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<!--
Copyright (c) 2013, Johnathan Mercer, Balaji Pandian, Nicolas Bonneel, Alexander Lex, Hanspeter Pfister
All rights reserved.
Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met:
Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
Neither the name of Harvard University nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission.
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
BioVis Project
Authors: Johnathan Mercer & Balaji Pandian
Page Layout:
Top: 6 histograms (standardized distances from family of proteins for 6 properties)
Middle: defective triosephosphate isomerase with outliers rendered
Bottom: Zoom of selected region and distance histogram (3-d distances to other residues)
-->
<!DOCTYPE html>
<html>
<head>
<meta charset="utf-8">
<!-- D3 Core Library -->
<script src="http://d3js.org/d3.v3.min.js"></script>
<!-- JQuery Library-->
<script src="https://code.jquery.com/jquery-1.11.1.min.js"></script>
<script src="js/helperFunctions.js" type="text/javascript"></script>
<script src="js/data.js" type="text/javascript"></script>
<!-- WebGL 3D Code -->
<script type="text/javascript" src="js/glMatrix-0.9.5.min.js"></script>
<script type="text/javascript" src="js/webgl-utils.js"></script>
<script type="text/javascript" src="js/lines.js"></script>
<script id="shader-fs" type="x-shader/x-fragment">
// Must keep shaders in HTML file.
precision mediump float;
varying vec4 vColor;
uniform int valMin;
uniform int valMax;
void main(void) {
if (vColor.w<float(valMin) || vColor.w>float(valMax))
gl_FragColor = vec4(0.5, 0.5, 0.5, 0.2);
else
gl_FragColor = vec4(vColor.r*1., vColor.g*1., vColor.b*1., 1.);
}
</script>
<script id="shader-vs" type="x-shader/x-vertex">
// Must keep shaders in HTML file.
attribute vec3 aVertexPosition;
attribute vec3 aTangent;
attribute vec4 aVertexColor;
uniform mat4 uMVMatrix;
uniform mat4 uPMatrix;
uniform float pixelOffset;
varying vec4 vColor;
void main(void) {
vec4 p = uPMatrix * uMVMatrix * vec4(aVertexPosition, 1.0);
p/=abs(p.w);
vec4 v = uPMatrix * uMVMatrix * vec4(aTangent, 0.0);
v.xy /= sqrt(v.x*v.x+v.y*v.y);
p.x += v.y*pixelOffset;
p.y -= v.x*pixelOffset;
gl_Position = p;
vColor = aVertexColor;
}
</script>
<script id="shaderCyl-fs" type="x-shader/x-fragment">
// Must keep shaders in HTML file.
precision mediump float;
varying vec4 vColor;
varying vec4 vNormals;
varying vec4 vPos;
uniform int valMin;
uniform int valMax;
float snoise(vec2 v) {
return fract(sin(dot(v.xy, vec2(12.9898, 78.233)))*43758.5453);
}
void main(void) {
float lighting = max(0.2, vNormals.z);
if (vColor.w<float(valMin) || vColor.w>float(valMax)) {
gl_FragColor = vec4(0.4*lighting, 0.4*lighting, 0.4*lighting, 0.4);
if ( snoise(floor(vPos.xy*2000.)/2000.) < 0.6) {
discard;
}
} else {
gl_FragColor = vec4(vColor.r*lighting, vColor.g*lighting, vColor.b*lighting, 1);
}
}
</script>
<script id="shaderCyl-vs" type="x-shader/x-vertex">
// Must keep shaders in HTML file.
attribute vec3 aVertexPosition;
attribute vec4 aVertexColor;
attribute vec3 aNormals;
uniform mat4 uMVMatrix;
uniform mat4 uPMatrix;
varying vec4 vColor;
varying vec4 vNormals;
varying vec4 vPos;
void main(void) {
vec4 p = uPMatrix * uMVMatrix * vec4(aVertexPosition, 1.0);
p/=abs(p.w);
gl_Position = p;
vPos = p;
vColor = aVertexColor;
vNormals = uMVMatrix*vec4(aNormals, 0.);
float n = sqrt(vNormals.x*vNormals.x+vNormals.y*vNormals.y+vNormals.z*vNormals.z);
vNormals/=n;
}
</script>
<script id="shaderQuad-fs" type="x-shader/x-fragment">
// Must keep shaders in HTML file.
