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Statistical Process Control Chart
Raw
Readme.md

Here we have Statistical Process Control chart created using d3 (see https://en.wikipedia.org/wiki/Statistical_process_control). The chart uses statistical summaries of the data to define whether fluctuations are caused by random variance or from some external influence causing a change in behaviour. In the latter case, a data point is considered a 'signal' and the process is considered 'out of control'. A more permanent change to the data may result in a process break being inserted, and a new process starts. SPC charts are common in manufacturing, but here we look at crimes per month in the West Midlands region of the UK.

Raw
crime.csv
Month Count
2011-01 25515
2011-02 25558
2011-03 28958
2011-04 31273
2011-05 30000
2011-06 29037
2011-07 29893
2011-08 28573
2011-09 24013
2011-10 24289
2011-11 22605
2011-12 20732
2012-01 20904
2012-02 20824
2012-03 22930
2012-04 20534
2012-05 22101
2012-06 20518
2012-07 22703
2012-08 22859
2012-09 20829
2012-10 21354
2012-11 20342
2012-12 19100
2013-01 20461
2013-02 18505
2013-03 19807
2013-04 20479
2013-05 21299
2013-06 21336
2013-07 24096
2013-08 22931
2013-09 20325
2013-10 20648
2013-11 19703
2013-12 18980
2014-01 18631
2014-02 17639
2014-03 20711
2014-04 20163
2014-05 20657
2014-06 21776
2014-07 22892
2014-08 21279
2014-09 21437
2014-10 21095
2014-11 20232
2014-12 18447
2015-01 19095
2015-02 17813
2015-03 19714
2015-04 19820
2015-05 20521
2015-06 21418
2015-07 21754
2015-08 20561
2015-09 20248
2015-10 21384
2015-11 20443
2015-12 19782
2016-01 19871
2016-02 19403
2016-03 20892
2016-04 20316
2016-05 22169
2016-06 21814
2016-07 23221
2016-08 22710
2016-09 22379
2016-10 23893
2016-11 21890
2016-12 21302
Raw
index.html
<!DOCTYPE html>
<html>
<head>
<meta charset="UTF-8">
<title>SPC</title>
<link rel="stylesheet" href="spc.css" type="text/css"></link>
<script src="https://d3js.org/d3.v4.min.js"></script>
<script src="spc.js" type="text/javascript"></script>
</head>
<body>
<div id="spcContainer">
<div id="chartContainer"></div>
<div id="metaContainer">
<div id="leftContainer">
<div class="leftItem title">
Statistical Process Control Chart
</div>
<div class="leftItem">
Crime per month in the West Midlands, UK, from January 2011 to December 2016.
</div>
<div class="leftItem">
Click on a data point to exclude it from statistical analysis.
Click anywhere in the chart to create a manual process break, or click below to automatically detect them.
Disable manual process breaks by clicking on the circle at the top of the break.
