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index.js
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index.js
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import RBF from './rbf.js';
var state = { // Object storing the state of the charts and several properties
svg: null,
liveUpdate: true
}
var data_dict = {}; // Object storing the data per each signal
var color_dict = { // Object storing predefined colors for each signal
'FPz': '#808080',
'F3': '#2e8b57',
'Fz': '#7f0000',
'F4': '#808000',
'FC5': '#483d8b',
'FC1': '#008000',
'FC2': '#008080',
'FC6': '#4682b4',
'T7': '#d2691e',
'C3': '#00008b',
'Cz': '#32cd32',
'C4': '#daa520',
'T8': '#800080',
'CP5': '#b03060',
'CP1': '#d2b48c',
'CP2': '#ff0000',
'CP6': '#00ff00',
'P7': '#9400d3',
'P3': '#00fa9a',
'Pz': '#dc143c',
'P4': '#00ffff',
'P8': '#0000ff',
'PO7': '#adff2f',
'PO3': '#da70d6',
'POz': '#d8bfd8',
'PO4': '#ff00ff',
'PO8': '#1e90ff',
'O1': '#fa8072',
'Oz': '#ffff54',
'O2': '#87ceeb',
'EOG1': '#ff1493',
'EOG2': '#7b68ee',
};
// Colors for the rectangle legend [blue, light_blue, green, yellow, red]
var legend_colors = ["#0400ff", "#00f7ff", "#00ff1a", "#fbff00", "#ff0000"];
const samplingFrequency = 128
// Create legend rectangle as a linear gradient
var legend = d3.select('#legend')
.append('svg')
.attr('width', 200)
.attr('height', 360);
var grad = legend.append('defs')
.append('linearGradient')
.attr('id', 'grad')
.attr('x1', '0%')
.attr('x2', '0%')
.attr('y1', '0%')
.attr('y2', '100%');
grad.selectAll('stop')
.data(legend_colors)
.enter()
.append('stop')
.style('stop-color', function (d) { return d; })
.attr('offset', function (d, i) {
return 100 * (i / (legend_colors.length - 1)) + '%';
})
legend.append('rect')
.attr('x', 10)
.attr('y', 10)
.attr('width', 40)
.attr('height', 340)
.style('fill', 'url(#grad)');
// Legend axis title
legend.append("text")
.attr("transform", "rotate(-90)")
.attr("y", 100)
.attr("x", -250)
.attr("font-family", "'Gill Sans MT', sans-serif")
.text("Average amplitude value");
legend.append("g")
.attr("transform", "translate(50, 10)")
.attr("height", 340);
// Initialize tooltip that shows on electrode hover
var tooltip = d3.select("body")
.append("div")
.attr("id", "tooltip")
.style("position", "absolute")
.style("visibility", "hidden");
function showTooltip(label, event) {
d3.select("#tooltip")
.html(label)
.style("top", (event.pageY - 50) + "px").style("left", (event.pageX + 20) + "px")
.style("background-color", "rgba(114, 114, 114, 0.55)")
.style("border-radius", "5px")
.style("padding", "10px 10px 10px 10px")
.style("color", "white")
}
// Function that builds the scalp map part of our visulization
// data: The eeg data containing the values for each electrode at each time step
// locations: The x,y coordinates of each of the electrodes and their labels
function ScalpMapChart(data, locations) {
// Find the min and max values of the entire dataset
// used for the interpolation range and legend axis
var dataset_max = -Number.MAX_VALUE;
var dataset_min = Number.MAX_VALUE;
for (let i = 0; i < data.length; i++) {
data_dict[data[i].name] = data[i].data;
if (data[i].name !== 'time') {
var curr_max = Math.max(...data[i].data);
var curr_min = Math.min(...data[i].data);
if (curr_max > dataset_max) {
dataset_max = curr_max;
}
if (curr_min < dataset_min) {
dataset_min = curr_min;
}
}
}
// Store min/max values in state object
state.dataset_max = dataset_max;
state.dataset_min = dataset_min;
