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Copy pathSpectrumViewer.vue
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SpectrumViewer.vue
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<template>
<v-container fluid>
<v-row>
<div class="spectrumViewerClass" id="spectrumViewerId"></div>
</v-row>
</v-container>
</template>
<script>
const d3 = require("d3v3");
import d3Tip from "d3-tip";
d3.tip = d3Tip;
export default {
props: {
defaultheight: {
type: Number,
default: 750,
},
height: {
type: Number,
default: 550,
},
plotdata: {
type: Object,
},
mirrorplotdata: {
type: Object,
},
peptide: {
type: Object,
},
peptideBottom: {
type: Object,
},
settings: {
type: Object,
},
score: {
type: Object,
},
scoreTop: {
type: Object,
},
scoreBottom: {
type: Object,
},
},
data: function () {
return {
subscript: [
"\u2080",
"\u2081",
"\u2082",
"\u2083",
"\u2084",
"\u2085",
"\u2086",
"\u2087",
"\u2088",
"\u2089",
"\u208B",
],
superscript: [
"\u2070",
"\u00B9",
"\u00B2",
"\u00B3",
"\u2074",
"\u2075",
"\u2076",
"\u2077",
"\u2078",
"\u2079",
"\u207B",
],
ionizationMode: "+",
tip: d3.tip().attr("class", "d3-tip").offset([0, 0]),
};
},
watch: {
plotdata: function () {
this.redraw();
},
mirrorplotdata: function () {
this.redraw();
},
peptide: function () {
this.redraw();
},
peptideBottom: function () {
this.redraw();
},
settings: function () {
this.redraw();
},
score: function () {
this.redraw();
},
scoreTop: function () {
this.redraw();
},
scoreBottom: function () {
this.redraw();
},
},
methods: {
redraw: function () {
if (this.peptide !== undefined) {
this.clearOldLines();
// draws the peptide sequence with the locations of bond breakages marked
this.drawInteractiveTitle();
this.drawInteractiveTitleBottom();
// draws the text elements which list precursor m/z, charge state, and # fragmented bonds.
this.drawPrecursorSummary();
this.drawCorrelationSummary();
this.drawCorrelationSummary(false);
this.drawOriginSummary();
this.drawOriginSummary(false);
// draws the elements contained in the annotated mass spectrum
this.drawAnnotation();
// draws the elements contained in the mass error scatterplot.
this.drawMassError();
}
},
clearOldLines: function () {
var dataset = d3
.select("#annotationContainer")
.selectAll(".line")
.data([]);
dataset.exit().remove();
},
drawMassError: function () {
var that = this;
var x,
y,
xAxis,
yAxis,
dummyXAxis,
dummyYAxis,
massErrorLabel,
shiftFactor,
options = this.getOptions(),
xValues = this.getMassErrorX(),
yValues = this.getMassError(),
colors = this.getColors(),
settings = this.getSettings(),
labels = this.getLabels(),
sequence = this.getSequence(),
theoMz = this.getTheoreticalMz(),
neutralLosses = this.getNeutralLosses(),
sequenceBottom = this.getSequenceBottom();
var intensityError = this.getIntensityError();
var intensityErrorScale = d3.scale
.linear()
.domain([d3.min(intensityError), d3.max(intensityError)])
.range([0, 1]);
// if x and y values are empty, initialize them to an empty array to squash an error caused by a race condition on page render
if (isNaN(d3.max(xValues))) {
xValues = [0];
}
if (isNaN(d3.max(yValues))) {
yValues = [0];
}
if (xValues && yValues) {
// extract what type of mass error we're looking at (ppm or Da)
massErrorLabel = settings.toleranceType;
// if we're looking at milliDalton mass error levels, shift the scale by a factor of 1000 to have more meaningful units.
shiftFactor = 1;
if (massErrorLabel === "Da" && settings.toleranceThreshold < 1) {
massErrorLabel = "mDa";
shiftFactor = 1000;
}
// add a fudge factor to prevent svg elements from getting cut off by the clip mask
var xScaleFudgeFactor = (d3.max(xValues) - d3.min(xValues)) * 0.025;
// define x and y scales.