precision mediump float;
varying vec4 vPos;
uniform sampler2D uSampler;
uniform float texW;
void main(void) {
vec4 v = vec4(0.,0.,0.,0.);
for (int i=-4; i<=4; i++) {
for (int j=-4; j<=4; j++) { // didnt manage to make mipmapping work ; manually filter
v+= texture2D(uSampler, vec2(vPos.x+float(i)/texW, vPos.y+float(j)/texW));
}
}
gl_FragColor = vec4(v.xyz/(81.), 1.);
}
</script>
<script id="shaderQuad-vs" type="x-shader/x-vertex">
// Must keep shaders in HTML file.
attribute vec3 aVertexPosition;
varying vec4 vPos;
void main(void) {
vec4 p = vec4(aVertexPosition.x*0.5+0.5, aVertexPosition.y*0.5+0.5, 0., 1.);
gl_Position = vec4(aVertexPosition.xy, 0.1, 1.);
vPos = p;
}
</script>
<script type="text/javascript" src="js/webGL.js"></script>
<link href="css/styles.css" rel="stylesheet" type="text/css">
<!-- stylesheet -->
<title>Mu-8</title>
</head>
<body onload="webGLStart();">
<div id="bodyWrapper">
<!-- <h2> BioVis Project: Identification of Mutations that Affect Protein Function </h2> -->
<div id="theTitle">
Mu-8: Visualizing Differences between a Protein and its Family
</div>
<div id="histogramOptions">
<input class="prettyButton prettyButton-small" onclick="selectAllHistograms()" type="submit" value="Select All">
<input class="prettyButton prettyButton-small" onclick="clearAllHistograms()" type="submit" value="Clear">
</div>
<br>
<div id="histogramWrapper">
<!-- Divs to hold the histograms -->
<div class="horizDiv" id="alpha"></div>
<div class="horizDiv" id="beta"></div>
<div class="horizDiv" id="comp"></div>
<div class="horizDiv" id="hydro"></div>
<div class="horizDiv" id="physico"></div>
<div class="horizDiv" id="other"></div>
</div>
<div id="mainChartWrapper">
<div id="mainArcChart"></div>
<div id="mainChart"></div>
</div>
<div id="zoomChartWrapper">
<div id="threedview">
<canvas id="canvas3d" style="border: none;" width="250" height="250"></canvas>
</div>
<div id="zoomedChartYAxis"></div>
<div id="zoomedChart"></div>
<div id="distanceHistogram"></div>
</div>
<!-- <p> </p> -->
<div id="controls">
<div class="selectDiv">
<div class="checkWrapper">
<input type="checkbox" value="0" checked id="checkRot" onclick="resetView()"> Auto rotate
</div>
<div class="selectWrapper">
<!-- Layout: -->
<div class="styled-select">
<span class="arrow"></span> <select id="selectLayout" onchange="layoutZoom()">
<option value="Stacked">
Stacked
</option>
<option value="Aligned">
Aligned
</option>
</select>
</div>
</div>
</div>
</div>
<hr>
<div class="explanation">
<img src="img/harvard.png" style="float: right; width: 300px;" alt="Harvard SEAS logo"/>
<p>Mu-8 (from 'mutate') is our approach to uncover which mutation
of an amino-acid sequence causes a functional breakdown in a protein.
