.bars.show){var delta;switch(s.bars.align){case"left":delta=0;break;case"right":delta=-s.bars.barWidth;break;default:delta=-s.bars.barWidth/2}if(s.bars.horizontal){ymin+=delta;ymax+=delta+s.bars.barWidth}else{xmin+=delta;xmax+=delta+s.bars.barWidth}}updateAxis(s.xaxis,xmin,xmax);updateAxis(s.yaxis,ymin,ymax)}$.each(allAxes(),function(_,axis){if(axis.datamin==topSentry)axis.datamin=null;if(axis.datamax==bottomSentry)axis.datamax=null})}function setupCanvases(){placeholder.css("padding",0).children().filter(function(){return!$(this).hasClass("flot-overlay")&&!$(this).hasClass("flot-base")}).remove();if(placeholder.css("position")=="static")placeholder.css("position","relative");surface=new Canvas("flot-base",placeholder);overlay=new Canvas("flot-overlay",placeholder);ctx=surface.context;octx=overlay.context;eventHolder=$(overlay.element).unbind();var existing=placeholder.data("plot");if(existing){existing.shutdown();overlay.clear()}placeholder.data("plot",plot)}function bindEvents(){if(options.grid.hoverable){eventHolder.mousemove(onMouseMove);eventHolder.bind("mouseleave",onMouseLeave)}if(options.grid.clickable)eventHolder.click(onClick);executeHooks(hooks.bindEvents,[eventHolder])}function shutdown(){if(redrawTimeout)clearTimeout(redrawTimeout);eventHolder.unbind("mousemove",onMouseMove);eventHolder.unbind("mouseleave",onMouseLeave);eventHolder.unbind("click",onClick);executeHooks(hooks.shutdown,[eventHolder])}function setTransformationHelpers(axis){function identity(x){return x}var s,m,t=axis.options.transform||identity,it=axis.options.inverseTransform;if(axis.direction=="x"){s=axis.scale=plotWidth/Math.abs(t(axis.max)-t(axis.min));m=Math.min(t(axis.max),t(axis.min))}else{s=axis.scale=plotHeight/Math.abs(t(axis.max)-t(axis.min));s=-s;m=Math.max(t(axis.max),t(axis.min))}if(t==identity)axis.p2c=function(p){return(p-m)*s};else axis.p2c=function(p){return(t(p)-m)*s};if(!it)axis.c2p=function(c){return m+c/s};else axis.c2p=function(c){return it(m+c/s)}}function measureTickLabels(axis){var opts=axis.options,ticks=axis.ticks||[],labelWidth=opts.labelWidth||0,labelHeight=opts.labelHeight||0,maxWidth=labelWidth||(axis.direction=="x"?Math.floor(surface.width/(ticks.length||1)):null),legacyStyles=axis.direction+"Axis "+axis.direction+axis.n+"Axis",layer="flot-"+axis.direction+"-axis flot-"+axis.direction+axis.n+"-axis "+legacyStyles,font=opts.font||"flot-tick-label tickLabel";for(var i=0;i<ticks.length;++i){var t=ticks[i];if(!t.label)continue;var info=surface.getTextInfo(layer,t.label,font,null,maxWidth);labelWidth=Math.max(labelWidth,info.width);labelHeight=Math.max(labelHeight,info.height)}axis.labelWidth=opts.labelWidth||labelWidth;axis.labelHeight=opts.labelHeight||labelHeight}function allocateAxisBoxFirstPhase(axis){var lw=axis.labelWidth,lh=axis.labelHeight,pos=axis.options.position,isXAxis=axis.direction==="x",tickLength=axis.options.tickLength,axisMargin=options.grid.axisMargin,padding=options.grid.labelMargin,innermost=true,outermost=true,first=true,found=false;$.each(isXAxis?xaxes:yaxes,function(i,a){if(a&&(a.show||a.reserveSpace)){if(a===axis){found=true}else if(a.options.position===pos){if(found){outermost=false}else{innermost=false}}if(!found){first=false}}});if(outermost){axisMargin=0}if(tickLength==null){tickLength=first?"full":5}if(!isNaN(+tickLength))padding+=+tickLength;if(isXAxis){lh+=padding;if(pos=="bottom"){plotOffset.bottom+=lh+axisMargin;axis.box={top:surface.height-plotOffset.bottom,height:lh}}else{axis.box={top:plotOffset.top+axisMargin,height:lh};plotOffset.top+=lh+axisMargin}}else{lw+=padding;if(pos=="left"){axis.box={left:plotOffset.left+axisMargin,width:lw};plotOffset.left+=lw+axisMargin}else{plotOffset.right+=lw+axisMargin;axis.box={left:surface.width-plotOffset.right,width:lw}}}axis.position=pos;axis.tickLength=tickLength;axis.box.padding=padding;axis.innermost=innermost}function allocateAxisBoxSecondPhase(axis){if(axis.direction=="x"){axis.box.left=plotOffset.left-axis.labelWidth/2;axis.box.width=surface.width-plotOffset.left-plotOffset.right+axis.labelWidth}else{axis.box.top=plotOffset.top-axis.labelHeight/2;axis.box.height=surface.height-plotOffset.bottom-plotOffset.top+axis.labelHeight}}function adjustLayoutForThingsStickingOut(){var minMargin=options.grid.minBorderMargin,axis,i;if(minMargin==null){minMargin=0;for(i=0;i<series.length;++i)minMargin=Math.max(minMargin,2*(series[i].points.radius+series[i].points.lineWidth/2))}var margins={left:minMargin,right:minMargin,top:minMargin,bottom:minMargin};$.each(allAxes(),function(_,axis){if(axis.reserveSpace&&axis.ticks&&axis.ticks.length){if(axis.direction==="x"){margins.left=Math.max(margins.left,axis.labelWidth/2);margins.right=Math.max(margins.right,axis.labelWidth/2)}else{margins.bottom=Math.max(margins.bottom,axis.labelHeight/2);margins.top=Math.max(margins.top,axis.labelHeight/2)}}});plotOffset.left=Math.ceil(Math.max(margins.left,plotOffset.left));plotOffset.right=Math.ceil(Math.max(margins.right,plotOffset.right));plotOffset.top=Math.ceil(Math.max(margins.top,plotOffset.top));plotOffset.bottom=Math.ceil(Math.max(margins.bottom,plotOffset.bottom))}function setupGrid(){var i,axes=allAxes(),showGrid=options.grid.show;for(var a in plotOffset){var margin=options.grid.margin||0;plotOffset[a]=typeof margin=="number"?margin:margin[a]||0}executeHooks(hooks.processOffset,[plotOffset]);for(var a in plotOffset){if(typeof options.grid.borderWidth=="object"){plotOffset[a]+=showGrid?options.grid.borderWidth[a]:0}else{plotOffset[a]+=showGrid?options.grid.borderWidth:0}}$.each(axes,function(_,axis){var axisOpts=axis.options;axis.show=axisOpts.show==null?axis.used:axisOpts.show;axis.reserveSpace=axisOpts.reserveSpace==null?axis.show:axisOpts.reserveSpace;setRange(axis)});if(showGrid){var allocatedAxes=$.grep(axes,function(axis){return axis.show||axis.reserveSpace});$.each(allocatedAxes,function(_,axis){setupTickGeneration(axis);setTicks(axis);snapRangeToTicks(axis,axis.ticks);measureTickLabels(axis)});for(i=allocatedAxes.length-1;i>=0;--i)allocateAxisBoxFirstPhase(allocatedAxes[i]);adjustLayoutForThingsStickingOut();$.each(allocatedAxes,function(_,axis){allocateAxisBoxSecondPhase(axis)})}plotWidth=surface.width-plotOffset.left-plotOffset.right;plotHeight=surface.height-plotOffset.bottom-plotOffset.top;$.each(axes,function(_,axis){setTransformationHelpers(axis)});if(showGrid){drawAxisLabels()}insertLegend()}function setRange(axis){var opts=axis.options,min=+(opts.min!=null?opts.min:axis.datamin),max=+(opts.max!=null?opts.max:axis.datamax),delta=max-min;if(delta==0){var widen=max==0?1:.01;if(opts.min==null)min-=widen;if(opts.max==null||opts.min!=null)max+=widen}else{var margin=opts.autoscaleMargin;if(margin!=null){if(opts.min==null){min-=delta*margin;if(min<0&&axis.datamin!=null&&axis.datamin>=0)min=0}if(opts.max==null){max+=delta*margin;if(max>0&&axis.datamax!=null&&axis.datamax<=0)max=0}}}axis.min=min;axis.max=max}function setupTickGeneration(axis){var opts=axis.options;var noTicks;if(typeof opts.ticks=="number"&&opts.ticks>0)noTicks=opts.ticks;else noTicks=.3*Math.sqrt(axis.direction=="x"?surface.width:surface.height);var delta=(axis.max-axis.min)/noTicks,dec=-Math.floor(Math.log(delta)/Math.LN10),maxDec=opts.tickDecimals;if(maxDec!=null&&dec>maxDec){dec=maxDec}var magn=Math.pow(10,-dec),norm=delta/magn,size;if(norm<1.5){size=1}else if(norm<3){size=2;if(norm>2.25&&(maxDec==null||dec+1<=maxDec)){size=2.5;++dec}}else if(norm<7.5){size=5}else{size=10}size*=magn;if(opts.minTickSize!=null&&size<opts.minTickSize){size=opts.minTickSize}axis.delta=delta;axis.tickDecimals=Math.max(0,maxDec!=null?maxDec:dec);axis.tickSize=opts.tickSize||size;if(opts.mode=="time"&&!axis.tickGenerator){throw new Error("Time mode requires the flot.time plugin.")}if(!axis.tickGenerator){axis.tickGenerator=function(axis){var ticks=[],start=floorInBase(axis.min,axis.tickSize),i=0,v=Number.NaN,prev;do{prev=v;v=start+i*axis.tickSize;ticks.push(v);++i}while(v<axis.max&&v!=prev);return ticks};axis.tickFormatter=function(value,axis){var factor=axis.tickDecimals?Math.pow(10,axis.tickDecimals):1;var formatted=""+Math.round(value*factor)/factor;if(axis.tickDecimals!=null){var decimal=formatted.indexOf(".");var precision=decimal==-1?0:formatted.length-decimal-1;if(precision<axis.tickDecimals){return(precision?formatted:formatted+".")+(""+factor).substr(1,axis.tickDecimals-precision)}}return formatted}}if($.isFunction(opts.tickFormatter))axis.tickFormatter=function(v,axis){return""+opts.tickFormatter(v,axis)};if(opts.alignTicksWithAxis!=null){var otherAxis=(axis.direction=="x"?xaxes:yaxes)[opts.alignTicksWithAxis-1];if(otherAxis&&otherAxis.used&&otherAxis!=axis){var niceTicks=axis.tickGenerator(axis);if(niceTicks.length>0){if(opts.min==null)axis.min=Math.min(axis.min,niceTicks[0]);if(opts.max==null&&niceTicks.length>1)axis.max=Math.max(axis.max,niceTicks[niceTicks.length-1])}axis.tickGenerator=function(axis){var ticks=[],v,i;for(i=0;i<otherAxis.ticks.length;++i){v=(otherAxis.ticks[i].v-otherAxis.min)/(otherAxis.max-otherAxis.min);v=axis.min+v*(axis.max-axis.min);ticks.push(v)}return ticks};if(!axis.mode&&opts.tickDecimals==null){var extraDec=Math.max(0,-Math.floor(Math.log(axis.delta)/Math.LN10)+1),ts=axis.tickGenerator(axis);if(!(ts.length>1&&/\..*0$/.test((ts[1]-ts[0]).toFixed(extraDec))))axis.tickDecimals=extraDec}}}}function setTicks(axis){var oticks=axis.options.ticks,ticks=[];if(oticks==null||typeof oticks=="number"&&oticks>0)ticks=axis.tickGenerator(axis);else if(oticks){if($.isFunction(oticks))ticks=oticks(axis);else ticks=oticks}var i,v;axis.ticks=[];for(i=0;i<ticks.length;++i){var label=null;var t=ticks[i];if(typeof t=="object"){v=+t[0];if(t.length>1)label=t[1]}else v=+t;if(label==null)label=axis.tickFormatter(v,axis);if(!isNaN(v))axis.ticks.push({v:v,label:label})}}function snapRangeToTicks(axis,ticks){if(axis.options.autoscaleMargin&&ticks.length>0){if(axis.options.min==null)axis.min=Math.min(axis.min,ticks[0].v);if(axis.options.max==null&&ticks.length>1)axis.max=Math.max(axis.max,ticks[ticks.length-1].v)}}function draw(){surface.clear();executeHooks(hooks.drawBackground,[ctx]);var grid=options.grid;if(grid.show&&grid.backgroundColor)drawBackground();if(grid.show&&!grid.aboveData){drawGrid()}for(var i=0;i<series.length;++i){executeHooks(hooks.drawSeries,[ctx,series[i]]);drawSeries(series[i])}executeHooks(hooks.draw,[ctx]);if(grid.show&&grid.aboveData){drawGrid()}surface.render();triggerRedrawOverlay()}function extractRange(ranges,coord){var axis,from,to,key,axes=allAxes();for(var i=0;i<axes.length;++i){axis=axes[i];if(axis.direction==coord){key=coord+axis.n+"axis";if(!ranges[key]&&axis.n==1)key=coord+"axis";if(ranges[key]){from=ranges[key].from;to=ranges[key].to;break}}}if(!ranges[key]){axis=coord=="x"?xaxes[0]:yaxes[0];from=ranges[coord+"1"];to=ranges[coord+"2"]}if(from!=null&&to!=null&&from>to){var tmp=from;from=to;to=tmp}return{from:from,to:to,axis:axis}}function drawBackground(){ctx.save();ctx.translate(plotOffset.left,plotOffset.top);ctx.fillStyle=getColorOrGradient(options.grid.backgroundColor,plotHeight,0,"rgba(255, 255, 255, 0)");ctx.fillRect(0,0,plotWidth,plotHeight);ctx.restore()}function drawGrid(){var i,axes,bw,bc;ctx.save();ctx.translate(plotOffset.left,plotOffset.top);var markings=options.grid.markings;if(markings){if($.isFunction(markings)){axes=plot.getAxes();axes.xmin=axes.xaxis.min;axes.xmax=axes.xaxis.max;axes.ymin=axes.yaxis.min;axes.ymax=axes.yaxis.max;markings=markings(axes)}for(i=0;i<markings.length;++i){var m=markings[i],xrange=extractRange(m,"x"),yrange=extractRange(m,"y");if(xrange.from==null)xrange.from=xrange.axis.min;if(xrange.to==null)xrange.to=xrange.axis.max; | |
| if(yrange.from==null)yrange.from=yrange.axis.min;if(yrange.to==null)yrange.to=yrange.axis.max;if(xrange.to<xrange.axis.min||xrange.from>xrange.axis.max||yrange.to<yrange.axis.min||yrange.from>yrange.axis.max)continue;xrange.from=Math.max(xrange.from,xrange.axis.min);xrange.to=Math.min(xrange.to,xrange.axis.max);yrange.from=Math.max(yrange.from,yrange.axis.min);yrange.to=Math.min(yrange.to,yrange.axis.max);var xequal=xrange.from===xrange.to,yequal=yrange.from===yrange.to;if(xequal&&yequal){continue}xrange.from=Math.floor(xrange.axis.p2c(xrange.from));xrange.to=Math.floor(xrange.axis.p2c(xrange.to));yrange.from=Math.floor(yrange.axis.p2c(yrange.from));yrange.to=Math.floor(yrange.axis.p2c(yrange.to));if(xequal||yequal){var lineWidth=m.lineWidth||options.grid.markingsLineWidth,subPixel=lineWidth%2?.5:0;ctx.beginPath();ctx.strokeStyle=m.color||options.grid.markingsColor;ctx.lineWidth=lineWidth;if(xequal){ctx.moveTo(xrange.to+subPixel,yrange.from);ctx.lineTo(xrange.to+subPixel,yrange.to)}else{ctx.moveTo(xrange.from,yrange.to+subPixel);ctx.lineTo(xrange.to,yrange.to+subPixel)}ctx.stroke()}else{ctx.fillStyle=m.color||options.grid.markingsColor;ctx.fillRect(xrange.from,yrange.to,xrange.to-xrange.from,yrange.from-yrange.to)}}}axes=allAxes();bw=options.grid.borderWidth;for(var j=0;j<axes.length;++j){var axis=axes[j],box=axis.box,t=axis.tickLength,x,y,xoff,yoff;if(!axis.show||axis.ticks.length==0)continue;ctx.lineWidth=1;if(axis.direction=="x"){x=0;if(t=="full")y=axis.position=="top"?0:plotHeight;else y=box.top-plotOffset.top+(axis.position=="top"?box.height:0)}else{y=0;if(t=="full")x=axis.position=="left"?0:plotWidth;else x=box.left-plotOffset.left+(axis.position=="left"?box.width:0)}if(!axis.innermost){ctx.strokeStyle=axis.options.color;ctx.beginPath();xoff=yoff=0;if(axis.direction=="x")xoff=plotWidth+1;else yoff=plotHeight+1;if(ctx.lineWidth==1){if(axis.direction=="x"){y=Math.floor(y)+.5}else{x=Math.floor(x)+.5}}ctx.moveTo(x,y);ctx.lineTo(x+xoff,y+yoff);ctx.stroke()}ctx.strokeStyle=axis.options.tickColor;ctx.beginPath();for(i=0;i<axis.ticks.length;++i){var v=axis.ticks[i].v;xoff=yoff=0;if(isNaN(v)||v<axis.min||v>axis.max||t=="full"&&(typeof bw=="object"&&bw[axis.position]>0||bw>0)&&(v==axis.min||v==axis.max))continue;if(axis.direction=="x"){x=axis.p2c(v);yoff=t=="full"?-plotHeight:t;if(axis.position=="top")yoff=-yoff}else{y=axis.p2c(v);xoff=t=="full"?-plotWidth:t;if(axis.position=="left")xoff=-xoff}if(ctx.lineWidth==1){if(axis.direction=="x")x=Math.floor(x)+.5;else y=Math.floor(y)+.5}ctx.moveTo(x,y);ctx.lineTo(x+xoff,y+yoff)}ctx.stroke()}if(bw){bc=options.grid.borderColor;if(typeof bw=="object"||typeof bc=="object"){if(typeof bw!=="object"){bw={top:bw,right:bw,bottom:bw,left:bw}}if(typeof bc!=="object"){bc={top:bc,right:bc,bottom:bc,left:bc}}if(bw.top>0){ctx.strokeStyle=bc.top;ctx.lineWidth=bw.top;ctx.beginPath();ctx.moveTo(0-bw.left,0-bw.top/2);ctx.lineTo(plotWidth,0-bw.top/2);ctx.stroke()}if(bw.right>0){ctx.strokeStyle=bc.right;ctx.lineWidth=bw.right;ctx.beginPath();ctx.moveTo(plotWidth+bw.right/2,0-bw.top);ctx.lineTo(plotWidth+bw.right/2,plotHeight);ctx.stroke()}if(bw.bottom>0){ctx.strokeStyle=bc.bottom;ctx.lineWidth=bw.bottom;ctx.beginPath();ctx.moveTo(plotWidth+bw.right,plotHeight+bw.bottom/2);ctx.lineTo(0,plotHeight+bw.bottom/2);ctx.stroke()}if(bw.left>0){ctx.strokeStyle=bc.left;ctx.lineWidth=bw.left;ctx.beginPath();ctx.moveTo(0-bw.left/2,plotHeight+bw.bottom);ctx.lineTo(0-bw.left/2,0);ctx.stroke()}}else{ctx.lineWidth=bw;ctx.strokeStyle=options.grid.borderColor;ctx.strokeRect(-bw/2,-bw/2,plotWidth+bw,plotHeight+bw)}}ctx.restore()}function drawAxisLabels(){$.each(allAxes(),function(_,axis){var box=axis.box,legacyStyles=axis.direction+"Axis "+axis.direction+axis.n+"Axis",layer="flot-"+axis.direction+"-axis flot-"+axis.direction+axis.n+"-axis "+legacyStyles,font=axis.options.font||"flot-tick-label tickLabel",tick,x,y,halign,valign;surface.removeText(layer);if(!axis.show||axis.ticks.length==0)return;for(var i=0;i<axis.ticks.length;++i){tick=axis.ticks[i];if(!tick.label||tick.v<axis.min||tick.v>axis.max)continue;if(axis.direction=="x"){halign="center";x=plotOffset.left+axis.p2c(tick.v);if(axis.position=="bottom"){y=box.top+box.padding}else{y=box.top+box.height-box.padding;valign="bottom"}}else{valign="middle";y=plotOffset.top+axis.p2c(tick.v);if(axis.position=="left"){x=box.left+box.width-box.padding;halign="right"}else{x=box.left+box.padding}}surface.addText(layer,x,y,tick.label,font,null,null,halign,valign)}})}function drawSeries(series){if(series.lines.show)drawSeriesLines(series);if(series.bars.show)drawSeriesBars(series);if(series.points.show)drawSeriesPoints(series)}function drawSeriesLines(series){function plotLine(datapoints,xoffset,yoffset,axisx,axisy){var points=datapoints.points,ps=datapoints.pointsize,prevx=null,prevy=null;ctx.beginPath();for(var i=ps;i<points.length;i+=ps){var x1=points[i-ps],y1=points[i-ps+1],x2=points[i],y2=points[i+1];if(x1==null||x2==null)continue;if(y1<=y2&&y1<axisy.min){if(y2<axisy.min)continue;x1=(axisy.min-y1)/(y2-y1)*(x2-x1)+x1;y1=axisy.min}else if(y2<=y1&&y2<axisy.min){if(y1<axisy.min)continue;x2=(axisy.min-y1)/(y2-y1)*(x2-x1)+x1;y2=axisy.min}if(y1>=y2&&y1>axisy.max){if(y2>axisy.max)continue;x1=(axisy.max-y1)/(y2-y1)*(x2-x1)+x1;y1=axisy.max}else if(y2>=y1&&y2>axisy.max){if(y1>axisy.max)continue;x2=(axisy.max-y1)/(y2-y1)*(x2-x1)+x1;y2=axisy.max}if(x1<=x2&&x1<axisx.min){if(x2<axisx.min)continue;y1=(axisx.min-x1)/(x2-x1)*(y2-y1)+y1;x1=axisx.min}else if(x2<=x1&&x2<axisx.min){if(x1<axisx.min)continue;y2=(axisx.min-x1)/(x2-x1)*(y2-y1)+y1;x2=axisx.min}if(x1>=x2&&x1>axisx.max){if(x2>axisx.max)continue;y1=(axisx.max-x1)/(x2-x1)*(y2-y1)+y1;x1=axisx.max}else if(x2>=x1&&x2>axisx.max){if(x1>axisx.max)continue;y2=(axisx.max-x1)/(x2-x1)*(y2-y1)+y1;x2=axisx.max}if(x1!=prevx||y1!=prevy)ctx.moveTo(axisx.p2c(x1)+xoffset,axisy.p2c(y1)+yoffset);prevx=x2;prevy=y2;ctx.lineTo(axisx.p2c(x2)+xoffset,axisy.p2c(y2)+yoffset)}ctx.stroke()}function plotLineArea(datapoints,axisx,axisy){var points=datapoints.points,ps=datapoints.pointsize,bottom=Math.min(Math.max(0,axisy.min),axisy.max),i=0,top,areaOpen=false,ypos=1,segmentStart=0,segmentEnd=0;while(true){if(ps>0&&i>points.length+ps)break;i+=ps;var x1=points[i-ps],y1=points[i-ps+ypos],x2=points[i],y2=points[i+ypos];if(areaOpen){if(ps>0&&x1!=null&&x2==null){segmentEnd=i;ps=-ps;ypos=2;continue}if(ps<0&&i==segmentStart+ps){ctx.fill();areaOpen=false;ps=-ps;ypos=1;i=segmentStart=segmentEnd+ps;continue}}if(x1==null||x2==null)continue;if(x1<=x2&&x1<axisx.min){if(x2<axisx.min)continue;y1=(axisx.min-x1)/(x2-x1)*(y2-y1)+y1;x1=axisx.min}else if(x2<=x1&&x2<axisx.min){if(x1<axisx.min)continue;y2=(axisx.min-x1)/(x2-x1)*(y2-y1)+y1;x2=axisx.min}if(x1>=x2&&x1>axisx.max){if(x2>axisx.max)continue;y1=(axisx.max-x1)/(x2-x1)*(y2-y1)+y1;x1=axisx.max}else if(x2>=x1&&x2>axisx.max){if(x1>axisx.max)continue;y2=(axisx.max-x1)/(x2-x1)*(y2-y1)+y1;x2=axisx.max}if(!areaOpen){ctx.beginPath();ctx.moveTo(axisx.p2c(x1),axisy.p2c(bottom));areaOpen=true}if(y1>=axisy.max&&y2>=axisy.max){ctx.lineTo(axisx.p2c(x1),axisy.p2c(axisy.max));ctx.lineTo(axisx.p2c(x2),axisy.p2c(axisy.max));continue}else if(y1<=axisy.min&&y2<=axisy.min){ctx.lineTo(axisx.p2c(x1),axisy.p2c(axisy.min));ctx.lineTo(axisx.p2c(x2),axisy.p2c(axisy.min));continue}var x1old=x1,x2old=x2;if(y1<=y2&&y1<axisy.min&&y2>=axisy.min){x1=(axisy.min-y1)/(y2-y1)*(x2-x1)+x1;y1=axisy.min}else if(y2<=y1&&y2<axisy.min&&y1>=axisy.min){x2=(axisy.min-y1)/(y2-y1)*(x2-x1)+x1;y2=axisy.min}if(y1>=y2&&y1>axisy.max&&y2<=axisy.max){x1=(axisy.max-y1)/(y2-y1)*(x2-x1)+x1;y1=axisy.max}else if(y2>=y1&&y2>axisy.max&&y1<=axisy.max){x2=(axisy.max-y1)/(y2-y1)*(x2-x1)+x1;y2=axisy.max}if(x1!=x1old){ctx.lineTo(axisx.p2c(x1old),axisy.p2c(y1))}ctx.lineTo(axisx.p2c(x1),axisy.p2c(y1));ctx.lineTo(axisx.p2c(x2),axisy.p2c(y2));if(x2!=x2old){ctx.lineTo(axisx.p2c(x2),axisy.p2c(y2));ctx.lineTo(axisx.p2c(x2old),axisy.p2c(y2))}}}ctx.save();ctx.translate(plotOffset.left,plotOffset.top);ctx.lineJoin="round";var lw=series.lines.lineWidth,sw=series.shadowSize;if(lw>0&&sw>0){ctx.lineWidth=sw;ctx.strokeStyle="rgba(0,0,0,0.1)";var angle=Math.PI/18;plotLine(series.datapoints,Math.sin(angle)*(lw/2+sw/2),Math.cos(angle)*(lw/2+sw/2),series.xaxis,series.yaxis);ctx.lineWidth=sw/2;plotLine(series.datapoints,Math.sin(angle)*(lw/2+sw/4),Math.cos(angle)*(lw/2+sw/4),series.xaxis,series.yaxis)}ctx.lineWidth=lw;ctx.strokeStyle=series.color;var fillStyle=getFillStyle(series.lines,series.color,0,plotHeight);if(fillStyle){ctx.fillStyle=fillStyle;plotLineArea(series.datapoints,series.xaxis,series.yaxis)}if(lw>0)plotLine(series.datapoints,0,0,series.xaxis,series.yaxis);ctx.restore()}function drawSeriesPoints(series){function plotPoints(datapoints,radius,fillStyle,offset,shadow,axisx,axisy,symbol){var points=datapoints.points,ps=datapoints.pointsize;for(var i=0;i<points.length;i+=ps){var x=points[i],y=points[i+1];if(x==null||x<axisx.min||x>axisx.max||y<axisy.min||y>axisy.max)continue;ctx.beginPath();x=axisx.p2c(x);y=axisy.p2c(y)+offset;if(symbol=="circle")ctx.arc(x,y,radius,0,shadow?Math.PI:Math.PI*2,false);else symbol(ctx,x,y,radius,shadow);ctx.closePath();if(fillStyle){ctx.fillStyle=fillStyle;ctx.fill()}ctx.stroke()}}ctx.save();ctx.translate(plotOffset.left,plotOffset.top);var lw=series.points.lineWidth,sw=series.shadowSize,radius=series.points.radius,symbol=series.points.symbol;if(lw==0)lw=1e-4;if(lw>0&&sw>0){var w=sw/2;ctx.lineWidth=w;ctx.strokeStyle="rgba(0,0,0,0.1)";plotPoints(series.datapoints,radius,null,w+w/2,true,series.xaxis,series.yaxis,symbol);ctx.strokeStyle="rgba(0,0,0,0.2)";plotPoints(series.datapoints,radius,null,w/2,true,series.xaxis,series.yaxis,symbol)}ctx.lineWidth=lw;ctx.strokeStyle=series.color;plotPoints(series.datapoints,radius,getFillStyle(series.points,series.color),0,false,series.xaxis,series.yaxis,symbol);ctx.restore()}function drawBar(x,y,b,barLeft,barRight,fillStyleCallback,axisx,axisy,c,horizontal,lineWidth){var left,right,bottom,top,drawLeft,drawRight,drawTop,drawBottom,tmp;if(horizontal){drawBottom=drawRight=drawTop=true;drawLeft=false;left=b;right=x;top=y+barLeft;bottom=y+barRight;if(right<left){tmp=right;right=left;left=tmp;drawLeft=true;drawRight=false}}else{drawLeft=drawRight=drawTop=true;drawBottom=false;left=x+barLeft;right=x+barRight;bottom=b;top=y;if(top<bottom){tmp=top;top=bottom;bottom=tmp;drawBottom=true;drawTop=false}}if(right<axisx.min||left>axisx.max||top<axisy.min||bottom>axisy.max)return;if(left<axisx.min){left=axisx.min;drawLeft=false}if(right>axisx.max){right=axisx.max;drawRight=false}if(bottom<axisy.min){bottom=axisy.min;drawBottom=false}if(top>axisy.max){top=axisy.max;drawTop=false}left=axisx.p2c(left);bottom=axisy.p2c(bottom);right=axisx.p2c(right);top=axisy.p2c(top);if(fillStyleCallback){c.fillStyle=fillStyleCallback(bottom,top);c.fillRect(left,top,right-left,bottom-top)}if(lineWidth>0&&(drawLeft||drawRight||drawTop||drawBottom)){c.beginPath();c.moveTo(left,bottom);if(drawLeft)c.lineTo(left,top);else c.moveTo(left,top);if(drawTop)c.lineTo(right,top);else c.moveTo(right,top);if(drawRight)c.lineTo(right,bottom);else c.moveTo(right,bottom);if(drawBottom)c.lineTo(left,bottom);else c.moveTo(left,bottom);c.stroke()}}function drawSeriesBars(series){function plotBars(datapoints,barLeft,barRight,fillStyleCallback,axisx,axisy){var points=datapoints.points,ps=datapoints.pointsize;for(var i=0;i<points.length;i+=ps){if(points[i]==null)continue;drawBar(points[i],points[i+1],points[i+2],barLeft,barRight,fillStyleCallback,axisx,axisy,ctx,series.bars.horizontal,series.bars.lineWidth)}}ctx.save();ctx.translate(plotOffset.left,plotOffset.top);ctx.lineWidth=series.bars.lineWidth;ctx.strokeStyle=series.color;var barLeft;switch(series.bars.align){case"left":barLeft=0;break;case"right":barLeft=-series.bars.barWidth;break;default:barLeft=-series.bars.barWidth/2}var fillStyleCallback=series.bars.fill?function(bottom,top){return 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| <h1>criterion performance measurements</h1> | |
