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annoy.html
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<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="utf-8">
<meta http-equiv="X-UA-Compatible" content="IE=edge">
<meta name="viewport" content="width=device-width, initial-scale=1">
<!-- The above 3 meta tags *must* come first in the head; any other head content must come *after* these tags -->
<title>annoy</title>
<script src="https://cdnjs.cloudflare.com/ajax/libs/Chart.js/2.5.0/Chart.js"></script>
<script src="https://ajax.googleapis.com/ajax/libs/jquery/1.12.4/jquery.min.js"></script>
<!-- Include all compiled plugins (below), or include individual files as needed -->
<link rel="stylesheet" href="https://maxcdn.bootstrapcdn.com/bootstrap/3.3.7/css/bootstrap.min.css" integrity="sha384-BVYiiSIFeK1dGmJRAkycuHAHRg32OmUcww7on3RYdg4Va+PmSTsz/K68vbdEjh4u" crossorigin="anonymous">
<!-- Bootstrap -->
<script src="https://maxcdn.bootstrapcdn.com/bootstrap/3.3.7/js/bootstrap.min.js" integrity="sha384-Tc5IQib027qvyjSMfHjOMaLkfuWVxZxUPnCJA7l2mCWNIpG9mGCD8wGNIcPD7Txa" crossorigin="anonymous"></script>
<style>
body { padding-top: 50px; }
</style>
<!-- HTML5 shim and Respond.js for IE8 support of HTML5 elements and media queries -->
<!-- WARNING: Respond.js doesn't work if you view the page via file:// -->
<!--[if lt IE 9]>
<script src="https://oss.maxcdn.com/html5shiv/3.7.3/html5shiv.min.js"></script>
<script src="https://oss.maxcdn.com/respond/1.4.2/respond.min.js"></script>
<![endif]-->
</head>
<body>
<nav class="navbar navbar-inverse navbar-fixed-top">
<div class="container">
<div class="navbar-header">
<a class="navbar-brand" href="index.html">ANN Benchmarks</a>
</div>
<div id="navbar" class="collapse navbar-collapse">
<ul class="nav navbar-nav">
<li class="active"><a href="index.html">Home</a></li>
</ul>
<ul class="nav navbar-nav">
<li class="active"><a href="index.html#datasets">Datasets</a></li>
</ul>
<ul class="nav navbar-nav">
<li class="active"><a href="index.html#algorithms">Algorithms</a></li>
</ul>
<ul class="nav navbar-nav">
<li class="active"><a href="index.html#contact">Contact</a></li>
</ul>
</div><!--/.nav-collapse -->
</div>
</nav>
<div class="container">
<h2>Plots for annoy</h2>
<h3>Recall/Queries per second (1/s)</h3>
<div id="RecallQueries per second (1/s)">
<canvas id="chartRecallQueries per second (1/s)" width="800" height="600"></canvas>
<script>
var ctx = document.getElementById("chartRecallQueries per second (1/s)");
var chart = new Chart(ctx, {
type: "line",
data: { datasets: [
{
label: "fashion-mnist-784-euclidean (k = 10)",
fill: false,
pointStyle: "rect",
borderColor: "rgba(229, 102, 102, 1)",
data: [
{ x: 0.9134399999999999 , y: 1625.082323400179, label: "Annoy(n_trees=200, search_k=100)" },
{ x: 0.91482 , y: 1621.962110942443, label: "Annoy(n_trees=200, search_k=400)" },
{ x: 0.95555 , y: 1280.2739648755403, label: "Annoy(n_trees=200, search_k=1000)" },
{ x: 0.9762700000000001 , y: 1029.8707915216003, label: "Annoy(n_trees=200, search_k=2000)" },
{ x: 0.9878199999999999 , y: 830.7160445412949, label: "Annoy(n_trees=200, search_k=4000)" },
{ x: 0.9884299999999999 , y: 648.2595824067312, label: "Annoy(n_trees=400, search_k=4000)" },
