Remove tuning web files
This commit is contained in:
Ryan Brott
2
TeamCode/src/main/assets/tuning/.gitignore
vendored
2
TeamCode/src/main/assets/tuning/.gitignore
vendored
@ -1,2 +0,0 @@
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latest.json
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*.py
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@ -1,264 +0,0 @@
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// TODO: time-interpolate data
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// https://en.wikipedia.org/wiki/Kahan_summation_algorithm#The_algorithm
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function kahanSum(xs) {
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let sum = 0;
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let c = 0;
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for (let i = 0; i < xs.length; i++) {
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const y = xs[i] - c;
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const t = sum + y;
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c = (t - sum) - y;
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sum = t;
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}
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return sum;
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}
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// https://en.wikipedia.org/wiki/Simple_linear_regression#Simple_linear_regression_without_the_intercept_term_(single_regressor)
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function fitLinearNoIntercept(xs, ys) {
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return kahanSum(
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xs.map((x, i) => x * ys[i])
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) / kahanSum(
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xs.map(x => x * x)
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);
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}
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function fitLinearWithScaling(xs, ys) {
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const xOffset = xs.reduce((a, b) => a + b, 0) / xs.length;
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const yOffset = ys.reduce((a, b) => a + b, 0) / ys.length;
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const xScale = xs.reduce((acc, x) => Math.max(acc, Math.abs(x - xOffset)), 0);
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const yScale = ys.reduce((acc, y) => Math.max(acc, Math.abs(y - yOffset)), 0);
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const data = xs.map((x, i) => [(x - xOffset) / xScale, (ys[i] - yOffset) / yScale]);
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const result = regression.linear(data);
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const [m, b] = result.equation;
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return [m * yScale / xScale, b * yScale - m * xOffset * yScale / xScale + yOffset];
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}
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// no output for first pair
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function numDerivOnline(xs, ys) {
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if (xs.length !== ys.length) {
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throw new Error(`${xs.length} !== ${ys.length}`);
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}
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return ys
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.slice(1)
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.map((y, i) => (y - ys[i]) / (xs[i + 1] - xs[i]));
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}
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// no output for first or last pair
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function numDerivOffline(xs, ys) {
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return ys
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.slice(2)
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.map((y, i) => (y - ys[i]) / (xs[i + 2] - xs[i]));
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}
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const CPS_STEP = 0x10000;
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function inverseOverflow(input, estimate) {
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// convert to uint16
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let real = input & 0xffff;
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// initial, modulo-based correction: it can recover the remainder of 5 of the upper 16 bits
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// because the velocity is always a multiple of 20 cps due to Expansion Hub's 50ms measurement window
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real += ((real % 20) / 4) * CPS_STEP;
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// estimate-based correction: it finds the nearest multiple of 5 to correct the upper bits by
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real += Math.round((estimate - real) / (5 * CPS_STEP)) * 5 * CPS_STEP;
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return real;
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}
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// no output for first or last pair
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function fixVels(ts, xs, vs) {
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if (ts.length !== xs.length || ts.length !== vs.length) {