Mu-8 was conceived as a contribution to the <a
href="http://biovis.net/year/2013/info/contest">2013 BioVis Contest</a> and
was originally developed with students of Harvard's <a href="http://cs171.org">CS 171 -
Visualization class</a>.</p>
<p>Mu-8 visualizes differences of principal components of a
mutated protein relative to its protein family, in addition to the
conservation of regions of the sequence, 3D structure and proximity
data.</p>
<h3>Citation</h3>
<p>Johnathan D Mercer, Balaji Pandian, Alexander Lex, Nicolas Bonneel, and Hanspeter Pfister:
<a href="http://people.seas.harvard.edu/~alex/papers/2014_bmc_mu8.pdf">Mu-8: Visualizing Differences between
Proteins and their Families</a>
BMC Proceedings, vol. 8, no. Suppl 2, p. S5, 2014. </p>
<p><i><a href="http://dx.doi.org/10.1186/1753-6561-8-S2-S5">Publisher</a> |
<a href="https://www.youtube.com/watch?v=AQzNNB38Yg4">YouTube</a> |
<a href="http://people.seas.harvard.edu/~alex/papers/2014_bmc_mu8.bib">BibTex</a> | <a href="https://github.com/alexsb/mu-8">Source Code</a></i></p>
<h3>Team:</h3>
<p>
<strong>Johnathan Mercer</strong> (mercer at fas.harvard.edu)<br>
<strong>Balaji Pandian</strong> (balajipandian at college.harvard.edu)<br>
<strong><a href="http://alexander-lex.com">Alexander Lex</a></strong> (alex at seas.harvard.edu)<br>
<strong><a href="http://people.seas.harvard.edu/~nbonneel/">Nicolas Bonneel</a></strong> (nbonneel at seas.harvard.edu)<br>
<strong><a href="http://vcg.seas.harvard.edu">Hanspeter Pfister</a></strong> (pfister at seas.harvard.edu)</p>
</div>
</div>
<script>
// Gather Data and store into array variables.
var alphaValues = [];
var betaValues = [];
var compValues = [];
var hydroValues = [];
var physicoValues = [];
var otherValues = [];
var seqLength = 248;
var globalTransitionTime = 300;
// standardized distances between dTIM and fmaily mean
// at the same time, calculate the cumulative max x extent and the cumulative negative max x extent
var cumMinNegX = [];
var cumMaxPosX = [];
var allStdDeviations = [];
var stdAlpha = [], stdBeta = [], stdComp = [], stdHydro = [], stdPhy = [], stdOth = [];
for (var i = 0; i < seqLength; i++) {
stdAlpha.push(1 / (alpha_dTIM_m_mean_std.points[i][2] / alpha_dTIM_m_mean.points[i][2]));
stdBeta.push(1 / (beta_dTIM_m_mean_std.points[i][2] / beta_dTIM_m_mean.points[i][2]));
stdComp.push(1 / (comp_dTIM_m_mean_std.points[i][2] / comp_dTIM_m_mean.points[i][2]));
stdHydro.push(1 / (hydro_dTIM_m_mean_std.points[i][2] / hydro_dTIM_m_mean.points[i][2]));
stdPhy.push(1 / (physico_dTIM_m_mean_std.points[i][2] / physico_dTIM_m_mean.points[i][2]));
stdOth.push(1 / (other_dTIM_m_mean_std.points[i][2] / other_dTIM_m_mean.points[i][2]));
var a, b, c, h, p, o;
if (alpha_dTIM_m_mean_std.points[i][2] > 3 || alpha_dTIM_m_mean_std.points[i][2] < -3) {
if (alpha_dTIM_m_mean_std.points[i][2] > 3) {
a = 3;
} else {
a = -3;
}
} else {
a = alpha_dTIM_m_mean_std.points[i][2];
}
if (beta_dTIM_m_mean_std.points[i][2] > 3 || beta_dTIM_m_mean_std.points[i][2] < -3) {
if (beta_dTIM_m_mean_std.points[i][2] > 3) {
b = 3;
} else {
b = -3;
}
} else {
b = beta_dTIM_m_mean_std.points[i][2];
}
if (comp_dTIM_m_mean_std.points[i][2] > 3 || comp_dTIM_m_mean_std.points[i][2] < -3) {
if (comp_dTIM_m_mean_std.points[i][2] > 3) {
c = 3;
} else {
c = -3;
}
} else {
c = comp_dTIM_m_mean_std.points[i][2];
}
if (hydro_dTIM_m_mean_std.points[i][2] > 3 || hydro_dTIM_m_mean_std.points[i][2] < -3) {
if (hydro_dTIM_m_mean_std.points[i][2] > 3) {
