2f:Ta66,function getAvgIMU(vararr, subjects, recipes, percents) { const avgSensorArr = [] for (let i = 0; i < subjects.length; i++) { for (let j = 0; j < recipes.length; j++) { let xAccelSum = 0 let yAccelSum = 0 let zAccelSum = 0 let rollSum = 0 let pitchSum = 0 let yawSum = 0 let xMagSum = 0 let yMagSum = 0 let zMagSum = 0 for (let k = 0; k < percents.length; k++) { let stepIndices = multiIndexOfPercent(vararr, subjects[i], recipes[j], percents[k]) let xAccelStepSum = 0 let yAccelStepSum = 0 let zAccelStepSum = 0 let rollStepSum = 0 let pitchStepSum = 0 let yawStepSum = 0 let xMagStepSum = 0 let yMagStepSum = 0 let zMagStepSum = 0 for (let p = 0; p < stepIndices.length; p++) { xAccelStepSum = xAccelStepSum + vararr[stepIndices[p]].Accel_X_Variance yAccelStepSum = yAccelStepSum + vararr[stepIndices[p]].Accel_Y_Variance zAccelStepSum = zAccelStepSum + vararr[stepIndices[p]].Accel_Z_Variance rollStepSum = rollStepSum + vararr[stepIndices[p]].Roll_Variance pitchStepSum = pitchStepSum + vararr[stepIndices[p]].Pitch_Variance yawStepSum = yawStepSum + vararr[stepIndices[p]].Yaw_Variance xMagStepSum = xMagStepSum + vararr[stepIndices[p]].Mag_X_Variance yMagStepSum = yMagStepSum + vararr[stepIndices[p]].Mag_Y_Variance zMagStepSum = zMagStepSum + vararr[stepIndices[p]].Mag_Z_Variance } xAccelSum = xAccelSum + (xAccelStepSum / stepIndices.length) yAccelSum = yAccelSum + (yAccelStepSum / stepIndices.length) zAccelSum = zAccelSum + (zAccelStepSum / stepIndices.length) rollSum = rollSum + (rollStepSum / stepIndices.length) pitchSum = pitchSum + (pitchStepSum / stepIndices.length) yawSum = yawSum + (yawStepSum / stepIndices.length) xMagSum = xMagSum + (xMagStepSum / stepIndices.length) yMagSum = yMagSum + (yMagStepSum / stepIndices.length) zMagSum = zMagSum + (zMagStepSum / stepIndices.length) } let accelAvg = ((xAccelSum / percents.length) + (yAccelSum / percents.length) + (zAccelSum / percents.length)) / 3 let gyroAvg = ((rollSum / percents.length) + (pitchSum / percents.length) + (yawSum / percents.length)) / 3 let magAvg = ((xMagSum / percents.length) + (yMagSum / percents.length) + (zMagSum / percents.length)) / 3 avgSensorArr.push({subject_ID: subjects[i], recipe_type: recipes[j], Accelerometer: accelAvg, Gyroscope: gyroAvg, Magnetometer: magAvg}) } } return avgSensorArr }30:T724,viewof selections = { const colWidth = 100; const fontSize = 15; const svg = d3.create('svg') .attr('width', colWidth * (recipes.length + 1) + 100) .attr('height', 25); const cols = svg.selectAll('g') .data(recipes) .join('g') // position the group for each row of the legend .attr('transform', (d, i) => `translate(${i * colWidth +colWidth}, 5)`); svg.append("text") .attr("x", 40) .attr("y", 8) .attr("text-anchor", "middle") .attr("dominant-baseline", "hanging") .attr("font-family", "sans-serif") .attr("font-size", "13px") .text("Select recipe:"); // add colored square to each col cols.append('rect') .attr('width', fontSize) .attr('height', fontSize) .attr('stroke-width', 2) .attr('stroke', d => recipeColor(d)) .attr('fill', d => recipeColor(d)) .on('click', onclick); // add label to each col cols.append('text') .attr('font-size', fontSize) .attr('x', colWidth - 80) .attr('y', fontSize / 2) .attr('font-family', 'sans-serif') .attr('dominant-baseline', 'middle') .text(d => d); // Track which origins are selected in the legend. // This is a map from car origin to a boolean for // whether or not it the origin is selected. // To start, all origins are selected. const selected = new Map(recipes.map(d => [d, true])); function onclick(event, d) { const isSelected = selected.get(d); // this refers to the square that was clicked const square = d3.select(this); // toggle the square square.attr('fill', d => isSelected ? 