2f:null 30:["$","title",null,{"children":"1-D data analysis Chathura Jayalath [UCFID:3948890] | Chathura Jayalath | Observable"}] 35:T770,{ let numOfBins = 20 let histData = eruptions let bandwidth = inBandwidth let amplitude = inAmplitude let kernalFunctionType = kernalEpanechnikovFactory; if (inKernalFunctionType == 'Gaussian'){ kernalFunctionType = kernalGaussianFactory }else if (inKernalFunctionType == 'Uniform'){ kernalFunctionType = kernalUniformFactory }else if (inKernalFunctionType == 'Triangular'){ kernalFunctionType = kernalTriangularFactory }else if (inKernalFunctionType == 'Tricube'){ kernalFunctionType = kernalTricubeFactory }else if (inKernalFunctionType == 'Cosine'){ kernalFunctionType = kernalCosineFactory }else{ kernalFunctionType = kernalEpanechnikovFactory } let trace1 = { x:histData, type:'histogram', histnorm : 'probability', name: 'Histogram', xbins: {size: (d3.max(histData) - d3.min(histData)) / (numOfBins - 1)}, marker: { color: 'white', line: { color: "black", width: 1 } } }; let kdeData = generateKernalDensity(eruptions, bandwidth, amplitude, kernalFunctionType()) let trace2 = { x: kdeData[0], y: kdeData[1], type: 'scatter', name: 'KDE' }; let layout = { title: { text:'Kernal Density Estimation of Eruptions', font: { family: 'Open Sans', size: 24 }, xref: 'paper' }, xaxis: { title: { text: 'Eruption Duration (minutes)', font: { family: 'Open Sans', size: 18, color: '#7f7f7f' } } }, yaxis: { title: { text: 'Probability', font: { family: 'Open Sans', size: 18, color: '#7f7f7f' } }, } }; const div = DOM.element('div'); div.setAttribute("id", "Div1"); Plotly.newPlot(div, [trace1, trace2], layout) return div }36:[] 33:{"id":"a363dbb7ab0db8b7","slug":"cap-5738-assignment-2-chathura-jayalath-ucfid-3948890","title":"1-D data analysis Chathura Jayalath [UCFID:3948890]","thumbnail":"ca1f663ebdeda358f1d3e664ac192f39402b3a6d1ed4b7efb40652d750eae1f4","access_level":"public","create_time":"$D2020-09-07T21:05:34.062Z","update_time":"$D2020-09-21T16:30:14.311Z","view_time":null,"first_public_time":"$D2020-09-08T00:55:20.237Z","has_unpublished_edits":null,"fork":false,"stars":0,"starred":false,"owner":{"type":"team","id":"faa67bfd1359f951","login":"deamonpog","name":"Chathura Jayalath","avatar_url":"https://avatars-next.observableusercontent.com/1bc13a0724d43e94c26de301357a2897d22e5c4e01e7f160ea8fba232ef861f1","tier":"starter_2024"},"version":449,"publish_version":449,"role":null,"authored":false,"authors":[{"type":"individual","id":"5fe81dea2f61079a","login":"deamonpog","name":"Chathura Jayalath","avatar_url":"https://avatars-next.observableusercontent.com/1bc13a0724d43e94c26de301357a2897d22e5c4e01e7f160ea8fba232ef861f1","tier":null}],"members":[{"type":"individual","id":"5fe81dea2f61079a","login":"deamonpog","name":"Chathura Jayalath","avatar_url":"https://avatars-next.observableusercontent.com/1bc13a0724d43e94c26de301357a2897d22e5c4e01e7f160ea8fba232ef861f1","tier":null,"role":"editor"}],"comments":[],"custom_thumbnail":false,"trashed":false,"lapsed":null,"subscribed":null,"forks":1,"collection":null,"type":"notebook","body":{"title":"1-D data analysis Chathura Jayalath [UCFID:3948890]","cells":[{"id":0,"value":"md`## CAP 5738: Assignment 2: \n# 1-D data analysis Chathura Jayalath [UCFID:3948890]`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":48,"value":"md`___\n## Plots`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":67,"value":"md`### Strip Plot of Eruptions`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":70,"value":"{\n let trace1 = {\n x:eruptions,\n y:Array(eruptions.length).fill(''),\n type:'scatter',\n mode:'markers',\n marker: { color: 'rgba(17, 157, 255,0.5)', size: 5}\n }\n let layout = {\n title: {\n text:'Strip Plot of Eruptions',\n font: {\n family: 'Open Sans',\n size: 24\n },\n xref: 'paper'\n },\n xaxis: {\n title: {\n text: 'Eruption Durations (minutes)',\n font: {\n family: 'Open Sans',\n size: 18,\n color: '#7f7f7f'\n }\n },\n }\n }\n const div = DOM.element('div');\n Plotly.newPlot(div, [trace1], layout)\n return div\n}","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":122,"value":"md`___\n### Jitter Plot of Eruptions`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":108,"value":"{\n let inJitterAmount = 1\n \n let trace1 = {\n x:eruptions,\n y:Array(eruptions.length).fill('').map(x => Math.random() * inJitterAmount - inJitterAmount/2),\n type:'scatter',\n mode:'markers',\n marker: { color: 'rgba(17, 157, 255,0.5)', size: 5}\n }\n let layout = {\n autosize: false,\n title: {\n text:'Jitter Plot of Eruptions',\n font: {\n family: 'Open Sans',\n size: 24\n },\n xref: 'paper'\n },\n xaxis: {\n title: {\n text: 'Eruption Durations (minutes)',\n font: {\n family: 'Open Sans',\n size: 18,\n color: '#7f7f7f'\n }\n },\n },\n yaxis: {\n showticklabels: false\n }\n }\n const div = DOM.element('div');\n Plotly.newPlot(div, [trace1], layout)\n return div\n}","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":51,"value":"md`___\n### Histogram of Eruptions`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":57,"value":"viewof inNumBins = {\n const form = html``;\n form.i.oninput = () => form.o.value = `${Math.round((form.value = form.i.valueAsNumber).toFixed(1))} Number of Bins`;\n form.i.oninput();\n return form;\n}","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":54,"value":"{\n let numOfBins = Math.round(inNumBins)\n let histData = eruptions\n \n let trace1 = {\n x:histData,\n type:'histogram',\n xbins: {size: (d3.max(histData) - d3.min(histData)) / (numOfBins - 1)},\n marker: {\n color: 'green',\n line: {\n color: \"black\", \n width: 1\n }\n\t }\n }\n \n let layout = {\n title: {\n text:'Histogram of Eruptions',\n font: {\n family: 'Open Sans',\n size: 24\n },\n xref: 'paper'\n },\n xaxis: {\n title: {\n text: 'Eruption Duration (minutes)',\n font: {\n family: 'Open Sans',\n size: 18,\n color: '#7f7f7f'\n }\n }\n },\n yaxis: {\n title: {\n text: 'Count',\n font: {\n family: 'Open Sans',\n size: 18,\n color: '#7f7f7f'\n }\n },\n }\n }\n \n const div = DOM.element('div');\n Plotly.newPlot(div, [trace1], layout)\n return div\n}","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":142,"value":"md`___\n### Kernal Density Estimation Plot of Eruptions`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":216,"value":"viewof inKernalFunctionType = DOM.select(['Epanechnikov','Gaussian','Uniform','Triangular','Tricube','Cosine'])","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":154,"value":"viewof inBandwidth = {\n const form = html``;\n form.i.oninput = () => form.o.value = `${(form.value = form.i.valueAsNumber).toFixed(3)} Bandwidth`;\n form.i.oninput();\n return form;\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":331,"value":"viewof inAmplitude = {\n const form = html``;\n form.i.oninput = () => form.o.value = `${(form.value = form.i.valueAsNumber).toFixed(3)} Amplitude`;\n form.i.oninput();\n return form;\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":146,"value":"$35","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":210,"value":"md`#### KDE Generator Function`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":148,"value":"function generateKernalDensity(inputArray, bandwidth, amplitude, kernalFunc) {\n let kernalStepSize = 0.001 // must be greater than 0\n let kernalStepsPerTick = Math.ceil(1/kernalStepSize)\n let xVals = Array.from(Array(Math.ceil((d3.max(inputArray) - d3.min(inputArray) + 2)) * kernalStepsPerTick).keys()).map(x => x * kernalStepSize + d3.min(inputArray) - 1)\n let yVals = Array.from(xVals)\n for (let i = 0; i < xVals.length; i++) {\n let theValue = 0\n for (let j = 0; j < inputArray.length; j++){\n let observedVal = inputArray[j]\n let shiftDist = xVals[i] - observedVal\n theValue += kernalFunc(shiftDist / bandwidth);\n }\n yVals[i] = amplitude * theValue / (bandwidth * inputArray.length)\n }\n return [xVals, yVals]\n}","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":213,"value":"md`#### Different Kernal Functions`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":150,"value":"function kernalEpanechnikovFactory(){\n return u => (Math.abs(u) < 1) ? 