x = d3.scale
.linear()
.domain([
d3.min(xValues) - xScaleFudgeFactor,
d3.max(xValues) + xScaleFudgeFactor,
])
.range([0, options.fragments.width], 0);
y = d3.scale
.linear()
.domain([d3.max(yValues) + 1, d3.min(yValues) - 1])
.range([options.fragments.height, 0]);
// here we define 4 scales instead of just 2. the dummy axes are only used to encapsulate the mass error chart in borders.
xAxis = d3.svg.axis().scale(x).orient("top").ticks(10);
yAxis = d3.svg.axis().scale(y).orient("left").ticks(5);
dummyXAxis = d3.svg.axis().scale(x).orient("top").tickValues([]);
dummyYAxis = d3.svg.axis().scale(y).orient("left").tickValues([]);
var plotData = [];
// Prevent non-annotated spectral features from displaying mass error circles
for (var i = 0; i < xValues.length; i++) {
// format our data for easy D3 visualization
// here we need the IDs
// TODO: do it tobi
plotData.push({
mz: xValues[i],
theoMz: theoMz[i],
top_id: this.getIntensityErrorIdsTop()[i],
bottom_id: this.getIntensityErrorIdsBottom()[i],
neutLoss: this.formatNeutralLoss(neutralLosses[i]),
error: yValues[i] * shiftFactor,
color: yValues[i] === 0 ? "grey" : "black",
radius: 1.5 + intensityErrorScale(intensityError[i]) * 3,
intensityDifference: intensityError[i],
topId: this.getIntensityErrorIdsTop()[i],
bottomId: this.getIntensityErrorIdsBottom()[i],
});
}
// give the y-axis a label based on the mass error unit
massErrorLabel = this.fragmentContainer
.selectAll(".yAnnotationLabel")
.text("Error (" + massErrorLabel + ")");
// base transition delay on the number of elements visualized
var delay = 1250 / plotData.length;
// bind axes to the fragmentContainer
this.fragmentContainer.selectAll("g.xAnnotation").call(xAxis);
this.fragmentContainer.selectAll("g.yAnnotation").call(yAxis);
this.fragmentContainer
.selectAll("g.xAnnotation_2")
.attr("transform", "translate(0, " + options.fragments.height + ")")
.call(dummyXAxis);
this.fragmentContainer
.selectAll("g.yAnnotation_2")
.attr("transform", "translate(" + options.fragments.width + ",0)")
.call(dummyYAxis);
// bind plotData to the chart to be rendered into circles by D3
this.circleDataset = this.massErrorContainer
.selectAll(".masserror")
.data(plotData);
this.circleDataset.enter().append("circle").attr("class", "masserror");
// actually render the circles and transition them in
this.circleDataset
.attr("cy", function () {
return y(0);
})
.style("fill", function (d) {
return d.color;
})
.attr("cx", function (d) {
return x(d.mz);
})
.attr("r", function (d) {
return d.radius;
})
.attr("opacity", 0)
.transition()
.delay(function (d, i) {
return i * delay;
})
.duration(1250)
.attr("cy", function (d) {
return y(d.error);
})
.attr("opacity", 1);
// remove unneeded circles
this.circleDataset.exit().remove();
// create a linear function
var line = d3.svg
.line()
.x(function (d) {
return x(d.x);
})
.y(function (d) {
return y(d.y);
})
.interpolate("linear");
// Define the points
var baseLine = [
{
lineData: [
{ x: x.domain()[0], y: 0 },
{ x: x.domain()[1], y: 0 },
],
color: "#A9A9A9",
},
];
// draw the zero line
var dataset = this.massErrorContainer
.selectAll(".zeroline")
.data(baseLine);
dataset.enter().append("path").attr("class", "zeroline");
dataset
.attr("d", function (d) {
return line(d.lineData);
})
.attr("opacity", 0)
.style("stroke", function (d) {
return d.color;
})
.transition()
.duration(1500)
.attr("opacity", 1);
dataset.exit().remove();
// attach the tooltip to the fragmentContainer
this.fragmentContainer.call(that.tip);
// bind interactive events. When a circle is highlighted, emphasize the mass error circle, indicate the fragement amino acid sequence, highlight the annotation label.