{ x: 0.99544 , y: 565.0486000878038, label: "Annoy(n_trees=200, search_k=10000)" },
{ x: 0.9979699999999999 , y: 394.80635897522404, label: "Annoy(n_trees=200, search_k=20000)" },
{ x: 0.9991099999999999 , y: 256.81304590170475, label: "Annoy(n_trees=200, search_k=40000)" },
{ x: 0.99985 , y: 132.190422266384, label: "Annoy(n_trees=200, search_k=100000)" },
{ x: 0.9999100000000001 , y: 76.35033617698305, label: "Annoy(n_trees=400, search_k=200000)" },
{ x: 0.9999800000000001 , y: 72.30990938032117, label: "Annoy(n_trees=200, search_k=200000)" },
{ x: 0.99999 , y: 37.64896504163767, label: "Annoy(n_trees=200, search_k=400000)" },
{ x: 1.0 , y: 8.937299642659495, label: "Annoy(n_trees=100, search_k=400000)" },
]
},
]},
options: {
responsive: false,
title:{
display:true,
text: 'Recall-Queries per second (1/s) tradeoff - up and to the right is better'
},
scales: {
xAxes: [{
display: true,
type: 'linear',
max: '1',
position: 'bottom',
scaleLabel: {
display: true,
labelString: ' Recall '
}
}],
yAxes: [{
display: true,
type: 'logarithmic',
scaleLabel: {
display: true,
labelString: ' Queries per second (1/s) '
}
}]
}
}
});
function pushOrConcat(base, toPush) {
if (toPush) {
if (Chart.helpers.isArray(toPush)) {
// base = base.concat(toPush);
Array.prototype.push.apply(base, toPush);
} else {
base.push(toPush);
}
}
return base;
}
Chart.Tooltip.prototype.getFooter = function(tooltipItem, data) {
var me = this;
var callbacks = me._options.callbacks;
var item = tooltipItem[0];
var beforeFooter = callbacks.beforeFooter.apply(me, arguments);
var footer = "Parameters: " + data.datasets[item.datasetIndex].data[item.index].label || '';
var afterFooter = callbacks.afterFooter.apply(me, arguments);
var lines = [];
lines = pushOrConcat(lines, beforeFooter);
lines = pushOrConcat(lines, footer);
lines = pushOrConcat(lines, afterFooter);
return lines;
}
</script>
</div>
<h3>Recall/Build time (s)</h3>
<div id="RecallBuild time (s)">
<canvas id="chartRecallBuild time (s)" width="800" height="600"></canvas>
<script>
var ctx = document.getElementById("chartRecallBuild time (s)");
var chart = new Chart(ctx, {
type: "line",
data: { datasets: [
{
label: "fashion-mnist-784-euclidean (k = 10)",
fill: false,
pointStyle: "rect",
borderColor: "rgba(229, 102, 102, 1)",
data: [
{ x: 0.99999 , y: 37.724881410598755, label: "Annoy(n_trees=200, search_k=400000)" },
{ x: 1.0 , y: 101.04058003425598, label: "Annoy(n_trees=100, search_k=400000)" },
]
},
]},
options: {
responsive: false,
title:{
display:true,
text: 'Recall-Build time (s) tradeoff - down and to the right is better'
},
scales: {
xAxes: [{
display: true,
type: 'linear',
max: '1',
position: 'bottom',
scaleLabel: {
display: true,
labelString: ' Recall '
}
}],
yAxes: [{
display: true,
type: 'logarithmic',
scaleLabel: {
display: true,
labelString: ' Build time (s) '
}
}]
}
}
});
function pushOrConcat(base, toPush) {
if (toPush) {
if (Chart.helpers.isArray(toPush)) {
// base = base.concat(toPush);
Array.prototype.push.apply(base, toPush);
} else {
base.push(toPush);
}
}
return base;
}
Chart.Tooltip.prototype.getFooter = function(tooltipItem, data) {
var me = this;
var callbacks = me._options.callbacks;
var item = tooltipItem[0];