h = 3;
} else {
h = -3;
}
} else {
h = hydro_dTIM_m_mean_std.points[i][2];
}
if (physico_dTIM_m_mean_std.points[i][2] > 3 || physico_dTIM_m_mean_std.points[i][2] < -3) {
if (physico_dTIM_m_mean_std.points[i][2] > 3) {
p = 3;
} else {
p = -3;
}
} else {
p = physico_dTIM_m_mean_std.points[i][2];
}
if (other_dTIM_m_mean_std.points[i][2] > 3 || other_dTIM_m_mean_std.points[i][2] < -3) {
if (other_dTIM_m_mean_std.points[i][2] > 3) {
o = 3;
} else {
o = -3;
}
} else {
o = other_dTIM_m_mean_std.points[i][2];
}
cumMinNegX.push(a * (a < 0) + b * (b < 0) + c * (c < 0) + h * (h < 0) + p * (p < 0) + o * (o < 0));
cumMaxPosX.push(a * (a > 0) + b * (b > 0) + c * (c > 0) + h * (h > 0) + p * (p > 0) + o * (o > 0));
alphaValues.push({
myvar: a
});
betaValues.push({
myvar: b
});
compValues.push({
myvar: c
});
hydroValues.push({
myvar: h
});
physicoValues.push({
myvar: p
});
otherValues.push({
myvar: o
});
}
allStdDeviations = [stdAlpha, stdBeta, stdComp, stdHydro, stdPhy, stdOth];
var globalCumMinNegX = d3.min(cumMinNegX);
var globalCumMaxPosX = d3.max(cumMaxPosX);
// Variables for iteration (Each one is an array corresponding to a specific index)
var allIndices = [alphaValues, betaValues, compValues, hydroValues, physicoValues, otherValues];
//replace this with a allIndexData[index]
var alphaData = alphaValues.map(function (d) {
return d.myvar;
});
var betaData = betaValues.map(function (d) {
return d.myvar;
});
var compData = compValues.map(function (d) {
return d.myvar;
});
var hydroData = hydroValues.map(function (d) {
return d.myvar;
});
var physicoData = physicoValues.map(function (d) {
return d.myvar;
});
var otherData = otherValues.map(function (d) {
return d.myvar;
});
var allIndexData = [alphaData, betaData, compData, hydroData, physicoData, otherData];
var posNegIndices = [];
var globalIsBrushedArray = [];
//create array of arrays that hold the pos/neg indices at each residue
for (var i = 0; i < seqLength; i++) {
var posArray = [];
var negArray = [];
for (var d = 0; d < allIndexData.length; d++) {
if (allIndexData[d][i] > 0) {
posArray.push(d);
} else {
negArray.push(d);
}
}
//create empty 'is brushed' arrays for each set of pos/neg scores
var gipb = [];
for (var p = 0; p < posArray.length; p++) {
gipb.push(0);
}
var ginb = [];
for (var p = 0; p < negArray.length; p++) {
ginb.push(0);
}
globalIsBrushedArray.push([gipb, ginb]);
posNegIndices.push([posArray, negArray]);
}
//////////////////////////////////////////
/////// Load the Distance Data////////////
/////////////////////////////////////////
var seqLength4DM = 248;
var matrixRows = [];
for (var p = 0; p < seqLength4DM; p++) {
var thisRow = [];
for (var i = 0; i < distMatrixArray.length; i++) {
if (distMatrixArray[i].OriginAminoAcid == p) {
thisRow.push([distMatrixArray[i].Distance, p]);
}
}
matrixRows.push(thisRow);
}
var histValueObjects = [];
for (var row = 0; row < matrixRows.length; row++) {
for (var col = 0; col < matrixRows.length; col++) {
if (row < col) { //upper diagonal
histValueObjects.push({
dist: matrixRows[row][col][0],
thisRow: matrixRows[row][col][1]
});
}
}
}
//for the distance histogram
var rawHistValues = histValueObjects.map(function (d) {
return d.dist;
});
var namesOfDivIds = ["#alpha", "#beta", "#comp", "#hydro", "#physico", "#other"];
var namesOfIndices = ["Alpha Helix & Turn Propensity", "Beta Sheet Propensity", "Composition", "Hydrophobicity", "Physico-Chemical Properties", "Other Characteristics"];