this.circleDataset.on("mouseenter", function (d, i) {
var label = labels[i];
//var charge = labelCharges[i];
//var neutralLoss = neutralLosses[i];
let fitting_top_peak = that.plotContainer
.selectAll(".bar")
.filter(function (e) {
return e.id == d.top_id;
});
let fitting_bottom_peak = that.plotContainer2
.selectAll(".bar")
.filter(function (e) {
return e.id == d.bottom_id;
});
var bottom_mz =
fitting_bottom_peak.data()[0] === undefined
? "-"
: d3.format(",.4f")(fitting_bottom_peak.data()[0].mz);
var top_mz =
fitting_top_peak.data()[0] === undefined
? "-"
: d3.format(",.4f")(fitting_top_peak.data()[0].mz);
var intensity_diff =
fitting_top_peak.data()[0] === undefined ||
fitting_bottom_peak.data()[0] === undefined
? "-"
: Math.abs(
d3.format(",.4f")(
fitting_top_peak.data()[0].percentBasePeak -
fitting_bottom_peak.data()[0].percentBasePeak
)
);
intensity_diff =
fitting_top_peak.data()[0] === undefined ||
fitting_bottom_peak.data()[0] === undefined
? fitting_top_peak.data()[0] === undefined
? d3.format(",.4f")(
fitting_bottom_peak.data()[0].percentBasePeak
)
: d3.format(",.4f")(fitting_top_peak.data()[0].percentBasePeak)
: Math.abs(
d3.format(",.4f")(
fitting_top_peak.data()[0].percentBasePeak -
fitting_bottom_peak.data()[0].percentBasePeak
)
);
fitting_top_peak.style("stroke", "black").style("width", 6);
fitting_bottom_peak.style("stroke", "black").style("width", 6);
// build the internal tooltip html
that.tip.html(function () {
return (
"" +
"<strong>Mass Error(ppm):</strong> <span style='color:red'>" +
d3.format(".4f")(d.error) +
"</span><br><br>" +
"<strong>Top</strong><strong style='font-style:italic;'> m/z:</strong> <span style='color:red'>" +
top_mz +
" </span><br><br>" +
"<strong>Bottom</strong><strong style='font-style:italic;'> m/z:</strong> <span style='color:red'>" +
bottom_mz +
" </span><br><br>" +
"<strong>Intensity difference(%)</strong>:</strong> <span style='color:red'>" +
intensity_diff +
" </span><br>"
);
});
// show the tooltip
that.tip.direction("e");
that.tip.offset([0, 0]);
that.tip.show(d, this);
// highlight all related fragment information on other plots
var labelObj = that.plotContainer
.selectAll(".barlabel")
.filter(function (e, j) {
//TODO correct id highlighting
return i === j;
});
// make the label a little bigger
labelObj.style("font-size", 18).style("font-weight", "bold");
// extract the sequence data and highlight the fragment on the peptide sequence
var fragmentType = label.charAt(0);
var fragmentNumber = label.slice(1);
var color = colors[i];
// select all text elements from the marked peptide sequence
var interactiveTitleObjects = that.titleContainer
.selectAll("text")
.data(sequence);
// if the fragment type is N-terminal, work from index 0
if (
fragmentType === "a" ||
fragmentType === "b" ||
fragmentType === "c" ||
fragmentType === "C"
) {
interactiveTitleObjects
.style("fill", function (d, i) {
if (i < fragmentNumber) {
return color;
} else {
return "black";
}
})
.style("stroke", function (d, i) {
if (i < fragmentNumber) {
return color;
} else {
return "none";
}
});
// if the fragment type is C-terminal, work from index -1
} else {