| <h2>overview</h2> | |
| <p><a href="#grokularation">want to understand this report?</a></p> | |
| <div id="overview" class="ovchart" style="width:900px;height:100px;"></div> | |
| <h2><a name="b0">quotes-at-end/regex/0</a></h2> | |
| <table width="100%"> | |
| <tbody> | |
| <tr> | |
| <td><div id="kde0" class="kdechart" | |
| style="width:450px;height:278px;"></div></td> | |
| <td><div id="time0" class="timechart" | |
| style="width:450px;height:278px;"></div></td> | |
| <!-- | |
| <td><div id="cycle0" class="cyclechart" | |
| style="width:300px;height:278px;"></div></td> | |
| --> | |
| </tr> | |
| </tbody> | |
| </table> | |
| <table> | |
| <thead class="analysis"> | |
| <th></th> | |
| <th class="cibound" | |
| title="0.95 confidence level">lower bound</th> | |
| <th>estimate</th> | |
| <th class="cibound" | |
| title="0.95 confidence level">upper bound</th> | |
| </thead> | |
| <tbody> | |
| <tr> | |
| <td>OLS regression</td> | |
| <td><span class="confinterval olstimelb0">xxx</span></td> | |
| <td><span class="olstimept0">xxx</span></td> | |
| <td><span class="confinterval olstimeub0">xxx</span></td> | |
| </tr> | |
| <tr> | |
| <td>R² goodness-of-fit</td> | |
| <td><span class="confinterval olsr2lb0">xxx</span></td> | |
| <td><span class="olsr2pt0">xxx</span></td> | |
| <td><span class="confinterval olsr2ub0">xxx</span></td> | |
| </tr> | |
| <tr> | |
| <td>Mean execution time</td> | |
| <td><span class="confinterval citime">4.376592509337157e-6</span></td> | |
| <td><span class="time">4.458155140693469e-6</span></td> | |
| <td><span class="confinterval citime">4.771119717693118e-6</span></td> | |
| </tr> | |
| <tr> | |
| <td>Standard deviation</td> | |
| <td><span class="confinterval citime">1.401071436511731e-7</span></td> | |
| <td><span class="time">4.830654807849732e-7</span></td> | |
| <td><span class="confinterval citime">9.907676008486333e-7</span></td> | |
| </tr> | |
| </tbody> | |
| </table> | |
| <span class="outliers"> | |
| <p>Outlying measurements have severe | |
| (<span class="percent">0.8885294735916837</span>%) | |
| effect on estimated standard deviation.</p> | |
| </span> | |
| <h2><a name="b1">quotes-at-end/regex/1000</a></h2> | |
| <table width="100%"> | |
| <tbody> | |
| <tr> | |
| <td><div id="kde1" class="kdechart" | |
| style="width:450px;height:278px;"></div></td> | |
| <td><div id="time1" class="timechart" | |
| style="width:450px;height:278px;"></div></td> | |
| <!-- | |
| <td><div id="cycle1" class="cyclechart" | |
| style="width:300px;height:278px;"></div></td> | |
| --> | |
| </tr> | |
| </tbody> | |
| </table> | |
| <table> | |
| <thead class="analysis"> | |
| <th></th> | |
| <th class="cibound" | |
| title="0.95 confidence level">lower bound</th> | |
| <th>estimate</th> | |
| <th class="cibound" | |
| title="0.95 confidence level">upper bound</th> | |
| </thead> | |
| <tbody> | |
| <tr> | |
| <td>OLS regression</td> | |
| <td><span class="confinterval olstimelb1">xxx</span></td> | |
| <td><span class="olstimept1">xxx</span></td> | |
| <td><span class="confinterval olstimeub1">xxx</span></td> | |
| </tr> | |
| <tr> | |
| <td>R² goodness-of-fit</td> | |
| <td><span class="confinterval olsr2lb1">xxx</span></td> | |
| <td><span class="olsr2pt1">xxx</span></td> | |
| <td><span class="confinterval olsr2ub1">xxx</span></td> | |
| </tr> | |
| <tr> | |
| <td>Mean execution time</td> | |
| <td><span class="confinterval citime">4.2964495659946687e-4</span></td> | |
| <td><span class="time">4.357199397885642e-4</span></td> | |
| <td><span class="confinterval citime">4.459115872690501e-4</span></td> | |
| </tr> | |
| <tr> | |
| <td>Standard deviation</td> | |
| <td><span class="confinterval citime">1.4317316426015797e-5</span></td> | |
| <td><span class="time">2.7790513237399025e-5</span></td> | |
| <td><span class="confinterval citime">4.3198083235844956e-5</span></td> | |
| </tr> | |
| </tbody> | |
| </table> | |
| <span class="outliers"> | |
| <p>Outlying measurements have severe | |
| (<span class="percent">0.5710355420865002</span>%) | |
| effect on estimated standard deviation.</p> | |
| </span> | |
| <h2><a name="b2">quotes-at-end/regex/2000</a></h2> | |
| <table width="100%"> | |
| <tbody> | |
| <tr> | |
| <td><div id="kde2" class="kdechart" | |
| style="width:450px;height:278px;"></div></td> | |
| <td><div id="time2" class="timechart" | |
| style="width:450px;height:278px;"></div></td> | |
| <!-- | |
| <td><div id="cycle2" class="cyclechart" | |
| style="width:300px;height:278px;"></div></td> | |
| --> | |
| </tr> | |
| </tbody> | |
| </table> | |
| <table> | |
| <thead class="analysis"> | |
| <th></th> | |
| <th class="cibound" | |
| title="0.95 confidence level">lower bound</th> | |
| <th>estimate</th> | |
| <th class="cibound" | |
| title="0.95 confidence level">upper bound</th> | |
| </thead> | |
| <tbody> | |
| <tr> | |
| <td>OLS regression</td> | |
| <td><span class="confinterval olstimelb2">xxx</span></td> | |
| <td><span class="olstimept2">xxx</span></td> | |
| <td><span class="confinterval olstimeub2">xxx</span></td> | |
| </tr> | |
| <tr> | |
| <td>R² goodness-of-fit</td> | |
| <td><span class="confinterval olsr2lb2">xxx</span></td> | |
| <td><span class="olsr2pt2">xxx</span></td> | |
| <td><span class="confinterval olsr2ub2">xxx</span></td> | |
| </tr> | |
| <tr> | |
| <td>Mean execution time</td> | |
| <td><span class="confinterval citime">9.717015679656082e-4</span></td> | |
| <td><span class="time">9.834023486487435e-4</span></td> | |
| <td><span class="confinterval citime">9.965182535757156e-4</span></td> | |
| </tr> | |
| <tr> | |
| <td>Standard deviation</td> | |
| <td><span class="confinterval citime">3.4081093347903085e-5</span></td> | |
| <td><span class="time">4.208771108044901e-5</span></td> | |
| <td><span class="confinterval citime">5.293618699753579e-5</span></td> | |
| </tr> | |
| </tbody> | |
| </table> | |
| <span class="outliers"> | |
| <p>Outlying measurements have moderate | |
| (<span class="percent">0.3242997877892952</span>%) | |
| effect on estimated standard deviation.</p> | |
| </span> | |
| <h2><a name="b3">quotes-at-end/regex/3000</a></h2> | |
| <table width="100%"> | |
| <tbody> | |
| <tr> | |
| <td><div id="kde3" class="kdechart" | |
| style="width:450px;height:278px;"></div></td> | |
| <td><div id="time3" class="timechart" | |
| style="width:450px;height:278px;"></div></td> | |
| <!-- | |
| <td><div id="cycle3" class="cyclechart" | |
| style="width:300px;height:278px;"></div></td> | |
| --> | |
| </tr> | |
| </tbody> | |
| </table> | |
| <table> | |
| <thead class="analysis"> | |
| <th></th> | |
| <th class="cibound" | |
| title="0.95 confidence level">lower bound</th> | |
| <th>estimate</th> | |
| <th class="cibound" | |
| title="0.95 confidence level">upper bound</th> | |
| </thead> | |
| <tbody> | |
| <tr> | |
| <td>OLS regression</td> | |
| <td><span class="confinterval olstimelb3">xxx</span></td> | |
| <td><span class="olstimept3">xxx</span></td> | |
| <td><span class="confinterval olstimeub3">xxx</span></td> | |
| </tr> | |
| <tr> | |
| <td>R² goodness-of-fit</td> | |
| <td><span class="confinterval olsr2lb3">xxx</span></td> | |
| <td><span class="olsr2pt3">xxx</span></td> | |
| <td><span class="confinterval olsr2ub3">xxx</span></td> | |
| </tr> | |
| <tr> | |
| <td>Mean execution time</td> | |
| <td><span class="confinterval citime">1.50062162571105e-3</span></td> | |
| <td><span class="time">1.5158980525330035e-3</span></td> | |
| <td><span class="confinterval citime">1.5347260443549767e-3</span></td> | |
| </tr> | |
| <tr> | |
| <td>Standard deviation</td> | |
| <td><span class="confinterval citime">4.388409563397097e-5</span></td> | |
| <td><span class="time">5.673340794639664e-5</span></td> | |
| <td><span class="confinterval citime">7.362009805872924e-5</span></td> | |
| </tr> | |
| </tbody> | |
| </table> | |
| <span class="outliers"> | |
| <p>Outlying measurements have moderate | |
| (<span class="percent">0.24254734713863602</span>%) | |
| effect on estimated standard deviation.</p> | |
| </span> | |
| <h2><a name="b4">quotes-at-end/regex/4000</a></h2> | |
| <table width="100%"> | |
| <tbody> | |
| <tr> | |
| <td><div id="kde4" class="kdechart" | |
| style="width:450px;height:278px;"></div></td> | |
| <td><div id="time4" class="timechart" | |
| style="width:450px;height:278px;"></div></td> | |
| <!-- | |
| <td><div id="cycle4" class="cyclechart" | |
| style="width:300px;height:278px;"></div></td> | |
| --> | |
| </tr> | |
| </tbody> | |
| </table> | |
| <table> | |
| <thead class="analysis"> | |
| <th></th> | |
| <th class="cibound" | |
| title="0.95 confidence level">lower bound</th> | |
| <th>estimate</th> | |
| <th class="cibound" | |
| title="0.95 confidence level">upper bound</th> | |
| </thead> | |
| <tbody> | |
| <tr> | |
| <td>OLS regression</td> | |
| <td><span class="confinterval olstimelb4">xxx</span></td> | |
| <td><span class="olstimept4">xxx</span></td> | |
| <td><span class="confinterval olstimeub4">xxx</span></td> | |
| </tr> | |
| <tr> | |
| <td>R² goodness-of-fit</td> | |
| <td><span class="confinterval olsr2lb4">xxx</span></td> | |
| <td><span class="olsr2pt4">xxx</span></td> | |
| <td><span class="confinterval olsr2ub4">xxx</span></td> | |
| </tr> | |
| <tr> | |
| <td>Mean execution time</td> | |
| <td><span class="confinterval citime">2.113760881184046e-3</span></td> | |
| <td><span class="time">2.1570241714561392e-3</span></td> | |
| <td><span class="confinterval citime">2.292621953506672e-3</span></td> | |
| </tr> | |
| <tr> | |
| <td>Standard deviation</td> | |
| <td><span class="confinterval citime">9.03516916041988e-5</span></td> | |
| <td><span class="time">2.2366910328583742e-4</span></td> | |
| <td><span class="confinterval citime">4.711654717410389e-4</span></td> | |
| </tr> | |
| </tbody> | |
| </table> | |
| <span class="outliers"> | |
| <p>Outlying measurements have severe | |
| (<span class="percent">0.7010461419115407</span>%) | |
| effect on estimated standard deviation.</p> | |
| </span> | |
| <h2><a name="b5">quotes-at-end/regex/5000</a></h2> | |
| <table width="100%"> | |
| <tbody> | |
| <tr> | |
| <td><div id="kde5" class="kdechart" | |
| style="width:450px;height:278px;"></div></td> | |
| <td><div id="time5" class="timechart" | |
| style="width:450px;height:278px;"></div></td> | |
| <!-- | |
| <td><div id="cycle5" class="cyclechart" | |
| style="width:300px;height:278px;"></div></td> | |
| --> | |
| </tr> | |
| </tbody> | |
| </table> | |
| <table> | |
| <thead class="analysis"> | |
| <th></th> | |
| <th class="cibound" | |
| title="0.95 confidence level">lower bound</th> | |
| <th>estimate</th> | |
| <th class="cibound" | |
| title="0.95 confidence level">upper bound</th> | |
| </thead> | |
| <tbody> | |
| <tr> | |
| <td>OLS regression</td> | |
| <td><span class="confinterval olstimelb5">xxx</span></td> | |
| <td><span class="olstimept5">xxx</span></td> | |
| <td><span class="confinterval olstimeub5">xxx</span></td> | |
| </tr> | |
| <tr> | |
| <td>R² goodness-of-fit</td> | |
| <td><span class="confinterval olsr2lb5">xxx</span></td> | |
| <td><span class="olsr2pt5">xxx</span></td> | |
| <td><span class="confinterval olsr2ub5">xxx</span></td> | |
| </tr> | |
| <tr> | |
| <td>Mean execution time</td> | |
| <td><span class="confinterval citime">2.6533650960983927e-3</span></td> | |
| <td><span class="time">2.68351137937369e-3</span></td> | |
| <td><span class="confinterval citime">2.717946992592386e-3</span></td> | |
| </tr> | |
| <tr> | |
| <td>Standard deviation</td> | |
| <td><span class="confinterval citime">9.16155123288573e-5</span></td> | |
| <td><span class="time">1.1235929938811189e-4</span></td> | |
| <td><span class="confinterval citime">1.4563959880195467e-4</span></td> | |
| </tr> | |
| </tbody> | |
| </table> | |
| <span class="outliers"> | |
| <p>Outlying measurements have moderate | |
| (<span class="percent">0.25680695628658834</span>%) | |
| effect on estimated standard deviation.</p> | |
| </span> | |
| <h2><a name="b6">quotes-at-end/regex/6000</a></h2> | |
| <table width="100%"> | |
| <tbody> | |
| <tr> | |
| <td><div id="kde6" class="kdechart" | |
| style="width:450px;height:278px;"></div></td> | |
| <td><div id="time6" class="timechart" | |
| style="width:450px;height:278px;"></div></td> | |
| <!-- | |
| <td><div id="cycle6" class="cyclechart" | |
| style="width:300px;height:278px;"></div></td> | |
| --> | |
| </tr> | |
| </tbody> | |
| </table> | |
| <table> | |
| <thead class="analysis"> | |
| <th></th> | |
| <th class="cibound" | |
| title="0.95 confidence level">lower bound</th> | |
| <th>estimate</th> | |
| <th class="cibound" | |
| title="0.95 confidence level">upper bound</th> | |
| </thead> | |
| <tbody> | |
| <tr> | |
| <td>OLS regression</td> | |
| <td><span class="confinterval olstimelb6">xxx</span></td> | |
| <td><span class="olstimept6">xxx</span></td> | |
| <td><span class="confinterval olstimeub6">xxx</span></td> | |
| </tr> | |
| <tr> | |
| <td>R² goodness-of-fit</td> | |
| <td><span class="confinterval olsr2lb6">xxx</span></td> | |
| <td><span class="olsr2pt6">xxx</span></td> | |
| <td><span class="confinterval olsr2ub6">xxx</span></td> | |
| </tr> | |
| <tr> | |
| <td>Mean execution time</td> | |
| <td><span class="confinterval citime">3.0906165360335305e-3</span></td> | |
| <td><span class="time">3.1242368400038745e-3</span></td> | |
| <td><span class="confinterval citime">3.162663876807104e-3</span></td> | |
| </tr> | |
| <tr> | |
| <td>Standard deviation</td> | |
| <td><span class="confinterval citime">9.866563922115313e-5</span></td> | |
| <td><span class="time">1.2166027246474091e-4</span></td> | |
| <td><span class="confinterval citime">1.5226391257779111e-4</span></td> | |
| </tr> | |
| </tbody> | |
| </table> | |
| <span class="outliers"> | |
| <p>Outlying measurements have moderate | |
| (<span class="percent">0.21389219685205732</span>%) | |
| effect on estimated standard deviation.</p> | |
| </span> | |
| <h2><a name="b7">quotes-at-end/regex/7000</a></h2> | |
| <table width="100%"> | |
| <tbody> | |
| <tr> | |
| <td><div id="kde7" class="kdechart" | |
| style="width:450px;height:278px;"></div></td> | |
| <td><div id="time7" class="timechart" | |
| style="width:450px;height:278px;"></div></td> | |
| <!-- | |
| <td><div id="cycle7" class="cyclechart" | |
| style="width:300px;height:278px;"></div></td> | |
| --> | |
| </tr> | |
| </tbody> | |
| </table> | |
| <table> | |
| <thead class="analysis"> | |
| <th></th> | |
| <th class="cibound" | |
| title="0.95 confidence level">lower bound</th> | |
| <th>estimate</th> | |
| <th class="cibound" | |
| title="0.95 confidence level">upper bound</th> | |
| </thead> | |
| <tbody> | |
| <tr> | |
| <td>OLS regression</td> | |
| <td><span class="confinterval olstimelb7">xxx</span></td> | |
| <td><span class="olstimept7">xxx</span></td> | |
| <td><span class="confinterval olstimeub7">xxx</span></td> | |
| </tr> | |
| <tr> | |
| <td>R² goodness-of-fit</td> | |
| <td><span class="confinterval olsr2lb7">xxx</span></td> | |
| <td><span class="olsr2pt7">xxx</span></td> | |
| <td><span class="confinterval olsr2ub7">xxx</span></td> | |
| </tr> | |
| <tr> | |
| <td>Mean execution time</td> | |
| <td><span class="confinterval citime">3.4990346735783487e-3</span></td> | |
| <td><span class="time">3.531167348945552e-3</span></td> | |
| <td><span class="confinterval citime">3.5782402674321492e-3</span></td> | |
| </tr> | |
| <tr> | |
| <td>Standard deviation</td> | |
| <td><span class="confinterval citime">9.35773564330949e-5</span></td> | |
| <td><span class="time">1.2242853659184336e-4</span></td> | |
| <td><span class="confinterval citime">1.6722369328386888e-4</span></td> | |
| </tr> | |
| </tbody> | |
| </table> | |
| <span class="outliers"> | |
| <p>Outlying measurements have moderate | |
| (<span class="percent">0.1813483156561053</span>%) | |
| effect on estimated standard deviation.</p> | |
| </span> | |
| <h2><a name="b8">quotes-at-end/regex/8000</a></h2> | |
| <table width="100%"> | |
| <tbody> | |
| <tr> | |
| <td><div id="kde8" class="kdechart" | |
| style="width:450px;height:278px;"></div></td> | |
| <td><div id="time8" class="timechart" | |
| style="width:450px;height:278px;"></div></td> | |
| <!-- | |
| <td><div id="cycle8" class="cyclechart" | |
| style="width:300px;height:278px;"></div></td> | |
| --> | |
| </tr> | |
| </tbody> | |
| </table> | |
| <table> | |
| <thead class="analysis"> | |
| <th></th> | |
| <th class="cibound" | |
| title="0.95 confidence level">lower bound</th> | |
| <th>estimate</th> | |
| <th class="cibound" | |
| title="0.95 confidence level">upper bound</th> | |
| </thead> | |
| <tbody> | |
| <tr> | |
| <td>OLS regression</td> | |
| <td><span class="confinterval olstimelb8">xxx</span></td> | |
| <td><span class="olstimept8">xxx</span></td> | |
| <td><span class="confinterval olstimeub8">xxx</span></td> | |
| </tr> | |
| <tr> | |
| <td>R² goodness-of-fit</td> | |
| <td><span class="confinterval olsr2lb8">xxx</span></td> | |
| <td><span class="olsr2pt8">xxx</span></td> | |
| <td><span class="confinterval olsr2ub8">xxx</span></td> | |
| </tr> | |
| <tr> | |
| <td>Mean execution time</td> | |
| <td><span class="confinterval citime">4.060828885934717e-3</span></td> | |
| <td><span class="time">4.109721774768918e-3</span></td> | |
| <td><span class="confinterval citime">4.166177164280723e-3</span></td> | |
| </tr> | |
| <tr> | |
| <td>Standard deviation</td> | |
| <td><span class="confinterval citime">1.365069498378244e-4</span></td> | |
| <td><span class="time">1.6358923692675424e-4</span></td> | |
| <td><span class="confinterval citime">2.0563582578511202e-4</span></td> | |
| </tr> | |
| </tbody> | |
| </table> | |
| <span class="outliers"> | |
| <p>Outlying measurements have moderate | |
| (<span class="percent">0.2156962243376071</span>%) | |
| effect on estimated standard deviation.</p> | |
| </span> | |
| <h2><a name="b9">quotes-at-end/regex/9000</a></h2> | |
| <table width="100%"> | |
| <tbody> | |
| <tr> | |
| <td><div id="kde9" class="kdechart" | |
| style="width:450px;height:278px;"></div></td> | |
| <td><div id="time9" class="timechart" | |