var histDataArray = []; //will hold the array of data values for histogram buckets needed for brush coloring of histograms
//color brewer 7 group qualitative minus the yellow
var colorOrder = ["#1F78B4", "#F781BF", "#4DAF4A", "#984EA3", "#FF7F00", "#A65628"]; //replaced #E41A1C" for #1F78B4
var hueOrder = [204, 328, 118, 292, 30, 22];
var saturationOrder = [0.71, 0.88, 0.41, 0.35, 1.00, 0.61];
// Brush function array holds the brush functions function brushX () {brushmove(X);} for X=0,..,5
var brushFunctionArray = [brush0, brush1, brush2, brush3, brush4, brush5];
// Brush Array Contains each of the brushes in order
var brushArray = [];
// define the width and height of each histogram
var margin = {
top: 20,
right: 30,
bottom: 20,
left: 30
},
width = 210 - margin.left - margin.right,
height = 120 - margin.top - margin.bottom;
/////////////////////////////////////////////////////////////////
// Global Y max and global min/max x extents for histograms ///
/////////////////////////////////////////////////////////////////
// x_extent array outside loop for brushing code.
var x_extent_array = [];
// set global y by iterating through the datasets
var globalYMax = 0,
min_x_extent = 0,
max_x_extent = 0;
for (var i = 0; i < allIndices.length; i++) {
var x_extent = d3.extent(allIndices[i].map(function (d) {
return d.myvar;
}));
// i use the ceiling and floor functions to get integer min/max for the x pixel space
x_extent[0] = Math.floor(x_extent[0]);
x_extent[1] = Math.ceil(x_extent[1]);
x_extent_array.push(x_extent);
if (x_extent_array[i][1] > max_x_extent) {
max_x_extent = x_extent_array[i][1];
}
if (x_extent_array[i][0] < min_x_extent) {
min_x_extent = x_extent_array[i][0];
}
// # of bins for histogram (sqrt(n))
var num_bins = Math.round(Math.sqrt(seqLength));
// this is the transformation function for input space to pixel space
var x = d3.scale
.linear()
.domain(x_extent)
.range([0, width]);
var data = d3.layout
.histogram()
.frequency(false)
.bins(x.ticks(num_bins))(allIndices[i].map(function (d) {
return d.myvar;
}));
histDataArray.push(data);
var localYMax = d3.max(data, function (d) {
return d.y;
});
//update the globalYMax
if (localYMax > globalYMax) {
globalYMax = localYMax;
}
}
function selectAllHistograms() {
// Loop over each histogram, set max extent, and call brush move
for (var i = 0; i < allIndices.length; i++) {
var hist = d3.select(namesOfDivIds[i]);
brushArray[i].extent([min_x_extent, max_x_extent]);
hist.select(".brush")
.call(brushArray[i]);
brushmove(i);
}
}
function clearAllHistograms() {
// Loop over each histogram, clear extent, and call brush move
for (var i = 0; i < allIndices.length; i++) {
var hist = d3.select(namesOfDivIds[i]);
brushArray[i].extent([0, 0]);
hist.select(".brush")
.call(brushArray[i]);
brushmove(i);
}
}
///////////////////////////////////////////////////////////////////////////////////////////////
//////////////////////////////// Insert the Histograms ////////////////////////////////
//////////////////////////////////////////////////////////////////////////////////////////////
// Loop over each of the indices to create the visualization (allIndices[i] = data to construct histogram i)
for (var i = 0; i < allIndices.length; i++) {
// # of bins for histogram
var num_bins = Math.round(Math.sqrt(seqLength));
// this is the transformation function for input space to pixel space
var x = d3.scale
.linear()
.domain([min_x_extent, max_x_extent])
.range([0, width]);
// Create x axis.