var beforeFooter = callbacks.beforeFooter.apply(me, arguments);
var footer = "Parameters: " + data.datasets[item.datasetIndex].data[item.index].label || '';
var afterFooter = callbacks.afterFooter.apply(me, arguments);
var lines = [];
lines = pushOrConcat(lines, beforeFooter);
lines = pushOrConcat(lines, footer);
lines = pushOrConcat(lines, afterFooter);
return lines;
}
</script>
</div>
<h3>Recall/Index size (kB)</h3>
<div id="RecallIndex size (kB)">
<canvas id="chartRecallIndex size (kB)" width="800" height="600"></canvas>
<script>
var ctx = document.getElementById("chartRecallIndex size (kB)");
var chart = new Chart(ctx, {
type: "line",
data: { datasets: [
{
label: "fashion-mnist-784-euclidean (k = 10)",
fill: false,
pointStyle: "rect",
borderColor: "rgba(229, 102, 102, 1)",
data: [
{ x: 1.0 , y: 309684.0, label: "Annoy(n_trees=100, search_k=400000)" },
]
},
]},
options: {
responsive: false,
title:{
display:true,
text: 'Recall-Index size (kB) tradeoff - down and to the right is better'
},
scales: {
xAxes: [{
display: true,
type: 'linear',
max: '1',
position: 'bottom',
scaleLabel: {
display: true,
labelString: ' Recall '
}
}],
yAxes: [{
display: true,
type: 'logarithmic',
scaleLabel: {
display: true,
labelString: ' Index size (kB) '
}
}]
}
}
});
function pushOrConcat(base, toPush) {
if (toPush) {
if (Chart.helpers.isArray(toPush)) {
// base = base.concat(toPush);
Array.prototype.push.apply(base, toPush);
} else {
base.push(toPush);
}
}
return base;
}
Chart.Tooltip.prototype.getFooter = function(tooltipItem, data) {
var me = this;
var callbacks = me._options.callbacks;
var item = tooltipItem[0];
var beforeFooter = callbacks.beforeFooter.apply(me, arguments);
var footer = "Parameters: " + data.datasets[item.datasetIndex].data[item.index].label || '';
var afterFooter = callbacks.afterFooter.apply(me, arguments);
var lines = [];
lines = pushOrConcat(lines, beforeFooter);
lines = pushOrConcat(lines, footer);
lines = pushOrConcat(lines, afterFooter);
return lines;
}
</script>
</div>
<h3>Recall/Distance computations</h3>
<div id="RecallDistance computations">
<canvas id="chartRecallDistance computations" width="800" height="600"></canvas>
<script>
var ctx = document.getElementById("chartRecallDistance computations");
var chart = new Chart(ctx, {
type: "line",
data: { datasets: [
{
label: "fashion-mnist-784-euclidean (k = 10)",
fill: false,
pointStyle: "rect",
borderColor: "rgba(229, 102, 102, 1)",
data: [
]
},
]},
options: {
responsive: false,
title:{
display:true,
text: 'Recall-Distance computations tradeoff - down and to the right is better'
},
scales: {
xAxes: [{
display: true,
type: 'linear',
max: '1',
position: 'bottom',
scaleLabel: {
display: true,
labelString: ' Recall '
}
}],
yAxes: [{
display: true,
type: 'logarithmic',
scaleLabel: {
display: true,
labelString: ' Distance computations '
}
}]
}
}
});
function pushOrConcat(base, toPush) {
if (toPush) {
if (Chart.helpers.isArray(toPush)) {
// base = base.concat(toPush);
Array.prototype.push.apply(base, toPush);
} else {
base.push(toPush);
}
}
return base;
}
Chart.Tooltip.prototype.getFooter = function(tooltipItem, data) {
var me = this;
var callbacks = me._options.callbacks;
var item = tooltipItem[0];