| style="width:450px;height:278px;"></div></td> | |
| <!-- | |
| <td><div id="cycle9" class="cyclechart" | |
| style="width:300px;height:278px;"></div></td> | |
| --> | |
| </tr> | |
| </tbody> | |
| </table> | |
| <table> | |
| <thead class="analysis"> | |
| <th></th> | |
| <th class="cibound" | |
| title="0.95 confidence level">lower bound</th> | |
| <th>estimate</th> | |
| <th class="cibound" | |
| title="0.95 confidence level">upper bound</th> | |
| </thead> | |
| <tbody> | |
| <tr> | |
| <td>OLS regression</td> | |
| <td><span class="confinterval olstimelb9">xxx</span></td> | |
| <td><span class="olstimept9">xxx</span></td> | |
| <td><span class="confinterval olstimeub9">xxx</span></td> | |
| </tr> | |
| <tr> | |
| <td>R² goodness-of-fit</td> | |
| <td><span class="confinterval olsr2lb9">xxx</span></td> | |
| <td><span class="olsr2pt9">xxx</span></td> | |
| <td><span class="confinterval olsr2ub9">xxx</span></td> | |
| </tr> | |
| <tr> | |
| <td>Mean execution time</td> | |
| <td><span class="confinterval citime">5.462832208243616e-3</span></td> | |
| <td><span class="time">5.649626209274329e-3</span></td> | |
| <td><span class="confinterval citime">6.180552702404998e-3</span></td> | |
| </tr> | |
| <tr> | |
| <td>Standard deviation</td> | |
| <td><span class="confinterval citime">3.486587322370169e-4</span></td> | |
| <td><span class="time">8.356363054551934e-4</span></td> | |
| <td><span class="confinterval citime">1.5813562764521079e-3</span></td> | |
| </tr> | |
| </tbody> | |
| </table> | |
| <span class="outliers"> | |
| <p>Outlying measurements have severe | |
| (<span class="percent">0.7833012337202382</span>%) | |
| effect on estimated standard deviation.</p> | |
| </span> | |
| <h2><a name="b10">quotes-at-end/regex/10000</a></h2> | |
| <table width="100%"> | |
| <tbody> | |
| <tr> | |
| <td><div id="kde10" class="kdechart" | |
| style="width:450px;height:278px;"></div></td> | |
| <td><div id="time10" class="timechart" | |
| style="width:450px;height:278px;"></div></td> | |
| <!-- | |
| <td><div id="cycle10" class="cyclechart" | |
| style="width:300px;height:278px;"></div></td> | |
| --> | |
| </tr> | |
| </tbody> | |
| </table> | |
| <table> | |
| <thead class="analysis"> | |
| <th></th> | |
| <th class="cibound" | |
| title="0.95 confidence level">lower bound</th> | |
| <th>estimate</th> | |
| <th class="cibound" | |
| title="0.95 confidence level">upper bound</th> | |
| </thead> | |
| <tbody> | |
| <tr> | |
| <td>OLS regression</td> | |
| <td><span class="confinterval olstimelb10">xxx</span></td> | |
| <td><span class="olstimept10">xxx</span></td> | |
| <td><span class="confinterval olstimeub10">xxx</span></td> | |
| </tr> | |
| <tr> | |
| <td>R² goodness-of-fit</td> | |
| <td><span class="confinterval olsr2lb10">xxx</span></td> | |
| <td><span class="olsr2pt10">xxx</span></td> | |
| <td><span class="confinterval olsr2ub10">xxx</span></td> | |
| </tr> | |
| <tr> | |
| <td>Mean execution time</td> | |
| <td><span class="confinterval citime">7.3062178221234095e-3</span></td> | |
| <td><span class="time">7.786360058070533e-3</span></td> | |
| <td><span class="confinterval citime">8.45434430027223e-3</span></td> | |
| </tr> | |
| <tr> | |
| <td>Standard deviation</td> | |
| <td><span class="confinterval citime">1.172633492754477e-3</span></td> | |
| <td><span class="time">1.583246607198702e-3</span></td> | |
| <td><span class="confinterval citime">2.1811144851149435e-3</span></td> | |
| </tr> | |
| </tbody> | |
| </table> | |
| <span class="outliers"> | |
| <p>Outlying measurements have severe | |
| (<span class="percent">0.8448548531179298</span>%) | |
| effect on estimated standard deviation.</p> | |
| </span> | |
| <h2><a name="b11">quotes-at-end/split/0</a></h2> | |
| <table width="100%"> | |
| <tbody> | |
| <tr> | |
| <td><div id="kde11" class="kdechart" | |
| style="width:450px;height:278px;"></div></td> | |
| <td><div id="time11" class="timechart" | |
| style="width:450px;height:278px;"></div></td> | |
| <!-- | |
| <td><div id="cycle11" class="cyclechart" | |
| style="width:300px;height:278px;"></div></td> | |
| --> | |
| </tr> | |
| </tbody> | |
| </table> | |
| <table> | |
| <thead class="analysis"> | |
| <th></th> | |
| <th class="cibound" | |
| title="0.95 confidence level">lower bound</th> | |
| <th>estimate</th> | |
| <th class="cibound" | |
| title="0.95 confidence level">upper bound</th> | |
| </thead> | |
| <tbody> | |
| <tr> | |
| <td>OLS regression</td> | |
| <td><span class="confinterval olstimelb11">xxx</span></td> | |
| <td><span class="olstimept11">xxx</span></td> | |
| <td><span class="confinterval olstimeub11">xxx</span></td> | |
| </tr> | |
| <tr> | |
| <td>R² goodness-of-fit</td> | |
| <td><span class="confinterval olsr2lb11">xxx</span></td> | |
| <td><span class="olsr2pt11">xxx</span></td> | |
| <td><span class="confinterval olsr2ub11">xxx</span></td> | |
| </tr> | |
| <tr> | |
| <td>Mean execution time</td> | |
| <td><span class="confinterval citime">5.538986196689419e-7</span></td> | |
| <td><span class="time">6.22187449447239e-7</span></td> | |
| <td><span class="confinterval citime">7.949742642839129e-7</span></td> | |
| </tr> | |
| <tr> | |
| <td>Standard deviation</td> | |
| <td><span class="confinterval citime">1.7186825602215652e-7</span></td> | |
| <td><span class="time">3.2964862653232276e-7</span></td> | |
| <td><span class="confinterval citime">6.389071364174194e-7</span></td> | |
| </tr> | |
| </tbody> | |
| </table> | |
| <span class="outliers"> | |
| <p>Outlying measurements have severe | |
| (<span class="percent">0.995268322613273</span>%) | |
| effect on estimated standard deviation.</p> | |
| </span> | |
| <h2><a name="b12">quotes-at-end/split/1000</a></h2> | |
| <table width="100%"> | |
| <tbody> | |
| <tr> | |
| <td><div id="kde12" class="kdechart" | |
| style="width:450px;height:278px;"></div></td> | |
| <td><div id="time12" class="timechart" | |
| style="width:450px;height:278px;"></div></td> | |
| <!-- | |
| <td><div id="cycle12" class="cyclechart" | |
| style="width:300px;height:278px;"></div></td> | |
| --> | |
| </tr> | |
| </tbody> | |
| </table> | |
| <table> | |
| <thead class="analysis"> | |
| <th></th> | |
| <th class="cibound" | |
| title="0.95 confidence level">lower bound</th> | |
| <th>estimate</th> | |
| <th class="cibound" | |
| title="0.95 confidence level">upper bound</th> | |
| </thead> | |
| <tbody> | |
| <tr> | |
| <td>OLS regression</td> | |
| <td><span class="confinterval olstimelb12">xxx</span></td> | |
| <td><span class="olstimept12">xxx</span></td> | |
| <td><span class="confinterval olstimeub12">xxx</span></td> | |
| </tr> | |
| <tr> | |
| <td>R² goodness-of-fit</td> | |
| <td><span class="confinterval olsr2lb12">xxx</span></td> | |
| <td><span class="olsr2pt12">xxx</span></td> | |
| <td><span class="confinterval olsr2ub12">xxx</span></td> | |
| </tr> | |
| <tr> | |
| <td>Mean execution time</td> | |
| <td><span class="confinterval citime">4.5573676064931155e-5</span></td> | |
| <td><span class="time">4.708084433504224e-5</span></td> | |
| <td><span class="confinterval citime">4.884738063200018e-5</span></td> | |
| </tr> | |
| <tr> | |
| <td>Standard deviation</td> | |
| <td><span class="confinterval citime">4.843038029050149e-6</span></td> | |
| <td><span class="time">5.414933448982818e-6</span></td> | |
| <td><span class="confinterval citime">5.9875273441678116e-6</span></td> | |
| </tr> | |
| </tbody> | |
| </table> | |
| <span class="outliers"> | |
| <p>Outlying measurements have severe | |
| (<span class="percent">0.8728263633076128</span>%) | |
| effect on estimated standard deviation.</p> | |
| </span> | |
| <h2><a name="b13">quotes-at-end/split/2000</a></h2> | |
| <table width="100%"> | |
| <tbody> | |
| <tr> | |
| <td><div id="kde13" class="kdechart" | |
| style="width:450px;height:278px;"></div></td> | |
| <td><div id="time13" class="timechart" | |
| style="width:450px;height:278px;"></div></td> | |
| <!-- | |
| <td><div id="cycle13" class="cyclechart" | |
| style="width:300px;height:278px;"></div></td> | |
| --> | |
| </tr> | |
| </tbody> | |
| </table> | |
| <table> | |
| <thead class="analysis"> | |
| <th></th> | |
| <th class="cibound" | |
| title="0.95 confidence level">lower bound</th> | |
| <th>estimate</th> | |
| <th class="cibound" | |
| title="0.95 confidence level">upper bound</th> | |
| </thead> | |
| <tbody> | |
| <tr> | |
| <td>OLS regression</td> | |
| <td><span class="confinterval olstimelb13">xxx</span></td> | |
| <td><span class="olstimept13">xxx</span></td> | |
| <td><span class="confinterval olstimeub13">xxx</span></td> | |
| </tr> | |
| <tr> | |
| <td>R² goodness-of-fit</td> | |
| <td><span class="confinterval olsr2lb13">xxx</span></td> | |
| <td><span class="olsr2pt13">xxx</span></td> | |
| <td><span class="confinterval olsr2ub13">xxx</span></td> | |
| </tr> | |
| <tr> | |
| <td>Mean execution time</td> | |
| <td><span class="confinterval citime">9.080960617405335e-5</span></td> | |
| <td><span class="time">9.175544401879408e-5</span></td> | |
| <td><span class="confinterval citime">9.281997776897075e-5</span></td> | |
| </tr> | |
| <tr> | |
| <td>Standard deviation</td> | |
| <td><span class="confinterval citime">2.9442787583642523e-6</span></td> | |
| <td><span class="time">3.5851245387713934e-6</span></td> | |
| <td><span class="confinterval citime">4.607188062742559e-6</span></td> | |
| </tr> | |
| </tbody> | |
| </table> | |
| <span class="outliers"> | |
| <p>Outlying measurements have moderate | |
| (<span class="percent">0.4049844817179876</span>%) | |
| effect on estimated standard deviation.</p> | |
| </span> | |
| <h2><a name="b14">quotes-at-end/split/3000</a></h2> | |
| <table width="100%"> | |
| <tbody> | |
| <tr> | |
| <td><div id="kde14" class="kdechart" | |
| style="width:450px;height:278px;"></div></td> | |
| <td><div id="time14" class="timechart" | |
| style="width:450px;height:278px;"></div></td> | |
| <!-- | |
| <td><div id="cycle14" class="cyclechart" | |
| style="width:300px;height:278px;"></div></td> | |
| --> | |
| </tr> | |
| </tbody> | |
| </table> | |
| <table> | |
| <thead class="analysis"> | |
| <th></th> | |
| <th class="cibound" | |
| title="0.95 confidence level">lower bound</th> | |
| <th>estimate</th> | |
| <th class="cibound" | |
| title="0.95 confidence level">upper bound</th> | |
| </thead> | |
| <tbody> | |
| <tr> | |
| <td>OLS regression</td> | |
| <td><span class="confinterval olstimelb14">xxx</span></td> | |
| <td><span class="olstimept14">xxx</span></td> | |
| <td><span class="confinterval olstimeub14">xxx</span></td> | |
| </tr> | |
| <tr> | |
| <td>R² goodness-of-fit</td> | |
| <td><span class="confinterval olsr2lb14">xxx</span></td> | |
| <td><span class="olsr2pt14">xxx</span></td> | |
| <td><span class="confinterval olsr2ub14">xxx</span></td> | |
| </tr> | |
| <tr> | |
| <td>Mean execution time</td> | |
| <td><span class="confinterval citime">1.440564353658698e-4</span></td> | |
| <td><span class="time">1.492091026857772e-4</span></td> | |
| <td><span class="confinterval citime">1.6075574829196206e-4</span></td> | |
| </tr> | |
| <tr> | |
| <td>Standard deviation</td> | |
| <td><span class="confinterval citime">1.0762215212231773e-5</span></td> | |
| <td><span class="time">2.3967861571288444e-5</span></td> | |
| <td><span class="confinterval citime">4.616910421268893e-5</span></td> | |
| </tr> | |
| </tbody> | |
| </table> | |
| <span class="outliers"> | |
| <p>Outlying measurements have severe | |
| (<span class="percent">0.9218355379486942</span>%) | |
| effect on estimated standard deviation.</p> | |
| </span> | |
| <h2><a name="b15">quotes-at-end/split/4000</a></h2> | |
| <table width="100%"> | |
| <tbody> | |
| <tr> | |
| <td><div id="kde15" class="kdechart" | |
| style="width:450px;height:278px;"></div></td> | |
| <td><div id="time15" class="timechart" | |
| style="width:450px;height:278px;"></div></td> | |
| <!-- | |
| <td><div id="cycle15" class="cyclechart" | |
| style="width:300px;height:278px;"></div></td> | |
| --> | |
| </tr> | |
| </tbody> | |
| </table> | |
| <table> | |
| <thead class="analysis"> | |
| <th></th> | |
| <th class="cibound" | |
| title="0.95 confidence level">lower bound</th> | |
| <th>estimate</th> | |
| <th class="cibound" | |
| title="0.95 confidence level">upper bound</th> | |
| </thead> | |
| <tbody> | |
| <tr> | |
| <td>OLS regression</td> | |
| <td><span class="confinterval olstimelb15">xxx</span></td> | |
| <td><span class="olstimept15">xxx</span></td> | |
| <td><span class="confinterval olstimeub15">xxx</span></td> | |
| </tr> | |
| <tr> | |
| <td>R² goodness-of-fit</td> | |
| <td><span class="confinterval olsr2lb15">xxx</span></td> | |
| <td><span class="olsr2pt15">xxx</span></td> | |
| <td><span class="confinterval olsr2ub15">xxx</span></td> | |
| </tr> | |
| <tr> | |
| <td>Mean execution time</td> | |
| <td><span class="confinterval citime">1.9305543655805782e-4</span></td> | |
| <td><span class="time">1.9855277139151233e-4</span></td> | |
| <td><span class="confinterval citime">2.179232141165588e-4</span></td> | |
| </tr> | |
| <tr> | |
| <td>Standard deviation</td> | |
| <td><span class="confinterval citime">1.010649889357945e-5</span></td> | |
| <td><span class="time">2.9079430830960728e-5</span></td> | |
| <td><span class="confinterval citime">5.223943071322985e-5</span></td> | |
| </tr> | |
| </tbody> | |
| </table> | |
| <span class="outliers"> | |
| <p>Outlying measurements have severe | |
| (<span class="percent">0.8971468906862803</span>%) | |
| effect on estimated standard deviation.</p> | |
| </span> | |
| <h2><a name="b16">quotes-at-end/split/5000</a></h2> | |
| <table width="100%"> | |
| <tbody> | |
| <tr> | |
| <td><div id="kde16" class="kdechart" | |
| style="width:450px;height:278px;"></div></td> | |
| <td><div id="time16" class="timechart" | |
| style="width:450px;height:278px;"></div></td> | |
| <!-- | |
| <td><div id="cycle16" class="cyclechart" | |
| style="width:300px;height:278px;"></div></td> | |
| --> | |
| </tr> | |
| </tbody> | |
| </table> | |
| <table> | |
| <thead class="analysis"> | |
| <th></th> | |
| <th class="cibound" | |
| title="0.95 confidence level">lower bound</th> | |
| <th>estimate</th> | |
| <th class="cibound" | |
| title="0.95 confidence level">upper bound</th> | |
| </thead> | |
| <tbody> | |
| <tr> | |
| <td>OLS regression</td> | |
| <td><span class="confinterval olstimelb16">xxx</span></td> | |
| <td><span class="olstimept16">xxx</span></td> | |
| <td><span class="confinterval olstimeub16">xxx</span></td> | |
| </tr> | |
| <tr> | |
| <td>R² goodness-of-fit</td> | |
| <td><span class="confinterval olsr2lb16">xxx</span></td> | |
| <td><span class="olsr2pt16">xxx</span></td> | |
| <td><span class="confinterval olsr2ub16">xxx</span></td> | |
| </tr> | |
| <tr> | |
| <td>Mean execution time</td> | |
| <td><span class="confinterval citime">2.456815609981741e-4</span></td> | |
| <td><span class="time">2.4946871564005484e-4</span></td> | |
| <td><span class="confinterval citime">2.539519072041001e-4</span></td> | |
| </tr> | |
| <tr> | |
| <td>Standard deviation</td> | |
| <td><span class="confinterval citime">1.1152373785734072e-5</span></td> | |
| <td><span class="time">1.3475219389873387e-5</span></td> | |
| <td><span class="confinterval citime">1.77054063380741e-5</span></td> | |
| </tr> | |
| </tbody> | |
| </table> | |
| <span class="outliers"> | |
| <p>Outlying measurements have severe | |
| (<span class="percent">0.5152268382609221</span>%) | |
| effect on estimated standard deviation.</p> | |
| </span> | |
| <h2><a name="b17">quotes-at-end/split/6000</a></h2> | |
| <table width="100%"> | |
| <tbody> | |
| <tr> | |
| <td><div id="kde17" class="kdechart" | |
| style="width:450px;height:278px;"></div></td> | |
| <td><div id="time17" class="timechart" | |
| style="width:450px;height:278px;"></div></td> | |
| <!-- | |
| <td><div id="cycle17" class="cyclechart" | |
| style="width:300px;height:278px;"></div></td> | |
| --> | |
| </tr> | |
| </tbody> | |
| </table> | |
| <table> | |
| <thead class="analysis"> | |
| <th></th> | |
| <th class="cibound" | |
| title="0.95 confidence level">lower bound</th> | |
| <th>estimate</th> | |
| <th class="cibound" | |
| title="0.95 confidence level">upper bound</th> | |
| </thead> | |
| <tbody> | |
| <tr> | |
| <td>OLS regression</td> | |
| <td><span class="confinterval olstimelb17">xxx</span></td> | |
| <td><span class="olstimept17">xxx</span></td> | |
| <td><span class="confinterval olstimeub17">xxx</span></td> | |
| </tr> | |
| <tr> | |
| <td>R² goodness-of-fit</td> | |
| <td><span class="confinterval olsr2lb17">xxx</span></td> | |
| <td><span class="olsr2pt17">xxx</span></td> | |
| <td><span class="confinterval olsr2ub17">xxx</span></td> | |
| </tr> | |
| <tr> | |
| <td>Mean execution time</td> | |
| <td><span class="confinterval citime">3.190482827813333e-4</span></td> | |
| <td><span class="time">3.2354400734501695e-4</span></td> | |
| <td><span class="confinterval citime">3.289034486287611e-4</span></td> | |
| </tr> | |
| <tr> | |
| <td>Standard deviation</td> | |
| <td><span class="confinterval citime">1.2841455040950525e-5</span></td> | |
| <td><span class="time">1.65033002893497e-5</span></td> | |
| <td><span class="confinterval citime">2.0993673283418676e-5</span></td> | |
| </tr> | |
| </tbody> | |
| </table> | |
| <span class="outliers"> | |
| <p>Outlying measurements have moderate | |
| (<span class="percent">0.4788252975791756</span>%) | |
| effect on estimated standard deviation.</p> | |
| </span> | |
| <h2><a name="b18">quotes-at-end/split/7000</a></h2> | |
| <table width="100%"> | |
| <tbody> | |
| <tr> | |
| <td><div id="kde18" class="kdechart" | |
| style="width:450px;height:278px;"></div></td> | |
| <td><div id="time18" class="timechart" | |
| style="width:450px;height:278px;"></div></td> | |
| <!-- | |
| <td><div id="cycle18" class="cyclechart" | |
| style="width:300px;height:278px;"></div></td> | |
| --> | |
| </tr> | |
| </tbody> | |
| </table> | |
| <table> | |
| <thead class="analysis"> | |
| <th></th> | |
| <th class="cibound" | |
| title="0.95 confidence level">lower bound</th> | |
| <th>estimate</th> | |
| <th class="cibound" | |
| title="0.95 confidence level">upper bound</th> | |
| </thead> | |
| <tbody> | |
| <tr> | |
| <td>OLS regression</td> | |
| <td><span class="confinterval olstimelb18">xxx</span></td> | |
| <td><span class="olstimept18">xxx</span></td> | |
| <td><span class="confinterval olstimeub18">xxx</span></td> | |
| </tr> | |
| <tr> | |
| <td>R² goodness-of-fit</td> | |
| <td><span class="confinterval olsr2lb18">xxx</span></td> | |
| <td><span class="olsr2pt18">xxx</span></td> | |
| <td><span class="confinterval olsr2ub18">xxx</span></td> | |
| </tr> | |
| <tr> | |
| <td>Mean execution time</td> | |
| <td><span class="confinterval citime">4.0037195858701484e-4</span></td> | |
| <td><span class="time">4.046413513379428e-4</span></td> | |
| <td><span class="confinterval citime">4.0974409450706805e-4</span></td> | |
| </tr> | |
| <tr> | |
| <td>Standard deviation</td> | |
| <td><span class="confinterval citime">1.311246120752574e-5</span></td> | |
| <td><span class="time">1.643005843446733e-5</span></td> | |
| <td><span class="confinterval citime">2.025874568040129e-5</span></td> | |
| </tr> | |
| </tbody> | |
| </table> | |
| <span class="outliers"> | |
| <p>Outlying measurements have moderate | |
| (<span class="percent">0.35614654659300615</span>%) | |
| effect on estimated standard deviation.</p> | |
| </span> | |
| <h2><a name="b19">quotes-at-end/split/8000</a></h2> | |
| <table width="100%"> | |
| <tbody> | |
| <tr> | |
| <td><div id="kde19" class="kdechart" | |
| style="width:450px;height:278px;"></div></td> | |
| <td><div id="time19" class="timechart" | |
| style="width:450px;height:278px;"></div></td> | |
| <!-- | |
| <td><div id="cycle19" class="cyclechart" | |
| style="width:300px;height:278px;"></div></td> | |
| --> | |
| </tr> | |
| </tbody> | |
| </table> | |
| <table> | |
| <thead class="analysis"> | |
| <th></th> | |
| <th class="cibound" | |
| title="0.95 confidence level">lower bound</th> | |
| <th>estimate</th> | |
| <th class="cibound" | |
| title="0.95 confidence level">upper bound</th> | |
| </thead> | |
| <tbody> | |
| <tr> | |
| <td>OLS regression</td> | |
| <td><span class="confinterval olstimelb19">xxx</span></td> | |
| <td><span class="olstimept19">xxx</span></td> | |
| <td><span class="confinterval olstimeub19">xxx</span></td> | |
| </tr> | |
| <tr> | |
| <td>R² goodness-of-fit</td> | |
| <td><span class="confinterval olsr2lb19">xxx</span></td> | |
| <td><span class="olsr2pt19">xxx</span></td> | |
| <td><span class="confinterval olsr2ub19">xxx</span></td> | |
| </tr> | |
| <tr> | |
| <td>Mean execution time</td> | |
| <td><span class="confinterval citime">4.741950695435005e-4</span></td> | |
| <td><span class="time">4.799024159103751e-4</span></td> | |