var xAxis = d3.svg
.axis()
.scale(x)
.orient("bottom")
.ticks(5);
var data = d3.layout
.histogram()
.frequency(false)
.bins(x.ticks(num_bins))(allIndices[i].map(function (d) {
return d.myvar;
}));
var y = d3.scale
.linear()
.domain([0, globalYMax])
.range([height, 0]);
//display y-axis as %
var formatPercent = d3.format(".0%");
var yAxis = d3.svg
.axis()
.scale(y)
.orient("left")
.tickFormat(formatPercent)
.ticks(5);
// specify the brush function
var brush = d3.svg
.brush()
.x(x)
.on("brush", brushFunctionArray[i])
.on("brushend", brushend);
//Initialize the brush
brush.extent([min_x_extent, max_x_extent]);
// add brush to brush array
brushArray.push(brush);
//append the svg
var svg = d3.select(namesOfDivIds[i])
.append("svg")
.attr("width", width + margin.left + margin.right)
.attr("height", height + margin.top + margin.bottom)
.append("g")
.attr("transform", "translate(" + margin.left + "," + margin.top + ")");
//histogram title
d3.select(namesOfDivIds[i] + " svg")
.append("text").text(namesOfIndices[i])
.attr("x", margin.left).attr("y", margin.top / 2)
.attr("stroke", colorOrder[i])
.attr("stroke-width", "0.5px")
.attr("font-size", "13px")
.attr("font-family", "Helvetica");
//create groups to hold the bars
var bar = svg.selectAll(".bar")
.data(data)
.enter()
.append("g")
.attr("class", ".bar")
.attr("transform", function (d) {
return "translate(" + x(d.x) + "," + y(d.y) + ")";
})
.call(brush);
//for each bar, append a rectangle
bar.append("rect")
.attr("x", 0)
.attr("width", x(data[0].x + data[0].dx) - x(data[0].x) - 1)
.attr("id", "histrect") //added this for the brushing (blue/grey)
.attr("fill", "#ccc")
.attr("height", function (d) {
return height - y(d.y);
});
svg.select(".brush")
.call(brush);
//context for the brush
var context = svg.append("g");
//append the group with brush
context.append("g")
.attr("class", "x brush")
.call(brush)
.selectAll("rect")
.attr("height", height);
//for the brush handle bars
context.selectAll("rect")
.attr("height", height);
context.selectAll(".resize")
.append("path")
.attr("d", resize_path);
//append x-axis
svg.append("g")
.attr("class", "x axis")
.attr("transform", "translate(0," + height + ")")
.call(xAxis);
//append the y-axis
svg.append("g")
.attr("class", "y axis")
.style("font-size", 10)
.style("font-family", "Helvetica")
.call(yAxis);
}
////////////////////////////////////////////////
// Parameters for the seqContextSVG //
////////////////////////////////////////////////
var positive_y_axis = 50,
negative_y_axis = 50;
var seq_rect_width = 5;
var seq_rect_height = 10;
var seq_svg_height = positive_y_axis + negative_y_axis + seq_rect_height;
var seq_svg_width = dTIM.length * seq_rect_width;
////////////////////////////////////////////////
// Parameters for the seqZoomSVG //
////////////////////////////////////////////////
var zoomLength = 15;
var zoomLayout = "Stacked";
var prevZoomLayout = "Stacked";
var zoomScaleFactor = 2.5; //this is the scale the size of the height of the zoom svg
var zoom_positive_y_axis = positive_y_axis * zoomScaleFactor,
zoom_negative_y_axis = negative_y_axis * zoomScaleFactor;
var zoom_seq_svg_width = seq_svg_width - 590;
var zoom_seq_rect_width = Math.round(zoom_seq_svg_width / zoomLength);