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throw new Error();
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}
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return numDerivOffline(ts, xs).map((est, i) => inverseOverflow(vs[i + 1], est));
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}
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// see https://github.com/FIRST-Tech-Challenge/FtcRobotController/issues/617
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function fixAngVels(vs) {
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if (vs.length === 0) {
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return [];
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}
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let offset = 0;
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lastV = vs[0];
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const vsFixed = [lastV];
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for (let i = 1; i < vs.length; i++) {
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if (Math.abs(vs[i] - lastV) > Math.PI) {
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offset -= Math.sign(vs[i] - lastV) * 2 * Math.PI;
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}
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vsFixed.push(offset + vs[i]);
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lastV = vs[i];
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}
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return vsFixed;
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}
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// data comes in pairs
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function newLinearRegressionChart(container, xs, ys, options, onChange) {
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if (xs.length !== ys.length) {
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throw new Error(`${xs.length} !== ${ys.length}`);
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}
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// cribbed from https://plotly.com/javascript/plotlyjs-events/#select-event
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const color = '#777';
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const colorLight = '#bbb';
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let mask = xs.map(() => true);
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function fit(xs, ys) {
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return options.noIntercept ? [fitLinearNoIntercept(xs, ys), 0] : fitLinearWithScaling(xs, ys);
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}
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const [m, b] = fit(xs, ys);
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if (onChange) onChange(m, b);
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const minX = xs.reduce((a, b) => Math.min(a, b), 0);
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const maxX = xs.reduce((a, b) => Math.max(a, b), 0);
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const chartDiv = document.createElement('div');
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const width = Math.max(0, window.innerWidth - 50);
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Plotly.newPlot(chartDiv, [{
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type: 'scatter',
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mode: 'markers',
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x: xs,
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y: ys,
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name: 'Samples',
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// markers seem to respond to selection
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marker: {color: mask.map(b => b ? color : colorLight), size: 5},
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}, {
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type: 'scatter',
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mode: 'lines',
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x: [minX, maxX],
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y: [m * minX + b, m * maxX + b],
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name: 'Regression Line',
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line: {color: 'red'}
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}], {
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title: options.title || '',
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// sets the starting tool from the modebar
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dragmode: 'select',
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showlegend: false,
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hovermode: false,
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width,
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height: width * 9 / 16,
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}, {
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// 'select2d', 'zoom2d', 'pan2d', 'lasso2d', 'zoomIn2d', 'zoomOut2d', 'autoScale2d', 'resetScale2d' left
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modeBarButtonsToRemove: [],
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});
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const results = document.createElement('p');
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function setResultText(m, b) {
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results.innerText = `${options.slope || 'slope'}: ${m}, ${options.intercept || 'y-intercept'}: ${b}`;