'white' : recipeColor(d)); selected.set(d, !isSelected); svg.property('value', selected).dispatch('input'); } svg.property('value', selected).dispatch('input'); return svg.node(); }31:Ta6f,{ // set up const margin2 = {top: 50, right: 120, bottom: 50, left: 120}; const visWidth2 = 400; const visHeight2 = 400; const svg = d3.create('svg') .attr('width', visWidth2 + margin2.left + margin2.right) .attr('height', visHeight2 + margin2.top + margin2.bottom); const g = svg.append("g") .attr("transform", `translate(${margin2.left}, ${margin2.top})`); // add title g.append("text") .attr("x", visWidth2 / 2) .attr("y", -margin2.top + 5) .attr("text-anchor", "middle") .attr("dominant-baseline", "hanging") .attr("font-family", "sans-serif") .attr("font-size", "16px") .text("IMU Variance vs. User Distance Travelled"); // create scales const x = d3.scaleLinear() .domain(d3.extent(comboArr, d => d["Average_Distance_Whole_Recording"])).nice() .range([0, visWidth2]); const y = d3.scaleLinear() .domain(d3.extent(comboArr, d => d[IMUsensor])).nice() .range([visHeight2, 0]); // create and add axes const xAxis = d3.axisBottom(x); g.append("g") // move to bottom of chart .attr("transform", `translate(0, ${visHeight2})`) // add axis .call(xAxis) // remove baseline from axis .call(g => g.select(".domain").remove()) // add grid lines // refernces https://observablehq.com/@d3/connected-scatterplot .call(g => g.selectAll('.tick line') .clone() .attr('stroke', '#d3d3d3') .attr('y1', -visHeight2) .attr('y2', 0)) // add title .append("text") .attr("x", visWidth2 / 2) .attr("y", 40) .attr("fill", "black") .attr("text-anchor", "middle") .text("Distance Travelled (m)"); const yAxis = d3.axisLeft(y); g.append("g") // add axis .call(yAxis) // remove baseline from axis .call(g => g.select(".domain").remove()) // add grid lines // refernces https://observablehq.com/@d3/connected-scatterplot .call(g => g.selectAll('.tick line') .clone() .attr('stroke', '#d3d3d3') .attr('x1', 0) .attr('x2', visWidth2)) // add title .append("text") .attr("x", -40) .attr("y", visHeight2 / 2) .attr("fill", "black") .attr("dominant-baseline", "middle") .text("Avg Variance"); // draw points g.append("g") .selectAll("circle") .data(comboArr.filter(d => selections.get(d.recipe_type))) .join("circle") .attr("cx", d => x(d["Average_Distance_Whole_Recording"])) .attr("cy", d => y(d[IMUsensor])) .attr("fill", d => recipeColor(d.recipe_type)) .attr("r", 3); return svg.node(); }32:T4b7,function addRange(distTimeComboArr) { const rangeArr = [] for (let i = 0; i < distTimeComboArr.length; i++) { let existing = distTimeComboArr[i] let completion_time = distTimeComboArr[i].Average_Completion_Time_Across_Sensors let range = "None" if (completion_time < 100){ range = "0-100 sec" } else if (completion_time > 100 && completion_time < 200){ range = "100-200 sec" } else if (completion_time > 200 && completion_time < 300){ range = "200-300 sec" } else if (completion_time > 300 && completion_time < 400){ range = "300-400 sec" } else if (completion_time > 400 && completion_time < 500){ range = "400-500 sec" } else if (completion_time > 500 && completion_time < 600){ range = "500-600 sec" } else if (completion_time > 600 && completion_time < 700){ range = "600-700 sec" } else if (completion_time > 700 && completion_time < 800){ range = "700-800 sec" } else if (completion_time > 800 && completion_time < 900){ range = "800-900 sec" } if (range != "None"){ existing.range = range rangeArr.push(existing) } } return rangeArr }33:T847,{ const margin = {top: 30, right: 0, bottom: 20, left: 40}; const visWidth = width - margin.left - margin.right; const visHeight = 500 - margin.top - margin.bottom; const svg = d3.create('svg') .attr('width', visWidth + margin.left + margin.right) .attr('height', visHeight + margin.top + margin.bottom); const g = svg.append('g') .attr('transform', `translate(${margin.left}, ${margin.top})`); // this scale will be used to position the groups for each month const group = d3.scaleBand() .domain(ranges) .range([0, visWidth]) .padding(0.2); let max = getMax(IMUsensorchosen) const y = d3.scaleLinear() .domain([0, max]).nice() .range([visHeight, 0]); // this scale will be used to position the bars within a group const x = d3.scaleBand() .domain(recipeGroupSort) .range([0, group.bandwidth()]) .padding(0.2); // set up the axes const xAxis = d3.axisBottom(group); const yAxis = d3.axisLeft(y); g.append('g') .attr('transform', `translate(0,${visHeight})`) .call(xAxis) .call(g => g.selectAll('.domain').remove()); g.append("g") .call(yAxis) .call(g => g.selectAll('.domain').remove()) .append('text') .attr('fill', 'black') .attr('text-anchor', 'start') .attr('dominant-baseline', 'hanging') .attr('font-weight', 'bold') .attr('y', -margin.top + 5) .attr('x', -margin.left) .text('Average Variance vs Average Task Completion Time'); // create and position one group for each month const groups = g.append('g') .selectAll('g') .data(IMUDataObj[IMUsensorchosen]) .join('g') .attr('transform', d => `translate(${group(d.range)},0)`); // add the bars to each group groups.selectAll('rect') .data(d => d.recipe_type) .join('rect') .attr('fill', d => recipeColor(d.recipe_type)) .attr('y', d => y(d.Variance)) .attr('height', d => visHeight - y(d.Variance)) .attr('x', d => x(d.recipe_type)) .attr('width', x.bandwidth()); return svg.node(); }34:[{"id":"5e2d479c2e9fd444bfc0f7ee2c2a319fe7c3d4477d712a2800e8e95a0357abd05f6458ed7bfdf9207a020d512fbb959b34779be4b54739397ffaa8122ff1ffda","href":"https://static.observableusercontent.com/files/5e2d479c2e9fd444bfc0f7ee2c2a319fe7c3d4477d712a2800e8e95a0357abd05f6458ed7bfdf9207a020d512fbb959b34779be4b54739397ffaa8122ff1ffda","name":"distances_all.csv","type":"text/csv","lastModified":1669841379792.756,"size":61023},{"id":"4de496bbb302acd3d2e2db1ae357fc195537e477f73189ef093e62c7595557df527ef6562d8d56abde094ebb0d901cb8213010167826722db35452a2277e964e","href":"https://static.observableusercontent.com/files/4de496bbb302acd3d2e2db1ae357fc195537e477f73189ef093e62c7595557df527ef6562d8d56abde094ebb0d901cb8213010167826722db35452a2277e964e","name":"variances.csv","type":"text/csv","lastModified":1669841350618.242,"size":32122136},{"id":"9bc182a3c3ddca80a2fbce5a5ad91a3e32a5b4817069b94f5cb2aa3ef52d73211f2c409867b2da11cc05aca96cb2c7b4e7e037a31bbd42fe6b3af8190b2674bc","href":"https://static.observableusercontent.com/files/9bc182a3c3ddca80a2fbce5a5ad91a3e32a5b4817069b94f5cb2aa3ef52d73211f2c409867b2da11cc05aca96cb2c7b4e7e037a31bbd42fe6b3af8190b2674bc","name":"completion_times_all.csv","type":"text/csv","lastModified":1669920383648.687,"size":47241}] 