| <td><span class="confinterval citime">4.8599139460695683e-4</span></td> | |
| </tr> | |
| <tr> | |
| <td>Standard deviation</td> | |
| <td><span class="confinterval citime">1.5664643609242203e-5</span></td> | |
| <td><span class="time">1.9421816067843573e-5</span></td> | |
| <td><span class="confinterval citime">2.4753235313123623e-5</span></td> | |
| </tr> | |
| </tbody> | |
| </table> | |
| <span class="outliers"> | |
| <p>Outlying measurements have moderate | |
| (<span class="percent">0.3389603785937259</span>%) | |
| effect on estimated standard deviation.</p> | |
| </span> | |
| <h2><a name="b20">quotes-at-end/split/9000</a></h2> | |
| <table width="100%"> | |
| <tbody> | |
| <tr> | |
| <td><div id="kde20" class="kdechart" | |
| style="width:450px;height:278px;"></div></td> | |
| <td><div id="time20" class="timechart" | |
| style="width:450px;height:278px;"></div></td> | |
| <!-- | |
| <td><div id="cycle20" class="cyclechart" | |
| style="width:300px;height:278px;"></div></td> | |
| --> | |
| </tr> | |
| </tbody> | |
| </table> | |
| <table> | |
| <thead class="analysis"> | |
| <th></th> | |
| <th class="cibound" | |
| title="0.95 confidence level">lower bound</th> | |
| <th>estimate</th> | |
| <th class="cibound" | |
| title="0.95 confidence level">upper bound</th> | |
| </thead> | |
| <tbody> | |
| <tr> | |
| <td>OLS regression</td> | |
| <td><span class="confinterval olstimelb20">xxx</span></td> | |
| <td><span class="olstimept20">xxx</span></td> | |
| <td><span class="confinterval olstimeub20">xxx</span></td> | |
| </tr> | |
| <tr> | |
| <td>R² goodness-of-fit</td> | |
| <td><span class="confinterval olsr2lb20">xxx</span></td> | |
| <td><span class="olsr2pt20">xxx</span></td> | |
| <td><span class="confinterval olsr2ub20">xxx</span></td> | |
| </tr> | |
| <tr> | |
| <td>Mean execution time</td> | |
| <td><span class="confinterval citime">5.685276734626736e-4</span></td> | |
| <td><span class="time">5.79819299266045e-4</span></td> | |
| <td><span class="confinterval citime">6.069364657473903e-4</span></td> | |
| </tr> | |
| <tr> | |
| <td>Standard deviation</td> | |
| <td><span class="confinterval citime">2.530524517237212e-5</span></td> | |
| <td><span class="time">5.6666023104275386e-5</span></td> | |
| <td><span class="confinterval citime">1.107737089208172e-4</span></td> | |
| </tr> | |
| </tbody> | |
| </table> | |
| <span class="outliers"> | |
| <p>Outlying measurements have severe | |
| (<span class="percent">0.7416322265530835</span>%) | |
| effect on estimated standard deviation.</p> | |
| </span> | |
| <h2><a name="b21">quotes-at-end/split/10000</a></h2> | |
| <table width="100%"> | |
| <tbody> | |
| <tr> | |
| <td><div id="kde21" class="kdechart" | |
| style="width:450px;height:278px;"></div></td> | |
| <td><div id="time21" class="timechart" | |
| style="width:450px;height:278px;"></div></td> | |
| <!-- | |
| <td><div id="cycle21" class="cyclechart" | |
| style="width:300px;height:278px;"></div></td> | |
| --> | |
| </tr> | |
| </tbody> | |
| </table> | |
| <table> | |
| <thead class="analysis"> | |
| <th></th> | |
| <th class="cibound" | |
| title="0.95 confidence level">lower bound</th> | |
| <th>estimate</th> | |
| <th class="cibound" | |
| title="0.95 confidence level">upper bound</th> | |
| </thead> | |
| <tbody> | |
| <tr> | |
| <td>OLS regression</td> | |
| <td><span class="confinterval olstimelb21">xxx</span></td> | |
| <td><span class="olstimept21">xxx</span></td> | |
| <td><span class="confinterval olstimeub21">xxx</span></td> | |
| </tr> | |
| <tr> | |
| <td>R² goodness-of-fit</td> | |
| <td><span class="confinterval olsr2lb21">xxx</span></td> | |
| <td><span class="olsr2pt21">xxx</span></td> | |
| <td><span class="confinterval olsr2ub21">xxx</span></td> | |
| </tr> | |
| <tr> | |
| <td>Mean execution time</td> | |
| <td><span class="confinterval citime">6.686209238606449e-4</span></td> | |
| <td><span class="time">6.840426688793642e-4</span></td> | |
| <td><span class="confinterval citime">7.063624397950608e-4</span></td> | |
| </tr> | |
| <tr> | |
| <td>Standard deviation</td> | |
| <td><span class="confinterval citime">4.486377914807235e-5</span></td> | |
| <td><span class="time">6.262835322963139e-5</span></td> | |
| <td><span class="confinterval citime">8.460855724926399e-5</span></td> | |
| </tr> | |
| </tbody> | |
| </table> | |
| <span class="outliers"> | |
| <p>Outlying measurements have severe | |
| (<span class="percent">0.7180074779052316</span>%) | |
| effect on estimated standard deviation.</p> | |
| </span> | |
| <h2><a name="grokularation">understanding this report</a></h2> | |
| <p>In this report, each function benchmarked by criterion is assigned | |
| a section of its own. The charts in each section are active; if | |
| you hover your mouse over data points and annotations, you will see | |
| more details.</p> | |
| <ul> | |
| <li>The chart on the left is a | |
| <a href="http://en.wikipedia.org/wiki/Kernel_density_estimation">kernel | |
| density estimate</a> (also known as a KDE) of time | |
| measurements. This graphs the probability of any given time | |
| measurement occurring. A spike indicates that a measurement of a | |
| particular time occurred; its height indicates how often that | |
| measurement was repeated.</li> | |
| <li>The chart on the right is the raw data from which the kernel | |
| density estimate is built. The <i>x</i> axis indicates the | |
| number of loop iterations, while the <i>y</i> axis shows measured | |
| execution time for the given number of loop iterations. The | |
| line behind the values is the linear regression prediction of | |
| execution time for a given number of iterations. Ideally, all | |
| measurements will be on (or very near) this line.</li> | |
| </ul> | |
| <p>Under the charts is a small table. | |
| The first two rows are the results of a linear regression run | |
| on the measurements displayed in the right-hand chart.</p> | |
| <ul> | |
| <li><i>OLS regression</i> indicates the | |
| time estimated for a single loop iteration using an ordinary | |
| least-squares regression model. This number is more accurate | |
| than the <i>mean</i> estimate below it, as it more effectively | |
| eliminates measurement overhead and other constant factors.</li> | |
| <li><i>R² goodness-of-fit</i> is a measure of how | |
| accurately the linear regression model fits the observed | |
| measurements. If the measurements are not too noisy, R² | |
| should lie between 0.99 and 1, indicating an excellent fit. If | |
| the number is below 0.99, something is confounding the accuracy | |
| of the linear model.</li> | |
| <li><i>Mean execution time</i> and <i>standard deviation</i> are | |
| statistics calculated from execution time | |
| divided by number of iterations.</li> | |
| </ul> | |
| <p>We use a statistical technique called | |
| the <a href="http://en.wikipedia.org/wiki/Bootstrapping_(statistics)">bootstrap</a> | |
| to provide confidence intervals on our estimates. The | |
| bootstrap-derived upper and lower bounds on estimates let you see | |
| how accurate we believe those estimates to be. (Hover the mouse | |
| over the table headers to see the confidence levels.)</p> | |
| <p>A noisy benchmarking environment can cause some or many | |
| measurements to fall far from the mean. These outlying | |
| measurements can have a significant inflationary effect on the | |
| estimate of the standard deviation. We calculate and display an | |
| estimate of the extent to which the standard deviation has been | |
| inflated by outliers.</p> | |
| <script type="text/javascript"> | |
| $(function () { | |
| function mangulate(rpt) { | |
| var measured = function(key) { | |
| var idx = rpt.reportKeys.indexOf(key); | |
| return rpt.reportMeasured.map(function(r) { return r[idx]; }); | |
| }; | |
| var number = rpt.reportNumber; | |
| var name = rpt.reportName; | |
| var mean = rpt.reportAnalysis.anMean.estPoint; | |
| var iters = measured("iters"); | |
| var times = measured("time"); | |
| var kdetimes = rpt.reportKDEs[0].kdeValues; | |
| var kdepdf = rpt.reportKDEs[0].kdePDF; | |
| var meanSecs = mean; | |
| var units = $.timeUnits(mean); | |
| var rgrs = rpt.reportAnalysis.anRegress[0]; | |
| var scale = units[0]; | |
| var olsTime = rgrs.regCoeffs.iters; | |
| $(".olstimept" + number).text(function() { | |
| return $.renderTime(olsTime.estPoint); | |
| }); | |
| $(".olstimelb" + number).text(function() { | |
| return $.renderTime(olsTime.estLowerBound); | |
| }); | |
| $(".olstimeub" + number).text(function() { | |
| return $.renderTime(olsTime.estUpperBound); | |
| }); | |
| $(".olsr2pt" + number).text(function() { | |
| return rgrs.regRSquare.estPoint.toFixed(3); | |
| }); | |
| $(".olsr2lb" + number).text(function() { | |
| return rgrs.regRSquare.estLowerBound.toFixed(3); | |
| }); | |
| $(".olsr2ub" + number).text(function() { | |
| return rgrs.regRSquare.estUpperBound.toFixed(3); | |
| }); | |
| mean *= scale; | |
| kdetimes = $.scaleBy(scale, kdetimes); | |
| var kq = $("#kde" + number); | |
| var k = $.plot(kq, | |
| [{ label: name + " time densities", | |
| data: $.zip(kdetimes, kdepdf), | |
| }], | |
| { xaxis: { tickFormatter: $.unitFormatter(scale) }, | |
| yaxis: { ticks: false }, | |
| grid: { borderColor: "#777", | |
| hoverable: true, markings: [ { color: '#6fd3fb', | |
| lineWidth: 1.5, xaxis: { from: mean, to: mean } } ] }, | |
| }); | |
| var o = k.pointOffset({ x: mean, y: 0}); | |
| kq.append('<div class="meanlegend" title="' + $.renderTime(meanSecs) + | |
| '" style="position:absolute;left:' + (o.left + 4) + | |
| 'px;bottom:139px;">mean</div>'); | |
| $.addTooltip("#kde" + number, | |
| function(secs) { return $.renderTime(secs / scale); }); | |
| var timepairs = new Array(times.length); | |
| var lastiter = iters[iters.length-1]; | |
| var olspairs = [[0,0], [lastiter, lastiter * scale * olsTime.estPoint]]; | |
| for (var i = 0; i < times.length; i++) | |
| timepairs[i] = [iters[i],times[i]*scale]; | |
| iterFormatter = function() { | |
| var denom = 0; | |
| return function(iters) { | |
| if (iters == 0) | |
| return ''; | |
| if (denom > 0) | |
| return (iters / denom).toFixed(); | |
| var power; | |
| if (iters >= 1e9) { | |
| denom = '1e9'; power = '⁹'; | |
| } | |
| if (iters >= 1e6) { | |
| denom = '1e6'; power = '⁶'; | |
| } | |
| else if (iters >= 1e3) { | |
| denom = '1e3'; power = '³'; | |
| } | |
| else denom = 1; | |
| if (denom > 1) { | |
| iters = (iters / denom).toFixed(); | |
| iters += '×10' + power + ' iters'; | |
| } else { | |
| iters += ' iters'; | |
| } | |
| return iters; | |
| }; | |
| }; | |
| $.plot($("#time" + number), | |
| [{ label: "regression", data: olspairs, | |
| lines: { show: true } }, | |
| { label: name + " times", data: timepairs, | |
| points: { show: true } }], | |
| { grid: { borderColor: "#777", hoverable: true }, | |
| xaxis: { tickFormatter: iterFormatter() }, | |
| yaxis: { tickFormatter: $.unitFormatter(scale) } }); | |
| $.addTooltip("#time" + number, | |
| function(iters,secs) { | |
| return ($.renderTime(secs / scale) + ' / ' + | |
| iters.toLocaleString() + ' iters'); | |
| }); | |
| if (0) { | |
| var cyclepairs = new Array(cycles.length); | |
| for (var i = 0; i < cycles.length; i++) | |
| cyclepairs[i] = [cycles[i],i]; | |
| $.plot($("#cycle" + number), | |
| [{ label: name + " cycles", | |
| data: cyclepairs }], | |
| { points: { show: true }, | |
| grid: { borderColor: "#777", hoverable: true }, | |
| xaxis: { tickFormatter: | |
| function(cycles,axis) { return cycles + ' cycles'; }}, | |
| yaxis: { ticks: false }, | |
| }); | |
| $.addTooltip("#cycles" + number, function(x,y) { return x + ' cycles'; }); | |
| } | |
| }; | |
| var reports = 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| |
| reports.map(mangulate); | |
| var benches = ["quotes-at-end/regex/0","quotes-at-end/regex/1000","quotes-at-end/regex/2000","quotes-at-end/regex/3000","quotes-at-end/regex/4000","quotes-at-end/regex/5000","quotes-at-end/regex/6000","quotes-at-end/regex/7000","quotes-at-end/regex/8000","quotes-at-end/regex/9000","quotes-at-end/regex/10000","quotes-at-end/split/0","quotes-at-end/split/1000","quotes-at-end/split/2000","quotes-at-end/split/3000","quotes-at-end/split/4000","quotes-at-end/split/5000","quotes-at-end/split/6000","quotes-at-end/split/7000","quotes-at-end/split/8000","quotes-at-end/split/9000","quotes-at-end/split/10000",]; | |
| var ylabels = [[-0,'<a href="#b0">quotes-at-end/regex/0</a>'],[-1,'<a href="#b1">quotes-at-end/regex/1000</a>'],[-2,'<a href="#b2">quotes-at-end/regex/2000</a>'],[-3,'<a href="#b3">quotes-at-end/regex/3000</a>'],[-4,'<a href="#b4">quotes-at-end/regex/4000</a>'],[-5,'<a href="#b5">quotes-at-end/regex/5000</a>'],[-6,'<a href="#b6">quotes-at-end/regex/6000</a>'],[-7,'<a href="#b7">quotes-at-end/regex/7000</a>'],[-8,'<a href="#b8">quotes-at-end/regex/8000</a>'],[-9,'<a href="#b9">quotes-at-end/regex/9000</a>'],[-10,'<a href="#b10">quotes-at-end/regex/10000</a>'],[-11,'<a href="#b11">quotes-at-end/split/0</a>'],[-12,'<a href="#b12">quotes-at-end/split/1000</a>'],[-13,'<a href="#b13">quotes-at-end/split/2000</a>'],[-14,'<a href="#b14">quotes-at-end/split/3000</a>'],[-15,'<a href="#b15">quotes-at-end/split/4000</a>'],[-16,'<a href="#b16">quotes-at-end/split/5000</a>'],[-17,'<a href="#b17">quotes-at-end/split/6000</a>'],[-18,'<a href="#b18">quotes-at-end/split/7000</a>'],[-19,'<a href="#b19">quotes-at-end/split/8000</a>'],[-20,'<a href="#b20">quotes-at-end/split/9000</a>'],[-21,'<a href="#b21">quotes-at-end/split/10000</a>'],]; | |
| var means = $.scaleTimes([4.458155140693469e-6,4.357199397885642e-4,9.834023486487435e-4,1.5158980525330035e-3,2.1570241714561392e-3,2.68351137937369e-3,3.1242368400038745e-3,3.531167348945552e-3,4.109721774768918e-3,5.649626209274329e-3,7.786360058070533e-3,6.22187449447239e-7,4.708084433504224e-5,9.175544401879408e-5,1.492091026857772e-4,1.9855277139151233e-4,2.4946871564005484e-4,3.2354400734501695e-4,4.046413513379428e-4,4.799024159103751e-4,5.79819299266045e-4,6.840426688793642e-4,]); | |
| var xs = []; | |
| var prev = null; | |
| for (var i = 0; i < means[0].length; i++) { | |
| var name = benches[i].split(/\//); | |
| name.pop(); | |
| name = name.join('/'); | |
| if (name != prev) { | |
| xs.push({ label: name, data: [[means[0][i], -i]]}); | |
| prev = name; | |
| } | |
| else | |
| xs[xs.length-1].data.push([means[0][i],-i]); | |
| } | |
| var oq = $("#overview"); | |
| o = $.plot(oq, xs, { bars: { show: true, horizontal: true, | |
| barWidth: 0.75, align: "center" }, | |
| grid: { borderColor: "#777", hoverable: true }, | |
| legend: { show: xs.length > 1 }, | |
| xaxis: { max: Math.max.apply(undefined,means[0]) * 1.02 }, | |
| yaxis: { ticks: ylabels, tickColor: '#ffffff' } }); | |
| if (benches.length > 3) | |
| o.getPlaceholder().height(28*benches.length); | |
| o.resize(); | |
| o.setupGrid(); | |
| o.draw(); | |
| $.addTooltip("#overview", function(x,y) { return $.renderTime(x / means[1]); }); | |
| }); | |
| $(document).ready(function () { | |
| $(".time").text(function(_, text) { | |
| return $.renderTime(text); | |
| }); | |
| $(".citime").text(function(_, text) { | |
| return $.renderTime(text); | |
| }); | |
| $(".percent").text(function(_, text) { | |
| return (text*100).toFixed(1); | |
| }); | |
| }); | |
| </script> | |
| </div> | |
| </div> | |
| <div id="footer"> | |
| <div class="body"> | |
| <div class="footfirst"> | |
| <h2>colophon</h2> | |
| <p>This report was created using the | |
| <a href="http://hackage.haskell.org/package/criterion">criterion</a> | |
| benchmark execution and performance analysis tool.</p> | |
| <p>Criterion is developed and maintained | |
| by <a href="http://www.serpentine.com/blog/">Bryan O'Sullivan</a>.</p> | |
| </div> | |
| </div> | |
| </div> | |
| </body> | |
| </html> |
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| This is free and unencumbered software released into the public domain. | |
| Anyone is free to copy, modify, publish, use, compile, sell, or | |
| distribute this software, either in source code form or as a compiled | |
| binary, for any purpose, commercial or non-commercial, and by any | |
| means. | |
| In jurisdictions that recognize copyright laws, the author or authors | |
| of this software dedicate any and all copyright interest in the | |
| software to the public domain. We make this dedication for the benefit | |
| of the public at large and to the detriment of our heirs and | |
| successors. We intend this dedication to be an overt act of | |
| relinquishment in perpetuity of all present and future rights to this | |
| software under copyright law. | |
| THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, | |
| EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF | |
| MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. | |
| IN NO EVENT SHALL THE AUTHORS BE LIABLE FOR ANY CLAIM, DAMAGES OR | |
| OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, | |
| ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR | |
| OTHER DEALINGS IN THE SOFTWARE. | |
| For more information, please refer to <http://unlicense.org/> |
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| module QCount where | |
| import Benchmarks (qCountMain) | |
| main = qCountMain |
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| module QLen where | |
| import Benchmarks (qLenMain) | |
| main = qLenMain |
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| module SLen where | |
| import Benchmarks (sLenMain) | |
| main = sLenMain |
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| <!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN" "http://www.w3.org/TR/html4/loose.dtd"> | |
| <html> | |
| <head> | |
| <meta http-equiv="Content-Type" content="text/html; charset=utf-8"> | |
| <title>criterion report</title> | |
| <script language="javascript" type="text/javascript"> | |
