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Last active Jul 31, 2016

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Matrix of Grouped Barcharts with Aggregate Scatterplots
license: gpl-3.0

A matrix of grouped bar charts

A convenient way to view many barcharts organized by two variables of data.

End of rows and columns are the aggregate datasets of those rows/columns.

<!DOCTYPE html>
<meta charset="utf-8">
<style>
svg {
font: 10px sans-serif;
padding: 20px;
}
.axis,
.frame {
shape-rendering: crispEdges;
}
.axis line {
stroke: #ddd;
}
.axis path {
display: none;
}
.frame {
fill: none;
stroke: #aaa;
}
.d3-tip {
line-height: 1;
font-weight: bold;
padding: 8px;
background: rgba(0, 0, 0, 0.8);
color: #fff;
border-radius: 2px;
}
/* Creates a small triangle extender for the tooltip */
.d3-tip:after {
box-sizing: border-box;
display: inline;
font-size: 8px;
width: 100%;
line-height: 1;
color: rgba(0, 0, 0, 0.8);
content: "\25BC";
position: absolute;
text-align: center;
}
/* Style northward tooltips differently */
.d3-tip.n:after {
margin: -1px 0 0 0;
top: 100%;
left: 0;
}
circle {
fill-opacity: .7;
}
</style>
<body>
<script src="http://d3js.org/d3.v3.min.js"></script>
<script src="http://labratrevenge.com/d3-tip/javascripts/d3.tip.v0.6.3.js"></script>
<script>
var width = 1200,
size = 320,
padding = 60;
var x = d3.scale.linear()
.range([padding / 2, size - padding / 2]);
var y = d3.scale.linear()
.range([size - padding / 2, padding / 2]);
var xAxis = d3.svg.axis()
.scale(x)
.orient("bottom")
.ticks(5);
var yAxis = d3.svg.axis()
.scale(y)
.orient("left")
.ticks(5);
var color = d3.scale.category20();
console.log(color)
var pivotColumns = ["partSize", "httpThreads"];
d3.json("outputRedacted.log", function(error, jdata) {
if (error) return console.warn(error);
data = jdata;
dataMatrix = prepareJson(data);
//console.log(dataMatrix);
traitMatrix = makeMatrix(data);
//console.log(traitMatrix);
avgMatrix = makeAvgLists(data, dataMatrix);
//console.log("avgMatrix", avgMatrix);
n = data[pivotColumns[0]].length;
m = data[pivotColumns[1]].length;
//traitMatrix.each(myPlot);
var svg = d3.select("body").append("svg")
.attr("width", size * (n + 3.5) + padding + 200)
.attr("height", size * (m + 3.5) + padding + 200)
.append("g")
.attr("transform", "translate(" + padding + "," + padding / 2 + ")");
console.log(traitMatrix);
var cell = svg.selectAll(".cell")
.data(traitMatrix)
.enter().append("g")
.attr("class", "cell")
.attr("transform", function(d) { return "translate(" + d.i * size + "," + (d.j)* size + ")"; })
.each(myPlot);
var cell2 = svg.selectAll(".cell2")
.data(avgMatrix[1])
.enter().append("g")
.attr("class", "cell2")
.attr("transform", function(d, i) { return "translate(" + (n) * size + "," + (i) * size + ")"; })
.each(meanPlot);
//console.log("avgMatrix", avgMatrix);
var cell3 = svg.selectAll(".cell3")
.data(avgMatrix[0])
.enter().append("g")
.attr("class", "cell3")
.attr("transform", function(d, i) { return "translate(" + i * size + "," + (m) * size +")"; })
.each(meanPlot2);
// var cell4 = svg.selectAll(".cell4")
// .data(avgMatrix)
// .enter().append("g")
// .attr("class", "cell4")
// .attr("transform", function(d, i) { return "translate(" + ((0 * 3) * size+2800) + "," + (i * (size+ 30) +1600) +")"; })