var grid = d3.select("#grid")
.append("svg");
grid.attr("height", 344)
.attr("width", 344);
let mask_r = Math.pow(43, 2);
// Build an 85x85 grid with rectangles
// Ids of the rectangles in the form #cellx_y
// (with x and y being the coordinates of the square 0,0 top-left)
for (let i = 0; i < 85; i++) {
for (let j = 0; j < 85; j++) {
// Mask area outside scalp outline (save on computations too)
let dist = Math.pow((42 - i), 2) + Math.pow((42 - j), 2)
if (dist <= mask_r) {
let name = "cell" + i + "_" + j;
grid.append("rect")
.attr("id", name)
.attr("width", 4)
.attr("height", 4)
.attr("x", i * 4)
.attr("y", j * 4);
}
}
}
var size = 170;
var scale_up = 2;
// Scalp outline
var map = grid.append("circle")
.attr("id", "scalp_map")
.attr("cx", size / 2 * scale_up)
.attr("cy", size / 2 * scale_up)
.attr("r", size / 2 * scale_up)
.attr("fill", "none")
.attr("stroke", "black")
.attr("stroke-width", 2);
// Scalp mask
grid.append("circle")
.attr("cx", size / 2 * scale_up)
.attr("cy", size / 2 * scale_up)
.attr("r", 173)
.attr("fill", "none")
.attr("stroke", "white")
.attr("stroke-width", 4);
// Array to contain all the electrodes
// Stores their label, (x,y) coordinates, amplitude (z) values and
// a boolean if the electrode is selected
var electrodes = [];
// Store the electrodes in the state
state.electrodes = electrodes;
// Locations of the electrodes from the .json file
var loc = locations;
var circles = [];
const mult = 4;
// Loop to add the electrode locations and amplitude values
for (let i = 0; i < loc.length; i++) {
// Adjust the xy coordinates from json to have the origin on the top-left
electrodes.push({
"name": loc[i].label,
"x": loc[i].x,
"y": loc[i].y,
"z": data.find(x => x.name === loc[i].label).data[0],
"checked": true,
})
// Label rectangles as #cellX_Y (X,Y coordinates on scalp)
let id = "#cell" + loc[i].x + "_" + loc[i].y;
d3.selectAll(id).style("fill", "black"); //White: enabled, Blacl: disabled
// Add circles in electrode locations
var circle = grid.append("circle")
.attr("id", "circle_" + loc[i].label)
.attr("cx", loc[i].x * mult + 1)
.attr("cy", loc[i].y * mult + 1)
.attr("r", 0)
.attr("fill", "white")
.attr("stroke", "black")
.attr("stroke-width", 2)
.on("click", () => {
// On click disable the corresponding channel
var checkbox = document.getElementById(loc[i].label);
checkbox.checked = !checkbox.checked;
d3.select("#circle_" + loc[i].label).attr("fill", checkbox.checked ? "white" : "black");
// Update the scalp map and the EEG plots
update(state.ranges);
updateEEG(electrodes.filter(d => d.checked).map(d => d.name));
var id = loc[i].label;
// Show appropriate name and value on tooltip
var msg = "";
if (checkbox.checked) {
msg = id + "<br>" + "Value: " + state.electrodes.find(x => x.name === id).z.toFixed(3);
state.svg.selectChild("#" + id + "_line").style("filter", "url(#glow)")
.attr("stroke-width", 3);
} else {
msg = id;
}
showTooltip(msg, event);
});
circles.push(circle);
}
// Initialize brushed at left-most point
update([0, 4000]);
state.ranges = [0, 4000];
// Compute the RBF diffusion
update_z(electrodes);
grid.on("mouseover", (event) => {
const [xm, ym] = d3.pointer(event);
circles.forEach((circle) => {
var dist = Math.pow((xm - circle.attr("cx")), 2) + Math.pow((ym - circle.attr("cy")), 2);
// Resize circle depending on the distance from pointer
circle.attr("r", Math.min(Math.max(20 - dist / 500, 0), 10));
circle.on("mouseover", function () {