2d:{"title":"Untitled","cells":[{"id":0,"value":"# Untitled","pinned":false,"hidden":false,"mode":"md"},{"id":98,"value":"import {swatches} from \"@d3/color-legend\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":10,"value":"variances = FileAttachment(\"variances.csv\").csv({typed: true})","pinned":false,"hidden":false,"mode":"ojs"},{"id":13,"value":"distances = FileAttachment(\"distances_all.csv\").csv({typed: true})","pinned":false,"hidden":false,"mode":"ojs"},{"id":37,"value":"subjects = Array.from(new Set(distances.map(d => d.subject_ID)))","pinned":false,"hidden":false,"mode":"ojs"},{"id":31,"value":"recipes = Array.from(new Set(distances.map(d => d.recipe_type)))","pinned":false,"hidden":false,"mode":"ojs"},{"id":33,"value":"sensors = Array.from(new Set(distances.map(d => d.sensor_ID)))","pinned":false,"hidden":false,"mode":"ojs"},{"id":65,"value":"percents = Array.from(new Set(variances.map(d => d.percent_through_recording)))","pinned":false,"hidden":false,"mode":"ojs"},{"id":48,"value":"//modified from https://stackoverflow.com/questions/24241462/how-to-search-for-multiple-indexes-of-same-values-in-javascript-array \nfunction multiIndexOf(arr, subject, recipe) { \n var idxs = [];\n for (var i = arr.length - 1; i >= 0; i--) {\n if (arr[i].subject_ID === subject && arr[i].recipe_type === recipe) {\n idxs.unshift(i);\n }\n }\n return idxs;\n};","pinned":false,"hidden":false,"mode":"ojs"},{"id":69,"value":"//modified from https://stackoverflow.com/questions/24241462/how-to-search-for-multiple-indexes-of-same-values-in-javascript-array \nfunction multiIndexOfPercent(arr, subject, recipe, percent) { \n var idxs = [];\n for (var i = arr.length - 1; i >= 0; i--) {\n if (arr[i].subject_ID === subject && arr[i].recipe_type === recipe && arr[i].percent_through_recording === percent) {\n idxs.unshift(i);\n }\n }\n return idxs;\n};","pinned":false,"hidden":false,"mode":"ojs"},{"id":28,"value":"function getAvgDistPerSession(distarr, subjects, recipes) {\n const avgDistArr = []\n for (let i = 0; i < subjects.length; i++) {\n for (let j = 0; j < recipes.length; j++) {\n let sessionIndices = multiIndexOf(distarr, subjects[i], recipes[j])\n let sessionSum = 0\n for (let k = 0; k < sessionIndices.length; k++) {\n sessionSum = sessionSum + distarr[sessionIndices[k]].Total_Distance\n }\n avgDistArr.push({subject_ID: subjects[i], recipe_type: recipes[j], Average_Distance: sessionSum / sessionIndices.length})\n }\n }\n return avgDistArr\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":123,"value":"avgDistArr = getAvgDistPerSession(distances, subjects, recipes)","pinned":false,"hidden":false,"mode":"ojs"},{"id":63,"value":"$2f","pinned":false,"hidden":false,"mode":"ojs"},{"id":76,"value":"avgIMUVars = getAvgIMU(variances, subjects, recipes, percents)","pinned":false,"hidden":false,"mode":"ojs"},{"id":134,"value":"function