</div>
<div class="leftItem">
<input class="button" type="button" onclick="toggleAutoDetect()" value="Toggle Process Break Detection">
</div>
</div>
<div id="spcLegend"></div>
</div>
</div>
<script type="text/javascript">
var dataFile = "crime.csv";
var properties;
var autoDetectProcesses = false;
var data
window.onload = function() {
d3.csv(dataFile, function(error, d) {
if (error) throw error;
data = d;
data.forEach(function(d) {
d.Date = spc.parseTime("%Y-%m")(d.Month);
d.Count = +d.Count;
});
spc.displayChart(data, "#chartContainer", properties = {"autoDetectProcess" : autoDetectProcesses});
spc.drawLegend("#spcLegend");
});
}
toggleAutoDetect = function () {
properties.autoDetectProcess = !properties.autoDetectProcess;
spc.displayChart(data, "#chartContainer", properties);
}
window.onresize = function() {
spc.resizeChart("#chartContainer", properties);
}
</script>
</body>
</html>
Raw
spc.css
.spc__axis--x path {
display: none;
}
.spc__line {
fill: none;
stroke: steelblue;
stroke-width: 1.5px;
}
.spc__point {
stroke: none;
fill: #28556E;
}
.spc__excluded {
fill: gray;
}
.spc__limit {
stroke: #22919E;
stroke-dasharray: "5, 5";
}
.spc__MEAN_LINE {
stroke: #22919E;
}
.spc__hoverLine {
stroke: #BBB;
}
.spc__processLines {
stroke: #DDD;
fill: white;
}
body, html {
margin: 0px;
padding: 0px;
width: 100%;
height: 100%;
}
body {
background: white;
font-family: sans-serif, arial;
font-size: 12px;
}
#spcContainer {
width: 960px;
height: 500px;
}
#chartContainer {
width: 100%;
height: 300px;
}
#spcLegend {
width: 100%;
}
#metaContainer {
height: 180px;
margin: 10px;
display: flex;
justify-content: space-between;
}
#leftContainer {
width: 100%;
display: flex;
flex-direction: column;
justify-content: flex-start;
}
.leftItem {
margin-bottom: 15px;
}
.title {
font-size: 20px;
}
.button {
background: #00BDA6;
padding:10px;
font-size:12px;
text-decoration:none;
color:#fff;
border: 1px solid #00BDA6;
-webkit-user-select: none;
}
.button:hover {
background: #fff;
border: 1px solid #00BDA6;
color: #00BDA6;
}
.button:active {
background: #22919E;
border: 1px solid #22919E;
color: #FFF;
}
Raw
spc.js
/**
* Statistical Process Control Chart
*
* @author Chris Rooney
*
* This library draws an SPC chart based on the input data (see
* https://en.wikipedia.org/wiki/Statistical_process_control).
*
* It uses the d3 data visaulisation library - https://d3js.org/
*/
spc = window.spc || {};
spc = function () {
/* The default size of the data points */
var ICON_SIZE = 9;
/**
* Wrapper for converting a string to date
* @param {string} format - The data format
*/
var parseTime = function(format) {
return d3.timeParse(format);
};
/* Default margin sizes */
var margin = {
top: 20,
right: 20,
bottom: 30,
left: 50
};
/**
* Draws an SPC chart
*
* @param {Array} data - The data to render
* @param {String} container - The container where the chart will be rendered
* @param {Object} properties - Properties to configure the SPC chart
*
* The properties object maintains persistent information regarding the chart,
* but can also be used to override defaults. For example:
* {
* "autoDetectProcess" : false, - Speficies whether the process breaks should be inserted manually.
* "autoDetectUntil" : d3.max(data, function(d) { return d[properties.xData]}), - If the above is true,
only do this up to a certain data (this is more used for demonstration purposes).
* "chartUpdateCallback" = function(p){ }, - Receive an update if the chart is modified.
* "xData" : "Date", - The date data column name
* "yData" : "Count" - The count data column name
* }
*
* So that we can resize the chart, we do only data processing and
* signal detection here, and do the drawing in resizeChart. Since you many want multiple SPC charts drawn,
* nothing persists in this library, and is instead stored in the properties object.