d3.select("#tooltip").style("visibility", "visible");
var id = this.id.slice(7);
// Show the tooltip on hover
var msg = "";
if (document.getElementById(id).checked) {
msg = id + "<br>" + "Value: " + state.electrodes.find(x => x.name === id).z.toFixed(3);
} else {
msg = id;
}
// Show channel tooltip and highlight the psd estimate
d3.select("#tooltip").attr("class", "animate_in");
showTooltip(msg, event);
state.svg.selectChild("#" + id + "_line").style("filter", "url(#glow)")
.attr("stroke-width", 3);
});
circle.on("mouseout", function () {
// Remove tooltip and highlighting
d3.select("#tooltip").attr("class", "animate_out");
state.svg.selectChild("#" + this.id.slice(7) + "_line").style("filter", null)
.attr("stroke-width", 1, 5);
});
})
});
// Scale down circles
grid.on("pointerleave", () => {
circles.forEach((circle) => {
circle.attr("r", 0);
})
});
}
// Function that updates the interpolation on the scalp map based on a new selection
function update_z(electrodes) {
var points_xy = [];
var z_values = [];
for (let i = 0; i < electrodes.length; i++) {
if (electrodes[i].checked) {
points_xy.push([electrodes[i].x, electrodes[i].y]);
z_values.push(electrodes[i].z);
}
}
var rbf = RBF(points_xy, z_values); // Radial basis intepolation of the amplitute values
var interpolated_z = [];
var interpolated_xy = [];
// Store the interpolated amplitute values for every location in the 85x85 grid
for (let i = 0; i < 85; i++) {
for (let j = 0; j < 85; j++) {
interpolated_z.push(rbf([i, j]));
interpolated_xy.push([i, j]);
}
}
// Generate an appropriate color based on the interpolated values
interpolateRGB(interpolated_z, interpolated_xy);
}
// Function to interpolateRGB values between [min,max] for selected amplitude values
function interpolateRGB(value_arr, coord_arr) {
//blue, light_blue, green, yellow, red
var colors = ["#ff0000", "#fbff00", "#00ff1a", "#00f7ff", "#0400ff"]
// Decrease min/max values since the selection is averaged
// Higher min/max reesults in a lower details with color contrast (only 5 are used)
var max = state.dataset_max / 10;
var min = state.dataset_min / 10;
//Build domain values based on the min/max values
var increment = (Math.abs(min) + Math.abs(max)) / (colors.length - 1);
var domain = [min, min + increment, 0, increment, max];
// Retrieving colors based on their value in the specified domain
var getColor = d3.scaleLinear()
.domain(domain)
.range(colors);
//Assign interpolatedRGB values to every sqaure in the grid
for (var i = 0; i < value_arr.length; i++) {
let id = "#cell" + coord_arr[i][0] + "_" + coord_arr[i][1];
d3.selectAll(id).attr("fill", getColor(value_arr[i]));
}
//Update legend values according to the input amplitude values
var scale = d3.scaleLinear()
.domain(domain.reverse())
.range([0, 100]);
// Fill up legend ticks
var ticks = scale.ticks();
ticks.push(-40, -50);
var y_axis = d3.axisRight()
.scale(scale)
.tickFormat(d3.format(",.0f"))
.tickValues(ticks);
legend.select("g").call(y_axis).attr("font-family", "'Gill Sans MT', sans-serif");
legend.select("g").call(y_axis).select(".domain").attr("d", "M 6 0 H 0 V 340 H 6"); //Extend legend axis line
}
// Function that creates the PSD plot element of our solution
function PSDChart(data) {
state.width = 700;
state.height = 480;
state.psds = [];
state.psd_clicked = false;
state.psd_info = {};
state.maxval = 0;
var margin = { top: 20, right: 30, bottom: 30, left: 60 };
state.margin = margin;