var zoom_seq_rect_height = seq_rect_height * zoomScaleFactor;
var zoom_seq_svg_height = zoom_positive_y_axis + zoom_negative_y_axis + zoom_seq_rect_height;
function setZoomParms(inZoomLength) {
zoom_seq_rect_width = zoom_seq_svg_width / inZoomLength;
}
var arcContextHeight = 100;
var seqArcContextSVG = d3.select("#mainArcChart")
.append("svg")
.attr("class", "seqArcContextSVG")
.attr("style", "border-bottom:1px solid black;")
.attr("width", seq_svg_width)
.attr("height", arcContextHeight);
//add the sequence (context) svg
var seqContextSVG = d3.select("#mainChart")
.append("svg")
.attr("class", "seqContextSVG")
.attr("width", seq_svg_width)
.attr("height", seq_svg_height);
//////////////////////////////////////////////////////////
///// thsi is where the x-axis context went originally
///////////////////////////////////////////////////////////
//this puts the rectangles on the svg
seqContextSVG.selectAll("rect")
.data(dTIM)
.enter()
.append("rect")
.attr("fill", function (d, i) {
if (d == scTIM[i]) {
return "#F7F7F7";
} else {
return "red";
}
})
.attr("stroke", "black")
.attr("stroke-width", 0.5)
.attr("x", function (d, i) {
return i * seq_rect_width;
})
.attr("y", function (d, i) {
return positive_y_axis;
})
.attr("width", seq_rect_width)
.attr("height", seq_rect_height);
//this puts the actual text on the bars
seqContextSVG.selectAll("text")
.data(dTIM)
.enter()
.append("text")
.attr("x", function (d, i) {
return (i * seq_rect_width) + seq_rect_width / 2 - 1;
})
.attr("y", function () {
return positive_y_axis + seq_rect_height / 2;
})
.attr("dx", ".35em")
.attr("dy", ".35em")
.attr("fill", function (d, i) {
if (d == scTIM[i]) {
return "black";
} else {
return "white";
}
})
.attr("font-size", "2px")
.attr("font-family", "Helvetica")
.text(String);
//////////////////////////////////////////////////
// Initialize the Brush for the Context Sequence//
//////////////////////////////////////////////////
// Create the x scale function for the sequence brush
var x = d3.scale
.linear()
.domain([0, 248])
.range([0, seq_svg_width]);
var seqContextBrush = d3.svg
.brush()
.x(x)
.on("brush", brushSeqContext);
//Initialize the brush to cover the first 15 residues
seqContextBrush.extent([0, zoomLength]);
seqContextSVG.select(".brush")
.call(seqContextBrush);
//append a group to hold the brush
var context = seqContextSVG.append("g");
//append the brush
context.append("g")
.attr("class", "x brush")
.attr("id", "seqContextBrush")
.call(seqContextBrush)
.selectAll("rect")
.attr("height", seq_svg_height);
var seqStdHeatSVG = d3.select("#mainChart")
.append("svg")
.attr("class", "stdHeatMap")
.attr("width", seq_svg_width)
.attr("height", allIndices.length * (seq_rect_width + 3));
var stdMaps = [], stdExtents = [];
for (var index = 0; index < allIndices.length; index++) {
stdExtents.push(d3.extent(allStdDeviations[index]));
//stdExtents[index][1] is the max and stdExtents[index][0] is the min
//[stdExtents[index][1],stdExtents[index][0]]
stdMaps.push(d3.scale
.linear()
.domain(stdExtents[index])
.range([0, 1])
.clamp(true)
);
}
for (var index = 0; index < allIndices.length; index++) {
//specify the name of the div based on the namesOfDivIds[index]
var nameOfDiv = namesOfDivIds[index].substring(1) + "heat";