*
*/
displayChart = function(data, container, properties) {
/* Clear the container */
d3.select(container).html("");
/* Add default properties where not specified */
configureProperties(properties, data);
/* Sort the data */
data.sort(function(a,b) {return a[properties.xData]-b[properties.xData];});
/* If we have any outliers that we don't want they we strip them from the data */
var strippedData = [];
data.forEach(function(d) {
var add = true;
for (let i in properties.datesToExclude) {
if (d[properties.xData] == i) {
add = false;
}
}
if (add) {
strippedData.push(d);
}
});
/* Add the SVG container to the parent container */
var g = d3.select(container).append("svg")
.attr("width", '100%')
.attr("height", '100%')
.append("g")
.attr("transform", "translate(" + margin.left + "," + margin.top + ")");
/* We store the x and y scales and axes in the properties object so we can resize. */
properties.x = d3.scaleUtc().rangeRound([0, 0]);
properties.y = d3.scaleLinear().rangeRound([0, 0]),
properties.x.domain(d3.extent(data, function(d) {
return d[properties.xData];
}));
properties.xAxis = d3.axisBottom(properties.x);
properties.xAxis.ticks(8);
g.append("g")
.attr("class", "axis spc__axis--x");
properties.yAxis = d3.axisLeft(properties.y);
var axisY = g.append("g");
axisY.attr("class", "axis spc__axis--y")
.append("text")
.attr("fill", "#000")
.attr("transform", "rotate(-90)")
.attr("y", 6)
.attr("dy", "0.71em")
.style("text-anchor", "end")
.text("Count");
/* We add a line that shows the x poistion of the cursor */
g.append("line").classed("spc__hoverLine", true);
/* We add a groups that contains all the control lines and process break lines */
var processLines = g.append("g").classed("spc__processLines", true);
var controlLines = g.append("g");
/* Append each data point */
var dataDots = g.selectAll("dot").data(data)
.enter().append("g");
dataDots.attr("class", "spc__point")
.attr("v", function(d) {
return d[properties.xData];
})
.on("click", function() {
/* When we click on a data point, toggler whether is should be omitted */
var d1 = d3.select(this).attr("v");
if (d1 in properties.datesToExclude) {
delete properties.datesToExclude[d1];
d3.select(container).html("");
properties.chartUpdateCallback(properties);
displayChart(data, container, properties);
} else {
properties.datesToExclude[d1] = true;
d3.select(container).html("");
properties.chartUpdateCallback(properties);
displayChart(data, container, properties);
}
d3.event.stopPropagation();
});
d3.select(container).select("svg")
.on("mousemove", function() {
/* Move the hover line when we move the cursor */
var x = d3.mouse(this)[0]-margin.left;
if (x > 0) {
d3.select(this).select(".spc__hoverLine").style("display", null);
d3.select(this).select(".spc__hoverLine").attr("x1", x).attr("x2", x);
} else {
d3.select(this).select(".spc__hoverLine").style("display", "none");
}
})
.on("mouseout", function() {
d3.select(this).select(".spc__hoverLine").style("display", "none");
})
.on("click", function() {
/* Create a new process when we click on the chart */
if (properties.autoDetectProcess) {
window.alert("Process breaks can only be set when automatic detection is disabled");
} else {
var xDate = properties.x.invert(d3.mouse(this)[0]-margin.left);
xDate = d3.bisector(function(d) { return d[properties.xData]; }).right(data, xDate, 1);
if (properties.manualProcesses.indexOf(xDate) === -1 && xDate < properties.dates.length) {
properties.manualProcesses.push(xDate);
properties.chartUpdateCallback(properties);
displayChart(data, container, properties);
}
}
});
if (properties.manualProcesses.length == 0 || properties.autoDetectProcess) {
/* If we don't have any process breaks, or we want to autodetect the processes, only create one process to start */
createProcess(properties.processes, 0);
} else {
/* Otherwise, create the manual process breaks */
var prev = 0;
for (let i = 0; i < properties.manualProcesses.length; ++i) {
var p = properties.manualProcesses[i];
createProcess(properties.processes, prev, p-1);
if (i == properties.manualProcesses.length - 1 ) {
createProcess(properties.processes, p, data.length-1);
}
prev = p;
}
}
/* Calculate the signals for each process (we do this iteratively) */
calculateSignals(data, properties.processes, 0, properties.autoDetectProcess, properties.autoDetectUntil, properties.datesToExclude);
/* Track the min and max y value so we can set our axis */
var maxY = 0, minY = Number.MAX_SAFE_INTEGER;
/* Loop through each process */
for (let i = 0; i < properties.processes.length; ++i) {
var process = properties.processes[i];
process.startDate = data[process.startIndex][properties.xData];
