2f:T5cd,

${Plot.plot({ width: 1200, color: { scheme: "Tableau10", legend: true }, marks: [ Plot.line(initial_values_data, { x: "X", y: "Y" }), Plot.dot(initial_values_data, { x: "X", y: "Y", fill: "Field", r: 15, tip: true }), Plot.image(initial_values_data, { x: "X", y: "Y", r: 30, src: "FieldUrl" }), Plot.line(initial_values_data, { x: "EnemyX", y: "EnemyY" }), Plot.dot(initial_values_data, { x: "EnemyX", y: "EnemyY", fill: "SecretBossStatus", r: 15, tip: true }), Plot.image(initial_values_data, { x: "EnemyX", y: "EnemyY", r: 30, src: "EnemyUrl" }), ] })}

30:T5c1,

${Plot.plot({ width: 1200, color: { scheme: "Tableau10", legend: true }, marks: [ Plot.line(train_values_data, { x: "X", y: "Y" }), Plot.dot(train_values_data, { x: "X", y: "Y", fill: "Field", r: 15, tip: true }), Plot.image(train_values_data, { x: "X", y: "Y", r: 30, src: "FieldUrl" }), Plot.line(train_values_data, { x: "EnemyX", y: "EnemyY" }), Plot.dot(train_values_data, { x: "EnemyX", y: "EnemyY", fill: "SecretBossStatus", r: 15, tip: true }), Plot.image(train_values_data, { x: "EnemyX", y: "EnemyY", r: 30, src: "EnemyUrl" }), ] })}

31:T5c7,

${Plot.plot({ width: 1200, color: { scheme: "Tableau10", legend: true }, marks: [ Plot.line(result_values_data, { x: "X", y: "Y" }), Plot.dot(result_values_data, { x: "X", y: "Y", fill: "Field", r: 15, tip: true }), Plot.image(result_values_data, { x: "X", y: "Y", r: 30, src: "FieldUrl" }), Plot.line(result_values_data, { x: "EnemyX", y: "EnemyY" }), Plot.dot(result_values_data, { x: "EnemyX", y: "EnemyY", fill: "SecretBossStatus", r: 15, tip: true }), Plot.image(result_values_data, { x: "EnemyX", y: "EnemyY", r: 30, src: "EnemyUrl" }), ] })}

32:T446,images = [ {Field: "Thomas", url: await FileAttachment("ThomasIdle.png").url()}, {Field: "Attack1", url: await FileAttachment("ThomasAttack1.png").url()}, {Field: "Attack2", url: await FileAttachment("ThomasAttack2.png").url()}, {Field: "Damage", url: await FileAttachment("ThomasDamage.png").url()}, {Field: "DualAttack", url: await FileAttachment("ThomasDualAttack.png").url()}, {Field: "ThomasJump", url: await FileAttachment("ThomasJump.png").url()}, {Field: "Kick", url: await FileAttachment("ThomasKick.png").url()}, {Field: "ThomasProtect", url: await FileAttachment("ThomasProtect.png").url()}, {Field: "Ability", url: await FileAttachment("ThomasShoot.png").url()}, {Field: "EnemyDamage", url: await FileAttachment("EnemyDamage.png").url()}, {Field: "SecretBoss", url: await FileAttachment("SecretBossIdle.png").url()}, {Field: "SecretBossProtect", url: await FileAttachment("SecretBossProtect.png").url()}, {Field: "Punch", url: await FileAttachment("SecretBossPunch.png").url()}, {Field: "Shoot", url: await FileAttachment("SecretBossShoot.png").url()}, ]33:Td2c,// Copyright 2018-2023 Observable, Inc. // Released under the ISC license. // https://observablehq.com/@d3/pie-chart function PieChart(data, { name = ([x]) => x, // given d in data, returns the (ordinal) label value = ([, y]) => y, // given d in data, returns the (quantitative) value title, // given d in data, returns the title text width = 640, // outer width, in pixels height = 400, // outer height, in pixels innerRadius = 0, // inner radius of pie, in pixels (non-zero for donut) outerRadius = Math.min(width, height) / 2, // outer radius of pie, in pixels labelRadius = (innerRadius * 0.2 + outerRadius * 0.8), // center radius of labels format = ",", // a format specifier for values (in the label) names, // array of names (the domain of the color scale) colors, // array of colors for names stroke = innerRadius > 0 ? "none" : "white", // stroke separating widths strokeWidth = 1, // width of stroke separating wedges strokeLinejoin = "round", // line join of stroke separating wedges padAngle = stroke === "none" ? 