0.75 * ( 1 - (u * u) ) : 0;\n}","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":241,"value":"function kernalGaussianFactory(){\n return u => Math.exp(-0.5 * u * u) / Math.sqrt(2 * Math.PI)\n}","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":246,"value":"function kernalUniformFactory(){\n return u => (Math.abs(u) <= 1)? 1/2 : 0;\n}","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":258,"value":"function kernalTriangularFactory(){\n return u => (Math.abs(u) <= 1) ? 1 - Math.abs(u) : 0;\n}","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":397,"value":"function kernalTricubeFactory(){\n const a = 70/81;\n return u => (Math.abs(u) <= 1) ? a * Math.pow((1 - Math.pow(Math.abs(u),3)), 3) : 0;\n}","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":404,"value":"function kernalCosineFactory(){\n const pi4 = Math.PI / 4;\n const pi2 = Math.PI / 2;\n return u => (Math.abs(u) <= 1) ? pi4 * Math.cos(pi2 * u) : 0;\n}","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":441,"value":"function generateKDEPlot(inputData, bandwidth, amplitude, kernalFunc, numOfBins){\nlet data = generateKernalDensity(inputData, bandwidth, amplitude, kernalFunc)\n let trace2 = {\n x: data[0],\n y: data[1],\n type: 'scatter',\n name: 'KDE'\n };\n \n let histData = inputData\n let trace1 = {\n x:histData,\n type:'histogram',\n histnorm : 'probability',\n name: 'Histogram',\n xbins: {size: (d3.max(histData) - d3.min(histData)) / (numOfBins - 1)},\n /*marker: {\n color: 'white',\n line: {\n color: \"black\", \n width: 1\n }\n }*/\n };\n return [trace1, trace2]\n}","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":409,"value":"{\n let Data = Array.from(Array(15).keys()).map(x=> x+5)\n let xvalues = Array.from(Array(170).keys() ).map(x => x * 0.1 + 5)\n let yvalues = Array.from(xvalues);\n let bandwidth = 5;\n for (let i =0; i < xvalues.length; i++){\n yvalues[i] = 0;\n for(let k=0; k < Data.length; k++){ \n yvalues[i] += (Math.abs( (xvalues[i] - Data[k])/bandwidth ) <= 1)? 0.5 : 0 ; \n } \n yvalues[i] /= (bandwidth * Data.length)\n }\n //return [Data, xvalues, yvalues]\n \n let trace_Cosine = {\n x : xvalues,\n y : yvalues,\n name : 'Cosine',\n type : 'scatter'\n }\n let histData = Data\n let trace1 = {\n x:histData,\n type:'histogram',\n xbins: {size: (d3.max(histData) - d3.min(histData)) / (20 - 1)},\n marker: {\n color: 'white',\n line: {\n color: \"black\", \n width: 1\n }\n\t }\n };\n \n const div = DOM.element('div');\n Plotly.newPlot(div, [trace1, trace_Cosine])\n return div\n}","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":432,"value":"Array.from(Array(170).keys() ).map(x => x * 0.1 + 5)","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":19,"value":"md`___\n## Importing Libraries`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":24,"value":"Plotly = require(\"https://cdn.plot.ly/plotly-latest.min.js\")","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":26,"value":"d3 = require(\"d3\")","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":29,"value":"md`___\n## Importing Test Data`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":35,"value":"oldFaithful = d3.tsv(\"https://gist.githubusercontent.com/mbostock/e3f4376d54e02d5d43ae32a7cf0e6aa9/raw/dcb23e8f6eefdbc4ada97d6eda22b2a4f256c263/faithful.tsv\", d3.autoType)","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":37,"value":"extract = attribute=>oldFaithful.map(d=>d[attribute])","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":39,"value":"eruptions = extract('eruptions')","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"}],"files":"$W36","stdlib":"1","titling":"auto"}} 34:"$33:body"