process.endDate = data[process.endIndex][properties.xData];
/* Define the process lines */
if (!process.startIndex == 0) {
processLines.append("line").classed("processLine_" + process.startIndex, true);
processLines.append("circle").classed("processSelection_" + process.startIndex, true)
.attr("v", process.startIndex)
.on("click", function() {
val = d3.select(this).attr("v");
for (let v in properties.manualProcesses) {
if (properties.manualProcesses[v] == val) {
properties.manualProcesses.splice(v,1);
properties.chartUpdateCallback(properties);
displayChart(data, container, properties);
}
d3.event.stopPropagation();
}
});
}
/* Define the control lines */
for (let i in ControlLinesEnum) {
g.append("line")
.attr("class", "spc__limit " + ControlLinesEnum[i].id + "_" + process.startIndex)
.attr("stroke-dasharray", ControlLinesEnum[i].dash);
}
controlLines.append("path").datum(data.slice(process.startIndex, process.endIndex+1))
.attr("class", "spc__line spc__line_" + process.startIndex);
/* Draw either a normal data point or a signal */
dataDots.filter(function (d) {
for (let datum of data.slice(process.startIndex, process.endIndex+1)) {
if (datum[properties.xData] == d[properties.xData]) {
return true;
}
}
return false;
}).each(function(d) {
d3.select(this).attr("transform", "translate(" + properties.x(d[properties.xData]) + "," + properties.y(d[properties.yData]) + ")");
if (d[properties.xData] in properties.datesToExclude ) {
d3.select(this).append("circle")
.attr("cx", 0)
.attr("cy", 0)
.attr("r" , ICON_SIZE * 0.5)
.attr("fill", "grey");
} else if (d[properties.xData] in properties.processes[i].signals) {
SignalEnum[properties.processes[i].signals[d[properties.xData]]].shape(d3.select(this), 0, 0, ICON_SIZE);
} else {
d3.select(this).append("rect")
.attr("x", function(d) {
return ICON_SIZE * -0.5;
})
.attr("y", function(d) {
return ICON_SIZE * -0.5;
}).attr("width" , ICON_SIZE).attr("height" , ICON_SIZE);
}
});
/* Detect the max and min control limits */
if (process.mean + 3.5 * process.sd > maxY) {
maxY = process.mean + 3.5 * process.sd;
}
if (process.mean - 3.5 * process.sd < minY) {
minY = process.mean - 3.5 * process.sd;
}
}
/* Update the y domain based on the min and max limits */
properties.y.domain([minY, maxY]);
/* Draw the chart */
resizeChart(container, properties);
};
/**
* Internal function for creating a new process (either manually or automatically).
*
* @param {Array} processes - The current processes
* @param {int} index - The start index of the processes
* @param {int} cap - The end index
*/
createProcess = function(processes, index, cap = -1) {
/* We start with a minimum end index of the start index +
the length of the eight-over-mean process (which is the signal
that triggers an automatic process break) */
var endIndex = index + SignalEnum.EIGHT_OVER_MEAN.length;
if (cap > -1 && endIndex > cap) {
/* If this exceeds the cap then reduce the end index */
endIndex = cap;
}
/* Add the process */
processes.push({
"startIndex" : index,
"endIndex" : endIndex,
"cap" : cap
});
/* If we have more than one process, then cap the
previous process to the start of this one */
if (processes.length > 1) {
processes[processes.length - 2].endIndex = index - 1;
}
}
/**
* Resize an existing SPC chart
*
* @param {String} container - The container where the chart is rendered
* @param {Object} properties - Properties to configure the SPC chart
*/
resizeChart = function(container, properties) {
/* Define the width and height of the chart */
var main = d3.select(container);
var box = d3.select(container).node().getBoundingClientRect();
var width = box.width - margin.right - margin.left;
var height = box.height - margin.top - margin.bottom;
/* Position the X axis */
main.select(".spc__axis--x")
.attr("transform", "translate(0," + height + ")")
/* Set the range of the x and y axes */
properties.x.rangeRound([0, width]);
properties.y.rangeRound([height, 0]);
/* Define the number of ticks based on the size of the chart */
properties.xAxis.ticks(width / 100);
main.select(".spc__axis--x").call(properties.xAxis);
properties.yAxis.ticks(height / 50 );
main.select(".spc__axis--y").call(properties.yAxis);
/* Create a line function for this chart */
var line = d3.line()
.x(function(d) {
return properties.x(d[properties.xData]);
})
.y(function(d) {
return properties.y(d[properties.yData]);
});
/* Position the data points */
main.selectAll(".spc__point").each(function(d) {
d3.select(this).attr("transform", "translate(" + properties.x(d[properties.xData]) + "," + properties.y(d[properties.yData]) + ")");
});