var svg = d3.select("#chart2")
.append("svg")
.attr("width", state.width + margin.left + margin.right)
.attr("height", state.height + margin.top + margin.bottom)
.append("g")
.attr("transform",
"translate(" + margin.left + "," + margin.top + ")");
state.legend = document.createElement('div');
document.getElementById("chart2").appendChild(state.legend);
state.svg = svg;
var data_dict = {};
for (var i = 0; i < data.length; i++) {
data_dict[data[i].name] = data[i].data;
}
state.data_length = data_dict['time'].length;
state.f = 128;
const value_names = Object.keys(data_dict);
state.value_names = value_names;
// Create and populate checkboxes for storing active channel data
var select = document.getElementById('selector');
for (var i = 1; i < value_names.length; i++) {
var div = document.createElement('div');
var checkbox = document.createElement('input');
checkbox.setAttribute('type', 'checkbox');
checkbox.setAttribute('id', value_names[i]);
checkbox.setAttribute('name', value_names[i]);
checkbox.setAttribute('onclick', 'update()');
var label = document.createElement('label');
label.setAttribute('for', value_names[i]);
label.innerHTML = value_names[i];
div.appendChild(checkbox);
div.appendChild(label);
select.appendChild(div);
// Enable all plots by default
checkbox.checked = true;
}
}
// Function that updates the state of the solution based on the current selection
// range_vals: selected brushed time interval
function update(range_vals) {
if (range_vals === undefined) {
range_vals = state.ranges;
}
// Get value ranges to calculate correct ranges for PSD
state.ranges = range_vals;
range_vals = range_vals.map(r => parseInt((r / 1000) * samplingFrequency));
// Reset the psd graph
state.svg.selectAll("*:not(line)").remove();
var checked = [];
for (var i = 1; i < state.value_names.length; i++) {
var check = document.getElementById(state.value_names[i]);
var electrode = state.electrodes.find(x => x.name === state.value_names[i]);
var id = "#cell" + electrode.x + "_" + electrode.y; // Used to update the state of the electrodes
if (check.checked) {
checked.push(state.value_names[i]);
d3.select(id).style("fill", "white"); // electrode is checked, fill in white
state.electrodes.find(x => x.name === state.value_names[i]).checked = true;
} else {
d3.select(id).style("fill", "black"); // electrode is unchecked, fill in black
state.electrodes.find(x => x.name === state.value_names[i]).checked = false;
}
}
state.psds = {};
var xy = [];
for (var i = 0; i < checked.length; i++) { // Loop over selected electrodes
var ranged_data = []
var sum = 0;
for (var j = parseInt(range_vals[0]); j < Math.min(parseInt(range_vals[1]), state.data_length); j++) {
var curr = parseFloat(data_dict[checked[i]][j]);
ranged_data.push(curr);
sum = sum + curr;
}
// Update electrode amplitudes based on the average of the brushed selection for each one
state.electrodes.find(x => x.name === checked[i]).z = sum / ranged_data.length
try {
// Get PSD estimates using the Welch method
var psd = bci.welch(ranged_data, state.f);
state.psds[checked[i]] = psd;
state.maxval = Math.max(state.maxval, d3.max(psd.estimates));
xy = plot(psd.frequencies, psd.estimates, state.svg, checked[i]);
} catch (error) {
// If the estimates cannot be calculated, display a message
state.svg.append("text")
.attr("y", state.height / 2)
.attr("x", state.width / 2)
.text("Could not compute PSD estimates. Select a larger portion of data.")