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}
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setResultText(m, b);
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function updatePlot() {
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Plotly.restyle(chartDiv, 'marker.color', [
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mask.map(b => b ? color : colorLight)
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], [0]);
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const [m, b] = fit(
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xs.filter((_, i) => mask[i]),
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ys.filter((_, i) => mask[i]),
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);
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setResultText(m, b);
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if (onChange) onChange(m, b);
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const minX = xs.reduce((a, b) => Math.min(a, b));
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const maxX = xs.reduce((a, b) => Math.max(a, b));
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Plotly.restyle(chartDiv, {
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x: [[minX, maxX]],
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y: [[m * minX + b, m * maxX + b]],
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}, [1]);
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}
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let pendingSelection = null;
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chartDiv.on('plotly_selected', function(eventData) {
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if (eventData === undefined) {
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return;
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}
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pendingSelection = eventData;
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});
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function applyPendingSelection(b) {
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if (pendingSelection === null) return false;
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for (const pt of pendingSelection.points) {
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mask[pt.pointIndex] = b;
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}
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Plotly.restyle(chartDiv, 'selectedpoints', [null], [0]);
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pendingSelection = null;
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return true;
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}
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const includeButton = document.createElement('button');
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includeButton.innerText = '[i]nclude';
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includeButton.addEventListener('click', () => {
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if (!applyPendingSelection(true)) return;
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updatePlot();
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});
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const excludeButton = document.createElement('button');
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excludeButton.innerText = '[e]xclude';
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excludeButton.addEventListener('click', () => {
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if (!applyPendingSelection(false)) return;
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updatePlot();
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});
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document.addEventListener('keydown', e => {
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if (e.key === 'i') {
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if (!applyPendingSelection(true)) return;
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updatePlot();
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} else if (e.key === 'e') {
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if (!applyPendingSelection(false)) return;
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updatePlot();
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}
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});
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while (container.firstChild) {
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container.removeChild(container.firstChild);
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}
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const buttons = document.createElement('div');
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buttons.appendChild(includeButton);
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buttons.appendChild(excludeButton);
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const bar = document.createElement('div');
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bar.setAttribute('class', 'bar');
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bar.appendChild(buttons);
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bar.appendChild(results);
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container.appendChild(bar);
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container.appendChild(chartDiv);
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return function(xsNew, ysNew) {
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if (xsNew.length !== ysNew.length) {