// .each(meanPlot3);
function myPlot(p) {
width = size - padding;
height = size - padding;
var cell = d3.select(this);
var x0 = d3.scale.ordinal()
.rangeRoundBands([0, width], .1);
var x1 = d3.scale.ordinal();
var y = d3.scale.linear()
.range([height, 0]);
var xAxis = d3.svg.axis()
.scale(x0)
.orient("bottom");
var yAxis = d3.svg.axis()
.scale(y)
.orient("left")
.tickFormat(d3.format(".2s"));
elementData = dataMatrix[p.x][p.y]["tests"];
//console.log(elementData);
//console.log(elementData["DOWN"][0]);
tests = Object.keys(dataMatrix[p.x][p.y]["tests"]["DOWN"]);
downSpeeds = [];
upSpeeds = [];
groupedData = [];
for (i=0; i<tests.length; i++) {
tests[i] = "Test" + tests[i]
downSpeeds.push(parseFloat(elementData["DOWN"][i][" mbps"]));
upSpeeds.push(parseFloat(elementData["UP"][i][" mbps"]));
groupedData.push({"test" : tests[i], "trans": [{"name": "UP", "value": upSpeeds[i]}, {"name": "DOWN", "value": downSpeeds[i]}], "UP": upSpeeds[i], "DOWN": downSpeeds[i] });
};
//console.log(groupedData);
var directions = ["UP", "DOWN"];
groupedData.forEach(function(d) {
d.direct = directions.map(function(name) { return {name: name, value: +d[name]}; }); //adds a function to data that allows you to request an array of the age ranges and their values for a given Interval
});
x0.domain(groupedData.map(function(d) { return d.test; }));
//console.log(groupedData.map(function(d) { return d.test; }));
x1.domain(directions).rangeRoundBands([0, x0.rangeBand()]);
console.log(x0.rangeBand())
//y.domain([d3.min([d3.min(upSpeeds), d3.min(downSpeeds)]), d3.max([d3.max(upSpeeds), d3.max(downSpeeds)])]);
y.domain([globMin, globMax+10]);
/*cell.append("rect")
.attr("class", "frame")
.attr("x", padding / 2)
.attr("y", padding / 2)
.attr("width", size - padding)
.attr("height", size - padding)
.attr("transform", "translate(" + width + "," + height + ")");*/
cell.append("g")
.attr("class", "x axis")
.attr("transform", "translate(0," + height + ")")
.call(xAxis);
cell.append("g")
.attr("class", "y axis")
.call(yAxis)
.append("text")
//.attr("transform", "rotate(-90)")
.attr("y", 10)
.style("font-size","12px")
.attr("dy", ".71em")
//.style("text-anchor", "end")
.text("mbps: " + pivotColumns[0] + "= " + p.x + " vs. " + pivotColumns[1] + "= "+ p.y );
//console.log(p.x + "" + p.y);
/*cell.append("text")
.attr("x", padding)
.attr("y", padding)
.attr("dy", ".71em")
.text(function(d) { return d.x; });*/
var Test = cell.selectAll(".Test")
.data(groupedData) //an array with each element a dict, keys given by Interval and ages
.enter().append("g")
.style("stroke", "black")
.attr("class", "g")
.attr("transform", function(d) { return "translate(" + x0(d.test) + ",0)"; });
//console.log(groupedData);
console.log(x1.rangeBand())
Test.selectAll("rect")
.data(function(d) { return d.direct; })
.enter().append("rect")
.attr("width", x1.rangeBand())
.attr("x", function(d) { return x1(d.name); })
.attr("y", function(d) { return y(d.value); })
.attr("height", function(d) { return height - y(d.value); })
.style("fill", function(d) { return color(d.name); })
.on("mouseover", function(d) {
d3.select(this).style("fill-opacity", .3);
//d3.select(this).glow({color: '#f00',width: 40});
//tip.show(d);
})
.on("mouseout", function(d) {