.attr("font-family", "'Gill Sans MT', sans-serif")
.style("text-anchor", "middle");
}
}
addScale(xy[0], xy[1], state.svg, 'Power spectral densities');
// Update the scalp map interpolation
update_z(state.electrodes);
}
// Function that adds the scale on the PSD plot
function addScale(x, y, svg, title) {
svg.append("g")
.attr("transform", "translate(0," + state.height + ")")
.call(d3.axisBottom(x)).attr("font-family", "'Gill Sans MT', sans-serif")
// y-axis label
svg.append("text")
.attr("transform", "rotate(-90)")
.attr("y", -30)
.attr("x", -state.height / 2)
.attr("font-family", "'Gill Sans MT', sans-serif")
.text("dB");
// x-axis label
svg.append("text")
.attr("y", state.height + 30)
.attr("x", state.width / 2)
.attr("font-family", "'Gill Sans MT', sans-serif")
.text("Hz");
svg.append("g")
.call(d3.axisLeft(y)).attr("font-family", "'Gill Sans MT', sans-serif");
svg.append("text")
.attr("x", (state.width / 2))
.attr("y", 0)
.attr("text-anchor", "middle")
.style("font-size", "20px")
.attr("font-family", "'Gill Sans MT', sans-serif")
.text(title);
}
function plot(xs, ys, svg, line_id) {
var x = d3.scaleLinear()
.domain(d3.extent(xs))
.range([0, state.width]);
state.psd_x = x;
// Initialized here for speed; can be initialized elsewhere for more speed
state.psd_inv_x = d3.scaleLinear()
.domain([0, state.width])
.range(d3.extent(xs));
state.psd_xs = xs;
// Add Y axis
var y = d3.scaleLog()
.domain([1 / 10000, state.maxval])
.range([state.height, 0]);
var data = [];
for (var i = 0; i < xs.length; i++) {
data.push({ t: xs[i], d: ys[i] });
}
//Container for the gradients
var defs = svg.append("defs");
//Filter for the outside glow effect line highlights
var filter = defs.append("filter")
.attr("id", "glow");
filter.append("feGaussianBlur")
.attr("stdDeviation", "4.5")
.attr("result", "coloredBlur");
var feMerge = filter.append("feMerge");
feMerge.append("feMergeNode")
.attr("in", "coloredBlur");
feMerge.append("feMergeNode")
.attr("in", "SourceGraphic");
// Add the plot lines
svg.append("path")
.datum(data)
.attr("id", line_id + "_line")
.attr("fill", "none")
.attr("stroke", color_dict[line_id])
.attr("stroke-width", 0.5)
.attr("d", d3.line()
.x(d => x(d.t))
.y(d => y(d.d))
).on("mouseenter", function () {
d3.select(this).style("filter", "url(#glow)") //Add the glow effect on line hover
.attr("stroke-width", 3);
d3.select("#circle_" + line_id).attr("r", 10); //Show the respective electrode on the scalp map
})
.on("mouseleave", function () {
d3.select(this).style("filter", null) //Remove the glow effect on mouse leave
.attr("stroke-width", 0.5);
d3.select("#circle_" + line_id).attr("r", 0); //Hide the electrode mark on mouse leave
})
return [x, y];
}
function addBrush(xScale, svg, width, height, margin) {
// BRUSHY BRUSHY
// Initializes the brush
const brush_size = 4000
function brushed(event) {
// Called when brush changes
const selection = event.selection;
if (selection === null) {
console.log(`no selection`);
} else {
// Get the newest brush location
var selectionRange = selection.map(xScale.invert).map(d => parseFloat(d) - brush_size);
// Disabling live update, only shows the effect of the selection on mouse-release
if (state.liveUpdate || (!state.live && event.type === 'end')) {
if (state.svg) {
// Update PSD and scalp map based on selection
update(selectionRange)
}
}
}
}
function beforebrushstarted(event) {
let x = xScale;
const dx = x(brush_size) - x(0); // Use a fixed width when recentering.
const [[cx]] = d3.pointers(event);
// Get locations pointer_x - brush_size / 2 and pointer_x + brush_size / 2
var [x0, x1] = [cx - dx / 2, cx + dx / 2];
// If brush is too far left, bring it to beginning of the axis
if (x0 - margin.left <= 0) {
[x0, x1] = [margin.left, margin.left + dx];
}
const [X0, X1] = x.range();
d3.select(this.parentNode)
.call(brush.move, x1 > X1 ? [X1 - dx, X1]
: x0 < X0 ? [X0, X0 + dx]
: [x0, x1]);
}
const brush = d3.brushX()
.extent([[margin.left, margin.top], [width + margin.right + margin.left, height + margin.top]])
.on("start brush end", brushed);
// Set brush to the initial position
svg.append("g")
.call(brush)
.call(brush.move, [5000, 5000 + brush_size].map(xScale))
.call(g => g.select(".overlay")
.datum({ type: "selection" })
.on("mousedown touchstart", beforebrushstarted));
}
// Get data groupped as a map with name => [(time, data)...]