/* Position the process break lines and control limit lines */
for (let j of properties.processes ) {
setLinePos(main.select(".processLine_" + j.startIndex), properties.x(j.startDate), 0, properties.x(j.startDate), height);
main.select(".processSelection_" + j.startIndex).attr("cx", properties.x(j.startDate)).attr("cy", 0.5 * ICON_SIZE).attr("r", 0.5*ICON_SIZE);
for (let i in ControlLinesEnum) {
if (j.startDate != j.endDate) {
setLinePos(main.select("." + ControlLinesEnum[i].id + "_" + j.startIndex), properties.x(j.startDate),
properties.y(j.mean + ControlLinesEnum[i].index * j.sd), properties.x(j.endDate), properties.y(j.mean + ControlLinesEnum[i].index * j.sd));
}
}
main.select(".spc__line_" + j.startIndex).attr("d", line);
}
main.select(".spc__hoverLine").attr("y1", 0).attr("y2", height);
};
/**
* Get the signal data without rendering the chart
*
* @param {Array} data - The data to render
* @param {Object} properties - Properties to configure the signal processing
*/
getSignals = function(data, properties) {
configureProperties(properties, data);
createProcess(properties.processes, 0);
calculateSignals(data, properties.processes, 0, properties.autoDetectProcess, properties.autoDetectUntil, properties.datesToExclude);
}
/**
* Internal function for detecting signals and process breaks
*
* @param {Array} data - The data to render
* @param {Object} processes - Existing processes
* @param {int} pIndex - The current process
* @param {bool} autoDetectProcess - Whether to auto detect process breaks
* @param {Date} autoDetectUntil - The limit for auto detecting process breaks
* @param {Array} datesToExclude - A list of dates to exclude
*/
calculateSignals = function(data, processes, pIndex, autoDetectProcess, autoDetectUntil, datesToExclude) {
/* Get the current process */
var process = processes[pIndex];
var signalTracker = {};
process.signals = {};
/* Cap the end of the process to the last data point, otherwise decrement it by one */
if (process.endIndex >= data.length) {
process.endIndex = data.length - 2;
} else {
process.endIndex--;
}
/* We both detect signals and process breaks here. So we need a bit of trickery to define when we enter this loop.
*
* This process is not very efficient since we need to add one data point at a time to detect whether there has beena process break.
* Since the new data point changes the summary statistics, we need to check all data points every time we add a new one. This gives
* us a running time close to O(n^2).
*
*/
var processFound = false;
while (!processFound && process.endIndex < data.length -1 && (process.cap == -1 || process.endIndex < process.cap) ) {
/* Reset the signal tracking variables and increase the end index by one (inlude a new data point) */
process.endIndex++;
process.signals = {};
signalTracker = {};
for (let i in SignalEnum) {
signalTracker[SignalEnum[i].id] = [];
};
/* generate summary statistics */
var stats = summaryStatistics(data, datesToExclude, process.startIndex, process.endIndex);
process.mean = stats.mean;
process.sd = stats.sd;
/* Loop through all the points in reverse order */
for (var j = process.endIndex; j >= process.startIndex; --j) {
var d = data[j];
if (!(d[properties.xData] in datesToExclude)) {
for (let i in SignalEnum) {
var sig = SignalEnum[i];
/* Check whether any data points are classified as a signal */
if (sig.rule(d[properties.yData], process.mean, process.sd)) {
/* Check whether a run has been detected, or a new process break should be inserted */
processFound = incrementSignal(signalTracker, sig, d[properties.xData], processes, j, j == process.startIndex ? false : autoDetectProcess, autoDetectUntil);
} else {
/* Otherwise, clear the run */
clearSignal(process.signals, signalTracker, sig);
}
/* If we have a process break, exit the loop */
if (processFound) {
break;
}
}
if (processFound) {
break;
}
}
}
if (processFound) {
/* If we have found a new process, regenerate the summary stats excluding the data points from the latest signal */
var stats = summaryStatistics(data, datesToExclude, process.startIndex, process.endIndex);
process.mean = stats.mean;
process.sd = stats.sd;
}
}
/* We flush out any remaining signals from our signal tracker */
for (let i in SignalEnum) {
var val = SignalEnum[i];
if (val.id in signalTracker) {
addSignalToTracker(process.signals, signalTracker, val);
}
};
/* If we have found a process, or we are working through multiple processes, then we recall this function */
if (processFound || pIndex < processes.length - 1) {
calculateSignals(data, processes, pIndex + 1, autoDetectProcess, autoDetectUntil, datesToExclude);
}
};
/**
* Internal - Generate the mean.