var beforeFooter = callbacks.beforeFooter.apply(me, arguments);
var footer = "Parameters: " + data.datasets[item.datasetIndex].data[item.index].label || '';
var afterFooter = callbacks.afterFooter.apply(me, arguments);
var lines = [];
lines = pushOrConcat(lines, beforeFooter);
lines = pushOrConcat(lines, footer);
lines = pushOrConcat(lines, afterFooter);
return lines;
}
</script>
</div>
<h3>Relative Error/Queries per second (1/s)</h3>
<div id="Relative ErrorQueries per second (1/s)">
<canvas id="chartRelative ErrorQueries per second (1/s)" width="800" height="600"></canvas>
<script>
var ctx = document.getElementById("chartRelative ErrorQueries per second (1/s)");
var chart = new Chart(ctx, {
type: "line",
data: { datasets: [
{
label: "fashion-mnist-784-euclidean (k = 10)",
fill: false,
pointStyle: "rect",
borderColor: "rgba(229, 102, 102, 1)",
data: [
{ x: 1.0049139508668592 , y: 1625.082323400179, label: "Annoy(n_trees=200, search_k=100)" },
{ x: 1.0048036625931978 , y: 1621.962110942443, label: "Annoy(n_trees=200, search_k=400)" },
{ x: 1.0022748028180786 , y: 1280.2739648755403, label: "Annoy(n_trees=200, search_k=1000)" },
{ x: 1.0011897679299653 , y: 1029.8707915216003, label: "Annoy(n_trees=200, search_k=2000)" },
{ x: 1.000569622309024 , y: 830.7160445412949, label: "Annoy(n_trees=200, search_k=4000)" },
{ x: 1.000538202304401 , y: 648.2595824067312, label: "Annoy(n_trees=400, search_k=4000)" },
{ x: 1.0002033597468838 , y: 565.0486000878038, label: "Annoy(n_trees=200, search_k=10000)" },
{ x: 1.00009551331559 , y: 394.80635897522404, label: "Annoy(n_trees=200, search_k=20000)" },
{ x: 1.0000397391936249 , y: 256.81304590170475, label: "Annoy(n_trees=200, search_k=40000)" },
{ x: 1.0000083331392902 , y: 132.190422266384, label: "Annoy(n_trees=200, search_k=100000)" },
{ x: 1.000003271259252 , y: 76.35033617698305, label: "Annoy(n_trees=400, search_k=200000)" },
{ x: 1.0000003220140985 , y: 72.30990938032117, label: "Annoy(n_trees=200, search_k=200000)" },
{ x: 1.000000223435517 , y: 37.64896504163767, label: "Annoy(n_trees=200, search_k=400000)" },
{ x: 1.0 , y: 8.937299642659495, label: "Annoy(n_trees=100, search_k=400000)" },
]
},
]},
options: {
responsive: false,
title:{
display:true,
text: 'Relative Error-Queries per second (1/s) tradeoff - up and to the left is better'
},
scales: {
xAxes: [{
display: true,
type: 'linear',
max: '1',
position: 'bottom',
scaleLabel: {
display: true,
labelString: ' Relative Error '
}
}],
yAxes: [{
display: true,
type: 'logarithmic',
scaleLabel: {
display: true,
labelString: ' Queries per second (1/s) '
}
}]
}
}
});
function pushOrConcat(base, toPush) {
if (toPush) {
if (Chart.helpers.isArray(toPush)) {
// base = base.concat(toPush);
Array.prototype.push.apply(base, toPush);
} else {
base.push(toPush);
}
}
return base;
}
Chart.Tooltip.prototype.getFooter = function(tooltipItem, data) {
var me = this;
var callbacks = me._options.callbacks;
var item = tooltipItem[0];
var beforeFooter = callbacks.beforeFooter.apply(me, arguments);
var footer = "Parameters: " + data.datasets[item.datasetIndex].data[item.index].label || '';
var afterFooter = callbacks.afterFooter.apply(me, arguments);
var lines = [];
lines = pushOrConcat(lines, beforeFooter);