interactiveTitleObjects
.style("fill", function (d, i) {
if (i < sequence.length - fragmentNumber) {
return "black";
} else {
return color;
}
})
.style("stroke", function (d, i) {
if (i < sequence.length - fragmentNumber) {
return "none";
} else {
return color;
}
});
}
// highlight the selected circle by making it bigger and giving it a stroke
that.circleDataset
.style("r", function (e, j) {
// TODO HIGHLIGHT CORRECTLY
// This is fine => its just self highlight
if (i === j) {
return 7;
}
})
.style("stroke", function (e, j) {
if (i === j) {
return "black";
}
});
});
// remove the tooltip and return all svg elements back to normal
that.circleDataset.on("mouseleave", function (d, i) {
that.tip.hide();
// turn all text elements back to black
that.titleContainer
.selectAll("text")
.data(sequence)
.style("fill", "black")
.style("stroke", "none");
that.titleContainerBottom
.selectAll("text")
.data(sequenceBottom)
.style("fill", "black")
.style("stroke", "none");
let fitting_top_peak = that.plotContainer
.selectAll(".bar")
.filter(function (e) {
// return e.id == d.bottom_id;
return e.id == d.top_id;
});
let fitting_bottom_peak = that.plotContainer2
.selectAll(".bar")
.filter(function (e) {
return e.id == d.bottom_id;
});
fitting_top_peak.style("stroke", "none").style("width", (d) => {
return d.width;
});
fitting_bottom_peak.style("stroke", "none").style("width", (d) => {
return d.width;
});
// return the barlabel back to 0
var labelObj = that.plotContainer
.selectAll(".barlabel")
.filter(function (e, j) {
return i === j;
});
labelObj.style("font-size", 14).style("font-weight", "normal");
// remove the stroke and resize the circle back to normal
that.circleDataset
.style("r", function (data) {
return data.radius;
})
.style("stroke", function () {
return "none";
});
});
}
},
drawAnnotation: function () {
var that = this;
let x,
y,
y2,
xAxis,
xTopAxis,
fragxAxis,
yAxis,
yAxis2,
barDataset,
barDataset2,
labelDataset,
labelDataset2,
options = this.getOptions(),
xValues = this.getX(),
yValues = this.getIntensities(),
percentBasePeak = this.getPercentBasePeak(),
xValues2 = this.getMirrorX(),
yValues2 = this.getMirrorIntensities(),
percentBasePeak2 = this.getMirrorPercentBasePeak(),
labels2 = this.getMirrorLabels(),
labelCharges2 = this.getMirrorLabelCharges(),
colors2 = this.getMirrorColors(),
id = this.getId(),
id2 = this.getIdMirror(),
massError = this.getMassError(),
colors = this.getColors(),
labels = this.getLabels(),
labelCharges = this.getLabelCharges(),
neutralLosses = this.getNeutralLosses(),
widths = this.getWidths(),
widths2 = this.getMirrorWidths(),
sequence = this.getSequence();
// since y axis is scaled to % relative abundance, yMax will always be 100%.
let yMin = 0,
yMin2 = -100;
let yMax = 100,
yMax2 = 0;
let xMin = d3.min([d3.min(xValues), d3.min(xValues2)]);
let xMax = d3.max([d3.max(xValues), d3.max(xValues2)]);
let TIC = 0,
TIC2 = 0;
let mirror = xValues2 ? true : false;
// create a variable to add a bit of a buffer between the edges of the svg so things don't get cut off.
let xScaleFudgeFactor = (xMax - xMin) * 0.025;
// Do stuff if there is data to visualize.