*
* @param {Array} data - the data Array
*/
mean = function(data) {
return d3.mean(data, function(d) {
return d[properties.yData];
});
}
/**
* Internal- Generate the standard deviation.
*
* @param {Array} data - the data Array
*/
sd = function(data) {
return d3.deviation(data, function(d) {
return d[properties.yData];
});
}
/**
* Internal - Generate summary statistics from a subset of the data.
*
* @param {Array} data - the data Array
* @param {Array} datesToExclude - an array out outliers
* @param {int} start - the start inedex (inclusive)
* @param {int} end - the end index (exclusive)
*/
summaryStatistics = function(data, datesToExclude, start, end) {
stats = {"mean" : 0, "sd" : 0};
end++;
if (isEmpty(datesToExclude)) {
stats.mean = mean(data.slice(start, end));
stats.sd = sd(data.slice(start, end));
} else {
var tmpData = [];
for (let i = start; i < end; i++) {
if (!(data[i][properties.xData] in datesToExclude)) {
tmpData.push(data[i]);
}
stats.mean = mean(tmpData);
stats.sd = sd(tmpData);
}
}
return stats;
}
/*
* Internal - if we have a signal, incretment the tracker. If we are detecting process breaks and we find one,
* create a new process and return true.
*/
incrementSignal = function(signalTracker, signalType, id, processes, index, autoDetectProcess, autoDetectUntil) {
signalTracker[signalType.id].push(id);
if ((signalType.id == SignalEnum.EIGHT_OVER_MEAN.id || signalType.id == SignalEnum.EIGHT_UNDER_MEAN.id) &&
signalTracker[signalType.id].length == SignalEnum.EIGHT_OVER_MEAN.length && autoDetectProcess && new Date(id) < new Date(autoDetectUntil)) {
createProcess(processes, index);
return true;
}
return false;
}
/*
* Internal - Clear a run of signals if below the expected threshold.
*/
clearSignal = function(signals, signalTracker, signalType) {
addSignalToTracker(signals, signalTracker, signalType);
signalTracker[signalType.id] = [];
}
/*
* Add a new signal to the tracker.
*/
addSignalToTracker = function(signals, signalTracker, signalType) {
if (signalTracker[signalType.id].length >= signalType.length) {
signalTracker[signalType.id].forEach(function (d) {
if ((d in signals && signalType.length < SignalEnum[signals[d]].length) || !(d in signals)) {
signals[d] = signalType.id;
}
});
}
}
/*
* Internal - Set the position of a line
*/
setLinePos = function(e, x1, y1, x2, y2) {
e.attr("x1", x1)
.attr("y1", y1)
.attr("x2", x2)
.attr("y2", y2);
}
/*
* Check whether an object has any children.
*
* @param {Object} obj - The object to check.
*/
isEmpty = function(obj) {
for(let prop in obj) {
if(obj.hasOwnProperty(prop))
return false;
}
return true;
}
/*
* Internal - Configure the properties object based on a default.