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throw new Error(`${xsNew.length} !== ${ysNew.length}`);
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}
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xs = xsNew;
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ys = ysNew;
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mask = xs.map(() => true);
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Plotly.restyle(chartDiv, {
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x: [xs],
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y: [ys],
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}, [0]);
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updatePlot();
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};
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}
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@ -1,183 +0,0 @@
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<!doctype html>
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<html>
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<head>
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<title>RR Dead Wheel Angular Ramp Regression</title>
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<style>
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body {
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font-family: Arial, Helvetica, sans-serif;
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}
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.content {
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margin: auto;
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}
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header {
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max-width: 600px;
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margin: auto;
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}
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.bar {
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display: flex;
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justify-content: space-between;
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align-items: center;
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}
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fieldset {
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display: flex;
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justify-content: space-between;
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}
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h1 {
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margin-bottom: 0;
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}
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details, a {
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display: block;
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margin: 1rem 0 1rem 0;
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}
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</style>
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<script src="/tuning/plotly-2.12.1.min.js"></script>
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<!-- https://tom-alexander.github.io/regression-js/ -->
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<script src="/tuning/regression-2.0.1.min.js"></script>
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<!-- <script src="/tuning/common.js"></script> -->
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<script src="common.js"></script>
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</head>
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<body>
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<div class="content">
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<header>
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<h1>RR Dead Wheel Angular Ramp Regression</h1>
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<details></details>
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<div id="download"></div>
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<fieldset>
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<legend>Feedforward Parameters</legend>
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<div>
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kV: <input id="kv" type="text" />
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</div>
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<div>
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kS: <input id="ks" type="text" />
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</div>
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<input id="update" type="button" value="update" />
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</fieldset>
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<p>
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<button id="latest">Latest</button>
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<input id="browse" type="file" accept="application/json">
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</p>
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</header>
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<div id="trackWidthChart"></div>
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<div id="deadWheelCharts"></div>
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</div>
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<script>
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function loadRegression(data) {
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const [_, angVels] = data.angVels.reduce((acc, vsArg) => {
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const vs = fixAngVels(vsArg.values.slice(0, -1)).map(v => Math.abs(v));