d3.select(this).style("fill-opacity", 1)
});
//console.log(data);
/*cell.selectAll("circle")
.data(data)
.enter().append("circle")
.attr("cx", function(d) { return x(d[p.x]); })
.attr("cy", function(d) { return y(d[p.y]); })
.attr("r", 3)
.style("fill", function(d) { return color(d.species); }); //wow color scales take strings natively!*/
};
function meanPlot(p) {
width = size - padding;
height = size - padding;
var cell2 = d3.select(this);
elementData = p;
//console.log(elementData["means"]);
//console.log(elementData["DOWN"][0]);
var x = d3.scale.linear()
.range([0, width/n - padding]);
columnNames = Object.keys(dataMatrix).sort(function(a, b){return a-b});
var x = d3.scale.ordinal()
.rangeRoundBands([0, width], 0);
//console.log("names", columnNames);
x.domain(columnNames);
//console.log("dom", x.domain());
//console.log(columnNames);
//x.domain([globMin, globMax+10]);
var y = d3.scale.linear()
.range([height, 0]);
y.domain([globMin, globMax+10]);
var z = d3.scale.category10();
// var tip = d3.tip()
// .attr('class', 'd3-tip')
// .offset([-10, 0])
// .html(function(d) {
// return "<strong>Value:</strong> <span style='color:red'>" + d.y + ": " + d.x + "</span>";
// });
//console.log(x.domain());
var xAxis = d3.svg.axis()
.scale(x)
.orient("bottom")
.tickValues(x.domain())
.ticks(columnNames.length);
var yAxis = d3.svg.axis()
.scale(y)
.orient("left")
var directions = ["up", "down"];
/*var series = directions.map(function(series){
return elementData["means"].map(function(d){
//console.log(d);
return {x: d["up"], y: d["down"], z: d["pivcol1"]};
});
});*/
var series = directions.map(function(series, i){
return elementData["means"].map(function(d){
//console.log(d, i);
return {x: d["pivcol1"], y: d[directions[i]]};
});
});
//console.log("element data", elementData);
// cell2.call(tip);
cell2.append("g")
.attr("class", "x axis")
.attr("transform", "translate(0," + height + ")")
.call(xAxis)
.selectAll("text")
.attr("y", 0)
.attr("x", 9)
.attr("dy", ".35em")
.attr("transform", "rotate(90)")
.style("text-anchor", "start");
cell2.append("g")
.attr("class", "y axis")
.call(yAxis).append("text")
//.attr("transform", "rotate(-90)")
.attr("y", 10)
.style("font-size","12px")
.attr("dy", ".71em")
//.style("text-anchor", "end")
.html("Mean mbps vs. httpThreads");// + "<br/>" + " partSize=" + elementData["pivcol2"]);
binarySwitch = ["UP","DOWN"]
cell2.selectAll(".series")
.data(series)
.enter().append("g")
.attr("class", "series")
.style("fill", function(d, i) { return color(binarySwitch[i]); })
.selectAll(".point")
.data(function(d) { return d; })
.enter().append("circle")
.attr("class", "point")
.attr("r", 4.5)
.attr("cx", function(d) { return x(d.x) + x.rangeBand()/2; })
.attr("cy", function(d) { return y(d.y); });
//.on('mouseover', tip.show);
};
function meanPlot2(p) {
width = size - padding;
height = size - padding;
var cell3 = d3.select(this);
columnNames = Object.keys(dataMatrix[Object.keys(dataMatrix)[1]]).sort(function(a, b){return a-b});
elementData = p;
//console.log("ele", elementData);
//console.log(elementData["DOWN"][0]);
////console.log(width/columnNames.length);
var x = d3.scale.ordinal()
.rangeRoundBands([0, width], 0);
//console.log("names", columnNames);
x.domain(columnNames);
//console.log("dom", x.domain());