if (xValues && yValues) {
// define x and y scales
x = d3.scale
.linear()
.domain([xMin - xScaleFudgeFactor, xMax + xScaleFudgeFactor])
.range([0, options.annotation.width]);
y = d3.scale
.linear()
.domain([yMin, yMax + yMax * 2 * options.annotation.padding])
.range([options.annotation.height, 0]);
if (mirror) {
y2 = d3.scale
.linear()
.domain([
yMin2 + yMin2 * 2 * options.annotation.padding,
yMax2 + yMax2 * options.annotation.padding,
])
.range([options.annotation.height, 0]);
}
// x-axis will be at the bottom with a suggested 10 axis ticks. That number may change depending on how D3 interprets the m/z range
xAxis = d3.svg.axis().scale(x).orient("bottom").ticks(10);
if (mirror) {
xTopAxis = d3.svg.axis().scale(x).orient("top").ticks(10);
}
// fragxAxis is actually the x axis from the fragment mass error chart. It's defined here so it can be updated on zoom.
fragxAxis = d3.svg.axis().scale(x).orient("top").ticks(10);
// Format the y-axis ticks to round itself to 2 significant figures. e.g. 50, 5.0, 0.50
yAxis = d3.svg
.axis()
.scale(y)
.orient("left")
.tickFormat(function (d) {
return d3.format("0.2r")(d);
});
if (mirror) {
yAxis2 = d3.svg
.axis()
.scale(y2)
.orient("left")
.tickFormat(function (d) {
return d3.format("0.2r")(d === 0 ? d : -d);
});
}
let plotData = [];
let mirrorPlotData = [];
var label, charge, neutralLoss;
// format all the data recieved from the php script in a way that's easier to plot using D3
for (let i = 0; i < xValues.length; i++) {
label = labels[i];
charge = labelCharges[i];
neutralLoss = neutralLosses[i];
// compile labels from the label text, neutral losses, charge, and ionization mode. {"y17", "-H2O", 2, "+"} => [y₁₇-H₂O]⁺²
label = this.formatLabel(
label,
neutralLoss,
charge,
this.ionizationMode
);
// sum up all intensities to calculate the total ion current
TIC += yValues[i];
// format our processed data in a format which makes it easier to process using D3.
plotData.push({
mz: xValues[i],
intensity: yValues[i],
id: id[i],
x: xValues[i],
y: percentBasePeak[i],
percentBasePeak: percentBasePeak[i],
color: colors[i],
label: label,
width: widths[i] * options.annotation.width * 0.001,
massError: massError[i],
points: [],
});
}
// format all the data recieved from the php script in a way that's easier to plot using D3
for (let i = 0; i < xValues2.length; i++) {
label = labels2[i];
charge = labelCharges2[i];
// compile labels from the label text, neutral losses, charge, and ionization mode. {"y17", "-H2O", 2, "+"} => [y₁₇-H₂O]⁺²
label = this.formatLabel(label, "", charge, this.ionizationMode);
// sum up all intensities to calculate the total ion current
TIC2 += yValues2[i];
// format our processed data in a format which makes it easier to process using D3.
mirrorPlotData.push({
mz: xValues2[i],
intensity: yValues2[i],
id: id2[i],
x: xValues2[i],
y: percentBasePeak2[i],
percentBasePeak: percentBasePeak2[i],
color: colors2[i],
label: label,
width: widths2[i] * options.annotation.width * 0.001,
massError: [], //massError[i],
points: [],
});
}
// set transition duration depending on the number of spectral features to visualize
var duration = 1500 / plotData.length;
var duration2 = 1500 / mirrorPlotData.length;
// actually render the x- and y-axes
this.container
.selectAll("g.xAnnotation")
.attr("transform", "translate(0, " + options.annotation.height + ")")
.call(xAxis);
this.container.selectAll("g.yAnnotation").call(yAxis);
this.container2.selectAll("g.xAnnotation").call(xTopAxis);
this.container2.selectAll("g.yAnnotation").call(yAxis2);
// bind the plotData variable to potential svg rectangle elements.
barDataset = this.plotContainer.selectAll(".bar").data(plotData);
// bind the plotData variable to potential svg text elements.
labelDataset = this.plotContainer.selectAll(".barlabel").data(plotData);
// bind the plotData variable to potential svg path elements.
var lineDataset = this.plotContainer.selectAll(".line").data(plotData);
// bind the plotData variable to potential svg rectangle elements.