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const maxV = vs.reduce((acc, v) => Math.max(acc, v), 0);
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const [accMaxV, _] = acc;
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if (maxV >= accMaxV) {
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return [maxV, vs];
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}
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return acc;
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}, [0, []]);
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const deadWheelCharts = document.getElementById('deadWheelCharts');
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data.parEncVels.forEach((vs, i) => {
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const div = document.createElement('div');
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newLinearRegressionChart(div,
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angVels.slice(1, -1),
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||||||
fixVels(
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||||||
vs.times.slice(0, -1),
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||||||
data.parEncPositions[i].values.slice(0, -1),
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||||||
vs.values.slice(0, -1)
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||||||
),
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||||||
{title: `Parallel Wheel ${i} Regression`, slope: 'y-position', noIntercept: true});
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||||||
deadWheelCharts.appendChild(div);
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||||||
});
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||||||
data.perpEncVels.forEach((vs, i) => {
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||||||
const div = document.createElement('div');
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||||||
newLinearRegressionChart(div,
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||||||
angVels.slice(1, -1),
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||||||
fixVels(
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||||||
vs.times.slice(0, -1),
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||||||
data.perpEncPositions[i].values.slice(0, -1),
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||||||
vs.values.slice(0, -1)
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||||||
),
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||||||
{title: `Perpendicular Wheel ${i} Regression`, slope: 'x-position', noIntercept: true});
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|
||||||
deadWheelCharts.appendChild(div);
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|
||||||
});
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|
||||||
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|
||||||
const setParams = (() => {
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|
||||||
const allPowers = [...data.leftPowers, ...data.rightPowers];
|
|
||||||
const appliedVoltages = data.voltages.values.slice(0, -1).map((v, i) =>
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||||||
allPowers.reduce((acc, ps) => Math.max(acc, ps.values[i]), 0) * v);
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|
||||||
|
|
||||||
const setTrackWidthData = newLinearRegressionChart(
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|
||||||
document.getElementById('trackWidthChart'),
|
|
||||||
[], [],
|
|
||||||
{title: 'Track Width Regression', slope: 'track width', noIntercept: true}
|
|
||||||
);
|
|
||||||
|
|
||||||
return (kV, kS) => setTrackWidthData(angVels, appliedVoltages.map((v, i) =>
|
|
||||||
(v - kS) / kV * (data.type === 'mecanum' ? 2 : 1)));
|
|
||||||
})();
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|
||||||
|
|
||||||
const kvInput = document.getElementById('kv');
|
|
||||||
const ksInput = document.getElementById('ks');
|
|
||||||
document.getElementById('update').addEventListener('click', () => {
|
|
||||||
setParams(parseFloat(kvInput.value), parseFloat(ksInput.value));
|
|
||||||
});
|
|
||||||
|
|
||||||
setParams(parseFloat(kvInput.value), parseFloat(ksInput.value));
|
|
||||||
}
|
|
||||||
|
|
||||||
const latestButton = document.getElementById('latest');
|
|
||||||
latestButton.addEventListener('click', function() {
|
|
||||||
fetch('/tuning/angular-ramp/latest.json')
|
|
||||||
.then(res => {
|
|
||||||
if (res.ok) {
|
|
||||||
const filename = res.headers.get('X-Filename');
|
|
||||||
|
|
||||||
const a = document.createElement('a');
|
|
||||||
a.innerText = 'Download';
|
|
||||||
a.href = `/tuning/angular-ramp/${filename}`;
|
|
||||||
a.download = `angular-ramp-${filename}`;
|
|
||||||
|
|
||||||
const download = document.getElementById('download');
|
|
||||||
download.innerHTML = '';
|
|
||||||
download.appendChild(a);
|
|
||||||
|
|
||||||
return res.json();
|
|
||||||
} else {
|
|
||||||
document.getElementById('trackWidthChart').innerText = 'No data files found';
|
|
||||||
throw new Error();
|
|
||||||
}
|
|
||||||
})
|
|
||||||
.then(loadRegression)
|
|
||||||
.catch((e) => {
|
|
||||||
const deadWheelCharts = document.getElementById('deadWheelCharts');
|
|
||||||
deadWheelCharts.innerHTML = '';
|
|
||||||
|
|
||||||
console.log(e);
|
|
||||||
});
|
|
||||||
});
|
|
||||||
|
|
||||||
const browseInput = document.getElementById('browse');
|
|
||||||
browseInput.addEventListener('change', function(evt) {
|
|
||||||
const reader = new FileReader();
|
|
||||||
reader.onload = function() {
|
|
||||||
loadRegression(JSON.parse(reader.result.trim()));