//console.log(columnNames);
//x.domain([globMin, globMax+10]);
var y = d3.scale.linear()
.range([height, 0]);
y.domain([globMin, globMax+10]);
var z = d3.scale.category10();
var tip = d3.tip()
.attr('class', 'd3-tip')
.offset([-10, 0])
.html(function(d) {
return "<strong>Value:</strong> <span style='color:red'>" + d.y + ": " + d.x + "</span>";
});
//console.log(x.domain());
var xAxis = d3.svg.axis()
.scale(x)
.orient("bottom")
.tickValues(x.domain())
.ticks(columnNames.length);
var yAxis = d3.svg.axis()
.scale(y)
.orient("left")
var directions = ["up", "down"];
/*var series = directions.map(function(series){
return elementData["means"].map(function(d){
//console.log(d);
return {x: d["up"], y: d["down"], z: d["pivcol1"]};
});
});*/
var series = directions.map(function(series, i){
return elementData["means"].map(function(d){
//console.log("point data", d, i);
return {x: d["pivcol2"], y: d[directions[i]]};
});
});
//console.log("series", series);
cell3.call(tip);
cell3.append("g")
.attr("class", "x axis")
.attr("transform", "translate(0," + height + ")")
.call(xAxis)
.selectAll("text")
.attr("y", 0)
.attr("x", 9)
.attr("dy", ".35em")
.attr("transform", "rotate(90)")
.style("text-anchor", "start");
cell3.append("g")
.attr("class", "y axis")
.call(yAxis).append("text")
//.attr("transform", "rotate(-90)")
.attr("y", 10)
.style("font-size","12px")
.attr("dy", ".71em")
//.style("text-anchor", "end")
.html("Mean mbps vs. partSize");// + "<br/>" + " partSize=" + elementData["pivcol2"]);
binarySwitch = ["UP","DOWN"]
cell3.selectAll(".series")
.data(series)
.enter().append("g")
.attr("class", "series")
.style("fill", function(d, i) { return color(binarySwitch[i]); })
.selectAll(".point")
.data(function(d) { return d; })
.enter().append("circle")
.attr("class", "point")
.attr("r", 4.5)
.attr("cx", function(d) { return x(d.x) + x.rangeBand()/2; })
.attr("cy", function(d) { return y(d.y); });
//.on('mouseover', tip.show);
};
function meanPlot3(p) {
width = size* 3 - padding;
height = size - padding;
var cell4 = d3.select(this);
console.log(Object.keys(dataMatrix[Object.keys(dataMatrix)[1]]));
threadData = p;
elementData = {"means": []};
namePairs = [];
str1 = "pivcol1";
str2 = "pivcol2";
if (Object.keys(threadData[0]).indexOf(str1) >= 0) {
for (unit in p) {
for (entry in p[0]["means"]){
elementData["means"].push({"up": p[unit]["means"][entry]["up"], "down": p[unit]["means"][entry]["down"], "pivcol": p[unit]["pivcol1"] + "," + p[unit]["means"][entry]["pivcol2"], "mem": p[unit]["pivcol1"]*p[unit]["means"][entry]["pivcol2"]});
namePairs.push(p[unit]["pivcol1"] + "," + p[unit]["means"][entry]["pivcol2"]);
console.log(p[unit]["pivcol1"]*10000);
};
//elementData.push({"pivcol": p[unit]["pivcol1"] + "," + p[unit]["means"][0]["pivcol2"], "means": tempList});
};
name = "partSize, httpThreads vs. Mean mbps & ";
} else if (Object.keys(threadData[0]).indexOf(str2) >= 0) {
for (unit in p) {
for (entry in p[0]["means"]){
elementData["means"].push({"up": p[unit]["means"][entry]["up"], "down": p[unit]["means"][entry]["down"], "pivcol": p[unit]["pivcol2"] + "," + p[unit]["means"][entry]["pivcol1"], "mem": p[unit]["pivcol2"]*p[unit]["means"][entry]["pivcol1"]});
namePairs.push(p[unit]["pivcol2"] + "," + p[unit]["means"][entry]["pivcol1"]);