const getGrouped = data => new Map(data.columns
.filter(c => c !== 'Time')
.map(c => [c,
data.map(v => (
{ 'time': v['Time'], 'value': v[c] }))]))
// Get extents per signal
const getExtents = data => d3.extent(data.columns
.filter(c => c !== 'Time')
.map(c => [c,
data.map(v => v[c])]).flatMap(e => d3.extent(e[1].map(d => parseFloat(d) / 5))))
// Initialize the eeg plots for each electrode in the data
const ChannelsChart = (data, eventData) => {
const grouped = getGrouped(data)
const extents = getExtents(data)
const time = d3.map(data, d => d.Time)
var sampler = fc.largestTriangleThreeBucket()
.x(function (d) { return d.time; })
.y(function (d) { return d.value; })
.bucketSize(10);
for (let [key, value] of grouped) {
grouped.set(key, sampler(value));
}
// Run the sampler
state.eeg = {}
// Dimensions:
const height = 800;
const width = 1200;
const margin = {
top: 60,
left: 50,
right: 50,
bottom: 50
}
const padding = 0;
const doublePadding = padding * 2;
state.eeg.height = height;
state.eeg.padding = padding;
state.eeg.margin = margin;
const plotHeight = (height - doublePadding) / grouped.size - padding;
const plotWidth = width - padding * 2;
//Scales:
const xScale = d3.scaleLinear()
.domain(d3.extent(data, d => d.Time))
.range([0, plotWidth + margin.right]);
state.xScale = xScale;
// const y_extent = d3.extent(data, d => d["Cz"])[1]
// Extent is now the max extent of all signals
const yScale = d3.scaleLinear()
.domain(extents)
.range([plotHeight, 0]);
state.yScale = yScale;
const svg = d3.select("#chart1")
.append("svg")
.attr("width", margin.left + width + margin.right)
.attr("height", margin.top + height + margin.bottom + (padding * grouped.size));
// y-axis label
svg.append("text")
.attr("transform", "rotate(-90)")
.attr("y", 15)
.attr("x", -height / 2 - 100)
.text("Electrode Labels")
.attr("font-family", "'Gill Sans MT', sans-serif");
// x-axis label
svg.append("text")
.attr("y", height + 100)
.attr("x", width / 2)
.attr("font-family", "'Gill Sans MT', sans-serif")
.text("Time(ms)");
// Title
svg.append("text")
.attr("y", 50)
.attr("x", width / 2)
.attr("font-family", "'Gill Sans MT', sans-serif")
.text("EEG plots per electrode");
// Plot events
eventData.forEach(r => {
// latency is the sample number, not the time
const eventStart = parseInt(r.latency / samplingFrequency) * 1000
const eventLength = 200
const rectWidth = xScale(eventLength)
const fillColor = r.type == 'square' ? 'Khaki' : 'DarkSeaGreen'
svg
.append("rect")
.attr("width", rectWidth)
.attr("height", height)
.attr("transform", `translate(${xScale(eventStart) + margin.left}, ${margin.top})`)
.attr("fill", fillColor)
})
const g = svg.append("g")
.attr("transform", "translate(" + [margin.left, margin.top] + ")");
// Place plots:
const plots = g.selectAll(null)
.data(grouped)
.enter()
.append("g")
.attr("transform", function (d, i) {
return "translate(" + [padding, i * (doublePadding + plotHeight) + padding] + ")";
})
// Plot line if needed:
plots.append("path")
.attr("d", function (d) {
return d3.line()
.x(d => xScale(d.time))
.y(d => yScale(d.value))
(d[1])
})
.attr("stroke", "#000000")
.attr("fill", "none")
// Plot axes
// Lower x axis
svg.append("g")
.attr("transform", "translate(" + [margin.left, grouped.size * plotHeight + margin.top] + ")")
.call(d3.axisBottom(xScale)
// .ticks(4)
).attr("font-family", "'Gill Sans MT', sans-serif");
// y axis
const activeNames = d3.map(plots.data(), d => d[0])
plots.each((d, i) => svg.append("g").attr('class', `yaxis`)