|
|
||||||
};
|
|
||||||
|
|
||||||
reader.readAsText(browseInput.files[0]);
|
|
||||||
});
|
|
||||||
</script>
|
|
||||||
</body>
|
|
||||||
</html>
|
|
||||||
@ -1,148 +0,0 @@
|
|||||||
<!doctype html>
|
|
||||||
<html>
|
|
||||||
<head>
|
|
||||||
<title>RR Drive Encoder Angular Ramp Regression</title>
|
|
||||||
|
|
||||||
<style>
|
|
||||||
body {
|
|
||||||
font-family: Arial, Helvetica, sans-serif;
|
|
||||||
}
|
|
||||||
|
|
||||||
.content {
|
|
||||||
margin: auto;
|
|
||||||
}
|
|
||||||
|
|
||||||
header {
|
|
||||||
max-width: 600px;
|
|
||||||
margin: auto;
|
|
||||||
}
|
|
||||||
|
|
||||||
.bar {
|
|
||||||
display: flex;
|
|
||||||
justify-content: space-between;
|
|
||||||
align-items: center;
|
|
||||||
}
|
|
||||||
|
|
||||||
h1 {
|
|
||||||
margin-bottom: 0;
|
|
||||||
}
|
|
||||||
|
|
||||||
details, a {
|
|
||||||
display: block;
|
|
||||||
margin: 1rem 0 1rem 0;
|
|
||||||
}
|
|
||||||
</style>
|
|
||||||
|
|
||||||
<script src="/tuning/plotly-2.12.1.min.js"></script>
|
|
||||||
|
|
||||||
<!-- https://tom-alexander.github.io/regression-js/ -->
|
|
||||||
<script src="/tuning/regression-2.0.1.min.js"></script>
|
|
||||||
|
|
||||||
<!-- <script src="/tuning/common.js"></script> -->
|
|
||||||
<script src="common.js"></script>
|
|
||||||
</head>
|
|
||||||
<body>
|
|
||||||
<div class="content">
|
|
||||||
<header>
|
|
||||||
<h1>RR Drive Encoder Angular Ramp Regression</h1>
|
|
||||||
<details></details>
|
|
||||||
|
|
||||||
<div id="download"></div>
|
|
||||||
|
|
||||||
<p>
|
|
||||||
<button id="latest">Latest</button>
|
|
||||||
<input id="browse" type="file" accept="application/json">
|
|
||||||
</p>
|
|
||||||
</header>
|
|
||||||
|
|
||||||
<div id="rampChart"></div>
|
|
||||||
<div id="trackWidthChart"></div>
|
|
||||||
</div>
|
|
||||||
|
|
||||||
<script>
|
|
||||||
function loadRegression(data) {
|
|
||||||
const leftEncVels = data.leftEncVels.map((vs, i) =>
|
|
||||||
fixVels(vs.times.slice(0, -1), data.leftEncPositions[i].values.slice(0, -1), vs.values.slice(0, -1)));
|
|
||||||
const rightEncVels = data.rightEncVels.map((vs, i) =>
|
|
||||||
fixVels(vs.times.slice(0, -1), data.rightEncPositions[i].values.slice(0, -1), vs.values.slice(0, -1)));
|
|
||||||
|
|
||||||
newLinearRegressionChart(
|
|
||||||
document.getElementById('rampChart'),
|
|
||||||
[
|
|
||||||
...leftEncVels.flatMap(vs => vs.values.slice(0, -1).map(v => -v)),
|
|
||||||
...rightEncVels.flatMap(vs => vs.values.slice(0, -1)),
|
|
||||||
],
|
|
||||||
[
|
|
||||||
...data.leftPowers.flatMap(ps => {
|
|
||||||
const psNew = ps.values.slice(0, -1).map((p, i) => -p * data.voltages.values[i]);
|
|
||||||
return psNew.slice(1, -1);
|
|
||||||
}),
|
|
||||||
...data.rightPowers.flatMap(ps => {
|
|
||||||
const psNew = ps.values.slice(0, -1).map((p, i) => p * data.voltages.values[i]);
|
|
||||||
return psNew.slice(1, -1);
|
|
||||||
}),
|
|
||||||
],
|
|
||||||
{title: 'Ramp Regression', slope: 'kV', intercept: 'kS'}
|
|
||||||
);
|
|
||||||
|
|
||||||
const p = data.angVels.reduce((acc, vsArg) => {
|
|
||||||
const vs = fixAngVels(vsArg.values).map(v => Math.abs(v));
|
|
||||||
const maxV = vs.reduce((acc, v) => Math.max(acc, v), 0);
|
|
||||||
const [accMaxV, _] = acc;
|
|
||||||
if (maxV >= accMaxV) {
|
|
||||||
return [maxV, vs];
|
|
||||||
}
|
|
||||||
return acc;
|
|
||||||
}, [0, []]);
|
|
||||||
const angVels = p[1].slice(1, -1);
|
|
||||||
|
|
||||||
newLinearRegressionChart(
|
|
||||||
document.getElementById('trackWidthChart'),
|
|
||||||
angVels,
|
|
||||||
angVels.map((_, i) =>
|
|
||||||
(leftEncVels.reduce((acc, vs) => acc - vs[i], 0) / data.leftEncVels.length
|
|
||||||
+ rightEncVels.reduce((acc, vs) => acc + vs[i], 0) / data.rightEncVels.length)
|
|
||||||
* (data.type === 'mecanum' ? 0.5 : 1)
|
|
||||||
),
|
|
||||||
{title: 'Track Width Regression', slope: 'track width', noIntercept: true}
|
|
||||||
);
|
|
||||||
}
|
|
||||||
|
|
||||||
const latestButton = document.getElementById('latest');
|
|
||||||
latestButton.addEventListener('click', function() {
|
|
||||||
fetch('/tuning/angular-ramp/latest.json')
|
|
||||||
.then(res => {
|
|
||||||
if (res.ok) {
|
|
||||||
const filename = res.headers.get('X-Filename');
|
|
||||||
|
|
||||||
const a = document.createElement('a');
|
|
||||||
a.innerText = 'Download';
|
|
||||||
a.href = `/tuning/angular-ramp/${filename}`;
|
|
||||||
a.download = `angular-ramp-${filename}`;
|
|
||||||
|
|
||||||
const download = document.getElementById('download');
|
|
||||||
download.innerHTML = '';
|
|
||||||
download.appendChild(a);
|
|
||||||
|
|
||||||
return res.json();
|
|
||||||
} else {
|
|
||||||
document.getElementById('trackWidthChart').innerText = 'No data files found';
|
|
||||||
throw new Error();
|
|
||||||
}
|
|
||||||
})
|
|
||||||
.then(loadRegression)
|
|
||||||
.catch(console.log.bind(console));
|
|
||||||
});
|
|
||||||
|
|
||||||
const browseInput = document.getElementById('browse');
|
|
||||||
browseInput.addEventListener('change', function(evt) {
|
|
||||||
const reader = new FileReader();
|
|
||||||
reader.onload = function() {
|
|
||||||
loadRegression(JSON.parse(reader.result.trim()));
|
|
||||||
};
|
|
||||||
|
|
||||||
reader.readAsText(browseInput.files[0]);
|
|
||||||
});
|
|
||||||
</script>
|
|
||||||
</body>
|
|
||||||
</html>
|
|
||||||
@ -1,116 +0,0 @@
|
|||||||
<!doctype html>
|
|
||||||
<html>
|
|
||||||
<head>
|
|
||||||
<title>RR Forward Ramp Regression</title>
|
|
||||||
|
|
||||||
<style>
|
|
||||||
body {
|
|
||||||
font-family: Arial, Helvetica, sans-serif;
|
|
||||||
}
|
|
||||||
|
|
||||||
.content {
|
|
||||||
margin: auto;
|
|
||||||
}
|
|
||||||
|
|
||||||
header {
|
|
||||||