1 / outerRadius : 0, // angular separation between wedges, in radians } = {}) { // Compute values. const N = d3.map(data, name); const V = d3.map(data, value); const I = d3.range(N.length).filter(i => !isNaN(V[i])); // Unique the names. if (names === undefined) names = N; names = new d3.InternSet(names); // Chose a default color scheme based on cardinality. if (colors === undefined) colors = d3.schemeSpectral[names.size]; if (colors === undefined) colors = d3.quantize(t => d3.interpolateSpectral(t * 0.8 + 0.1), names.size); // Construct scales. const color = d3.scaleOrdinal(names, colors); // Compute titles. if (title === undefined) { const formatValue = d3.format(format); title = i => `${N[i]}\n${formatValue(V[i])}`; } else { const O = d3.map(data, d => d); const T = title; title = i => T(O[i], i, data); } // Construct arcs. const arcs = d3.pie().padAngle(padAngle).sort(null).value(i => V[i])(I); const arc = d3.arc().innerRadius(innerRadius).outerRadius(outerRadius); const arcLabel = d3.arc().innerRadius(labelRadius).outerRadius(labelRadius); const svg = d3.create("svg") .attr("width", width) .attr("height", height) .attr("viewBox", [-width / 2, -height / 2, width, height]) .attr("style", "max-width: 100%; height: auto; height: intrinsic;"); svg.append("g") .attr("stroke", stroke) .attr("stroke-width", strokeWidth) .attr("stroke-linejoin", strokeLinejoin) .selectAll("path") .data(arcs) .join("path") .attr("fill", d => color(N[d.data])) .attr("d", arc) .append("title") .text(d => title(d.data)); svg.append("g") .attr("font-family", "sans-serif") .attr("font-size", 10) .attr("text-anchor", "middle") .selectAll("text") .data(arcs) .join("text") .attr("transform", d => `translate(${arcLabel.centroid(d)})`) .selectAll("tspan") .data(d => { const lines = `${title(d.data)}`.split(/\n/); return (d.endAngle - d.startAngle) > 0.25 ? lines : lines.slice(0, 1); }) .join("tspan") .attr("x", 0) .attr("y", (_, i) => `${i * 1.1}em`) .attr("font-weight", (_, i) => i ? null : "bold") .text(d => d); return Object.assign(svg.node(), {scales: {color}}); 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2d:{"title":"[BACKUP] Dual Elemental: Data visualization","cells":[{"id":0,"value":"# [BACKUP] Dual Elemental: Data visualization","pinned":false,"hidden":false,"mode":"md"},{"id":1234,"value":"In this Observable, you'll find the charts for the project \"Disseny i desenvolupament d’un videojoc Musou 2D\namb intel·ligència artificial controlada per una xarxa neuronal\", specifically for the data from the sklearn models in Python, with the goal of visualizing the behavior of each dataset.","pinned":false,"hidden":false,"mode":"html"},{"id":492,"value":"toc({headers: \"h2, h3, h4\", hideStartingFrom: \"Appendix\", skip: \"Set the colors of your marks\"})","pinned":false,"hidden":false,"mode":"ojs"},{"id":608,"value":"## Visualization","pinned":false,"hidden":false,"mode":"md"},{"id":472,"value":"### Values for fields","pinned":false,"hidden":false,"mode":"md"},{"id":1238,"value":"This chart is used to visualize that, in each dataset, at least one of Thomas's movements has been used, and that both he and the Secret Boss have taken damage at some point during the game.","pinned":false,"hidden":false,"mode":"md"},{"id":443,"value":"#### Initial Data","pinned":false,"hidden":false,"mode":"md"},{"id":470,"value":"viewof field_values_selected = Inputs.select(Object.keys(fields), {\n value: \"Attack1\",\n label: \"Pick a field:\"\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":475,"value":"PieChart(initial_field_data, {\n name: d => d.field,\n value: d => d.count,\n width,\n height: 500\n});","pinned":false,"hidden":false,"mode":"ojs"},{"id":617,"value":"#### Train Data","pinned":false,"hidden":false,"mode":"md"},{"id":39,"value":"PieChart(train_field_data, {\n name: d => d.field,\n value: d => d.count,\n width,\n height: 500\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":620,"value":"#### Result Data","pinned":false,"hidden":false,"mode":"md"},{"id":550,"value":"PieChart(result_field_data, {\n name: d => d.field,\n value: d => d.count,\n width,\n height: 