//append the non-visible placeholders on the svg
seqStdHeatSVG.selectAll("rect#" + nameOfDiv)
.data(allStdDeviations[index].map(function (d) {
return d;
}))
.enter()
.append("rect")
.attr("class", "stdHeatRects")
.attr("id", nameOfDiv)
.attr("fill", function (d, i) {
return d3.hsl(0, 0, 1 - stdMaps[index](d)).toString();
})
.attr("x", function (d, i) {
return i * seq_rect_width;
})
.attr("y", function (d, i) {
return index * seq_rect_width + (index * 2)
})
.attr("width", seq_rect_width)
.attr("height", seq_rect_width);
}
//now put hidden rectangles on the svg (for the scores), for each of the 6 indices, so I can transition them later
for (var index = 0; index < allIndices.length; index++) {
//specify the name of the div based on the namesOfDivIds[index]
var nameOfDiv = namesOfDivIds[index].substring(1) + "scoreNonZoom";
//append the non-visible placeholders on the svg
seqContextSVG.selectAll("rect#" + nameOfDiv)
.data(dTIM)
.enter()
.append("rect")
.attr("class", "seqContextScoreRects")
.attr("id", nameOfDiv)
.attr("opacity", 0) // note these are not visible at first
.attr("x", function (d, i) {
return i * seq_rect_width;
})
.attr("y", function (d, i) {
return positive_y_axis;
})
.attr("width", seq_rect_width)
.attr("height", 0);
}
//add an x-axis (separate svg right below it)
var svgForSequenceXAxis = d3.select("#mainChart")
.append("svg")
.attr("class", "x_axis_for_seq")
.attr("width", seq_svg_width)
.attr("height", 20);
//add a break inbetween the x-axis for the sequence and the zoom
var xAxisPadding = 2.5;
// axis for the sequence
var xToAppendAxis = d3.scale
.linear()
.domain([1, 248]) //changed from 0 to 1
.range([xAxisPadding, seq_svg_width - xAxisPadding]);
// Create x axis for the seq svg
var xAxisForSequence = d3.svg
.axis()
.scale(xToAppendAxis)
.orient("bottom")
.ticks(25);
//append x-axis to the sequence
svgForSequenceXAxis.append("g")
.attr("class", "seqXAxis")
.attr("transform", "translate(0," + 0 + ")")
.call(xAxisForSequence);
//one br between the context x-axis and the next set of components
document.write("<br>");
/////////////////////////////////////
//// Add the Distance Histogram ////
////////////////////////////////////
var marginDistHist = {
top: 50,
right: 30,
bottom: 50,
left: 30
},
widthDistHist = 300 - marginDistHist.left - marginDistHist.right,
heightDistHist = 300 - marginDistHist.top - marginDistHist.bottom;
var xExtentDistHist = d3.extent(rawHistValues.map(function (d) {
return d;
}));
xExtentDistHist[0] = Math.floor(xExtentDistHist[0]);
xExtentDistHist[1] = Math.ceil(xExtentDistHist[1]);
var numBinsDistHist = 20;
var xDistHist = d3.scale
.linear()
.domain(xExtentDistHist)
.range([0, widthDistHist]);
var xAxisDistHist = d3.svg
.axis()
.scale(xDistHist)
.orient("bottom")
.ticks(10);
var distHistData = d3.layout
.histogram()
.frequency(false)
.bins(xDistHist.ticks(numBinsDistHist))(rawHistValues.map(function (d) {
return d;
}));
var yDistHist = d3.scale
.linear()
.domain([0, d3.max(distHistData, function (d) {
return d.y;
})])
.range([heightDistHist, 0]);
//display y-axis as %
var formatPercent = d3.format(".0%");
var yAxisDistHist = d3.svg
.axis()
.scale(yDistHist)
.orient("left")
.tickFormat(formatPercent)