combineAvgVarDistArrs(varavgarr, distavgarr) {\n const comboArr = []\n for (let i = 0; i < varavgarr.length; i++) {\n let subject_id = varavgarr[i].subject_ID\n let recipe_type = varavgarr[i].recipe_type\n let vars = varavgarr[i]\n let distIndex = -1\n distIndex = distavgarr.findIndex(element => element.subject_ID === subject_id && element.recipe_type === recipe_type)\n if (distIndex != -1){\n vars.Average_Distance_Whole_Recording = distavgarr[distIndex].Average_Distance\n comboArr.push(vars)\n }\n }\n return comboArr\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":106,"value":"comboArr = combineAvgVarDistArrs(avgIMUVars, avgDistArr)","pinned":false,"hidden":false,"mode":"ojs"},{"id":93,"value":"recipeColor = d3.scaleOrdinal()\n .domain(recipes)\n .range(d3.schemeCategory10)","pinned":false,"hidden":false,"mode":"ojs"},{"id":157,"value":"IMUsensorlist = [\"Accelerometer\", \"Gyroscope\", \"Magnetometer\"]","pinned":false,"hidden":false,"mode":"ojs"},{"id":155,"value":"viewof IMUsensor = Inputs.select(IMUsensorlist, {value: \"Accelerometer\", label: \"Select IMU sensor:\"})","pinned":false,"hidden":false,"mode":"ojs"},{"id":148,"value":"$30","pinned":false,"hidden":false,"mode":"ojs"},{"id":139,"value":"$31","pinned":true,"hidden":false,"mode":"ojs"},{"id":206,"value":"# Question 3","pinned":false,"hidden":false,"mode":"md"},{"id":211,"value":"completionTimes = FileAttachment(\"completion_times_all.csv\").csv({typed: true})","pinned":false,"hidden":false,"mode":"ojs"},{"id":204,"value":"function getAvgCompTimePerSession(comptimearr, subjects, recipes) {\n const avgCompTimeArr = []\n for (let i = 0; i < subjects.length; i++) {\n for (let j = 0; j < recipes.length; j++) {\n let sessionIndices = multiIndexOf(comptimearr, subjects[i], recipes[j])\n let sessionSum = 0\n for (let k = 0; k < sessionIndices.length; k++) {\n sessionSum = sessionSum + comptimearr[sessionIndices[k]].completion_time_sec\n }\n avgCompTimeArr.push({subject_ID: subjects[i], recipe_type: recipes[j], Average_Completion_Time_Across_Sensors: sessionSum / sessionIndices.length})\n }\n }\n return avgCompTimeArr\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":217,"value":"avgCompTimeArr = getAvgCompTimePerSession(completionTimes, subjects, recipes)","pinned":false,"hidden":false,"mode":"ojs"},{"id":222,"value":"function combineAvgVarCompTimeArrs(avgvararr, avgcomptimearr) {\n const comboArr2 = []\n for (let i = 0; i < avgvararr.length; i++) {\n let subject_id = avgvararr[i].subject_ID\n let recipe_type = avgvararr[i].recipe_type\n let vars = avgvararr[i]\n let comptimeIndex = -1\n comptimeIndex = avgcomptimearr.findIndex(element => element.subject_ID === subject_id && element.recipe_type === recipe_type)\n if (comptimeIndex != -1){\n vars.Average_Completion_Time_Across_Sensors = avgcomptimearr[comptimeIndex].Average_Completion_Time_Across_Sensors\n comboArr2.push(vars)\n }\n }\n return comboArr2\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":238,"value":"varTimeComboArr = combineAvgVarCompTimeArrs(avgIMUVars, avgCompTimeArr)","pinned":false,"hidden":false,"mode":"ojs"},{"id":228,"value":"$32","pinned":false,"hidden":false,"mode":"ojs"},{"id":231,"value":"varTimeComboRangeArr = addRange(varTimeComboArr)","pinned":false,"hidden":false,"mode":"ojs"},{"id":256,"value":"accelData = {\n const