*/
configureProperties = function(properties, data) {
defaultProperties = {
"processes" : [],
"manualProcesses" : [],
"autoDetectProcess" : false,
"datesToExclude" : {},
"autoDetectUntil" : 0,
"dates" : [],
"yData" : "Count",
"xData" : "Date",
"chartUpdateCallback" : function(p){}
}
defaultProperties.autoDetectUntil = d3.max(data, function(d) { return d[defaultProperties.xData]}),
data.forEach(function(d) {
defaultProperties.dates.push(d[defaultProperties.xData]);
})
for (let key of Object.keys(defaultProperties)) {
if (!(key in properties)) {
properties[key] = defaultProperties[key];
}
}
properties.manualProcesses.sort(function(a, b) {
return a - b;
});
properties.processes = [];
}
/**
* Control line definitions
*/
ControlLinesEnum = {
UCL3_LINE : {id: "UCL3_LINE", index : 3, "dash": "0"},
UCL2_LINE : {id: "UCL2_LINE", index : 2, "dash": "5, 5"},
UCL1_LINE : {id: "UCL1_LINE", index : 1.5, "dash": "10, 10"},
MEAN_LINE : {id: "spc__MEAN_LINE", index : 0, "dash": "0"},
LCL1_LINE : {id: "LCL1_LINE", index : -1.5, "dash": "10, 10"},
LCL2_LINE : {id: "LCL2_LINE", index : -2, "dash": "5, 5"},
LCL3_LINE : {id: "LCL3_LINE", index : -3, "dash": "0"}
}
/**
* Check whether a signal is above or below the mean.
*
* @param {SignalEnum} sig - The signal to check.
*/
signalIsBelow = function(sig) {
if (SignalEnum[sig].rule(0,1,0)) {
return true;
}
return false;
}
/*
* Signal definitions
*/
SignalEnum = {
EIGHT_OVER_MEAN : { "id" : "EIGHT_OVER_MEAN", "length" : 8, "index" : 4, "rule" : function(v,mean, sd = 0) {
if (v > mean) {
return true;
}
return false;
}, "shape" : function (container, x, y, size) {
createCross(size, x, y, container, "#00BDA6");
},
"desc" : "Eight data points in a row over the mean"},
EIGHT_UNDER_MEAN : { "id" : "EIGHT_UNDER_MEAN", "length" : 8, "index" : 3, "rule" : function(v,mean, sd = 0) {
if (v < mean) {
return true;
}
return false;
}, "shape" : function (container, x, y, size) {
createDiamond(size, x, y, container, "#00BDA6");
},
"desc" : "Eight data points in a row under the mean"},
TWO_OVER_TWO : { "id" : "TWO_OVER_TWO", "length" : 2, "index" : 6, "rule" : function(v,mean,sd) {
if (v > mean + sd * 2) {
return true;
}
return false;
}, "shape" : function (container, x, y, size) {
createCross(size, x, y, container, "#22919E");
},
"desc" : "Two data points in a row over 2 standard deviations above the mean"},
TWO_UNDER_TWO : { "id" : "TWO_UNDER_TWO", "length" : 2, "index" : 1, "rule": function(v,mean, sd) {
if (v < mean - sd * 2) {
return true;
}
return false;
}, "shape" : function (container, x, y, size) {
createDiamond(size, x, y, container, "#22919E");
},
"desc" : "Two data points in a row over 2 standard deviations below the mean"},
THREE_OVER_ONE_FIVE : { "id" : "THREE_OVER_ONE_FIVE", "length" : 3, "index" : 5, "rule": function(v,mean, sd) {
if (v > mean + sd * 1.5) {
return true;
}
return false;
}, "shape" : function (container, x, y, size) {
createCross(size, x, y, container, "#ff7c40");
},
"desc" : "Three data points in a row over 1.5 standard deviations above the mean"},
THREE_UNDER_ONE_FIVE : { "id" : "THREE_UNDER_ONE_FIVE", "length" : 3, "index" : 2, "rule": function(v,mean, sd) {
if (v < mean - sd * 1.5) {
return true;
}
return false;
}, "shape" : function (container, x, y, size) {
createDiamond(size, x, y, container, "#ff7c40");
},
"desc" : "Three data points in a row over 1.5 standard deviations below the mean"},
ONE_OVER_THREE : { "id" : "ONE_OVER_THREE", "length" : 1, "index" : 7, "rule": function(v,mean, sd) {
if (v > mean + sd*3) {
return true;
}
return false;
}, "shape" : function(container, x, y, size) {