};
//elementData.push({"pivcol": p[unit]["pivcol1"] + "," + p[unit]["means"][0]["pivcol2"], "means": tempList});
};
name = "httpThreads, partSize vs. Mean mbps & ";
}
console.log("pairs", namePairs);
console.log("ele", elementData);
//console.log(elementData["DOWN"][0]);
columnNames = namePairs.sort(function(a, b){return b-a}).reverse();
////console.log(width/columnNames.length);
var x = d3.scale.ordinal()
.rangeRoundBands([0, width], 0);
//console.log("names", columnNames);
x.domain(columnNames);
//console.log("dom", x.domain());
//console.log(columnNames);
//x.domain([globMin, globMax+10]);
var y = d3.scale.linear()
.range([height, 0]);
y.domain([globMin, globMax+10]);
var z = d3.scale.category10();
var y1 = d3.scale.linear().range([height, 0]);
y1.domain([0, 3355443200]);
var tip = d3.tip()
.attr('class', 'd3-tip')
.offset([-10, 0])
.html(function(d) {
return "<strong>Value:</strong> <span style='color:red'>" + d.y + ": " + d.x + "</span>";
});
//console.log(x.domain());
var xAxis = d3.svg.axis()
.scale(x)
.orient("bottom")
.tickValues(x.domain())
.ticks(columnNames.length);
var yAxis = d3.svg.axis()
.scale(y)
.orient("left");
var yAxisRight = d3.svg.axis()
.scale(y1)
.orient("right");
var directions = ["up", "down"];
var mapped = ["mem"]
/*var series = directions.map(function(series){
return elementData["means"].map(function(d){
//console.log(d);
return {x: d["up"], y: d["down"], z: d["pivcol1"]};
});
});*/
var series = directions.map(function(series, i){
return elementData["means"].map(function(d){
//console.log("point data", d, i);
return {x: d["pivcol"], y: d[directions[i]]};
});
});
var memList = mapped.map(function(series, i){
return elementData["means"].map(function(d){
//console.log("point data", d, i);
return {x: d["pivcol"], y: d[mapped[i]]};
});
});;
console.log("series", series);
console.log("mem", memList);
cell4.call(tip);
cell4.append("g")
.attr("class", "x axis")
.attr("transform", "translate(0," + height + ")")
.call(xAxis)
.selectAll("text")
.attr("y", 0)
.attr("x", 9)
.attr("dy", ".35em")
.attr("transform", "rotate(90)")
.style("text-anchor", "start");
cell4.append("g")
.attr("class", "y axis")
.call(yAxis).append("text")
//.attr("transform", "rotate(-90)")
.attr("y", 10)
.style("font-size","12px")
.attr("dy", ".71em")
//.style("text-anchor", "end")
.html(name + "Memory cost");// + "<br/>" + " partSize=" + elementData["pivcol2"]);
cell4.append("g")
.attr("class", "y axis")
.attr("transform", "translate(" + width + " ,0)")
.style("fill", "red")
.call(yAxisRight);
binarySwitch = ["UP","DOWN"]
console.log(series);
cell4.selectAll(".series")
.data(series)
.enter().append("g")
.attr("class", "series")
.style("fill", function(d, i) { return color(binarySwitch[i]); })
.selectAll(".point")
.data(function(d) { return d; })
.enter().append("circle")
.attr("class", "point")
.attr("r", 4.5)
.attr("cx", function(d) { return x(d.x) + x.rangeBand()/2; })
.attr("cy", function(d) { return y(d.y); });
//.on('mouseover', tip.show);
cell4.selectAll(".memseries")
.data(memList)
.enter().append("g")
.attr("class", "memseries")
.style("fill", "red")
.selectAll(".point")
.data(function(d) { return d; })
.enter().append("circle")
.attr("class", "point")
.attr("r", 4.5)