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series=[],options={colors:["#edc240","#afd8f8","#cb4b4b","#4da74d","#9440ed"],legend:{show:true,noColumns:1,labelFormatter:null,labelBoxBorderColor:"#ccc",container:null,position:"ne",margin:5,backgroundColor:null,backgroundOpacity:.85,sorted:null},xaxis:{show:null,position:"bottom",mode:null,font:null,color:null,tickColor:null,transform:null,inverseTransform:null,min:null,max:null,autoscaleMargin:null,ticks:null,tickFormatter:null,labelWidth:null,labelHeight:null,reserveSpace:null,tickLength:null,alignTicksWithAxis:null,tickDecimals:null,tickSize:null,minTickSize:null},yaxis:{autoscaleMargin:.02,position:"left"},xaxes:[],yaxes:[],series:{points:{show:false,radius:3,lineWidth:2,fill:true,fillColor:"#ffffff",symbol:"circle"},lines:{lineWidth:2,fill:false,fillColor:null,steps:false},bars:{show:false,lineWidth:2,barWidth:1,fill:true,fillColor:null,align:"left",horizontal:false,zero:true},shadowSize:3,highlightColor:null},grid:{show:true,aboveData:false,color:"#545454",backgroundColor:null,borderColor:null,tickColor:null,margin:0,labelMargin:5,axisMargin:8,borderWidth:2,minBorderMargin:null,markings:null,markingsColor:"#f4f4f4",markingsLineWidth:2,clickable:false,hoverable:false,autoHighlight:true,mouseActiveRadius:10},interaction:{redrawOverlayInterval:1e3/60},hooks:{}},surface=null,overlay=null,eventHolder=null,ctx=null,octx=null,xaxes=[],yaxes=[],plotOffset={left:0,right:0,top:0,bottom:0},plotWidth=0,plotHeight=0,hooks={processOptions:[],processRawData:[],processDatapoints:[],processOffset:[],drawBackground:[],drawSeries:[],draw:[],bindEvents:[],drawOverlay:[],shutdown:[]},plot=this;plot.setData=setData;plot.setupGrid=setupGrid;plot.draw=draw;plot.getPlaceholder=function(){return placeholder};plot.getCanvas=function(){return surface.element};plot.getPlotOffset=function(){return plotOffset};plot.width=function(){return plotWidth};plot.height=function(){return plotHeight};plot.offset=function(){var o=eventHolder.offset();o.left+=plotOffset.left;o.top+=plotOffset.top;return o};plot.getData=function(){return series};plot.getAxes=function(){var res={},i;$.each(xaxes.concat(yaxes),function(_,axis){if(axis)res[axis.direction+(axis.n!=1?axis.n:"")+"axis"]=axis});return res};plot.getXAxes=function(){return xaxes};plot.getYAxes=function(){return yaxes};plot.c2p=canvasToAxisCoords;plot.p2c=axisToCanvasCoords;plot.getOptions=function(){return options};plot.highlight=highlight;plot.unhighlight=unhighlight;plot.triggerRedrawOverlay=triggerRedrawOverlay;plot.pointOffset=function(point){return{left:parseInt(xaxes[axisNumber(point,"x")-1].p2c(+point.x)+plotOffset.left,10),top:parseInt(yaxes[axisNumber(point,"y")-1].p2c(+point.y)+plotOffset.top,10)}};plot.shutdown=shutdown;plot.destroy=function(){shutdown();placeholder.removeData("plot").empty();series=[];options=null;surface=null;overlay=null;eventHolder=null;ctx=null;octx=null;xaxes=[];yaxes=[];hooks=null;highlights=[];plot=null};plot.resize=function(){var width=placeholder.width(),height=placeholder.height();surface.resize(width,height);overlay.resize(width,height)};plot.hooks=hooks;initPlugins(plot);parseOptions(options_);setupCanvases();setData(data_);setupGrid();draw();bindEvents();function executeHooks(hook,args){args=[plot].concat(args);for(var i=0;i<hook.length;++i)hook[i].apply(this,args)}function initPlugins(){var classes={Canvas:Canvas};for(var i=0;i<plugins.length;++i){var p=plugins[i];p.init(plot,classes);if(p.options)$.extend(true,options,p.options)}}function parseOptions(opts){$.extend(true,options,opts);if(opts&&opts.colors){options.colors=opts.colors}if(options.xaxis.color==null)options.xaxis.color=$.color.parse(options.grid.color).scale("a",.22).toString();if(options.yaxis.color==null)options.yaxis.color=$.color.parse(options.grid.color).scale("a",.22).toString();if(options.xaxis.tickColor==null)options.xaxis.tickColor=options.grid.tickColor||options.xaxis.color;if(options.yaxis.tickColor==null)options.yaxis.tickColor=options.grid.tickColor||options.yaxis.color;if(options.grid.borderColor==null)options.grid.borderColor=options.grid.color;if(options.grid.tickColor==null)options.grid.tickColor=$.color.parse(options.grid.color).scale("a",.22).toString();var i,axisOptions,axisCount,fontSize=placeholder.css("font-size"),fontSizeDefault=fontSize?+fontSize.replace("px",""):13,fontDefaults={style:placeholder.css("font-style"),size:Math.round(.8*fontSizeDefault),variant:placeholder.css("font-variant"),weight:placeholder.css("font-weight"),family:placeholder.css("font-family")};axisCount=options.xaxes.length||1;for(i=0;i<axisCount;++i){axisOptions=options.xaxes[i];if(axisOptions&&!axisOptions.tickColor){axisOptions.tickColor=axisOptions.color}axisOptions=$.extend(true,{},options.xaxis,axisOptions);options.xaxes[i]=axisOptions;if(axisOptions.font){axisOptions.font=$.extend({},fontDefaults,axisOptions.font);if(!axisOptions.font.color){axisOptions.font.color=axisOptions.color}if(!axisOptions.font.lineHeight){axisOptions.font.lineHeight=Math.round(axisOptions.font.size*1.15)}}}axisCount=options.yaxes.length||1;for(i=0;i<axisCount;++i){axisOptions=options.yaxes[i];if(axisOptions&&!axisOptions.tickColor){axisOptions.tickColor=axisOptions.color}axisOptions=$.extend(true,{},options.yaxis,axisOptions);options.yaxes[i]=axisOptions;if(axisOptions.font){axisOptions.font=$.extend({},fontDefaults,axisOptions.font);if(!axisOptions.font.color){axisOptions.font.color=axisOptions.color}if(!axisOptions.font.lineHeight){axisOptions.font.lineHeight=Math.round(axisOptions.font.size*1.15)}}}if(options.xaxis.noTicks&&options.xaxis.ticks==null)options.xaxis.ticks=options.xaxis.noTicks;if(options.yaxis.noTicks&&options.yaxis.ticks==null)options.yaxis.ticks=options.yaxis.noTicks;if(options.x2axis){options.xaxes[1]=$.extend(true,{},options.xaxis,options.x2axis);options.xaxes[1].position="top";if(options.x2axis.min==null){options.xaxes[1].min=null}if(options.x2axis.max==null){options.xaxes[1].max=null}}if(options.y2axis){options.yaxes[1]=$.extend(true,{},options.yaxis,options.y2axis);options.yaxes[1].position="right";if(options.y2axis.min==null){options.yaxes[1].min=null}if(options.y2axis.max==null){options.yaxes[1].max=null}}if(options.grid.coloredAreas)options.grid.markings=options.grid.coloredAreas;if(options.grid.coloredAreasColor)options.grid.markingsColor=options.grid.coloredAreasColor;if(options.lines)$.extend(true,options.series.lines,options.lines);if(options.points)$.extend(true,options.series.points,options.points);if(options.bars)$.extend(true,options.series.bars,options.bars);if(options.shadowSize!=null)options.series.shadowSize=options.shadowSize;if(options.highlightColor!=null)options.series.highlightColor=options.highlightColor;for(i=0;i<options.xaxes.length;++i)getOrCreateAxis(xaxes,i+1).options=options.xaxes[i];for(i=0;i<options.yaxes.length;++i)getOrCreateAxis(yaxes,i+1).options=options.yaxes[i];for(var n in hooks)if(options.hooks[n]&&options.hooks[n].length)hooks[n]=hooks[n].concat(options.hooks[n]);executeHooks(hooks.processOptions,[options])}function setData(d){series=parseData(d);fillInSeriesOptions();processData()}function parseData(d){var res=[];for(var i=0;i<d.length;++i){var s=$.extend(true,{},options.series);if(d[i].data!=null){s.data=d[i].data;delete d[i].data;$.extend(true,s,d[i]);d[i].data=s.data}else s.data=d[i];res.push(s)}return res}function axisNumber(obj,coord){var a=obj[coord+"axis"];if(typeof a=="object")a=a.n;if(typeof a!="number")a=1;return a}function allAxes(){return $.grep(xaxes.concat(yaxes),function(a){return a})}function canvasToAxisCoords(pos){var res={},i,axis;for(i=0;i<xaxes.length;++i){axis=xaxes[i];if(axis&&axis.used)res["x"+axis.n]=axis.c2p(pos.left)}for(i=0;i<yaxes.length;++i){axis=yaxes[i];if(axis&&axis.used)res["y"+axis.n]=axis.c2p(pos.top)}if(res.x1!==undefined)res.x=res.x1;if(res.y1!==undefined)res.y=res.y1;return res}function axisToCanvasCoords(pos){var res={},i,axis,key;for(i=0;i<xaxes.length;++i){axis=xaxes[i];if(axis&&axis.used){key="x"+axis.n;if(pos[key]==null&&axis.n==1)key="x";if(pos[key]!=null){res.left=axis.p2c(pos[key]);break}}}for(i=0;i<yaxes.length;++i){axis=yaxes[i];if(axis&&axis.used){key="y"+axis.n;if(pos[key]==null&&axis.n==1)key="y";if(pos[key]!=null){res.top=axis.p2c(pos[key]);break}}}return res}function getOrCreateAxis(axes,number){if(!axes[number-1])axes[number-1]={n:number,direction:axes==xaxes?"x":"y",options:$.extend(true,{},axes==xaxes?options.xaxis:options.yaxis)};return axes[number-1]}function fillInSeriesOptions(){var neededColors=series.length,maxIndex=-1,i;for(i=0;i<series.length;++i){var sc=series[i].color;if(sc!=null){neededColors--;if(typeof sc=="number"&&sc>maxIndex){maxIndex=sc}}}if(neededColors<=maxIndex){neededColors=maxIndex+1}var c,colors=[],colorPool=options.colors,colorPoolSize=colorPool.length,variation=0;for(i=0;i<neededColors;i++){c=$.color.parse(colorPool[i%colorPoolSize]||"#666");if(i%colorPoolSize==0&&i){if(variation>=0){if(variation<.5){variation=-variation-.2}else variation=0}else variation=-variation}colors[i]=c.scale("rgb",1+variation)}var colori=0,s;for(i=0;i<series.length;++i){s=series[i];if(s.color==null){s.color=colors[colori].toString();++colori}else if(typeof s.color=="number")s.color=colors[s.color].toString();if(s.lines.show==null){var v,show=true;for(v in s)if(s[v]&&s[v].show){show=false;break}if(show)s.lines.show=true}if(s.lines.zero==null){s.lines.zero=!!s.lines.fill}s.xaxis=getOrCreateAxis(xaxes,axisNumber(s,"x"));s.yaxis=getOrCreateAxis(yaxes,axisNumber(s,"y"))}}function processData(){var topSentry=Number.POSITIVE_INFINITY,bottomSentry=Number.NEGATIVE_INFINITY,fakeInfinity=Number.MAX_VALUE,i,j,k,m,length,s,points,ps,x,y,axis,val,f,p,data,format;function updateAxis(axis,min,max){if(min<axis.datamin&&min!=-fakeInfinity)axis.datamin=min;if(max>axis.datamax&&max!=fakeInfinity)axis.datamax=max}$.each(allAxes(),function(_,axis){axis.datamin=topSentry;axis.datamax=bottomSentry;axis.used=false});for(i=0;i<series.length;++i){s=series[i];s.datapoints={points:[]};executeHooks(hooks.processRawData,[s,s.data,s.datapoints])}for(i=0;i<series.length;++i){s=series[i];data=s.data;format=s.datapoints.format;if(!format){format=[];format.push({x:true,number:true,required:true});format.push({y:true,number:true,required:true});if(s.bars.show||s.lines.show&&s.lines.fill){var autoscale=!!(s.bars.show&&s.bars.zero||s.lines.show&&s.lines.zero);format.push({y:true,number:true,required:false,defaultValue:0,autoscale:autoscale});if(s.bars.horizontal){delete format[format.length-1].y;format[format.length-1].x=true}}s.datapoints.format=format}if(s.datapoints.pointsize!=null)continue;s.datapoints.pointsize=format.length;ps=s.datapoints.pointsize;points=s.datapoints.points;var insertSteps=s.lines.show&&s.lines.steps;s.xaxis.used=s.yaxis.used=true;for(j=k=0;j<data.length;++j,k+=ps){p=data[j];var nullify=p==null;if(!nullify){for(m=0;m<ps;++m){val=p[m];f=format[m];if(f){if(f.number&&val!=null){val=+val;if(isNaN(val))val=null;else if(val==Infinity)val=fakeInfinity;else if(val==-Infinity)val=-fakeInfinity}if(val==null){if(f.required)nullify=true;if(f.defaultValue!=null)val=f.defaultValue}}points[k+m]=val}}if(nullify){for(m=0;m<ps;++m){val=points[k+m];if(val!=null){f=format[m];if(f.autoscale!==false){if(f.x){updateAxis(s.xaxis,val,val)}if(f.y){updateAxis(s.yaxis,val,val)}}}points[k+m]=null}}else{if(insertSteps&&k>0&&points[k-ps]!=null&&points[k-ps]!=points[k]&&points[k-ps+1]!=points[k+1]){for(m=0;m<ps;++m)points[k+ps+m]=points[k+m];points[k+1]=points[k-ps+1];k+=ps}}}}for(i=0;i<series.length;++i){s=series[i];executeHooks(hooks.processDatapoints,[s,s.datapoints])}for(i=0;i<series.length;++i){s=series[i];points=s.datapoints.points;ps=s.datapoints.pointsize;format=s.datapoints.format;var xmin=topSentry,ymin=topSentry,xmax=bottomSentry,ymax=bottomSentry;for(j=0;j<points.length;j+=ps){if(points[j]==null)continue;for(m=0;m<ps;++m){val=points[j+m];f=format[m];if(!f||f.autoscale===false||val==fakeInfinity||val==-fakeInfinity)continue;if(f.x){if(val<xmin)xmin=val;if(val>xmax)xmax=val}if(f.y){if(val<ymin)ymin=val;if(val>ymax)ymax=val}}}if(s.bars.show){var delta;switch(s.bars.align){case"left":delta=0;break;case"right":delta=-s.bars.barWidth;break;default:delta=-s.bars.barWidth/2}if(s.bars.horizontal){ymin+=delta;ymax+=delta+s.bars.barWidth}else{xmin+=delta;xmax+=delta+s.bars.barWidth}}updateAxis(s.xaxis,xmin,xmax);updateAxis(s.yaxis,ymin,ymax)}$.each(allAxes(),function(_,axis){if(axis.datamin==topSentry)axis.datamin=null;if(axis.datamax==bottomSentry)axis.datamax=null})}function setupCanvases(){placeholder.css("padding",0).children().filter(function(){return!$(this).hasClass("flot-overlay")&&!$(this).hasClass("flot-base")}).remove();if(placeholder.css("position")=="static")placeholder.css("position","relative");surface=new Canvas("flot-base",placeholder);overlay=new Canvas("flot-overlay",placeholder);ctx=surface.context;octx=overlay.context;eventHolder=$(overlay.element).unbind();var existing=placeholder.data("plot");if(existing){existing.shutdown();overlay.clear()}placeholder.data("plot",plot)}function bindEvents(){if(options.grid.hoverable){eventHolder.mousemove(onMouseMove);eventHolder.bind("mouseleave",onMouseLeave)}if(options.grid.clickable)eventHolder.click(onClick);executeHooks(hooks.bindEvents,[eventHolder])}function shutdown(){if(redrawTimeout)clearTimeout(redrawTimeout);eventHolder.unbind("mousemove",onMouseMove);eventHolder.unbind("mouseleave",onMouseLeave);eventHolder.unbind("click",onClick);executeHooks(hooks.shutdown,[eventHolder])}function setTransformationHelpers(axis){function identity(x){return x}var s,m,t=axis.options.transform||identity,it=axis.options.inverseTransform;if(axis.direction=="x"){s=axis.scale=plotWidth/Math.abs(t(axis.max)-t(axis.min));m=Math.min(t(axis.max),t(axis.min))}else{s=axis.scale=plotHeight/Math.abs(t(axis.max)-t(axis.min));s=-s;m=Math.max(t(axis.max),t(axis.min))}if(t==identity)axis.p2c=function(p){return(p-m)*s};else axis.p2c=function(p){return(t(p)-m)*s};if(!it)axis.c2p=function(c){return m+c/s};else axis.c2p=function(c){return it(m+c/s)}}function measureTickLabels(axis){var opts=axis.options,ticks=axis.ticks||[],labelWidth=opts.labelWidth||0,labelHeight=opts.labelHeight||0,maxWidth=labelWidth||(axis.direction=="x"?Math.floor(surface.width/(ticks.length||1)):null),legacyStyles=axis.direction+"Axis "+axis.direction+axis.n+"Axis",layer="flot-"+axis.direction+"-axis flot-"+axis.direction+axis.n+"-axis "+legacyStyles,font=opts.font||"flot-tick-label tickLabel";for(var i=0;i<ticks.length;++i){var t=ticks[i];if(!t.label)continue;var info=surface.getTextInfo(layer,t.label,font,null,maxWidth);labelWidth=Math.max(labelWidth,info.width);labelHeight=Math.max(labelHeight,info.height)}axis.labelWidth=opts.labelWidth||labelWidth;axis.labelHeight=opts.labelHeight||labelHeight}function allocateAxisBoxFirstPhase(axis){var lw=axis.labelWidth,lh=axis.labelHeight,pos=axis.options.position,isXAxis=axis.direction==="x",tickLength=axis.options.tickLength,axisMargin=options.grid.axisMargin,padding=options.grid.labelMargin,innermost=true,outermost=true,first=true,found=false;$.each(isXAxis?xaxes:yaxes,function(i,a){if(a&&(a.show||a.reserveSpace)){if(a===axis){found=true}else if(a.options.position===pos){if(found){outermost=false}else{innermost=false}}if(!found){first=false}}});if(outermost){axisMargin=0}if(tickLength==null){tickLength=first?"full":5}if(!isNaN(+tickLength))padding+=+tickLength;if(isXAxis){lh+=padding;if(pos=="bottom"){plotOffset.bottom+=lh+axisMargin;axis.box={top:surface.height-plotOffset.bottom,height:lh}}else{axis.box={top:plotOffset.top+axisMargin,height:lh};plotOffset.top+=lh+axisMargin}}else{lw+=padding;if(pos=="left"){axis.box={left:plotOffset.left+axisMargin,width:lw};plotOffset.left+=lw+axisMargin}else{plotOffset.right+=lw+axisMargin;axis.box={left:surface.width-plotOffset.right,width:lw}}}axis.position=pos;axis.tickLength=tickLength;axis.box.padding=padding;axis.innermost=innermost}function allocateAxisBoxSecondPhase(axis){if(axis.direction=="x"){axis.box.left=plotOffset.left-axis.labelWidth/2;axis.box.width=surface.width-plotOffset.left-plotOffset.right+axis.labelWidth}else{axis.box.top=plotOffset.top-axis.labelHeight/2;axis.box.height=surface.height-plotOffset.bottom-plotOffset.top+axis.labelHeight}}function adjustLayoutForThingsStickingOut(){var minMargin=options.grid.minBorderMargin,axis,i;if(minMargin==null){minMargin=0;for(i=0;i<series.length;++i)minMargin=Math.max(minMargin,2*(series[i].points.radius+series[i].points.lineWidth/2))}var margins={left:minMargin,right:minMargin,top:minMargin,bottom:minMargin};$.each(allAxes(),function(_,axis){if(axis.reserveSpace&&axis.ticks&&axis.ticks.length){if(axis.direction==="x"){margins.left=Math.max(margins.left,axis.labelWidth/2);margins.right=Math.max(margins.right,axis.labelWidth/2)}else{margins.bottom=Math.max(margins.bottom,axis.labelHeight/2);margins.top=Math.max(margins.top,axis.labelHeight/2)}}});plotOffset.left=Math.ceil(Math.max(margins.left,plotOffset.left));plotOffset.right=Math.ceil(Math.max(margins.right,plotOffset.right));plotOffset.top=Math.ceil(Math.max(margins.top,plotOffset.top));plotOffset.bottom=Math.ceil(Math.max(margins.bottom,plotOffset.bottom))}function setupGrid(){var i,axes=allAxes(),showGrid=options.grid.show;for(var a in plotOffset){var margin=options.grid.margin||0;plotOffset[a]=typeof margin=="number"?margin:margin[a]||0}executeHooks(hooks.processOffset,[plotOffset]);for(var a in plotOffset){if(typeof options.grid.borderWidth=="object"){plotOffset[a]+=showGrid?options.grid.borderWidth[a]:0}else{plotOffset[a]+=showGrid?options.grid.borderWidth:0}}$.each(axes,function(_,axis){var axisOpts=axis.options;axis.show=axisOpts.show==null?axis.used:axisOpts.show;axis.reserveSpace=axisOpts.reserveSpace==null?axis.show:axisOpts.reserveSpace;setRange(axis)});if(showGrid){var allocatedAxes=$.grep(axes,function(axis){return axis.show||axis.reserveSpace});$.each(allocatedAxes,function(_,axis){setupTickGeneration(axis);setTicks(axis);snapRangeToTicks(axis,axis.ticks);measureTickLabels(axis)});for(i=allocatedAxes.length-1;i>=0;--i)allocateAxisBoxFirstPhase(allocatedAxes[i]);adjustLayoutForThingsStickingOut();$.each(allocatedAxes,function(_,axis){allocateAxisBoxSecondPhase(axis)})}plotWidth=surface.width-plotOffset.left-plotOffset.right;plotHeight=surface.height-plotOffset.bottom-plotOffset.top;$.each(axes,function(_,axis){setTransformationHelpers(axis)});if(showGrid){drawAxisLabels()}insertLegend()}function setRange(axis){var opts=axis.options,min=+(opts.min!=null?opts.min:axis.datamin),max=+(opts.max!=null?opts.max:axis.datamax),delta=max-min;if(delta==0){var widen=max==0?1:.01;if(opts.min==null)min-=widen;if(opts.max==null||opts.min!=null)max+=widen}else{var margin=opts.autoscaleMargin;if(margin!=null){if(opts.min==null){min-=delta*margin;if(min<0&&axis.datamin!=null&&axis.datamin>=0)min=0}if(opts.max==null){max+=delta*margin;if(max>0&&axis.datamax!=null&&axis.datamax<=0)max=0}}}axis.min=min;axis.max=max}function setupTickGeneration(axis){var opts=axis.options;var noTicks;if(typeof opts.ticks=="number"&&opts.ticks>0)noTicks=opts.ticks;else noTicks=.3*Math.sqrt(axis.direction=="x"?surface.width:surface.height);var delta=(axis.max-axis.min)/noTicks,dec=-Math.floor(Math.log(delta)/Math.LN10),maxDec=opts.tickDecimals;if(maxDec!=null&&dec>maxDec){dec=maxDec}var magn=Math.pow(10,-dec),norm=delta/magn,size;if(norm<1.5){size=1}else if(norm<3){size=2;if(norm>2.25&&(maxDec==null||dec+1<=maxDec)){size=2.5;++dec}}else if(norm<7.5){size=5}else{size=10}size*=magn;if(opts.minTickSize!=null&&size<opts.minTickSize){size=opts.minTickSize}axis.delta=delta;axis.tickDecimals=Math.max(0,maxDec!=null?maxDec:dec);axis.tickSize=opts.tickSize||size;if(opts.mode=="time"&&!axis.tickGenerator){throw new Error("Time mode requires the flot.time plugin.")}if(!axis.tickGenerator){axis.tickGenerator=function(axis){var ticks=[],start=floorInBase(axis.min,axis.tickSize),i=0,v=Number.NaN,prev;do{prev=v;v=start+i*axis.tickSize;ticks.push(v);++i}while(v<axis.max&&v!=prev);return ticks};axis.tickFormatter=function(value,axis){var factor=axis.tickDecimals?Math.pow(10,axis.tickDecimals):1;var formatted=""+Math.round(value*factor)/factor;if(axis.tickDecimals!=null){var decimal=formatted.indexOf(".");var precision=decimal==-1?0:formatted.length-decimal-1;if(precision<axis.tickDecimals){return(precision?formatted:formatted+".")+(""+factor).substr(1,axis.tickDecimals-precision)}}return formatted}}if($.isFunction(opts.tickFormatter))axis.tickFormatter=function(v,axis){return""+opts.tickFormatter(v,axis)};if(opts.alignTicksWithAxis!=null){var otherAxis=(axis.direction=="x"?xaxes:yaxes)[opts.alignTicksWithAxis-1];if(otherAxis&&otherAxis.used&&otherAxis!=axis){var niceTicks=axis.tickGenerator(axis);if(niceTicks.length>0){if(opts.min==null)axis.min=Math.min(axis.min,niceTicks[0]);if(opts.max==null&&niceTicks.length>1)axis.max=Math.max(axis.max,niceTicks[niceTicks.length-1])}axis.tickGenerator=function(axis){var ticks=[],v,i;for(i=0;i<otherAxis.ticks.length;++i){v=(otherAxis.ticks[i].v-otherAxis.min)/(otherAxis.max-otherAxis.min);v=axis.min+v*(axis.max-axis.min);ticks.push(v)}return ticks};if(!axis.mode&&opts.tickDecimals==null){var extraDec=Math.max(0,-Math.floor(Math.log(axis.delta)/Math.LN10)+1),ts=axis.tickGenerator(axis);if(!(ts.length>1&&/\..*0$/.test((ts[1]-ts[0]).toFixed(extraDec))))axis.tickDecimals=extraDec}}}}function setTicks(axis){var oticks=axis.options.ticks,ticks=[];if(oticks==null||typeof oticks=="number"&&oticks>0)ticks=axis.tickGenerator(axis);else if(oticks){if($.isFunction(oticks))ticks=oticks(axis);else ticks=oticks}var i,v;axis.ticks=[];for(i=0;i<ticks.length;++i){var label=null;var t=ticks[i];if(typeof t=="object"){v=+t[0];if(t.length>1)label=t[1]}else v=+t;if(label==null)label=axis.tickFormatter(v,axis);if(!isNaN(v))axis.ticks.push({v:v,label:label})}}function snapRangeToTicks(axis,ticks){if(axis.options.autoscaleMargin&&ticks.length>0){if(axis.options.min==null)axis.min=Math.min(axis.min,ticks[0].v);if(axis.options.max==null&&ticks.length>1)axis.max=Math.max(axis.max,ticks[ticks.length-1].v)}}function draw(){surface.clear();executeHooks(hooks.drawBackground,[ctx]);var grid=options.grid;if(grid.show&&grid.backgroundColor)drawBackground();if(grid.show&&!grid.aboveData){drawGrid()}for(var i=0;i<series.length;++i){executeHooks(hooks.drawSeries,[ctx,series[i]]);drawSeries(series[i])}executeHooks(hooks.draw,[ctx]);if(grid.show&&grid.aboveData){drawGrid()}surface.render();triggerRedrawOverlay()}function extractRange(ranges,coord){var axis,from,to,key,axes=allAxes();for(var i=0;i<axes.length;++i){axis=axes[i];if(axis.direction==coord){key=coord+axis.n+"axis";if(!ranges[key]&&axis.n==1)key=coord+"axis";if(ranges[key]){from=ranges[key].from;to=ranges[key].to;break}}}if(!ranges[key]){axis=coord=="x"?xaxes[0]:yaxes[0];from=ranges[coord+"1"];to=ranges[coord+"2"]}if(from!=null&&to!=null&&from>to){var tmp=from;from=to;to=tmp}return{from:from,to:to,axis:axis}}function drawBackground(){ctx.save();ctx.translate(plotOffset.left,plotOffset.top);ctx.fillStyle=getColorOrGradient(options.grid.backgroundColor,plotHeight,0,"rgba(255, 255, 255, 0)");ctx.fillRect(0,0,plotWidth,plotHeight);ctx.restore()}function drawGrid(){var i,axes,bw,bc;ctx.save();ctx.translate(plotOffset.left,plotOffset.top);var markings=options.grid.markings;if(markings){if($.isFunction(markings)){axes=plot.getAxes();axes.xmin=axes.xaxis.min;axes.xmax=axes.xaxis.max;axes.ymin=axes.yaxis.min;axes.ymax=axes.yaxis.max;markings=markings(axes)}for(i=0;i<markings.length;++i){var m=markings[i],xrange=extractRange(m,"x"),yrange=extractRange(m,"y");if(xrange.from==null)xrange.from=xrange.axis.min;if(xrange.to==null)xrange.to=xrange.axis.max; | |