accelvars = d3.rollup(varTimeComboRangeArr,\n bars => d3.mean(bars, c => c.Accelerometer),\n d => d.range,\n d => d.recipe_type);\n \n return Array.from(accelvars, (([range, map]) => {\n map.set('range', range);\n return Object.fromEntries(map)\n }));\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":311,"value":"gyroData = {\n const gyrovars = d3.rollup(varTimeComboRangeArr,\n bars => d3.mean(bars, c => c.Gyroscope),\n d => d.range,\n d => d.recipe_type);\n \n return Array.from(gyrovars, (([range, map]) => {\n map.set('range', range);\n return Object.fromEntries(map)\n }));\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":314,"value":"magData = {\n const magvars = d3.rollup(varTimeComboRangeArr,\n bars => d3.mean(bars, c => c.Magnetometer),\n d => d.range,\n d => d.recipe_type);\n \n return Array.from(magvars, (([range, map]) => {\n map.set('range', range);\n return Object.fromEntries(map)\n }));\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":268,"value":"recipeGroupSort = d3.groupSort(\n varTimeComboRangeArr,\n accel => -d3.sum(accel, c => c.Accelerometer),\n d => d.recipe_type\n)","pinned":false,"hidden":false,"mode":"ojs"},{"id":264,"value":"accelDataWithRecipeArray = accelData.map(d => ({\n range: d.range,\n sensor: \"Accelerometer\",\n recipe_type: recipeGroupSort.map(b => ({recipe_type: b, Variance: d[b]}))\n}))","pinned":false,"hidden":false,"mode":"ojs"},{"id":317,"value":"gyroDataWithRecipeArray = gyroData.map(d => ({\n range: d.range,\n sensor: \"Gyroscope\",\n recipe_type: recipeGroupSort.map(b => ({recipe_type: b, Variance: d[b]}))\n}))","pinned":false,"hidden":false,"mode":"ojs"},{"id":320,"value":"magDataWithRecipeArray = magData.map(d => ({\n range: d.range,\n sensor: \"Magnetometer\",\n recipe_type: recipeGroupSort.map(b => ({recipe_type: b, Variance: d[b]}))\n}))","pinned":false,"hidden":false,"mode":"ojs"},{"id":345,"value":"function getObj(accelDataWithRecipeArray, gyroDataWithRecipeArray, magDataWithRecipeArray){\n let IMUDataObj = {}\n IMUDataObj.Accelerometer = accelDataWithRecipeArray\n IMUDataObj.Gyroscope = gyroDataWithRecipeArray\n IMUDataObj.Magnetometer = magDataWithRecipeArray\n return IMUDataObj\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":351,"value":"IMUDataObj = getObj(accelDataWithRecipeArray, gyroDataWithRecipeArray, magDataWithRecipeArray)","pinned":false,"hidden":false,"mode":"ojs"},{"id":281,"value":"ranges = [\"100-200 sec\", \"200-300 sec\", \"300-400 sec\", \"400-500 sec\", \"500-600 sec\", \"600-700 sec\", \"700-800 sec\", \"800-900 sec\"]","pinned":false,"hidden":false,"mode":"ojs"},{"id":372,"value":"function getMax(IMUSensorChosen){\n let max = 0\n if (IMUSensorChosen == \"Accelerometer\"){\n max = 0.015\n }\n else if (IMUSensorChosen == \"Gyroscope\"){\n max = 0.17\n }\n else if (IMUSensorChosen == \"Magnetometer\"){\n max = 0.01\n }\n return max\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":325,"value":"viewof IMUsensorchosen = Inputs.select(IMUsensorlist, {value: \"Accelerometer\", label: \"Select IMU sensor:\"})","pinned":false,"hidden":false,"mode":"ojs"},{"id":382,"value":"swatches({color: recipeColor})","pinned":false,"hidden":false,"mode":"ojs"},{"id":279,"value":"$33","pinned":false,"hidden":false,"mode":"ojs"}],"files":"$W34","stdlib":"1","titling":"auto"}