createCross(size, x, y, container, "#eb4551");
},
"desc" : "One data point over 3 standard deviations above the mean"},
ONE_UNDER_THREE: { "id" : "ONE_UNDER_THREE", "length" : 1, "index" : 0, "rule": function(v,mean, sd) {
if (v < mean - sd * 3) {
return true;
}
return false;
}, "shape" : function(container, x, y, size) {
createDiamond(size, x, y, container, "#eb4551");
},
"desc" : "One data point over 3 standard deviations below the mean"}
}
/**
* Drawing functions
**/
createCircle = function(size, x, y, container, colour) {
container.append("circle")
.attr("cx", function(d) {
return x;
})
.attr("cy", function(d) {
return y;
})
.attr("r", size / 2)
.attr("fill", colour);
}
createDiamond = function(size, x, y, container, colour) {
var r = size / 2;
container.append('polyline')
.attr('points', function(d) {
return (-r+x) + " " + y
+ " " + x + " " + (-r + y)
+ " " + (r+x) + " " + y
+ " " + x + " " + (r+y)
+ " " + (-r+x) + " " + y;
} )
.attr("fill", colour);
}
createTriangle = function(size, x, y, container, colour) {
var r = size / 2;
container.append('polyline')
.attr('points', function(d) {
return (-r+x) + " " + (r+y)
+ " " + (r+x) + " " + (r+y)
+ " " + x + " " + (-r+y)
+ " " + (-r+x) + " " + (r+y);
})
.attr("fill", colour);
}
createCross = function(size, x, y, container, colour) {
var s = 1.0 / size * (size / 2.5);
var r = size / 2;
container.append("polyline")
.attr('points', function(d) {
return (x - r) + " " + (y - (1-s) * r) // left , above middle
+ " " + (x - (1-s)*r) + " " + (y - r) // near left , top
+ " " + x + " " + (y - s * r) // middle , above middle
+ " " + (x + ((1-s)* r)) + " " + (y - r) // near right, top
+ " " + (x + r) + " " + (y - r + (s * r)) // right, near top
+ " " + (x + s * r) + " " + y // right of middle, middle
+ " " + (x + r) + " " + (y + r - (s * r)) // right, near bottom
+ " " + (x + ((1-s)* r)) + " " + (y + r) // near right, bottom
+ " " + x + " " + (y + s * r) // middle, below middle
+ " " + (x - (1-s)*r) + " " + (y + r) // near left, bottom
+ " " + (x - r) + " " + (y + (1-s) * r) // left, near bottom
+ " " + (x - s * r) + " " + y // left of middle, middle
+ " " + (x - r) + " " + (y - (1-s) * r); // left , near top
} )
.attr("fill", colour);
}
/**
* Draw the signal details
*
* @param {String} container - The container housing the legend
*/
drawLegend = function(container) {
var svg = d3.select(container).append("svg").attr("width", '100%')
.attr("height", '100%');
var width = d3.select(container).node().getBoundingClientRect().width;
var height = d3.select(container).node().getBoundingClientRect().height;
var sigArray = Object.keys(SignalEnum).map(function (key) { return SignalEnum[key]; });
sigArray.sort(function(a,b) { return b.length - a.length });
var numEntries = sigArray.length;
var boxH = height / numEntries;
var c = 0;
for (let sig of sigArray) {
sig.shape(svg, 0.5 * boxH, 0.5 * boxH + c * boxH, ICON_SIZE);
svg.append("text")
.attr("x", boxH)
.attr("y", c * boxH + (0.5 * boxH))
.attr("width", width - boxH)
.attr("height", boxH)
.attr("text-anchor", "start")
.attr("dominant-baseline", "central")
.text(sig.desc)
c++;
}
}
/**
* Declare public functions
*/
return {
"parseTime" : parseTime,
"displayChart" : displayChart,
"resizeChart" : resizeChart,
"getSignals" : getSignals,
"isEmpty" : isEmpty,
"signalIsBelow" : signalIsBelow,
"SignalEnum" : SignalEnum,
"drawLegend" : drawLegend
}
}();
@apmaster
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There is a lot of detail in the chart. Lot of work has been done on this project

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