barDataset2 = this.plotContainer2
.selectAll(".bar")
.data(mirrorPlotData);
// bind the plotData variable to potential svg text elements.
labelDataset2 = this.plotContainer2
.selectAll(".barlabel")
.data(mirrorPlotData);
// bind the plotData variable to potential svg path elements.
var lineDataset2 = this.plotContainer2
.selectAll(".line")
.data(mirrorPlotData);
// bind the popup tooltip to the annotated mass spectrum.
this.plotContainer.call(that.tip);
// bind the popup tooltip to the annotated mass spectrum.
this.plotContainer2.call(that.tip);
// create potential bars
barDataset.enter().append("rect").attr("class", "bar");
// create potential bars
barDataset2.enter().append("rect").attr("class", "bar");
// remove unneeded bars
barDataset
.exit()
.attr("y", function () {
return y(-10);
})
.attr("x", function (d) {
return x(d3.min(xValues)) - d.width / 2;
})
.remove();
// remove unneeded bars
barDataset2
.exit()
.attr("y", function () {
return y(-10);
})
.attr("x", function (d) {
return x(d3.min(xValues2)) - d.width / 2;
})
.remove();
// draw spectral features and transition them from the origin. x coordinate is the spectral feature m/z, and y coordinate is the % relative abundance
barDataset
.attr("x", function () {
return x(0);
})
.attr("y", function () {
return y(0);
})
.transition()
.delay(function (d, i) {
return (duration / 2) * i;
})
.duration(1000)
.attr("width", function (d) {
return d.width;
})
.attr("x", function (d) {
return x(d.mz) - d.width / 2;
})
.attr("height", function (d) {
return options.annotation.height - y(d.percentBasePeak);
})
.attr("y", function (d) {
return y(d.percentBasePeak);
})
.attr("fill", function (d) {
return d.color;
})
.attr("opacity", 1)
.attr("align", "right");
// draw spectral features and transition them from the origin. x coordinate is the spectral feature m/z, and y coordinate is the % relative abundance
barDataset2
.attr("x", function () {
return x(0);
})
.attr("y", function () {
return y(0);
})
.transition()
.delay(function (d, i) {
return (duration2 / 2) * i;
})
.duration(1000)
.attr("width", function (d) {
return d.width;
})
.attr("x", function (d) {
return x(d.mz) - d.width / 2;
})
.attr("height", function (d) {
return options.annotation.height - y(d.percentBasePeak);
})
.attr("y", function () {
return y(0) - 100 + 1;
})
.attr("fill", function (d) {
return d.color;
})
.attr("opacity", 1)
.attr("align", "right");
// define zoom functionality on the x-axis
var zoomX = d3.behavior
.zoom()
.scaleExtent([1, 1000])
.x(x)
.on("zoom", function () {
// define translation object to move svg elements from original to zoomed position on the svg
var t = zoomX.translate();
var maxX = d3.max(x.range());
var tx = Math.max(
Math.min(0, t[0]),
options.annotation.width - maxX * zoomX.scale()
);
// update translation to new coordinates.
// zoomX.translate([ 0, 0 ]);
zoomX.translate([tx, t[1]]);
// calling the x axes here seems to be necessary to get them to scale correctly.
that.container.selectAll("g.xAnnotation").call(xAxis);
that.container2.selectAll("g.xAnnotation").call(xTopAxis);
that.fragmentContainer.selectAll("g.xAnnotation").call(fragxAxis);
// using the new scale, update the spectral peak positions
barDataset
.attr("x", function (d) {
return x(d.mz) - d.width / 2;
})
.attr("width", function (d) {
return (
d.width +
options.annotation.zoomFactor *
Math.log10(zoomX.scale()) *
d.width
);
});
// using the new scale, update the spectral peak positions
barDataset2
.attr("x", function (d) {
return x(d.mz) - d.width / 2;
})
.attr("width", function (d) {
return (
d.width +
options.annotation.zoomFactor *
Math.log10(zoomX.scale()) *
d.width
);
});
// using the new scale, update the annotation label positions
labelDataset.attr("x", function (d) {
return x(d.x);
});
// using the new scale, update the annotation label positions
labelDataset2.attr("x", function (d) {
return x(d.x);
});
// using the new scale, update the mass error circles
that.circleDataset.attr("cx", function (d) {
return x(d.mz);
});
// using the new scale, update the mass error circles
//circleDataset2.attr("cx", function(d) {
// return x(d.mz);
//});
// using the new scale, redraw the lines connecting the spectral peaks to annotation labels.