max-width: 600px;
|
|
||||||
margin: auto;
|
|
||||||
}
|
|
||||||
|
|
||||||
.bar {
|
|
||||||
display: flex;
|
|
||||||
justify-content: space-between;
|
|
||||||
align-items: center;
|
|
||||||
}
|
|
||||||
|
|
||||||
h1 {
|
|
||||||
margin-bottom: 0;
|
|
||||||
}
|
|
||||||
|
|
||||||
details, a {
|
|
||||||
display: block;
|
|
||||||
margin: 1rem 0 1rem 0;
|
|
||||||
}
|
|
||||||
</style>
|
|
||||||
|
|
||||||
<script src="/tuning/plotly-2.12.1.min.js"></script>
|
|
||||||
|
|
||||||
<!-- https://tom-alexander.github.io/regression-js/ -->
|
|
||||||
<script src="/tuning/regression-2.0.1.min.js"></script>
|
|
||||||
|
|
||||||
<!-- <script src="/tuning/common.js"></script> -->
|
|
||||||
<script src="common.js"></script>
|
|
||||||
</head>
|
|
||||||
<body>
|
|
||||||
<div class="content">
|
|
||||||
<header>
|
|
||||||
<h1>RR Forward Ramp Regression</h1>
|
|
||||||
<details></details>
|
|
||||||
|
|
||||||
<div id="download"></div>
|
|
||||||
|
|
||||||
<p>
|
|
||||||
<button id="latest">Latest</button>
|
|
||||||
<input id="browse" type="file" accept="application/json">
|
|
||||||
</p>
|
|
||||||
</header>
|
|
||||||
|
|
||||||
<div id="rampChart"></div>
|
|
||||||
</div>
|
|
||||||
|
|
||||||
<script>
|
|
||||||
function loadRegression(data) {
|
|
||||||
const forwardEncVels = data.forwardEncVels.flatMap((vs, i) =>
|
|
||||||
fixVels(vs.times.slice(0, -1), data.forwardEncPositions[i].values.slice(0, -1), vs.values.slice(0, -1)));
|
|
||||||
const appliedVoltages = data.forwardEncVels.flatMap(() => {
|
|
||||||
const voltages = data.voltages.values.slice(0, -1).map((v, i) =>
|
|
||||||
data.powers.reduce((acc, ps) => Math.max(acc, ps.values[i]), 0) * v);
|
|
||||||
|
|
||||||
return voltages.slice(1, voltages.length - 1);
|
|
||||||
});
|
|
||||||
|
|
||||||
newLinearRegressionChart(
|
|
||||||
document.getElementById('rampChart'),
|
|
||||||
forwardEncVels, appliedVoltages,
|
|
||||||
{title: 'Ramp Regression', slope: 'kV', intercept: 'kS', noIntercept: false}
|
|
||||||
);
|
|
||||||
}
|
|
||||||
|
|
||||||
const latestButton = document.getElementById('latest');
|
|
||||||
latestButton.addEventListener('click', function() {
|
|
||||||
fetch('/tuning/forward-ramp/latest.json')
|
|
||||||
.then(res => {
|
|
||||||
if (res.ok) {
|
|
||||||
const filename = res.headers.get('X-Filename');
|
|
||||||
|
|
||||||
const a = document.createElement('a');
|
|
||||||
a.innerText = 'Download';
|
|
||||||
a.href = `/tuning/forward-ramp/${filename}`;
|
|
||||||
a.download = `forward-ramp-${filename}`;
|
|
||||||
|
|
||||||
const download = document.getElementById('download');
|
|
||||||
download.innerHTML = '';
|
|
||||||
download.appendChild(a);
|
|
||||||
|
|
||||||
return res.json();
|
|
||||||
} else {
|
|
||||||
document.getElementById('rampChart').innerText = 'No data files found';
|
|
||||||
throw new Error();
|
|
||||||
}
|
|
||||||
})
|
|
||||||
.then(loadRegression)
|
|
||||||
.catch(console.log.bind(console));
|
|
||||||
});
|
|
||||||
|
|
||||||
const browseInput = document.getElementById('browse');
|
|
||||||
browseInput.addEventListener('change', function(evt) {
|
|
||||||
const reader = new FileReader();
|
|
||||||
reader.onload = function() {
|
|
||||||
loadRegression(JSON.parse(reader.result.trim()));
|
|
||||||
};
|
|
||||||
|
|
||||||
reader.readAsText(browseInput.files[0]);
|
|
||||||
});
|
|
||||||
</script>
|
|
||||||
</body>
|
|
||||||
</html>
|
|
||||||
File diff suppressed because one or more lines are too long
File diff suppressed because one or more lines are too long
@ -1,118 +0,0 @@
|
|||||||
<!doctype html>
|
|
||||||
<html>
|
|
||||||
<head>
|
|
||||||
<title>RR Tests</title>
|
|
||||||
|
|
||||||
<style>
|
|
||||||
body {
|
|
||||||
font-family: Arial, Helvetica, sans-serif;
|
|
||||||
}
|
|
||||||
|
|
||||||
#content {
|
|
||||||
max-width: 600px;
|
|
||||||
margin: auto;
|
|
||||||
}
|
|
||||||
|
|
||||||
.bar {
|
|
||||||
display: flex;
|
|
||||||
justify-content: space-between;
|
|
||||||
align-items: center;
|
|
||||||
}
|
|
||||||
|
|
||||||
fieldset {
|
|
||||||
display: flex;
|
|
||||||
justify-content: space-between;
|
|
||||||
}
|
|
||||||
</style>
|
|
||||||
|
|
||||||
<script src="/tuning/plotly-2.12.1.min.js"></script>
|
|
||||||
|
|
||||||
<!-- https://tom-alexander.github.io/regression-js/ -->
|
|
||||||
<script src="/tuning/regression-2.0.1.min.js"></script>
|
|
||||||
|
|
||||||
<!-- <script src="/tuning/common.js"></script> -->
|
|
||||||
<script src="common.js"></script>
|
|
||||||
</head>
|
|
||||||
<body>
|
|
||||||
<div id="content">
|
|
||||||
<h1>RR Tests</h1>
|
|
||||||
<p></p>
|
|
||||||
</div>
|
|
||||||
|
|
||||||
<script>
|
|
||||||
function newChart(container, xs, ys, options) {
|
|
||||||
if (xs.length !== ys.length) {
|
|
||||||
throw new Error();
|
|
||||||
}
|
|
||||||
|
|
||||||
// cribbed from https://plotly.com/javascript/plotlyjs-events/#select-event
|
|
||||||
const color = '#777';
|
|
||||||
const colorLight = '#bbb';
|
|
||||||
|
|
||||||
const chartDiv = document.createElement('div');
|
|
||||||
Plotly.newPlot(chartDiv, [{
|
|
||||||
type: 'scatter',
|
|
||||||
mode: 'markers',
|
|
||||||
x: xs,
|
|
||||||
y: ys,
|
|
||||||
name: 'Samples',
|
|
||||||
}], {
|
|
||||||
title: options.title || '',
|
|
||||||
// sets the starting tool from the modebar
|
|
||||||
dragmode: 'zoom',
|
|
||||||
showlegend: false,
|
|
||||||
hovermode: false,
|
|
||||||
width: 600,
|
|
||||||
}, {
|
|
||||||
// 'zoom2d', 'select2d', 'resetScale2d' left
|
|
||||||
modeBarButtonsToRemove: ['pan2d', 'lasso2d', 'zoomIn2d', 'zoomOut2d', 'autoScale2d'],
|
|
||||||
});
|
|
||||||
|
|
||||||
container.appendChild(chartDiv);
|
|
||||||
}
|
|
||||||
|