lines = pushOrConcat(lines, footer);
lines = pushOrConcat(lines, afterFooter);
return lines;
}
</script>
</div>
<h3>Recall/Candidates generated</h3>
<div id="RecallCandidates generated">
<canvas id="chartRecallCandidates generated" width="800" height="600"></canvas>
<script>
var ctx = document.getElementById("chartRecallCandidates generated");
var chart = new Chart(ctx, {
type: "line",
data: { datasets: [
{
label: "fashion-mnist-784-euclidean (k = 10)",
fill: false,
pointStyle: "rect",
borderColor: "rgba(229, 102, 102, 1)",
data: [
{ x: 1.0 , y: 10.0, label: "Annoy(n_trees=100, search_k=400000)" },
]
},
]},
options: {
responsive: false,
title:{
display:true,
text: 'Recall-Candidates generated tradeoff - down and to the right is better'
},
scales: {
xAxes: [{
display: true,
type: 'linear',
max: '1',
position: 'bottom',
scaleLabel: {
display: true,
labelString: ' Recall '
}
}],
yAxes: [{
display: true,
type: 'logarithmic',
scaleLabel: {
display: true,
labelString: ' Candidates generated '
}
}]
}
}
});
function pushOrConcat(base, toPush) {
if (toPush) {
if (Chart.helpers.isArray(toPush)) {
// base = base.concat(toPush);
Array.prototype.push.apply(base, toPush);
} else {
base.push(toPush);
}
}
return base;
}
Chart.Tooltip.prototype.getFooter = function(tooltipItem, data) {
var me = this;
var callbacks = me._options.callbacks;
var item = tooltipItem[0];
var beforeFooter = callbacks.beforeFooter.apply(me, arguments);
var footer = "Parameters: " + data.datasets[item.datasetIndex].data[item.index].label || '';
var afterFooter = callbacks.afterFooter.apply(me, arguments);
var lines = [];
lines = pushOrConcat(lines, beforeFooter);
lines = pushOrConcat(lines, footer);
lines = pushOrConcat(lines, afterFooter);
return lines;
}
</script>
</div>
<h3>Recall/Index size (kB)/Queries per second (s)</h3>
<div id="RecallIndex size (kB)/Queries per second (s)">
<canvas id="chartRecallIndex size (kB)/Queries per second (s)" width="800" height="600"></canvas>
<script>
var ctx = document.getElementById("chartRecallIndex size (kB)/Queries per second (s)");
var chart = new Chart(ctx, {
type: "line",
data: { datasets: [
{
label: "fashion-mnist-784-euclidean (k = 10)",
fill: false,
pointStyle: "rect",
borderColor: "rgba(229, 102, 102, 1)",
data: [
{ x: 0.9134399999999999 , y: 246.75919135036472, label: "Annoy(n_trees=200, search_k=100)" },
{ x: 0.91482 , y: 247.233888692379, label: "Annoy(n_trees=200, search_k=400)" },
{ x: 0.95555 , y: 313.21733550910955, label: "Annoy(n_trees=200, search_k=1000)" },
{ x: 0.9762700000000001 , y: 389.37311680383687, label: "Annoy(n_trees=200, search_k=2000)" },
{ x: 0.9878199999999999 , y: 482.72090401411054, label: "Annoy(n_trees=200, search_k=4000)" },
{ x: 0.99544 , y: 709.6805477222443, label: "Annoy(n_trees=200, search_k=10000)" },
{ x: 0.9979699999999999 , y: 1015.697926043701, label: "Annoy(n_trees=200, search_k=20000)" },
{ x: 0.9991099999999999 , y: 1561.462730960655, label: "Annoy(n_trees=200, search_k=40000)" },
{ x: 0.99985 , y: 3033.5329377488133, label: "Annoy(n_trees=200, search_k=100000)" },
{ x: 0.9999800000000001 , y: 5545.629961875343, label: "Annoy(n_trees=200, search_k=200000)" },
{ x: 0.99999 , y: 10651.129441579915, label: "Annoy(n_trees=200, search_k=400000)" },