500\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":490,"value":"### Position of Thomas' movements","pinned":false,"hidden":false,"mode":"md"},{"id":1240,"value":"The following charts are used to analyze Thomas's positioning when he has performed one of his movements or if either Thomas or the Secret Boss have taken damage. To better interpret these charts, I have added the game's background in a negative style.","pinned":false,"hidden":false,"mode":"md"},{"id":507,"value":"viewof field_thomas_position = Inputs.select(Object.keys(fields), {\n value: \"Attack1\",\n label: \"Pick a field:\"\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":699,"value":"#### Initial Data","pinned":false,"hidden":false,"mode":"md"},{"id":510,"value":"Plot.plot({\n width: 1200,\n color: { \n scheme: \"blues\"\n },\n style: {\n background: `url(${await FileAttachment(\"BackgroundNegative2.jpg\").url()})`,\n backgroundSize: \"cover\"\n },\n marks: [\n Plot.density(initialData, {x: \"X\", y: \"Y\", stroke: \"blue\", strokeWidth: 0.25, bandwidth: 10}),\n Plot.density(initialData, {x: \"X\", y: \"Y\", stroke: \"blue\", thresholds: 4, bandwidth: 10}),\n Plot.dot(initialData, {\n filter: (d) => d[field_thomas_position] == 1,\n x: \"X\",\n y: \"Y\",\n fill: field_thomas_position,\n r: 3,\n tip: true\n }),\n ]\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":702,"value":"#### Train Data","pinned":false,"hidden":false,"mode":"md"},{"id":146,"value":"Plot.plot({\n width: 1200,\n color: {\n scheme: \"blues\"\n },\n style: {\n background: `url(${await FileAttachment(\"BackgroundNegative2.jpg\").url()})`,\n backgroundSize: \"cover\"\n },\n marks: [\n Plot.density(trainData, {x: \"X\", y: \"Y\", stroke: \"blue\", strokeWidth: 0.25, bandwidth: 10}),\n Plot.density(trainData, {x: \"X\", y: \"Y\", stroke: \"blue\", thresholds: 4, bandwidth: 10}),\n Plot.dot(trainData, {\n filter: (d) => d[field_thomas_position] == 1,\n x: \"X\",\n y: \"Y\",\n fill: field_thomas_position,\n r: 3,\n tip: true\n }),\n ]\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":632,"value":"#### Result Data","pinned":false,"hidden":false,"mode":"md"},{"id":566,"value":"Plot.plot({\n width: 1200,\n color: { \n scheme: \"blues\"\n },\n style: {\n background: `url(${await FileAttachment(\"BackgroundNegative2.jpg\").url()})`,\n backgroundSize: \"cover\"\n },\n marks: [\n Plot.density(resultData, {x: \"X\", y: \"Y\", stroke: \"blue\", strokeWidth: 0.25, bandwidth: 10}),\n Plot.density(resultData, {x: \"X\", y: \"Y\", stroke: \"blue\", thresholds: 4, bandwidth: 10}),\n Plot.dot(resultData, {\n filter: (d) => d[field_thomas_position] == 1,\n x: \"X\",\n y: \"Y\",\n fill: field_thomas_position,\n r: 3,\n tip: true\n }),\n ]\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":515,"value":"### Position of Secret Boss' movements","pinned":false,"hidden":false,"mode":"md"},{"id":1246,"value":"The following charts are used to analyze the positioning of SecretBoss when he has performed any of his movements (moveCode). To better interpret these charts, I have added the game's background in a negative style. In this case, the points on the charts are red or similar colors.","pinned":false,"hidden":false,"mode":"md"},{"id":513,"value":"viewof field_move_code_selected = Inputs.select(Object.keys(move_codes), {\n value: \"Shoot\",\n label: \"Pick a field:\"\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":637,"value":"#### Initial Data","pinned":false,"hidden":false,"mode":"md"},{"id":518,"value":"Plot.plot({\n width: 1200,\n color: {\n scheme: \"Reds\"\n },\n style: {\n background: `url(${await FileAttachment(\"BackgroundNegative2.jpg\").url()})`,\n backgroundSize: \"cover\"\n },\n marks: [\n Plot.density(initialData, {x: \"EnemyX\", y: \"EnemyY\", stroke: \"red\", strokeWidth: 0.25, bandwidth: 10}),\n Plot.density(initialData, {x: \"EnemyX\", y: \"EnemyY\", stroke: \"red\", thresholds: 4, bandwidth: 10}),\n Plot.dot(initialData, {\n filter: (d) => d.moveCode == field_move_code_selected,\n