.attr("transform", "translate(" + [margin.left, i * plotHeight + margin.top] + ")")
.call(d3.axisLeft(yScale)
.ticks(1).tickFormat(activeNames[i])
).attr("font-family", "'Gill Sans MT', sans-serif")
.selectAll("text").style("stroke", color_dict[activeNames[i]]));
addBrush(xScale, svg, width, height, margin);
state.plots = plots;
state.eeg.svg = svg;
return svg.node()
}
function updateEEG(active) {
// Update the EEG chart based on active signals
// Calculate new plot height of each signal
const plotHeight = (state.eeg.height - state.eeg.padding * 2) / active.length - state.eeg.padding;
state.yScale.range([plotHeight, 0]);
// Reset all axes
state.eeg.svg.selectAll(".yaxis").remove();
// Add new axes
active.forEach((n, i) => state.eeg.svg.append("g").attr('class', `yaxis`)
.attr("transform", "translate(" + [state.eeg.margin.left, i * plotHeight + state.eeg.margin.top] + ")")
.call(d3.axisLeft(state.yScale)
.ticks(1).tickFormat(n)
).attr("font-family", "'Gill Sans MT', sans-serif")
.selectAll("text").style("stroke", color_dict[n]));
// Remove disabled plots
state.plots.selectAll("path").filter(c => !active.includes(c[0])).attr('d', '')
// Update chart by adding active plots
state.plots.selectAll("path").filter(c => active.includes(c[0]))
.attr("d", function (d) {
return d3.line()
.x(d => state.xScale(d.time))
.y(d => state.yScale(d.value))
(d[1])
});
state.plots.filter(c => active.includes(c[0]))
.attr("transform", function (d, i) {
return "translate(" + [state.eeg.padding, i * (state.eeg.padding * 2 + plotHeight) + state.eeg.padding] + ")";
})
}
// Toggles the live update functionality
function toggleLiveUpdate() {
var checkBox = document.getElementById("liveUpdate");
state.liveUpdate = checkBox.checked == true ? true : false;
}
const formatDataForPSD = (eegData) => eegData.columns
.map(c => ({
name: c == 'Time' ? 'time' : c,
data: eegData.map(v => parseFloat(v[c]))
}))
// Unimplemented embedding for an ERP plot
const formatERPData = (eegData, eventData) => {
// Formats data for the events ERP events
const erpTimeIdx = [...Array(128).keys()]
const template = { "Time": 0, "FPz": 0, "EOG1": 0, "F3": 0, "Fz": 0, "F4": 0, "EOG2": 0, "FC5": 0, "FC1": 0, "FC2": 0, "FC6": 0, "T7": 0, "C3": 0, "C4": 0, "Cz": 0, "T8": 0, "CP5": 0, "CP1": 0, "CP2": 0, "CP6": 0, "P7": 0, "P3": 0, "Pz": 0, "P4": 0, "P8": 0, "PO7": 0, "PO3": 0, "POz": 0, "PO4": 0, "PO8": 0, "O1": 0, "Oz": 0, "O2": 0 }
let erpObjectAcc = structuredClone(template)
const erpData =
erpTimeIdx
.map(erpTimeId =>
eventData
.filter(e => e.type == `square`)
.map(e => parseInt(e.latency))
.map(latencyId => eegData.slice(latencyId - 13, latencyId + 115))
.map(e => e.map((eegForErpEvent, i) => ({ 'index': i, data: eegForErpEvent })))
.flat()
.filter(i => i.index == erpTimeId)
)
.map(i => {
erpObjectAcc = structuredClone(template)
return i.reduce((accumulator, currentValue) => {
Object.entries(erpObjectAcc)
.forEach(e => accumulator[e[0]] = (parseFloat(accumulator[e[0]]) + parseFloat(currentValue.data[e[0]])) / 2)
return accumulator
}, erpObjectAcc)
}
)
return erpData
}
// Load datasets and tun code
d3.csv("/data/eeg-lab-example-yes-transpose-all.csv").then(eegData =>
d3.csv('data/events-all.csv').then(eventData => {
ChannelsChart(eegData, eventData)
const eegDataPSDFormat = formatDataForPSD(eegData)
PSDChart(eegDataPSDFormat);
d3.json("/data/locations.json").then(locations =>
ScalpMapChart(eegDataPSDFormat, locations)
);
})
)
window.onload = function () {
document.getElementById("liveUpdate").onclick = toggleLiveUpdate
}