{ x: 1.0 , y: 34650.73482842817, label: "Annoy(n_trees=100, search_k=400000)" },
]
},
]},
options: {
responsive: false,
title:{
display:true,
text: 'Recall-Index size (kB)/Queries per second (s) tradeoff - down and to the right is better'
},
scales: {
xAxes: [{
display: true,
type: 'linear',
max: '1',
position: 'bottom',
scaleLabel: {
display: true,
labelString: ' Recall '
}
}],
yAxes: [{
display: true,
type: 'logarithmic',
scaleLabel: {
display: true,
labelString: ' Index size (kB)/Queries per second (s) '
}
}]
}
}
});
function pushOrConcat(base, toPush) {
if (toPush) {
if (Chart.helpers.isArray(toPush)) {
// base = base.concat(toPush);
Array.prototype.push.apply(base, toPush);
} else {
base.push(toPush);
}
}
return base;
}
Chart.Tooltip.prototype.getFooter = function(tooltipItem, data) {
var me = this;
var callbacks = me._options.callbacks;
var item = tooltipItem[0];
var beforeFooter = callbacks.beforeFooter.apply(me, arguments);
var footer = "Parameters: " + data.datasets[item.datasetIndex].data[item.index].label || '';
var afterFooter = callbacks.afterFooter.apply(me, arguments);
var lines = [];
lines = pushOrConcat(lines, beforeFooter);
lines = pushOrConcat(lines, footer);
lines = pushOrConcat(lines, afterFooter);
return lines;
}
</script>
</div>
<h3>Epsilon 0.01 Recall/Queries per second (1/s)</h3>
<div id="Epsilon 0.01 RecallQueries per second (1/s)">
<canvas id="chartEpsilon 0.01 RecallQueries per second (1/s)" width="800" height="600"></canvas>
<script>
var ctx = document.getElementById("chartEpsilon 0.01 RecallQueries per second (1/s)");
var chart = new Chart(ctx, {
type: "line",
data: { datasets: [
{
label: "fashion-mnist-784-euclidean (k = 10)",
fill: false,
pointStyle: "rect",
borderColor: "rgba(229, 102, 102, 1)",
data: [
{ x: 0.95784 , y: 1625.082323400179, label: "Annoy(n_trees=200, search_k=100)" },
{ x: 0.95885 , y: 1621.962110942443, label: "Annoy(n_trees=200, search_k=400)" },
{ x: 0.98368 , y: 1280.2739648755403, label: "Annoy(n_trees=200, search_k=1000)" },
{ x: 0.99262 , y: 1029.8707915216003, label: "Annoy(n_trees=200, search_k=2000)" },
{ x: 0.9971099999999999 , y: 830.7160445412949, label: "Annoy(n_trees=200, search_k=4000)" },
{ x: 0.9972 , y: 648.2595824067312, label: "Annoy(n_trees=400, search_k=4000)" },
{ x: 0.99918 , y: 565.0486000878038, label: "Annoy(n_trees=200, search_k=10000)" },
{ x: 0.99969 , y: 394.80635897522404, label: "Annoy(n_trees=200, search_k=20000)" },
{ x: 0.99971 , y: 347.78820659550024, label: "Annoy(n_trees=400, search_k=20000)" },
{ x: 0.9998699999999999 , y: 256.81304590170475, label: "Annoy(n_trees=200, search_k=40000)" },
{ x: 0.9999 , y: 238.68082327944268, label: "Annoy(n_trees=400, search_k=40000)" },
{ x: 1.0 , y: 132.190422266384, label: "Annoy(n_trees=200, search_k=100000)" },
]
},
]},
options: {
responsive: false,
title:{
display:true,
text: 'Epsilon 0.01 Recall-Queries per second (1/s) tradeoff - up and to the right is better'
},
scales: {
xAxes: [{
display: true,
type: 'linear',
max: '1',
position: 'bottom',
scaleLabel: {
display: true,
labelString: ' Epsilon 0.01 Recall '
}
}],
yAxes: [{
display: true,
type: 'logarithmic',
scaleLabel: {
display: true,
labelString: ' Queries per second (1/s) '