|
||||||
function numDeriv(xs, ys) {
|
|
||||||
const ret = ys.slice(1).map((y, i) => (y - ys[i]) / (xs[i + 1] - xs[i]));
|
|
||||||
ret.unshift(0);
|
|
||||||
return ret;
|
|
||||||
}
|
|
||||||
|
|
||||||
const params = new URLSearchParams(window.location.search);
|
|
||||||
const online = params.get('online') === 'true';
|
|
||||||
|
|
||||||
fetch(`/tuning/test/${params.get('file')}.csv`)
|
|
||||||
.then(res => res.text())
|
|
||||||
.then(text => {
|
|
||||||
const lines = text.split('\n');
|
|
||||||
const data = lines
|
|
||||||
.slice(1, lines.length - 1)
|
|
||||||
.map(line => line.split(',').map(x => parseFloat(x)))
|
|
||||||
|
|
||||||
const xs = data.map(xs => xs[0]);
|
|
||||||
const vs = data.map(xs => xs[1]);
|
|
||||||
const ts = data.map(xs => xs[2]);
|
|
||||||
|
|
||||||
const container = document.getElementById('content');
|
|
||||||
newChart(container, ts, vs, {title: 'Raw Velocity Over Time'});
|
|
||||||
|
|
||||||
const tsNew = (online ? ts.slice(1) : ts.slice(1, ts.length - 1));
|
|
||||||
const dxdts = (online ? numDerivOnline : numDerivOffline)(ts, xs);
|
|
||||||
newChart(
|
|
||||||
container,
|
|
||||||
tsNew,
|
|
||||||
dxdts,
|
|
||||||
{title: `${online ? 'Online' : 'Offline'} Position Derivative Over Time`}
|
|
||||||
);
|
|
||||||
|
|
||||||
const vsNew = dxdts.map((est, i) => inverseOverflow(vs[i + 1], est));
|
|
||||||
newChart(
|
|
||||||
container,
|
|
||||||
tsNew,
|
|
||||||
vsNew,
|
|
||||||
{title: 'Corrected Velocity Over Time'}
|
|
||||||
);
|
|
||||||
})
|
|
||||||
.catch(console.log.bind(console));
|
|
||||||
</script>
|
|
||||||
</body>
|
|
||||||
</html>
|
|
||||||
@ -1,219 +0,0 @@
|
|||||||
pos,vel,time
|
|
||||||
248474,-23244.000000,2250.761012
|
|
||||||
256050,-23244.000000,2250.792090
|
|
||||||
261029,-23044.000000,2250.812276
|
|
||||||
265827,-23104.000000,2250.832364
|
|
||||||
270750,-23404.000000,2250.853347
|
|
||||||
275564,-23584.000000,2250.872950
|
|
||||||
280730,-23244.000000,2250.895051
|
|
||||||
285076,-23464.000000,2250.912948
|
|
||||||
289471,-23244.000000,2250.931340
|
|
||||||
295065,-23284.000000,2250.954710
|
|
||||||
299341,-25184.000000,2250.972536
|
|
||||||
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|
|
||||||
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|
|
||||||
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|
|
||||||
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|
|
||||||
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|
|
||||||
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|
|
||||||
333217,-23224.000000,2251.114403
|
|
||||||
337719,-23904.000000,2251.133205
|
|
||||||
342702,-23244.000000,2251.154108
|
|
||||||
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|
|
||||||
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|
|
||||||
356826,-23224.000000,2251.213216
|
|
||||||
361581,-23704.000000,2251.233083
|
|
||||||
368943,-24464.000000,2251.263826
|
|
||||||
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|
|
||||||
379505,-22004.000000,2251.309094
|
|
||||||
383474,-23244.000000,2251.324622
|
|
||||||
387117,-23244.000000,2251.340667
|
|
||||||
391575,-23244.000000,2251.358790
|
|
||||||
396711,-23264.000000,2251.380079
|
|
||||||
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|
|
||||||
406717,-23244.000000,2251.421884
|
|
||||||
409944,-23204.000000,2251.435380
|
|
||||||
413772,-23224.000000,2251.451349
|
|
||||||
417264,-23204.000000,2251.466198
|
|
||||||
421303,-26524.000000,2251.482893
|
|
||||||
426176,-23244.000000,2251.503336
|
|
||||||
430443,-23264.000000,2251.521113
|
|
||||||
434626,-23244.000000,2251.538644
|
|
||||||
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|
|
||||||
442742,-23224.000000,2251.572622
|
|
||||||
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|
|
||||||
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|
|
||||||
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|
|
||||||
462471,-23244.000000,2251.655411
|
|
||||||
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|
|
||||||
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|
|
||||||
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|
|
||||||
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|
|
||||||
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|
|
||||||
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|
|
||||||
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|
|
||||||
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|
|
||||||
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|
|
||||||
511649,-23004.000000,2251.861069
|
|
||||||
515151,-23204.000000,2251.875656
|
|
||||||
518685,-19624.000000,2251.890619
|
|
||||||
523224,-23464.000000,2251.909380
|
|
||||||
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|
|
||||||
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|
|
||||||
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|
|
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|
|
||||||
543748,-23224.000000,2251.995638
|
|
||||||
548572,-23244.000000,2252.015653
|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
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|
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|
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|
|
||||||
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|
|
||||||
|
@ -1,308 +0,0 @@
|
|||||||
pos,vel,time
|
|
||||||
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|
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|
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|
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||||||
|
Reference in New Issue
Block a user