| if(yrange.from==null)yrange.from=yrange.axis.min;if(yrange.to==null)yrange.to=yrange.axis.max;if(xrange.to<xrange.axis.min||xrange.from>xrange.axis.max||yrange.to<yrange.axis.min||yrange.from>yrange.axis.max)continue;xrange.from=Math.max(xrange.from,xrange.axis.min);xrange.to=Math.min(xrange.to,xrange.axis.max);yrange.from=Math.max(yrange.from,yrange.axis.min);yrange.to=Math.min(yrange.to,yrange.axis.max);var xequal=xrange.from===xrange.to,yequal=yrange.from===yrange.to;if(xequal&&yequal){continue}xrange.from=Math.floor(xrange.axis.p2c(xrange.from));xrange.to=Math.floor(xrange.axis.p2c(xrange.to));yrange.from=Math.floor(yrange.axis.p2c(yrange.from));yrange.to=Math.floor(yrange.axis.p2c(yrange.to));if(xequal||yequal){var lineWidth=m.lineWidth||options.grid.markingsLineWidth,subPixel=lineWidth%2?.5:0;ctx.beginPath();ctx.strokeStyle=m.color||options.grid.markingsColor;ctx.lineWidth=lineWidth;if(xequal){ctx.moveTo(xrange.to+subPixel,yrange.from);ctx.lineTo(xrange.to+subPixel,yrange.to)}else{ctx.moveTo(xrange.from,yrange.to+subPixel);ctx.lineTo(xrange.to,yrange.to+subPixel)}ctx.stroke()}else{ctx.fillStyle=m.color||options.grid.markingsColor;ctx.fillRect(xrange.from,yrange.to,xrange.to-xrange.from,yrange.from-yrange.to)}}}axes=allAxes();bw=options.grid.borderWidth;for(var j=0;j<axes.length;++j){var axis=axes[j],box=axis.box,t=axis.tickLength,x,y,xoff,yoff;if(!axis.show||axis.ticks.length==0)continue;ctx.lineWidth=1;if(axis.direction=="x"){x=0;if(t=="full")y=axis.position=="top"?0:plotHeight;else y=box.top-plotOffset.top+(axis.position=="top"?box.height:0)}else{y=0;if(t=="full")x=axis.position=="left"?0:plotWidth;else x=box.left-plotOffset.left+(axis.position=="left"?box.width:0)}if(!axis.innermost){ctx.strokeStyle=axis.options.color;ctx.beginPath();xoff=yoff=0;if(axis.direction=="x")xoff=plotWidth+1;else yoff=plotHeight+1;if(ctx.lineWidth==1){if(axis.direction=="x"){y=Math.floor(y)+.5}else{x=Math.floor(x)+.5}}ctx.moveTo(x,y);ctx.lineTo(x+xoff,y+yoff);ctx.stroke()}ctx.strokeStyle=axis.options.tickColor;ctx.beginPath();for(i=0;i<axis.ticks.length;++i){var v=axis.ticks[i].v;xoff=yoff=0;if(isNaN(v)||v<axis.min||v>axis.max||t=="full"&&(typeof bw=="object"&&bw[axis.position]>0||bw>0)&&(v==axis.min||v==axis.max))continue;if(axis.direction=="x"){x=axis.p2c(v);yoff=t=="full"?-plotHeight:t;if(axis.position=="top")yoff=-yoff}else{y=axis.p2c(v);xoff=t=="full"?-plotWidth:t;if(axis.position=="left")xoff=-xoff}if(ctx.lineWidth==1){if(axis.direction=="x")x=Math.floor(x)+.5;else y=Math.floor(y)+.5}ctx.moveTo(x,y);ctx.lineTo(x+xoff,y+yoff)}ctx.stroke()}if(bw){bc=options.grid.borderColor;if(typeof bw=="object"||typeof bc=="object"){if(typeof bw!=="object"){bw={top:bw,right:bw,bottom:bw,left:bw}}if(typeof bc!=="object"){bc={top:bc,right:bc,bottom:bc,left:bc}}if(bw.top>0){ctx.strokeStyle=bc.top;ctx.lineWidth=bw.top;ctx.beginPath();ctx.moveTo(0-bw.left,0-bw.top/2);ctx.lineTo(plotWidth,0-bw.top/2);ctx.stroke()}if(bw.right>0){ctx.strokeStyle=bc.right;ctx.lineWidth=bw.right;ctx.beginPath();ctx.moveTo(plotWidth+bw.right/2,0-bw.top);ctx.lineTo(plotWidth+bw.right/2,plotHeight);ctx.stroke()}if(bw.bottom>0){ctx.strokeStyle=bc.bottom;ctx.lineWidth=bw.bottom;ctx.beginPath();ctx.moveTo(plotWidth+bw.right,plotHeight+bw.bottom/2);ctx.lineTo(0,plotHeight+bw.bottom/2);ctx.stroke()}if(bw.left>0){ctx.strokeStyle=bc.left;ctx.lineWidth=bw.left;ctx.beginPath();ctx.moveTo(0-bw.left/2,plotHeight+bw.bottom);ctx.lineTo(0-bw.left/2,0);ctx.stroke()}}else{ctx.lineWidth=bw;ctx.strokeStyle=options.grid.borderColor;ctx.strokeRect(-bw/2,-bw/2,plotWidth+bw,plotHeight+bw)}}ctx.restore()}function drawAxisLabels(){$.each(allAxes(),function(_,axis){var box=axis.box,legacyStyles=axis.direction+"Axis "+axis.direction+axis.n+"Axis",layer="flot-"+axis.direction+"-axis flot-"+axis.direction+axis.n+"-axis "+legacyStyles,font=axis.options.font||"flot-tick-label tickLabel",tick,x,y,halign,valign;surface.removeText(layer);if(!axis.show||axis.ticks.length==0)return;for(var i=0;i<axis.ticks.length;++i){tick=axis.ticks[i];if(!tick.label||tick.v<axis.min||tick.v>axis.max)continue;if(axis.direction=="x"){halign="center";x=plotOffset.left+axis.p2c(tick.v);if(axis.position=="bottom"){y=box.top+box.padding}else{y=box.top+box.height-box.padding;valign="bottom"}}else{valign="middle";y=plotOffset.top+axis.p2c(tick.v);if(axis.position=="left"){x=box.left+box.width-box.padding;halign="right"}else{x=box.left+box.padding}}surface.addText(layer,x,y,tick.label,font,null,null,halign,valign)}})}function drawSeries(series){if(series.lines.show)drawSeriesLines(series);if(series.bars.show)drawSeriesBars(series);if(series.points.show)drawSeriesPoints(series)}function drawSeriesLines(series){function plotLine(datapoints,xoffset,yoffset,axisx,axisy){var points=datapoints.points,ps=datapoints.pointsize,prevx=null,prevy=null;ctx.beginPath();for(var i=ps;i<points.length;i+=ps){var x1=points[i-ps],y1=points[i-ps+1],x2=points[i],y2=points[i+1];if(x1==null||x2==null)continue;if(y1<=y2&&y1<axisy.min){if(y2<axisy.min)continue;x1=(axisy.min-y1)/(y2-y1)*(x2-x1)+x1;y1=axisy.min}else if(y2<=y1&&y2<axisy.min){if(y1<axisy.min)continue;x2=(axisy.min-y1)/(y2-y1)*(x2-x1)+x1;y2=axisy.min}if(y1>=y2&&y1>axisy.max){if(y2>axisy.max)continue;x1=(axisy.max-y1)/(y2-y1)*(x2-x1)+x1;y1=axisy.max}else if(y2>=y1&&y2>axisy.max){if(y1>axisy.max)continue;x2=(axisy.max-y1)/(y2-y1)*(x2-x1)+x1;y2=axisy.max}if(x1<=x2&&x1<axisx.min){if(x2<axisx.min)continue;y1=(axisx.min-x1)/(x2-x1)*(y2-y1)+y1;x1=axisx.min}else if(x2<=x1&&x2<axisx.min){if(x1<axisx.min)continue;y2=(axisx.min-x1)/(x2-x1)*(y2-y1)+y1;x2=axisx.min}if(x1>=x2&&x1>axisx.max){if(x2>axisx.max)continue;y1=(axisx.max-x1)/(x2-x1)*(y2-y1)+y1;x1=axisx.max}else if(x2>=x1&&x2>axisx.max){if(x1>axisx.max)continue;y2=(axisx.max-x1)/(x2-x1)*(y2-y1)+y1;x2=axisx.max}if(x1!=prevx||y1!=prevy)ctx.moveTo(axisx.p2c(x1)+xoffset,axisy.p2c(y1)+yoffset);prevx=x2;prevy=y2;ctx.lineTo(axisx.p2c(x2)+xoffset,axisy.p2c(y2)+yoffset)}ctx.stroke()}function plotLineArea(datapoints,axisx,axisy){var points=datapoints.points,ps=datapoints.pointsize,bottom=Math.min(Math.max(0,axisy.min),axisy.max),i=0,top,areaOpen=false,ypos=1,segmentStart=0,segmentEnd=0;while(true){if(ps>0&&i>points.length+ps)break;i+=ps;var x1=points[i-ps],y1=points[i-ps+ypos],x2=points[i],y2=points[i+ypos];if(areaOpen){if(ps>0&&x1!=null&&x2==null){segmentEnd=i;ps=-ps;ypos=2;continue}if(ps<0&&i==segmentStart+ps){ctx.fill();areaOpen=false;ps=-ps;ypos=1;i=segmentStart=segmentEnd+ps;continue}}if(x1==null||x2==null)continue;if(x1<=x2&&x1<axisx.min){if(x2<axisx.min)continue;y1=(axisx.min-x1)/(x2-x1)*(y2-y1)+y1;x1=axisx.min}else if(x2<=x1&&x2<axisx.min){if(x1<axisx.min)continue;y2=(axisx.min-x1)/(x2-x1)*(y2-y1)+y1;x2=axisx.min}if(x1>=x2&&x1>axisx.max){if(x2>axisx.max)continue;y1=(axisx.max-x1)/(x2-x1)*(y2-y1)+y1;x1=axisx.max}else if(x2>=x1&&x2>axisx.max){if(x1>axisx.max)continue;y2=(axisx.max-x1)/(x2-x1)*(y2-y1)+y1;x2=axisx.max}if(!areaOpen){ctx.beginPath();ctx.moveTo(axisx.p2c(x1),axisy.p2c(bottom));areaOpen=true}if(y1>=axisy.max&&y2>=axisy.max){ctx.lineTo(axisx.p2c(x1),axisy.p2c(axisy.max));ctx.lineTo(axisx.p2c(x2),axisy.p2c(axisy.max));continue}else if(y1<=axisy.min&&y2<=axisy.min){ctx.lineTo(axisx.p2c(x1),axisy.p2c(axisy.min));ctx.lineTo(axisx.p2c(x2),axisy.p2c(axisy.min));continue}var x1old=x1,x2old=x2;if(y1<=y2&&y1<axisy.min&&y2>=axisy.min){x1=(axisy.min-y1)/(y2-y1)*(x2-x1)+x1;y1=axisy.min}else if(y2<=y1&&y2<axisy.min&&y1>=axisy.min){x2=(axisy.min-y1)/(y2-y1)*(x2-x1)+x1;y2=axisy.min}if(y1>=y2&&y1>axisy.max&&y2<=axisy.max){x1=(axisy.max-y1)/(y2-y1)*(x2-x1)+x1;y1=axisy.max}else if(y2>=y1&&y2>axisy.max&&y1<=axisy.max){x2=(axisy.max-y1)/(y2-y1)*(x2-x1)+x1;y2=axisy.max}if(x1!=x1old){ctx.lineTo(axisx.p2c(x1old),axisy.p2c(y1))}ctx.lineTo(axisx.p2c(x1),axisy.p2c(y1));ctx.lineTo(axisx.p2c(x2),axisy.p2c(y2));if(x2!=x2old){ctx.lineTo(axisx.p2c(x2),axisy.p2c(y2));ctx.lineTo(axisx.p2c(x2old),axisy.p2c(y2))}}}ctx.save();ctx.translate(plotOffset.left,plotOffset.top);ctx.lineJoin="round";var lw=series.lines.lineWidth,sw=series.shadowSize;if(lw>0&&sw>0){ctx.lineWidth=sw;ctx.strokeStyle="rgba(0,0,0,0.1)";var angle=Math.PI/18;plotLine(series.datapoints,Math.sin(angle)*(lw/2+sw/2),Math.cos(angle)*(lw/2+sw/2),series.xaxis,series.yaxis);ctx.lineWidth=sw/2;plotLine(series.datapoints,Math.sin(angle)*(lw/2+sw/4),Math.cos(angle)*(lw/2+sw/4),series.xaxis,series.yaxis)}ctx.lineWidth=lw;ctx.strokeStyle=series.color;var fillStyle=getFillStyle(series.lines,series.color,0,plotHeight);if(fillStyle){ctx.fillStyle=fillStyle;plotLineArea(series.datapoints,series.xaxis,series.yaxis)}if(lw>0)plotLine(series.datapoints,0,0,series.xaxis,series.yaxis);ctx.restore()}function drawSeriesPoints(series){function plotPoints(datapoints,radius,fillStyle,offset,shadow,axisx,axisy,symbol){var points=datapoints.points,ps=datapoints.pointsize;for(var i=0;i<points.length;i+=ps){var x=points[i],y=points[i+1];if(x==null||x<axisx.min||x>axisx.max||y<axisy.min||y>axisy.max)continue;ctx.beginPath();x=axisx.p2c(x);y=axisy.p2c(y)+offset;if(symbol=="circle")ctx.arc(x,y,radius,0,shadow?Math.PI:Math.PI*2,false);else symbol(ctx,x,y,radius,shadow);ctx.closePath();if(fillStyle){ctx.fillStyle=fillStyle;ctx.fill()}ctx.stroke()}}ctx.save();ctx.translate(plotOffset.left,plotOffset.top);var lw=series.points.lineWidth,sw=series.shadowSize,radius=series.points.radius,symbol=series.points.symbol;if(lw==0)lw=1e-4;if(lw>0&&sw>0){var w=sw/2;ctx.lineWidth=w;ctx.strokeStyle="rgba(0,0,0,0.1)";plotPoints(series.datapoints,radius,null,w+w/2,true,series.xaxis,series.yaxis,symbol);ctx.strokeStyle="rgba(0,0,0,0.2)";plotPoints(series.datapoints,radius,null,w/2,true,series.xaxis,series.yaxis,symbol)}ctx.lineWidth=lw;ctx.strokeStyle=series.color;plotPoints(series.datapoints,radius,getFillStyle(series.points,series.color),0,false,series.xaxis,series.yaxis,symbol);ctx.restore()}function drawBar(x,y,b,barLeft,barRight,fillStyleCallback,axisx,axisy,c,horizontal,lineWidth){var left,right,bottom,top,drawLeft,drawRight,drawTop,drawBottom,tmp;if(horizontal){drawBottom=drawRight=drawTop=true;drawLeft=false;left=b;right=x;top=y+barLeft;bottom=y+barRight;if(right<left){tmp=right;right=left;left=tmp;drawLeft=true;drawRight=false}}else{drawLeft=drawRight=drawTop=true;drawBottom=false;left=x+barLeft;right=x+barRight;bottom=b;top=y;if(top<bottom){tmp=top;top=bottom;bottom=tmp;drawBottom=true;drawTop=false}}if(right<axisx.min||left>axisx.max||top<axisy.min||bottom>axisy.max)return;if(left<axisx.min){left=axisx.min;drawLeft=false}if(right>axisx.max){right=axisx.max;drawRight=false}if(bottom<axisy.min){bottom=axisy.min;drawBottom=false}if(top>axisy.max){top=axisy.max;drawTop=false}left=axisx.p2c(left);bottom=axisy.p2c(bottom);right=axisx.p2c(right);top=axisy.p2c(top);if(fillStyleCallback){c.fillStyle=fillStyleCallback(bottom,top);c.fillRect(left,top,right-left,bottom-top)}if(lineWidth>0&&(drawLeft||drawRight||drawTop||drawBottom)){c.beginPath();c.moveTo(left,bottom);if(drawLeft)c.lineTo(left,top);else c.moveTo(left,top);if(drawTop)c.lineTo(right,top);else c.moveTo(right,top);if(drawRight)c.lineTo(right,bottom);else c.moveTo(right,bottom);if(drawBottom)c.lineTo(left,bottom);else c.moveTo(left,bottom);c.stroke()}}function drawSeriesBars(series){function plotBars(datapoints,barLeft,barRight,fillStyleCallback,axisx,axisy){var points=datapoints.points,ps=datapoints.pointsize;for(var i=0;i<points.length;i+=ps){if(points[i]==null)continue;drawBar(points[i],points[i+1],points[i+2],barLeft,barRight,fillStyleCallback,axisx,axisy,ctx,series.bars.horizontal,series.bars.lineWidth)}}ctx.save();ctx.translate(plotOffset.left,plotOffset.top);ctx.lineWidth=series.bars.lineWidth;ctx.strokeStyle=series.color;var barLeft;switch(series.bars.align){case"left":barLeft=0;break;case"right":barLeft=-series.bars.barWidth;break;default:barLeft=-series.bars.barWidth/2}var fillStyleCallback=series.bars.fill?function(bottom,top){return 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| <h1>criterion performance measurements</h1> | |
| <h2>overview</h2> | |
| <p><a href="#grokularation">want to understand this report?</a></p> | |
| <div id="overview" class="ovchart" style="width:900px;height:100px;"></div> | |
| <h2><a name="b0">quotes-count/regex/0</a></h2> | |
| <table width="100%"> | |
| <tbody> | |
| <tr> | |
| <td><div id="kde0" class="kdechart" | |
| style="width:450px;height:278px;"></div></td> | |
| <td><div id="time0" class="timechart" | |
| style="width:450px;height:278px;"></div></td> | |
| <!-- | |
| <td><div id="cycle0" class="cyclechart" | |
| style="width:300px;height:278px;"></div></td> | |
| --> | |
| </tr> | |
| </tbody> | |
| </table> | |
| <table> | |
| <thead class="analysis"> | |
| <th></th> | |
| <th class="cibound" | |
| title="0.95 confidence level">lower bound</th> | |
| <th>estimate</th> | |
| <th class="cibound" | |
| title="0.95 confidence level">upper bound</th> | |
| </thead> | |
| <tbody> | |
| <tr> | |
| <td>OLS regression</td> | |
| <td><span class="confinterval olstimelb0">xxx</span></td> | |
| <td><span class="olstimept0">xxx</span></td> | |
| <td><span class="confinterval olstimeub0">xxx</span></td> | |
| </tr> | |
| <tr> | |
| <td>R² goodness-of-fit</td> | |
| <td><span class="confinterval olsr2lb0">xxx</span></td> | |
| <td><span class="olsr2pt0">xxx</span></td> | |
| <td><span class="confinterval olsr2ub0">xxx</span></td> | |
| </tr> | |
| <tr> | |
| <td>Mean execution time</td> | |
| <td><span class="confinterval citime">6.378769783136373e-3</span></td> | |
| <td><span class="time">6.508789525916955e-3</span></td> | |
| <td><span class="confinterval citime">6.796784326473453e-3</span></td> | |
| </tr> | |
| <tr> | |
| <td>Standard deviation</td> | |
| <td><span class="confinterval citime">2.970392895537065e-4</span></td> | |
| <td><span class="time">5.764048378659903e-4</span></td> | |
| <td><span class="confinterval citime">1.0050973548530987e-3</span></td> | |
| </tr> | |
| </tbody> | |
| </table> | |
| <span class="outliers"> | |
| <p>Outlying measurements have severe | |
| (<span class="percent">0.5248072317418451</span>%) | |
| effect on estimated standard deviation.</p> | |
| </span> | |
| <h2><a name="b1">quotes-count/regex/100</a></h2> | |
| <table width="100%"> | |
| <tbody> | |
| <tr> | |
| <td><div id="kde1" class="kdechart" | |
| style="width:450px;height:278px;"></div></td> | |
| <td><div id="time1" class="timechart" | |
| style="width:450px;height:278px;"></div></td> | |
| <!-- | |
| <td><div id="cycle1" class="cyclechart" | |
| style="width:300px;height:278px;"></div></td> | |
| --> | |
| </tr> | |
| </tbody> | |
| </table> | |
| <table> | |
| <thead class="analysis"> | |
| <th></th> | |
| <th class="cibound" | |
| title="0.95 confidence level">lower bound</th> | |
| <th>estimate</th> | |
| <th class="cibound" | |
| title="0.95 confidence level">upper bound</th> | |
| </thead> | |
| <tbody> | |
| <tr> | |
| <td>OLS regression</td> | |
| <td><span class="confinterval olstimelb1">xxx</span></td> | |
| <td><span class="olstimept1">xxx</span></td> | |
| <td><span class="confinterval olstimeub1">xxx</span></td> | |
| </tr> | |
| <tr> | |
| <td>R² goodness-of-fit</td> | |
| <td><span class="confinterval olsr2lb1">xxx</span></td> | |
| <td><span class="olsr2pt1">xxx</span></td> | |
| <td><span class="confinterval olsr2ub1">xxx</span></td> | |
| </tr> | |
| <tr> | |
| <td>Mean execution time</td> | |
| <td><span class="confinterval citime">6.808547904953387e-3</span></td> | |
| <td><span class="time">7.079196590085842e-3</span></td> | |
| <td><span class="confinterval citime">7.633653917094895e-3</span></td> | |
| </tr> | |
| <tr> | |
| <td>Standard deviation</td> | |
| <td><span class="confinterval citime">5.508729148928845e-4</span></td> | |
| <td><span class="time">1.061759874400244e-3</span></td> | |
| <td><span class="confinterval citime">1.7213561446548832e-3</span></td> | |
| </tr> | |
| </tbody> | |
| </table> | |
| <span class="outliers"> | |
| <p>Outlying measurements have severe | |
| (<span class="percent">0.7596183307033366</span>%) | |
| effect on estimated standard deviation.</p> | |
| </span> | |
| <h2><a name="b2">quotes-count/regex/200</a></h2> | |
| <table width="100%"> | |
| <tbody> | |
| <tr> | |
| <td><div id="kde2" class="kdechart" | |
| style="width:450px;height:278px;"></div></td> | |
| <td><div id="time2" class="timechart" | |
| style="width:450px;height:278px;"></div></td> | |
| <!-- | |
| <td><div id="cycle2" class="cyclechart" | |
| style="width:300px;height:278px;"></div></td> | |
| --> | |
| </tr> | |
| </tbody> | |
| </table> | |
| <table> | |
| <thead class="analysis"> | |
| <th></th> | |
| <th class="cibound" | |
| title="0.95 confidence level">lower bound</th> | |
| <th>estimate</th> | |
| <th class="cibound" | |
| title="0.95 confidence level">upper bound</th> | |
| </thead> | |
| <tbody> | |
| <tr> | |
| <td>OLS regression</td> | |
| <td><span class="confinterval olstimelb2">xxx</span></td> | |
| <td><span class="olstimept2">xxx</span></td> | |
| <td><span class="confinterval olstimeub2">xxx</span></td> | |
| </tr> | |
| <tr> | |
| <td>R² goodness-of-fit</td> | |
| <td><span class="confinterval olsr2lb2">xxx</span></td> | |
| <td><span class="olsr2pt2">xxx</span></td> | |
| <td><span class="confinterval olsr2ub2">xxx</span></td> | |
| </tr> | |
| <tr> | |
| <td>Mean execution time</td> | |
| <td><span class="confinterval citime">7.0820544262298665e-3</span></td> | |
| <td><span class="time">7.334779764842226e-3</span></td> | |
| <td><span class="confinterval citime">8.065844158742527e-3</span></td> | |
| </tr> | |
| <tr> | |
| <td>Standard deviation</td> | |
| <td><span class="confinterval citime">4.975275102423931e-4</span></td> | |
| <td><span class="time">1.14631232194043e-3</span></td> | |
| <td><span class="confinterval citime">2.3122218150700654e-3</span></td> | |
| </tr> | |
| </tbody> | |
| </table> | |
| <span class="outliers"> | |
| <p>Outlying measurements have severe | |
| (<span class="percent">0.7605515081235925</span>%) | |
| effect on estimated standard deviation.</p> | |
| </span> | |
| <h2><a name="b3">quotes-count/regex/300</a></h2> | |
| <table width="100%"> | |
| <tbody> | |
| <tr> | |
| <td><div id="kde3" class="kdechart" | |
| style="width:450px;height:278px;"></div></td> | |
| <td><div id="time3" class="timechart" | |
| style="width:450px;height:278px;"></div></td> | |
| <!-- | |
| <td><div id="cycle3" class="cyclechart" | |
| style="width:300px;height:278px;"></div></td> | |
| --> | |
| </tr> | |
| </tbody> | |
| </table> | |
| <table> | |
| <thead class="analysis"> | |
| <th></th> | |
| <th class="cibound" | |
| title="0.95 confidence level">lower bound</th> | |
| <th>estimate</th> | |
| <th class="cibound" | |
| title="0.95 confidence level">upper bound</th> | |
| </thead> | |
| <tbody> | |
| <tr> | |
| <td>OLS regression</td> | |
| <td><span class="confinterval olstimelb3">xxx</span></td> | |
| <td><span class="olstimept3">xxx</span></td> | |
| <td><span class="confinterval olstimeub3">xxx</span></td> | |
| </tr> | |
| <tr> | |
| <td>R² goodness-of-fit</td> | |
| <td><span class="confinterval olsr2lb3">xxx</span></td> | |
| <td><span class="olsr2pt3">xxx</span></td> | |
| <td><span class="confinterval olsr2ub3">xxx</span></td> | |
| </tr> | |
| <tr> | |
| <td>Mean execution time</td> | |
| <td><span class="confinterval citime">6.961539201830106e-3</span></td> | |
| <td><span class="time">7.0571176592769385e-3</span></td> | |
| <td><span class="confinterval citime">7.1852805324026225e-3</span></td> | |
| </tr> | |
| <tr> | |
| <td>Standard deviation</td> | |
| <td><span class="confinterval citime">2.494718039433142e-4</span></td> | |
| <td><span class="time">3.2417370573936433e-4</span></td> | |
| <td><span class="confinterval citime">4.306812772515932e-4</span></td> | |
| </tr> | |
| </tbody> | |
| </table> | |
| <span class="outliers"> | |
| <p>Outlying measurements have moderate | |
| (<span class="percent">0.21751805082411735</span>%) | |
| effect on estimated standard deviation.</p> | |
| </span> | |
| <h2><a name="b4">quotes-count/regex/400</a></h2> | |
| <table width="100%"> | |
| <tbody> | |
| <tr> | |
| <td><div id="kde4" class="kdechart" | |
| style="width:450px;height:278px;"></div></td> | |
| <td><div id="time4" class="timechart" | |
| style="width:450px;height:278px;"></div></td> | |
| <!-- | |
| <td><div id="cycle4" class="cyclechart" | |
| style="width:300px;height:278px;"></div></td> | |
| --> | |
| </tr> | |
| </tbody> | |
| </table> | |
| <table> | |
| <thead class="analysis"> | |
| <th></th> | |
| <th class="cibound" | |
| title="0.95 confidence level">lower bound</th> | |
| <th>estimate</th> | |
| <th class="cibound" | |
| title="0.95 confidence level">upper bound</th> | |
| </thead> | |
| <tbody> | |
| <tr> | |
| <td>OLS regression</td> | |
| <td><span class="confinterval olstimelb4">xxx</span></td> | |
| <td><span class="olstimept4">xxx</span></td> | |
| <td><span class="confinterval olstimeub4">xxx</span></td> | |