.attr("cx", function(d) { return x(d.x) + x.rangeBand()/2; })
.attr("cy", function(d) { return y1(d.y); });
};
});
function makeAvgLists(json, matrix) {
col1Avgs = [];
col2Avgs = [];
col1 = json[pivotColumns[0]];
col2 = json[pivotColumns[1]];
//console.log(col1,col2);
for (num1 in col1){
col1Avgs.push({"pivcol1": col1[num1], "means": []});
for (num2 in col2){
//console.log(matrix[col1[num1]][col2[num2]]["MeanUP"],matrix[col1[num1]][col2[num2]]["MeanDOWN"]);
col1Avgs[num1]["means"].push({"pivcol2": col2[num2], "up": matrix[col1[num1]][col2[num2]]["MeanUP"], "down": matrix[col1[num1]][col2[num2]]["MeanDOWN"]});
}
}
for (num2 in col2){
col2Avgs.push({"pivcol2": col2[num2], "means": []});
for (num1 in col1){
//console.log(matrix[col2[num2]][col1[num1]]["MeanUP"],matrix[col2[num2]][col1[num1]]["MeanDOWN"]);
col2Avgs[num2]["means"].push({"pivcol1": col1[num1], "up": matrix[col1[num1]][col2[num2]]["MeanUP"], "down": matrix[col1[num1]][col2[num2]]["MeanDOWN"]});
}
}
//console.log(col2Avgs);
return [col1Avgs, col2Avgs];
}
function makeMatrix(json) {
//console.log(json[pivotColumns[0]]);
return cross(json[pivotColumns[0]].sort(function(a, b){return a-b}),json[pivotColumns[1]].sort(function(a, b){return a-b}));
}
function prepareJson(json) {
//console.log(json);
//for (str in pivotColumns) {
// console.log(pivotColumns[str]);
//}
dataMatrix = {}
for (i=0; i<json[pivotColumns[0]].length; i++) {
dataMatrix[json[pivotColumns[0]][i]] = {}
for (j=0; j< json[pivotColumns[1]].length; j++) {
dataMatrix[json[pivotColumns[0]][i]][json[pivotColumns[1]][j]] = {}
}
}
for (i=0; i<json["data"].length; i++) {
dataMatrix[json["data"][i][pivotColumns[0]]][json["data"][i][pivotColumns[1]]] = json["data"][i];
}
mins = [];
maxes = [];
meansUP = [];
meansDOWN = [];
for (s in json["data"]){
tempMeansUP = [];
tempMeansDOWN = [];
for (k in json["data"][s]["tests"]["UP"]){
tempMeansUP.push(parseFloat(json["data"][s]["tests"]["UP"][k][" mbps"]));
tempMeansDOWN.push(parseFloat(json["data"][s]["tests"]["DOWN"][k][" mbps"]));
mins.push(d3.min([parseFloat(json["data"][s]["tests"]["UP"][k][" mbps"]),parseFloat(json["data"][s]["tests"]["DOWN"][k][" mbps"])]));
maxes.push(d3.max([parseFloat(json["data"][s]["tests"]["UP"][k][" mbps"]),parseFloat(json["data"][s]["tests"]["DOWN"][k][" mbps"])]));
}
dataMatrix[json["data"][s][pivotColumns[0]]][json["data"][s][pivotColumns[1]]]["MeanUP"] = d3.mean(tempMeansUP);
dataMatrix[json["data"][s][pivotColumns[0]]][json["data"][s][pivotColumns[1]]]["MeanDOWN"] = d3.mean(tempMeansDOWN);
//meansUP.push([d3.mean(tempMeansUP), json["data"][s]]);
//meansDOWN.push([d3.mean(tempMeansDOWN), json["data"][s]]);
}
//console.log(meansUP);
//console.log(meansDOWN);
//console.log(dataMatrix);
globMin = d3.min(mins);
globMax = d3.max(maxes);
return dataMatrix;
};
function cross(a, b) { //this is cross product of two lists, outputs a list of dicts with keys i,j,x,y, where i is index in first list, j in second index, x is the value of a[i], y is the value of b[j], and the order of the output list is 00, 01, ..., 10, ...
var c = [], n = a.length, m = b.length, i, j;
for (i = -1; ++i < n;) for (j = -1; ++j < m;) c.push({x: a[i], i: i, y: b[j], j: j});
return c;
}
</script>
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