lineDataset.forEach(function (d) {
that.drawLine(x, y, d);
});
// using the new scale, redraw the lines connecting the spectral peaks to annotation labels.
lineDataset2.forEach(function (d) {
that.drawLine(x, y, d);
});
});
// define zoom functionality on the y-axis
var zoomY = d3.behavior
.zoom()
.scaleExtent([1, 1000])
.y(y)
.on("zoom", function () {
// define translation object to move svg elements from original to zoomed position on the svg
var t = zoomY.translate();
var maxY = d3.max(y.range());
var ty = Math.max(
Math.min(0, t[1]),
options.annotation.height - maxY * zoomY.scale()
);
// update translation to new coordinates.
zoomY.translate([t[0], ty]);
// make sure y domain keeps min at 0;
y.domain([0, y.domain()[1]]);
// calling the y axis here seems to be necessary to get them to scale correctly.
that.container.selectAll("g.yAnnotation").call(yAxis);
//this.container2.selectAll("g.yAnnotation").call(yAxis2);
// using the new scale, update the spectral peak rectangle heights
barDataset
.attr("y", function (d) {
return y(d.percentBasePeak);
})
.attr("height", function (d) {
var height = options.annotation.height - y(d.percentBasePeak);
if (height < 0) {
height = 0;
}
return height;
});
// using the new scale, update the annotation label positions
labelDataset.attr("y", function (d) {
return y(d.y + yMax * 0.005);
});
// using the new scale, redraw the lines connecting the spectral peaks to annotation labels.
lineDataset.forEach(function (d) {
that.drawLine(x, y, d);
});
});
// define zoom functionality on the y-axis
var zoomY2 = d3.behavior
.zoom()
.scaleExtent([1, 1000])
.y(y2)
.on("zoom", function () {
// define translation object to move svg elements from original to zoomed position on the svg
var t = zoomY2.translate();
var maxY = d3.max(y2.range());
var ty = Math.max(
Math.min(0, t[1]),
options.annotation.height - maxY * zoomY2.scale()
);
// update translation to new coordinates.
zoomY2.translate([t[0], ty]);
// make sure y domain keeps min at 0;
y2.domain([y2.domain()[0], 0]);
// calling the y axis here seems to be necessary to get them to scale correctly.
that.container2.selectAll("g.yAnnotation").call(yAxis2);
//this.container2.selectAll("g.yAnnotation").call(yAxis2);
// using the new scale, update the spectral peak rectangle heights
barDataset2
.attr("y", function () {
return y2(0);
})
.attr("height", function (d) {
var height = -y2(d.percentBasePeak);
//var height = options.annotation.height - y2(d.percentBasePeak);
if (height < 0) {
height = 0;
}
return height;
});
// using the new scale, update the annotation label positions
labelDataset2.attr("y", function (d) {
// return (y(0) - 170 + options.annotation.height - y(d.percentBasePeak)) ;
//
return y2(0) - y2(d.percentBasePeak + yMax * 0.005) + 12;
});
// using the new scale, redraw the lines connecting the spectral peaks to annotation labels.
lineDataset2.forEach(function (d) {
that.drawLine(x, y, d);
});
});
// bind a mouseenter event to the rendered spectral peak to highlight the spectral feature and show a tooltip.
barDataset.on("mouseenter", function (d) {
// highlight the peak that is being hovered over using a black stroke
d3.select(this).style("stroke", function () {
return "black";
});
// define the inner HTML of the tooltip