| </tr> | |
| <tr> | |
| <td>R² goodness-of-fit</td> | |
| <td><span class="confinterval olsr2lb4">xxx</span></td> | |
| <td><span class="olsr2pt4">xxx</span></td> | |
| <td><span class="confinterval olsr2ub4">xxx</span></td> | |
| </tr> | |
| <tr> | |
| <td>Mean execution time</td> | |
| <td><span class="confinterval citime">7.013553515966101e-3</span></td> | |
| <td><span class="time">7.131743543934675e-3</span></td> | |
| <td><span class="confinterval citime">7.281873662320588e-3</span></td> | |
| </tr> | |
| <tr> | |
| <td>Standard deviation</td> | |
| <td><span class="confinterval citime">2.787917005386712e-4</span></td> | |
| <td><span class="time">3.7989759019432936e-4</span></td> | |
| <td><span class="confinterval citime">5.215710790156165e-4</span></td> | |
| </tr> | |
| </tbody> | |
| </table> | |
| <span class="outliers"> | |
| <p>Outlying measurements have moderate | |
| (<span class="percent">0.2728710559875426</span>%) | |
| effect on estimated standard deviation.</p> | |
| </span> | |
| <h2><a name="b5">quotes-count/regex/500</a></h2> | |
| <table width="100%"> | |
| <tbody> | |
| <tr> | |
| <td><div id="kde5" class="kdechart" | |
| style="width:450px;height:278px;"></div></td> | |
| <td><div id="time5" class="timechart" | |
| style="width:450px;height:278px;"></div></td> | |
| <!-- | |
| <td><div id="cycle5" class="cyclechart" | |
| style="width:300px;height:278px;"></div></td> | |
| --> | |
| </tr> | |
| </tbody> | |
| </table> | |
| <table> | |
| <thead class="analysis"> | |
| <th></th> | |
| <th class="cibound" | |
| title="0.95 confidence level">lower bound</th> | |
| <th>estimate</th> | |
| <th class="cibound" | |
| title="0.95 confidence level">upper bound</th> | |
| </thead> | |
| <tbody> | |
| <tr> | |
| <td>OLS regression</td> | |
| <td><span class="confinterval olstimelb5">xxx</span></td> | |
| <td><span class="olstimept5">xxx</span></td> | |
| <td><span class="confinterval olstimeub5">xxx</span></td> | |
| </tr> | |
| <tr> | |
| <td>R² goodness-of-fit</td> | |
| <td><span class="confinterval olsr2lb5">xxx</span></td> | |
| <td><span class="olsr2pt5">xxx</span></td> | |
| <td><span class="confinterval olsr2ub5">xxx</span></td> | |
| </tr> | |
| <tr> | |
| <td>Mean execution time</td> | |
| <td><span class="confinterval citime">7.491625722336375e-3</span></td> | |
| <td><span class="time">7.694039257768677e-3</span></td> | |
| <td><span class="confinterval citime">8.214790003992108e-3</span></td> | |
| </tr> | |
| <tr> | |
| <td>Standard deviation</td> | |
| <td><span class="confinterval citime">4.352807789452845e-4</span></td> | |
| <td><span class="time">8.657388085231769e-4</span></td> | |
| <td><span class="confinterval citime">1.5624130216690905e-3</span></td> | |
| </tr> | |
| </tbody> | |
| </table> | |
| <span class="outliers"> | |
| <p>Outlying measurements have severe | |
| (<span class="percent">0.631861620688459</span>%) | |
| effect on estimated standard deviation.</p> | |
| </span> | |
| <h2><a name="b6">quotes-count/regex/600</a></h2> | |
| <table width="100%"> | |
| <tbody> | |
| <tr> | |
| <td><div id="kde6" class="kdechart" | |
| style="width:450px;height:278px;"></div></td> | |
| <td><div id="time6" class="timechart" | |
| style="width:450px;height:278px;"></div></td> | |
| <!-- | |
| <td><div id="cycle6" class="cyclechart" | |
| style="width:300px;height:278px;"></div></td> | |
| --> | |
| </tr> | |
| </tbody> | |
| </table> | |
| <table> | |
| <thead class="analysis"> | |
| <th></th> | |
| <th class="cibound" | |
| title="0.95 confidence level">lower bound</th> | |
| <th>estimate</th> | |
| <th class="cibound" | |
| title="0.95 confidence level">upper bound</th> | |
| </thead> | |
| <tbody> | |
| <tr> | |
| <td>OLS regression</td> | |
| <td><span class="confinterval olstimelb6">xxx</span></td> | |
| <td><span class="olstimept6">xxx</span></td> | |
| <td><span class="confinterval olstimeub6">xxx</span></td> | |
| </tr> | |
| <tr> | |
| <td>R² goodness-of-fit</td> | |
| <td><span class="confinterval olsr2lb6">xxx</span></td> | |
| <td><span class="olsr2pt6">xxx</span></td> | |
| <td><span class="confinterval olsr2ub6">xxx</span></td> | |
| </tr> | |
| <tr> | |
| <td>Mean execution time</td> | |
| <td><span class="confinterval citime">7.5372930758575395e-3</span></td> | |
| <td><span class="time">7.686660550289231e-3</span></td> | |
| <td><span class="confinterval citime">8.172047123704734e-3</span></td> | |
| </tr> | |
| <tr> | |
| <td>Standard deviation</td> | |
| <td><span class="confinterval citime">2.336681721198147e-4</span></td> | |
| <td><span class="time">6.959785734132105e-4</span></td> | |
| <td><span class="confinterval citime">1.3677832045458378e-3</span></td> | |
| </tr> | |
| </tbody> | |
| </table> | |
| <span class="outliers"> | |
| <p>Outlying measurements have severe | |
| (<span class="percent">0.5137004708537729</span>%) | |
| effect on estimated standard deviation.</p> | |
| </span> | |
| <h2><a name="b7">quotes-count/regex/700</a></h2> | |
| <table width="100%"> | |
| <tbody> | |
| <tr> | |
| <td><div id="kde7" class="kdechart" | |
| style="width:450px;height:278px;"></div></td> | |
| <td><div id="time7" class="timechart" | |
| style="width:450px;height:278px;"></div></td> | |
| <!-- | |
| <td><div id="cycle7" class="cyclechart" | |
| style="width:300px;height:278px;"></div></td> | |
| --> | |
| </tr> | |
| </tbody> | |
| </table> | |
| <table> | |
| <thead class="analysis"> | |
| <th></th> | |
| <th class="cibound" | |
| title="0.95 confidence level">lower bound</th> | |
| <th>estimate</th> | |
| <th class="cibound" | |
| title="0.95 confidence level">upper bound</th> | |
| </thead> | |
| <tbody> | |
| <tr> | |
| <td>OLS regression</td> | |
| <td><span class="confinterval olstimelb7">xxx</span></td> | |
| <td><span class="olstimept7">xxx</span></td> | |
| <td><span class="confinterval olstimeub7">xxx</span></td> | |
| </tr> | |
| <tr> | |
| <td>R² goodness-of-fit</td> | |
| <td><span class="confinterval olsr2lb7">xxx</span></td> | |
| <td><span class="olsr2pt7">xxx</span></td> | |
| <td><span class="confinterval olsr2ub7">xxx</span></td> | |
| </tr> | |
| <tr> | |
| <td>Mean execution time</td> | |
| <td><span class="confinterval citime">7.90249340500977e-3</span></td> | |
| <td><span class="time">8.2475439004429e-3</span></td> | |
| <td><span class="confinterval citime">9.067048245496903e-3</span></td> | |
| </tr> | |
| <tr> | |
| <td>Standard deviation</td> | |
| <td><span class="confinterval citime">3.079229620197865e-4</span></td> | |
| <td><span class="time">1.3910571011937567e-3</span></td> | |
| <td><span class="confinterval citime">2.4196130364929785e-3</span></td> | |
| </tr> | |
| </tbody> | |
| </table> | |
| <span class="outliers"> | |
| <p>Outlying measurements have severe | |
| (<span class="percent">0.7775467911759378</span>%) | |
| effect on estimated standard deviation.</p> | |
| </span> | |
| <h2><a name="b8">quotes-count/regex/800</a></h2> | |
| <table width="100%"> | |
| <tbody> | |
| <tr> | |
| <td><div id="kde8" class="kdechart" | |
| style="width:450px;height:278px;"></div></td> | |
| <td><div id="time8" class="timechart" | |
| style="width:450px;height:278px;"></div></td> | |
| <!-- | |
| <td><div id="cycle8" class="cyclechart" | |
| style="width:300px;height:278px;"></div></td> | |
| --> | |
| </tr> | |
| </tbody> | |
| </table> | |
| <table> | |
| <thead class="analysis"> | |
| <th></th> | |
| <th class="cibound" | |
| title="0.95 confidence level">lower bound</th> | |
| <th>estimate</th> | |
| <th class="cibound" | |
| title="0.95 confidence level">upper bound</th> | |
| </thead> | |
| <tbody> | |
| <tr> | |
| <td>OLS regression</td> | |
| <td><span class="confinterval olstimelb8">xxx</span></td> | |
| <td><span class="olstimept8">xxx</span></td> | |
| <td><span class="confinterval olstimeub8">xxx</span></td> | |
| </tr> | |
| <tr> | |
| <td>R² goodness-of-fit</td> | |
| <td><span class="confinterval olsr2lb8">xxx</span></td> | |
| <td><span class="olsr2pt8">xxx</span></td> | |
| <td><span class="confinterval olsr2ub8">xxx</span></td> | |
| </tr> | |
| <tr> | |
| <td>Mean execution time</td> | |
| <td><span class="confinterval citime">8.38970168821735e-3</span></td> | |
| <td><span class="time">9.021159821052883e-3</span></td> | |
| <td><span class="confinterval citime">1.028208728659287e-2</span></td> | |
| </tr> | |
| <tr> | |
| <td>Standard deviation</td> | |
| <td><span class="confinterval citime">1.3020656191009123e-3</span></td> | |
| <td><span class="time">2.2689003475098615e-3</span></td> | |
| <td><span class="confinterval citime">3.2953586499006506e-3</span></td> | |
| </tr> | |
| </tbody> | |
| </table> | |
| <span class="outliers"> | |
| <p>Outlying measurements have severe | |
| (<span class="percent">0.8999104271401048</span>%) | |
| effect on estimated standard deviation.</p> | |
| </span> | |
| <h2><a name="b9">quotes-count/regex/900</a></h2> | |
| <table width="100%"> | |
| <tbody> | |
| <tr> | |
| <td><div id="kde9" class="kdechart" | |
| style="width:450px;height:278px;"></div></td> | |
| <td><div id="time9" class="timechart" | |
| style="width:450px;height:278px;"></div></td> | |
| <!-- | |
| <td><div id="cycle9" class="cyclechart" | |
| style="width:300px;height:278px;"></div></td> | |
| --> | |
| </tr> | |
| </tbody> | |
| </table> | |
| <table> | |
| <thead class="analysis"> | |
| <th></th> | |
| <th class="cibound" | |
| title="0.95 confidence level">lower bound</th> | |
| <th>estimate</th> | |
| <th class="cibound" | |
| title="0.95 confidence level">upper bound</th> | |
| </thead> | |
| <tbody> | |
| <tr> | |
| <td>OLS regression</td> | |
| <td><span class="confinterval olstimelb9">xxx</span></td> | |
| <td><span class="olstimept9">xxx</span></td> | |
| <td><span class="confinterval olstimeub9">xxx</span></td> | |
| </tr> | |
| <tr> | |
| <td>R² goodness-of-fit</td> | |
| <td><span class="confinterval olsr2lb9">xxx</span></td> | |
| <td><span class="olsr2pt9">xxx</span></td> | |
| <td><span class="confinterval olsr2ub9">xxx</span></td> | |
| </tr> | |
| <tr> | |
| <td>Mean execution time</td> | |
| <td><span class="confinterval citime">8.562386745245981e-3</span></td> | |
| <td><span class="time">9.087716805777902e-3</span></td> | |
| <td><span class="confinterval citime">9.893469506950756e-3</span></td> | |
| </tr> | |
| <tr> | |
| <td>Standard deviation</td> | |
| <td><span class="confinterval citime">1.2087620477751924e-3</span></td> | |
| <td><span class="time">1.793643804614194e-3</span></td> | |
| <td><span class="confinterval citime">2.3713887969557526e-3</span></td> | |
| </tr> | |
| </tbody> | |
| </table> | |
| <span class="outliers"> | |
| <p>Outlying measurements have severe | |
| (<span class="percent">0.8296080551682851</span>%) | |
| effect on estimated standard deviation.</p> | |
| </span> | |
| <h2><a name="b10">quotes-count/regex/1000</a></h2> | |
| <table width="100%"> | |
| <tbody> | |
| <tr> | |
| <td><div id="kde10" class="kdechart" | |
| style="width:450px;height:278px;"></div></td> | |
| <td><div id="time10" class="timechart" | |
| style="width:450px;height:278px;"></div></td> | |
| <!-- | |
| <td><div id="cycle10" class="cyclechart" | |
| style="width:300px;height:278px;"></div></td> | |
| --> | |
| </tr> | |
| </tbody> | |
| </table> | |
| <table> | |
| <thead class="analysis"> | |
| <th></th> | |
| <th class="cibound" | |
| title="0.95 confidence level">lower bound</th> | |
| <th>estimate</th> | |
| <th class="cibound" | |
| title="0.95 confidence level">upper bound</th> | |
| </thead> | |
| <tbody> | |
| <tr> | |
| <td>OLS regression</td> | |
| <td><span class="confinterval olstimelb10">xxx</span></td> | |
| <td><span class="olstimept10">xxx</span></td> | |
| <td><span class="confinterval olstimeub10">xxx</span></td> | |
| </tr> | |
| <tr> | |
| <td>R² goodness-of-fit</td> | |
| <td><span class="confinterval olsr2lb10">xxx</span></td> | |
| <td><span class="olsr2pt10">xxx</span></td> | |
| <td><span class="confinterval olsr2ub10">xxx</span></td> | |
| </tr> | |
| <tr> | |
| <td>Mean execution time</td> | |
| <td><span class="confinterval citime">8.497220001578387e-3</span></td> | |
| <td><span class="time">8.894703957165361e-3</span></td> | |
| <td><span class="confinterval citime">9.562667723598237e-3</span></td> | |
| </tr> | |
| <tr> | |
| <td>Standard deviation</td> | |
| <td><span class="confinterval citime">9.292518638268567e-4</span></td> | |
| <td><span class="time">1.4308553481106798e-3</span></td> | |
| <td><span class="confinterval citime">1.906384195264841e-3</span></td> | |
| </tr> | |
| </tbody> | |
| </table> | |
| <span class="outliers"> | |
| <p>Outlying measurements have severe | |
| (<span class="percent">0.7697334700273534</span>%) | |
| effect on estimated standard deviation.</p> | |
| </span> | |
| <h2><a name="b11">quotes-count/split/0</a></h2> | |
| <table width="100%"> | |
| <tbody> | |
| <tr> | |
| <td><div id="kde11" class="kdechart" | |
| style="width:450px;height:278px;"></div></td> | |
| <td><div id="time11" class="timechart" | |
| style="width:450px;height:278px;"></div></td> | |
| <!-- | |
| <td><div id="cycle11" class="cyclechart" | |
| style="width:300px;height:278px;"></div></td> | |
| --> | |
| </tr> | |
| </tbody> | |
| </table> | |
| <table> | |
| <thead class="analysis"> | |
| <th></th> | |
| <th class="cibound" | |
| title="0.95 confidence level">lower bound</th> | |
| <th>estimate</th> | |
| <th class="cibound" | |
| title="0.95 confidence level">upper bound</th> | |
| </thead> | |
| <tbody> | |
| <tr> | |
| <td>OLS regression</td> | |
| <td><span class="confinterval olstimelb11">xxx</span></td> | |
| <td><span class="olstimept11">xxx</span></td> | |
| <td><span class="confinterval olstimeub11">xxx</span></td> | |
| </tr> | |
| <tr> | |
| <td>R² goodness-of-fit</td> | |
| <td><span class="confinterval olsr2lb11">xxx</span></td> | |
| <td><span class="olsr2pt11">xxx</span></td> | |
| <td><span class="confinterval olsr2ub11">xxx</span></td> | |
| </tr> | |
| <tr> | |
| <td>Mean execution time</td> | |
| <td><span class="confinterval citime">2.728349420578041e-3</span></td> | |
| <td><span class="time">2.873765393991234e-3</span></td> | |
| <td><span class="confinterval citime">3.099725759227768e-3</span></td> | |
| </tr> | |
| <tr> | |
| <td>Standard deviation</td> | |
| <td><span class="confinterval citime">4.1872520293329143e-4</span></td> | |
| <td><span class="time">5.867428910639399e-4</span></td> | |
| <td><span class="confinterval citime">8.105661321059851e-4</span></td> | |
| </tr> | |
| </tbody> | |
| </table> | |
| <span class="outliers"> | |
| <p>Outlying measurements have severe | |
| (<span class="percent">0.8939278570228467</span>%) | |
| effect on estimated standard deviation.</p> | |
| </span> | |
| <h2><a name="b12">quotes-count/split/100</a></h2> | |
| <table width="100%"> | |
| <tbody> | |
| <tr> | |
| <td><div id="kde12" class="kdechart" | |
| style="width:450px;height:278px;"></div></td> | |
| <td><div id="time12" class="timechart" | |
| style="width:450px;height:278px;"></div></td> | |
| <!-- | |
| <td><div id="cycle12" class="cyclechart" | |
| style="width:300px;height:278px;"></div></td> | |
| --> | |
| </tr> | |
| </tbody> | |
| </table> | |
| <table> | |
| <thead class="analysis"> | |
| <th></th> | |
| <th class="cibound" | |
| title="0.95 confidence level">lower bound</th> | |
| <th>estimate</th> | |
| <th class="cibound" | |
| title="0.95 confidence level">upper bound</th> | |
| </thead> | |
| <tbody> | |
| <tr> | |
| <td>OLS regression</td> | |
| <td><span class="confinterval olstimelb12">xxx</span></td> | |
| <td><span class="olstimept12">xxx</span></td> | |
| <td><span class="confinterval olstimeub12">xxx</span></td> | |
| </tr> | |
| <tr> | |
| <td>R² goodness-of-fit</td> | |
| <td><span class="confinterval olsr2lb12">xxx</span></td> | |
| <td><span class="olsr2pt12">xxx</span></td> | |
| <td><span class="confinterval olsr2ub12">xxx</span></td> | |
| </tr> | |
| <tr> | |
| <td>Mean execution time</td> | |
| <td><span class="confinterval citime">3.097680920133191e-3</span></td> | |
| <td><span class="time">3.2919083002466492e-3</span></td> | |
| <td><span class="confinterval citime">3.5819589057029494e-3</span></td> | |
| </tr> | |
| <tr> | |
| <td>Standard deviation</td> | |
| <td><span class="confinterval citime">5.945765251594602e-4</span></td> | |
| <td><span class="time">7.75608090268007e-4</span></td> | |
| <td><span class="confinterval citime">9.751981625905112e-4</span></td> | |
| </tr> | |
| </tbody> | |
| </table> | |
| <span class="outliers"> | |
| <p>Outlying measurements have severe | |
| (<span class="percent">0.9135226388942608</span>%) | |
| effect on estimated standard deviation.</p> | |
| </span> | |
| <h2><a name="b13">quotes-count/split/200</a></h2> | |
| <table width="100%"> | |
| <tbody> | |
| <tr> | |
| <td><div id="kde13" class="kdechart" | |
| style="width:450px;height:278px;"></div></td> | |
| <td><div id="time13" class="timechart" | |
| style="width:450px;height:278px;"></div></td> | |
| <!-- | |
| <td><div id="cycle13" class="cyclechart" | |
| style="width:300px;height:278px;"></div></td> | |
| --> | |
| </tr> | |
| </tbody> | |
| </table> | |
| <table> | |
| <thead class="analysis"> | |
| <th></th> | |
| <th class="cibound" | |
| title="0.95 confidence level">lower bound</th> | |
| <th>estimate</th> | |
| <th class="cibound" | |
| title="0.95 confidence level">upper bound</th> | |
| </thead> | |
| <tbody> | |
| <tr> | |
| <td>OLS regression</td> | |
| <td><span class="confinterval olstimelb13">xxx</span></td> | |
| <td><span class="olstimept13">xxx</span></td> | |
| <td><span class="confinterval olstimeub13">xxx</span></td> | |
| </tr> | |
| <tr> | |
| <td>R² goodness-of-fit</td> | |
| <td><span class="confinterval olsr2lb13">xxx</span></td> | |
| <td><span class="olsr2pt13">xxx</span></td> | |
| <td><span class="confinterval olsr2ub13">xxx</span></td> | |
| </tr> | |
| <tr> | |
| <td>Mean execution time</td> | |
| <td><span class="confinterval citime">3.275679797422639e-3</span></td> | |
| <td><span class="time">3.5891373460715985e-3</span></td> | |
| <td><span class="confinterval citime">4.1848081337569785e-3</span></td> | |
| </tr> | |
| <tr> | |
| <td>Standard deviation</td> | |
| <td><span class="confinterval citime">8.674348635171308e-4</span></td> | |
| <td><span class="time">1.1378272199268208e-3</span></td> | |
| <td><span class="confinterval citime">1.5062082437732843e-3</span></td> | |
| </tr> | |
| </tbody> | |
| </table> | |
| <span class="outliers"> | |
| <p>Outlying measurements have severe | |
| (<span class="percent">0.9524009365646766</span>%) | |
| effect on estimated standard deviation.</p> | |
| </span> | |
| <h2><a name="b14">quotes-count/split/300</a></h2> | |
| <table width="100%"> | |
| <tbody> | |
| <tr> | |
| <td><div id="kde14" class="kdechart" | |
| style="width:450px;height:278px;"></div></td> | |
| <td><div id="time14" class="timechart" | |
| style="width:450px;height:278px;"></div></td> | |
| <!-- | |
| <td><div id="cycle14" class="cyclechart" | |
| style="width:300px;height:278px;"></div></td> | |
| --> | |
| </tr> | |
| </tbody> | |
| </table> | |
| <table> | |
| <thead class="analysis"> | |
| <th></th> | |
| <th class="cibound" | |
| title="0.95 confidence level">lower bound</th> | |
| <th>estimate</th> | |
| <th class="cibound" | |
| title="0.95 confidence level">upper bound</th> | |
| </thead> | |
| <tbody> | |
| <tr> | |
| <td>OLS regression</td> | |
| <td><span class="confinterval olstimelb14">xxx</span></td> | |
| <td><span class="olstimept14">xxx</span></td> | |
| <td><span class="confinterval olstimeub14">xxx</span></td> | |
| </tr> | |
| <tr> | |
| <td>R² goodness-of-fit</td> | |
| <td><span class="confinterval olsr2lb14">xxx</span></td> | |
| <td><span class="olsr2pt14">xxx</span></td> | |
| <td><span class="confinterval olsr2ub14">xxx</span></td> | |
| </tr> | |
| <tr> | |
| <td>Mean execution time</td> | |
| <td><span class="confinterval citime">5.509983301969804e-3</span></td> | |
| <td><span class="time">6.345851616791659e-3</span></td> | |
| <td><span class="confinterval citime">7.649994199623435e-3</span></td> | |
| </tr> | |
| <tr> | |
| <td>Standard deviation</td> | |
| <td><span class="confinterval citime">2.0636906725263553e-3</span></td> | |
| <td><span class="time">3.0589378779165856e-3</span></td> | |
| <td><span class="confinterval citime">4.175685790991899e-3</span></td> | |
| </tr> | |
| </tbody> | |
| </table> | |
| <span class="outliers"> | |
| <p>Outlying measurements have severe | |
| (<span class="percent">0.9720065225362509</span>%) | |
| effect on estimated standard deviation.</p> | |
| </span> | |
| <h2><a name="b15">quotes-count/split/400</a></h2> | |
| <table width="100%"> | |
| <tbody> | |
| <tr> | |
| <td><div id="kde15" class="kdechart" | |
| style="width:450px;height:278px;"></div></td> | |