}
}]
}
}
});
function pushOrConcat(base, toPush) {
if (toPush) {
if (Chart.helpers.isArray(toPush)) {
// base = base.concat(toPush);
Array.prototype.push.apply(base, toPush);
} else {
base.push(toPush);
}
}
return base;
}
Chart.Tooltip.prototype.getFooter = function(tooltipItem, data) {
var me = this;
var callbacks = me._options.callbacks;
var item = tooltipItem[0];
var beforeFooter = callbacks.beforeFooter.apply(me, arguments);
var footer = "Parameters: " + data.datasets[item.datasetIndex].data[item.index].label || '';
var afterFooter = callbacks.afterFooter.apply(me, arguments);
var lines = [];
lines = pushOrConcat(lines, beforeFooter);
lines = pushOrConcat(lines, footer);
lines = pushOrConcat(lines, afterFooter);
return lines;
}
</script>
</div>
<h3>Epsilon 0.1 Recall/Queries per second (1/s)</h3>
<div id="Epsilon 0.1 RecallQueries per second (1/s)">
<canvas id="chartEpsilon 0.1 RecallQueries per second (1/s)" width="800" height="600"></canvas>
<script>
var ctx = document.getElementById("chartEpsilon 0.1 RecallQueries per second (1/s)");
var chart = new Chart(ctx, {
type: "line",
data: { datasets: [
{
label: "fashion-mnist-784-euclidean (k = 10)",
fill: false,
pointStyle: "rect",
borderColor: "rgba(229, 102, 102, 1)",
data: [
{ x: 0.99953 , y: 1625.082323400179, label: "Annoy(n_trees=200, search_k=100)" },
{ x: 0.99957 , y: 1621.962110942443, label: "Annoy(n_trees=200, search_k=400)" },
{ x: 0.9998799999999999 , y: 1280.2739648755403, label: "Annoy(n_trees=200, search_k=1000)" },
{ x: 0.99999 , y: 1029.8707915216003, label: "Annoy(n_trees=200, search_k=2000)" },
{ x: 1.0 , y: 830.7160445412949, label: "Annoy(n_trees=200, search_k=4000)" },
]
},
]},
options: {
responsive: false,
title:{
display:true,
text: 'Epsilon 0.1 Recall-Queries per second (1/s) tradeoff - up and to the right is better'
},
scales: {
xAxes: [{
display: true,
type: 'linear',
max: '1',
position: 'bottom',
scaleLabel: {
display: true,
labelString: ' Epsilon 0.1 Recall '
}
}],
yAxes: [{
display: true,
type: 'logarithmic',
scaleLabel: {
display: true,
labelString: ' Queries per second (1/s) '
}
}]
}
}
});
function pushOrConcat(base, toPush) {
if (toPush) {
if (Chart.helpers.isArray(toPush)) {
// base = base.concat(toPush);
Array.prototype.push.apply(base, toPush);
} else {
base.push(toPush);
}
}
return base;
}
Chart.Tooltip.prototype.getFooter = function(tooltipItem, data) {
var me = this;
var callbacks = me._options.callbacks;
var item = tooltipItem[0];
var beforeFooter = callbacks.beforeFooter.apply(me, arguments);
var footer = "Parameters: " + data.datasets[item.datasetIndex].data[item.index].label || '';
var afterFooter = callbacks.afterFooter.apply(me, arguments);
var lines = [];
lines = pushOrConcat(lines, beforeFooter);
lines = pushOrConcat(lines, footer);
lines = pushOrConcat(lines, afterFooter);
return lines;
}
</script>
</div>
<hr />
<hr />
<div id="contact">
<h2>Contact</h2>
<p>ANN-Benchmarks has been developed by Martin Aumueller (maau@itu.dk), Erik Bernhardsson (mail@erikbern.com), and Alec Faitfull (alef@itu.dk). Please use
<a href="https://github.com/erikbern/ann-benchmarks/">Github</a> to submit your implementation or improvements.</p>
</div>
</div>
</body>
</html>