| <td><div id="time15" class="timechart" | |
| style="width:450px;height:278px;"></div></td> | |
| <!-- | |
| <td><div id="cycle15" class="cyclechart" | |
| style="width:300px;height:278px;"></div></td> | |
| --> | |
| </tr> | |
| </tbody> | |
| </table> | |
| <table> | |
| <thead class="analysis"> | |
| <th></th> | |
| <th class="cibound" | |
| title="0.95 confidence level">lower bound</th> | |
| <th>estimate</th> | |
| <th class="cibound" | |
| title="0.95 confidence level">upper bound</th> | |
| </thead> | |
| <tbody> | |
| <tr> | |
| <td>OLS regression</td> | |
| <td><span class="confinterval olstimelb15">xxx</span></td> | |
| <td><span class="olstimept15">xxx</span></td> | |
| <td><span class="confinterval olstimeub15">xxx</span></td> | |
| </tr> | |
| <tr> | |
| <td>R² goodness-of-fit</td> | |
| <td><span class="confinterval olsr2lb15">xxx</span></td> | |
| <td><span class="olsr2pt15">xxx</span></td> | |
| <td><span class="confinterval olsr2ub15">xxx</span></td> | |
| </tr> | |
| <tr> | |
| <td>Mean execution time</td> | |
| <td><span class="confinterval citime">3.481609271855278e-3</span></td> | |
| <td><span class="time">3.6583161853550915e-3</span></td> | |
| <td><span class="confinterval citime">3.947122484286917e-3</span></td> | |
| </tr> | |
| <tr> | |
| <td>Standard deviation</td> | |
| <td><span class="confinterval citime">4.607786515776497e-4</span></td> | |
| <td><span class="time">7.237671017133755e-4</span></td> | |
| <td><span class="confinterval citime">1.0727040797996132e-3</span></td> | |
| </tr> | |
| </tbody> | |
| </table> | |
| <span class="outliers"> | |
| <p>Outlying measurements have severe | |
| (<span class="percent">0.8868345208055448</span>%) | |
| effect on estimated standard deviation.</p> | |
| </span> | |
| <h2><a name="b16">quotes-count/split/500</a></h2> | |
| <table width="100%"> | |
| <tbody> | |
| <tr> | |
| <td><div id="kde16" class="kdechart" | |
| style="width:450px;height:278px;"></div></td> | |
| <td><div id="time16" class="timechart" | |
| style="width:450px;height:278px;"></div></td> | |
| <!-- | |
| <td><div id="cycle16" class="cyclechart" | |
| style="width:300px;height:278px;"></div></td> | |
| --> | |
| </tr> | |
| </tbody> | |
| </table> | |
| <table> | |
| <thead class="analysis"> | |
| <th></th> | |
| <th class="cibound" | |
| title="0.95 confidence level">lower bound</th> | |
| <th>estimate</th> | |
| <th class="cibound" | |
| title="0.95 confidence level">upper bound</th> | |
| </thead> | |
| <tbody> | |
| <tr> | |
| <td>OLS regression</td> | |
| <td><span class="confinterval olstimelb16">xxx</span></td> | |
| <td><span class="olstimept16">xxx</span></td> | |
| <td><span class="confinterval olstimeub16">xxx</span></td> | |
| </tr> | |
| <tr> | |
| <td>R² goodness-of-fit</td> | |
| <td><span class="confinterval olsr2lb16">xxx</span></td> | |
| <td><span class="olsr2pt16">xxx</span></td> | |
| <td><span class="confinterval olsr2ub16">xxx</span></td> | |
| </tr> | |
| <tr> | |
| <td>Mean execution time</td> | |
| <td><span class="confinterval citime">3.558220126837303e-3</span></td> | |
| <td><span class="time">3.8107832401766116e-3</span></td> | |
| <td><span class="confinterval citime">4.127774471513878e-3</span></td> | |
| </tr> | |
| <tr> | |
| <td>Standard deviation</td> | |
| <td><span class="confinterval citime">7.820801349397283e-4</span></td> | |
| <td><span class="time">9.642698201648883e-4</span></td> | |
| <td><span class="confinterval citime">1.118547477613515e-3</span></td> | |
| </tr> | |
| </tbody> | |
| </table> | |
| <span class="outliers"> | |
| <p>Outlying measurements have severe | |
| (<span class="percent">0.9316196705316067</span>%) | |
| effect on estimated standard deviation.</p> | |
| </span> | |
| <h2><a name="b17">quotes-count/split/600</a></h2> | |
| <table width="100%"> | |
| <tbody> | |
| <tr> | |
| <td><div id="kde17" class="kdechart" | |
| style="width:450px;height:278px;"></div></td> | |
| <td><div id="time17" class="timechart" | |
| style="width:450px;height:278px;"></div></td> | |
| <!-- | |
| <td><div id="cycle17" class="cyclechart" | |
| style="width:300px;height:278px;"></div></td> | |
| --> | |
| </tr> | |
| </tbody> | |
| </table> | |
| <table> | |
| <thead class="analysis"> | |
| <th></th> | |
| <th class="cibound" | |
| title="0.95 confidence level">lower bound</th> | |
| <th>estimate</th> | |
| <th class="cibound" | |
| title="0.95 confidence level">upper bound</th> | |
| </thead> | |
| <tbody> | |
| <tr> | |
| <td>OLS regression</td> | |
| <td><span class="confinterval olstimelb17">xxx</span></td> | |
| <td><span class="olstimept17">xxx</span></td> | |
| <td><span class="confinterval olstimeub17">xxx</span></td> | |
| </tr> | |
| <tr> | |
| <td>R² goodness-of-fit</td> | |
| <td><span class="confinterval olsr2lb17">xxx</span></td> | |
| <td><span class="olsr2pt17">xxx</span></td> | |
| <td><span class="confinterval olsr2ub17">xxx</span></td> | |
| </tr> | |
| <tr> | |
| <td>Mean execution time</td> | |
| <td><span class="confinterval citime">3.3072581136372025e-3</span></td> | |
| <td><span class="time">3.4271861004137364e-3</span></td> | |
| <td><span class="confinterval citime">3.698641217709505e-3</span></td> | |
| </tr> | |
| <tr> | |
| <td>Standard deviation</td> | |
| <td><span class="confinterval citime">2.574367794768943e-4</span></td> | |
| <td><span class="time">5.512594398141777e-4</span></td> | |
| <td><span class="confinterval citime">9.885011380248356e-4</span></td> | |
| </tr> | |
| </tbody> | |
| </table> | |
| <span class="outliers"> | |
| <p>Outlying measurements have severe | |
| (<span class="percent">0.8209397668076144</span>%) | |
| effect on estimated standard deviation.</p> | |
| </span> | |
| <h2><a name="b18">quotes-count/split/700</a></h2> | |
| <table width="100%"> | |
| <tbody> | |
| <tr> | |
| <td><div id="kde18" class="kdechart" | |
| style="width:450px;height:278px;"></div></td> | |
| <td><div id="time18" class="timechart" | |
| style="width:450px;height:278px;"></div></td> | |
| <!-- | |
| <td><div id="cycle18" class="cyclechart" | |
| style="width:300px;height:278px;"></div></td> | |
| --> | |
| </tr> | |
| </tbody> | |
| </table> | |
| <table> | |
| <thead class="analysis"> | |
| <th></th> | |
| <th class="cibound" | |
| title="0.95 confidence level">lower bound</th> | |
| <th>estimate</th> | |
| <th class="cibound" | |
| title="0.95 confidence level">upper bound</th> | |
| </thead> | |
| <tbody> | |
| <tr> | |
| <td>OLS regression</td> | |
| <td><span class="confinterval olstimelb18">xxx</span></td> | |
| <td><span class="olstimept18">xxx</span></td> | |
| <td><span class="confinterval olstimeub18">xxx</span></td> | |
| </tr> | |
| <tr> | |
| <td>R² goodness-of-fit</td> | |
| <td><span class="confinterval olsr2lb18">xxx</span></td> | |
| <td><span class="olsr2pt18">xxx</span></td> | |
| <td><span class="confinterval olsr2ub18">xxx</span></td> | |
| </tr> | |
| <tr> | |
| <td>Mean execution time</td> | |
| <td><span class="confinterval citime">3.3913513393833182e-3</span></td> | |
| <td><span class="time">3.5825147410941324e-3</span></td> | |
| <td><span class="confinterval citime">3.954911602271986e-3</span></td> | |
| </tr> | |
| <tr> | |
| <td>Standard deviation</td> | |
| <td><span class="confinterval citime">3.7252311262407525e-4</span></td> | |
| <td><span class="time">8.208134306367953e-4</span></td> | |
| <td><span class="confinterval citime">1.3040445466159306e-3</span></td> | |
| </tr> | |
| </tbody> | |
| </table> | |
| <span class="outliers"> | |
| <p>Outlying measurements have severe | |
| (<span class="percent">0.9095927070607838</span>%) | |
| effect on estimated standard deviation.</p> | |
| </span> | |
| <h2><a name="b19">quotes-count/split/800</a></h2> | |
| <table width="100%"> | |
| <tbody> | |
| <tr> | |
| <td><div id="kde19" class="kdechart" | |
| style="width:450px;height:278px;"></div></td> | |
| <td><div id="time19" class="timechart" | |
| style="width:450px;height:278px;"></div></td> | |
| <!-- | |
| <td><div id="cycle19" class="cyclechart" | |
| style="width:300px;height:278px;"></div></td> | |
| --> | |
| </tr> | |
| </tbody> | |
| </table> | |
| <table> | |
| <thead class="analysis"> | |
| <th></th> | |
| <th class="cibound" | |
| title="0.95 confidence level">lower bound</th> | |
| <th>estimate</th> | |
| <th class="cibound" | |
| title="0.95 confidence level">upper bound</th> | |
| </thead> | |
| <tbody> | |
| <tr> | |
| <td>OLS regression</td> | |
| <td><span class="confinterval olstimelb19">xxx</span></td> | |
| <td><span class="olstimept19">xxx</span></td> | |
| <td><span class="confinterval olstimeub19">xxx</span></td> | |
| </tr> | |
| <tr> | |
| <td>R² goodness-of-fit</td> | |
| <td><span class="confinterval olsr2lb19">xxx</span></td> | |
| <td><span class="olsr2pt19">xxx</span></td> | |
| <td><span class="confinterval olsr2ub19">xxx</span></td> | |
| </tr> | |
| <tr> | |
| <td>Mean execution time</td> | |
| <td><span class="confinterval citime">3.226182432507404e-3</span></td> | |
| <td><span class="time">3.2549362389548775e-3</span></td> | |
| <td><span class="confinterval citime">3.285800638047227e-3</span></td> | |
| </tr> | |
| <tr> | |
| <td>Standard deviation</td> | |
| <td><span class="confinterval citime">8.043574026843295e-5</span></td> | |
| <td><span class="time">9.70930816756201e-5</span></td> | |
| <td><span class="confinterval citime">1.1539675825116305e-4</span></td> | |
| </tr> | |
| </tbody> | |
| </table> | |
| <span class="outliers"> | |
| <p>Outlying measurements have moderate | |
| (<span class="percent">0.1380529535988627</span>%) | |
| effect on estimated standard deviation.</p> | |
| </span> | |
| <h2><a name="b20">quotes-count/split/900</a></h2> | |
| <table width="100%"> | |
| <tbody> | |
| <tr> | |
| <td><div id="kde20" class="kdechart" | |
| style="width:450px;height:278px;"></div></td> | |
| <td><div id="time20" class="timechart" | |
| style="width:450px;height:278px;"></div></td> | |
| <!-- | |
| <td><div id="cycle20" class="cyclechart" | |
| style="width:300px;height:278px;"></div></td> | |
| --> | |
| </tr> | |
| </tbody> | |
| </table> | |
| <table> | |
| <thead class="analysis"> | |
| <th></th> | |
| <th class="cibound" | |
| title="0.95 confidence level">lower bound</th> | |
| <th>estimate</th> | |
| <th class="cibound" | |
| title="0.95 confidence level">upper bound</th> | |
| </thead> | |
| <tbody> | |
| <tr> | |
| <td>OLS regression</td> | |
| <td><span class="confinterval olstimelb20">xxx</span></td> | |
| <td><span class="olstimept20">xxx</span></td> | |
| <td><span class="confinterval olstimeub20">xxx</span></td> | |
| </tr> | |
| <tr> | |
| <td>R² goodness-of-fit</td> | |
| <td><span class="confinterval olsr2lb20">xxx</span></td> | |
| <td><span class="olsr2pt20">xxx</span></td> | |
| <td><span class="confinterval olsr2ub20">xxx</span></td> | |
| </tr> | |
| <tr> | |
| <td>Mean execution time</td> | |
| <td><span class="confinterval citime">3.314826071573803e-3</span></td> | |
| <td><span class="time">3.347974478414667e-3</span></td> | |
| <td><span class="confinterval citime">3.378053014574549e-3</span></td> | |
| </tr> | |
| <tr> | |
| <td>Standard deviation</td> | |
| <td><span class="confinterval citime">9.097732801754994e-5</span></td> | |
| <td><span class="time">1.0962762833546085e-4</span></td> | |
| <td><span class="confinterval citime">1.396245831486277e-4</span></td> | |
| </tr> | |
| </tbody> | |
| </table> | |
| <span class="outliers"> | |
| <p>Outlying measurements have moderate | |
| (<span class="percent">0.15823330884048273</span>%) | |
| effect on estimated standard deviation.</p> | |
| </span> | |
| <h2><a name="b21">quotes-count/split/1000</a></h2> | |
| <table width="100%"> | |
| <tbody> | |
| <tr> | |
| <td><div id="kde21" class="kdechart" | |
| style="width:450px;height:278px;"></div></td> | |
| <td><div id="time21" class="timechart" | |
| style="width:450px;height:278px;"></div></td> | |
| <!-- | |
| <td><div id="cycle21" class="cyclechart" | |
| style="width:300px;height:278px;"></div></td> | |
| --> | |
| </tr> | |
| </tbody> | |
| </table> | |
| <table> | |
| <thead class="analysis"> | |
| <th></th> | |
| <th class="cibound" | |
| title="0.95 confidence level">lower bound</th> | |
| <th>estimate</th> | |
| <th class="cibound" | |
| title="0.95 confidence level">upper bound</th> | |
| </thead> | |
| <tbody> | |
| <tr> | |
| <td>OLS regression</td> | |
| <td><span class="confinterval olstimelb21">xxx</span></td> | |
| <td><span class="olstimept21">xxx</span></td> | |
| <td><span class="confinterval olstimeub21">xxx</span></td> | |
| </tr> | |
| <tr> | |
| <td>R² goodness-of-fit</td> | |
| <td><span class="confinterval olsr2lb21">xxx</span></td> | |
| <td><span class="olsr2pt21">xxx</span></td> | |
| <td><span class="confinterval olsr2ub21">xxx</span></td> | |
| </tr> | |
| <tr> | |
| <td>Mean execution time</td> | |
| <td><span class="confinterval citime">3.4096093383593185e-3</span></td> | |
| <td><span class="time">3.4486621692642974e-3</span></td> | |
| <td><span class="confinterval citime">3.485214447776158e-3</span></td> | |
| </tr> | |
| <tr> | |
| <td>Standard deviation</td> | |
| <td><span class="confinterval citime">1.0527541107807822e-4</span></td> | |
| <td><span class="time">1.236630232364907e-4</span></td> | |
| <td><span class="confinterval citime">1.5202257190618078e-4</span></td> | |
| </tr> | |
| </tbody> | |
| </table> | |
| <span class="outliers"> | |
| <p>Outlying measurements have moderate | |
| (<span class="percent">0.18200882207685162</span>%) | |
| effect on estimated standard deviation.</p> | |
| </span> | |
| <h2><a name="grokularation">understanding this report</a></h2> | |
| <p>In this report, each function benchmarked by criterion is assigned | |
| a section of its own. The charts in each section are active; if | |
| you hover your mouse over data points and annotations, you will see | |
| more details.</p> | |
| <ul> | |
| <li>The chart on the left is a | |
| <a href="http://en.wikipedia.org/wiki/Kernel_density_estimation">kernel | |
| density estimate</a> (also known as a KDE) of time | |
| measurements. This graphs the probability of any given time | |
| measurement occurring. A spike indicates that a measurement of a | |
| particular time occurred; its height indicates how often that | |
| measurement was repeated.</li> | |
| <li>The chart on the right is the raw data from which the kernel | |
| density estimate is built. The <i>x</i> axis indicates the | |
| number of loop iterations, while the <i>y</i> axis shows measured | |
| execution time for the given number of loop iterations. The | |
| line behind the values is the linear regression prediction of | |
| execution time for a given number of iterations. Ideally, all | |
| measurements will be on (or very near) this line.</li> | |
| </ul> | |
| <p>Under the charts is a small table. | |
| The first two rows are the results of a linear regression run | |
| on the measurements displayed in the right-hand chart.</p> | |
| <ul> | |
| <li><i>OLS regression</i> indicates the | |
| time estimated for a single loop iteration using an ordinary | |
| least-squares regression model. This number is more accurate | |
| than the <i>mean</i> estimate below it, as it more effectively | |
| eliminates measurement overhead and other constant factors.</li> | |
| <li><i>R² goodness-of-fit</i> is a measure of how | |
| accurately the linear regression model fits the observed | |
| measurements. If the measurements are not too noisy, R² | |
| should lie between 0.99 and 1, indicating an excellent fit. If | |
| the number is below 0.99, something is confounding the accuracy | |
| of the linear model.</li> | |
| <li><i>Mean execution time</i> and <i>standard deviation</i> are | |
| statistics calculated from execution time | |
| divided by number of iterations.</li> | |
| </ul> | |
| <p>We use a statistical technique called | |
| the <a href="http://en.wikipedia.org/wiki/Bootstrapping_(statistics)">bootstrap</a> | |
| to provide confidence intervals on our estimates. The | |
| bootstrap-derived upper and lower bounds on estimates let you see | |
| how accurate we believe those estimates to be. (Hover the mouse | |
| over the table headers to see the confidence levels.)</p> | |
| <p>A noisy benchmarking environment can cause some or many | |
| measurements to fall far from the mean. These outlying | |
| measurements can have a significant inflationary effect on the | |
| estimate of the standard deviation. We calculate and display an | |
| estimate of the extent to which the standard deviation has been | |
| inflated by outliers.</p> | |
| <script type="text/javascript"> | |
| $(function () { | |
| function mangulate(rpt) { | |
| var measured = function(key) { | |
| var idx = rpt.reportKeys.indexOf(key); | |
| return rpt.reportMeasured.map(function(r) { return r[idx]; }); | |
| }; | |
| var number = rpt.reportNumber; | |
| var name = rpt.reportName; | |
| var mean = rpt.reportAnalysis.anMean.estPoint; | |
| var iters = measured("iters"); | |
| var times = measured("time"); | |
| var kdetimes = rpt.reportKDEs[0].kdeValues; | |
| var kdepdf = rpt.reportKDEs[0].kdePDF; | |
| var meanSecs = mean; | |
| var units = $.timeUnits(mean); | |
| var rgrs = rpt.reportAnalysis.anRegress[0]; | |
| var scale = units[0]; | |
| var olsTime = rgrs.regCoeffs.iters; | |
| $(".olstimept" + number).text(function() { | |
| return $.renderTime(olsTime.estPoint); | |
| }); | |
| $(".olstimelb" + number).text(function() { | |
| return $.renderTime(olsTime.estLowerBound); | |
| }); | |
| $(".olstimeub" + number).text(function() { | |
| return $.renderTime(olsTime.estUpperBound); | |
| }); | |
| $(".olsr2pt" + number).text(function() { | |
| return rgrs.regRSquare.estPoint.toFixed(3); | |
| }); | |
| $(".olsr2lb" + number).text(function() { | |
| return rgrs.regRSquare.estLowerBound.toFixed(3); | |
| }); | |
| $(".olsr2ub" + number).text(function() { | |
| return rgrs.regRSquare.estUpperBound.toFixed(3); | |
| }); | |
| mean *= scale; | |
| kdetimes = $.scaleBy(scale, kdetimes); | |
| var kq = $("#kde" + number); | |
| var k = $.plot(kq, | |
| [{ label: name + " time densities", | |
| data: $.zip(kdetimes, kdepdf), | |
| }], | |
| { xaxis: { tickFormatter: $.unitFormatter(scale) }, | |
| yaxis: { ticks: false }, | |
| grid: { borderColor: "#777", | |
| hoverable: true, markings: [ { color: '#6fd3fb', | |
| lineWidth: 1.5, xaxis: { from: mean, to: mean } } ] }, | |
| }); | |
| var o = k.pointOffset({ x: mean, y: 0}); | |
| kq.append('<div class="meanlegend" title="' + $.renderTime(meanSecs) + | |
| '" style="position:absolute;left:' + (o.left + 4) + | |
| 'px;bottom:139px;">mean</div>'); | |
| $.addTooltip("#kde" + number, | |
| function(secs) { return $.renderTime(secs / scale); }); | |
| var timepairs = new Array(times.length); | |
| var lastiter = iters[iters.length-1]; | |
| var olspairs = [[0,0], [lastiter, lastiter * scale * olsTime.estPoint]]; | |
| for (var i = 0; i < times.length; i++) | |
| timepairs[i] = [iters[i],times[i]*scale]; | |
| iterFormatter = function() { | |
| var denom = 0; | |
| return function(iters) { | |
| if (iters == 0) | |
| return ''; | |
| if (denom > 0) | |
| return (iters / denom).toFixed(); | |
| var power; | |
| if (iters >= 1e9) { | |
| denom = '1e9'; power = '⁹'; | |
| } | |
| if (iters >= 1e6) { | |
| denom = '1e6'; power = '⁶'; | |
| } | |
| else if (iters >= 1e3) { | |
| denom = '1e3'; power = '³'; | |
| } | |
| else denom = 1; | |
| if (denom > 1) { | |
| iters = (iters / denom).toFixed(); | |
| iters += '×10' + power + ' iters'; | |
| } else { | |
| iters += ' iters'; | |
| } | |
| return iters; | |
| }; | |
| }; | |
| $.plot($("#time" + number), | |
| [{ label: "regression", data: olspairs, | |
| lines: { show: true } }, | |
| { label: name + " times", data: timepairs, | |
| points: { show: true } }], | |
| { grid: { borderColor: "#777", hoverable: true }, | |
| xaxis: { tickFormatter: iterFormatter() }, | |
| yaxis: { tickFormatter: $.unitFormatter(scale) } }); | |
| $.addTooltip("#time" + number, | |
| function(iters,secs) { | |
| return ($.renderTime(secs / scale) + ' / ' + | |
| iters.toLocaleString() + ' iters'); | |
| }); | |
| if (0) { | |
| var cyclepairs = new Array(cycles.length); | |
| for (var i = 0; i < cycles.length; i++) | |
| cyclepairs[i] = [cycles[i],i]; | |
| $.plot($("#cycle" + number), | |
| [{ label: name + " cycles", | |
| data: cyclepairs }], | |
| { points: { show: true }, | |
| grid: { borderColor: "#777", hoverable: true }, | |
| xaxis: { tickFormatter: | |
| function(cycles,axis) { return cycles + ' cycles'; }}, | |
| yaxis: { ticks: false }, | |
| }); | |
| $.addTooltip("#cycles" + number, function(x,y) { return x + ' cycles'; }); | |
| } | |
| }; | |
| var reports = 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