x: \"EnemyX\",\n y: \"EnemyY\",\n fill: \"moveCode\",\n r: 3,\n tip: true\n }),\n ]\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":641,"value":"#### Train Data","pinned":false,"hidden":false,"mode":"md"},{"id":435,"value":"Plot.plot({\n width: 1200,\n color: { \n scheme: \"Reds\"\n },\n style: {\n background: `url(${await FileAttachment(\"BackgroundNegative2.jpg\").url()})`,\n backgroundSize: \"cover\"\n },\n marks: [\n Plot.density(trainData, {x: \"EnemyX\", y: \"EnemyY\", stroke: \"red\", strokeWidth: 0.25, bandwidth: 10}),\n Plot.density(trainData, {x: \"EnemyX\", y: \"EnemyY\", stroke: \"red\", thresholds: 4, bandwidth: 10}),\n Plot.dot(trainData, {\n filter: (d) => d.moveCode == field_move_code_selected,\n x: \"EnemyX\",\n y: \"EnemyY\",\n fill: \"moveCode\",\n r: 3,\n tip: true\n }),\n ]\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":648,"value":"#### Result Data","pinned":false,"hidden":false,"mode":"md"},{"id":576,"value":"Plot.plot({\n width: 1200,\n color: { \n scheme: \"Reds\"\n },\n style: {\n background: `url(${await FileAttachment(\"BackgroundNegative2.jpg\").url()})`,\n backgroundSize: \"cover\"\n },\n marks: [\n Plot.density(resultData, {x: \"EnemyX\", y: \"EnemyY\", stroke: \"red\", strokeWidth: 0.25, bandwidth: 10}),\n Plot.density(resultData, {x: \"EnemyX\", y: \"EnemyY\", stroke: \"red\", thresholds: 4, bandwidth: 10}),\n Plot.dot(resultData, {\n filter: (d) => d.moveCode == field_move_code_selected,\n x: \"EnemyX\",\n y: \"EnemyY\",\n fill: \"moveCode\",\n r: 3,\n tip: true\n }),\n ]\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":742,"value":"### Thomas Moves vs Secret Boss Move Codes","pinned":false,"hidden":false,"mode":"md"},{"id":1251,"value":"This chart represents every ten lines of the dataset to facilitate the analysis of the AI's behavior according to the current environment. You can continue studying the following cases automatically with the Play button or navigate through them with the arrows for greater precision. Additionally, this is an image-based chart where the characters and the game background are displayed to aid interpretation. The name of the animation appears in the corresponding color, and each is connected to the next by a line to avoid confusion.","pinned":false,"hidden":false,"mode":"html"},{"id":792,"value":"#### Initial Data","pinned":false,"hidden":false,"mode":"md"},{"id":1021,"value":"viewof position_initial = Scrubber(Array.from({length: initialData.length - 9}, (_, i) => i), {initial: 0, autoplay: false, loop: false, delay: 220})","pinned":false,"hidden":false,"mode":"ojs"},{"id":1058,"value":"Inputs.bind(\n Inputs.button(\n [\n [\"<<\", (value) => 0],\n [\"<\", (value) => {\n if (value > 0) {\n return value - 1\n } return value\n }],\n [\">\", (value) => {\n if (value < initialData.length - 10) {\n return value + 1\n } return value\n }],\n [\">>\", (value) => initialData.length - 10]\n ],\n { label: \"Buttons:\", value: 0 }\n ),\n viewof position_initial\n)","pinned":false,"hidden":false,"mode":"ojs"},{"id":886,"value":"$2f","pinned":false,"hidden":false,"mode":"html"},{"id":957,"value":"#### Train Data","pinned":false,"hidden":false,"mode":"md"},{"id":771,"value":"viewof position_train = Scrubber(Array.from({length: trainData.length - 9}, (_, i) => i), {initial: 0, autoplay: false, loop: false, delay: 220})","pinned":false,"hidden":false,"mode":"ojs"},{"id":1077,"value":"Inputs.bind(\n Inputs.button(\n [\n [\"<<\", (value) => 0],\n [\"<\", (value) => {\n if (value > 0) {\n return value - 1\n } return value\n }],\n [\">\", (value) => {\n if (value < trainData.length - 10) {\n return value + 1\n } return value\n }],\n [\">>\", (value) => trainData.length - 10]\n ],\n { label: \"Buttons:\", value: 0 }\n ),\n viewof position_train\n)","pinned":false,"hidden":false,"mode":"ojs"},{"id":962,"value":"$30","pinned":false,"hidden":false,"mode":"html"},{"id":967,"value":"#### Result Data","pinned":false,"hidden":false,"mode":"md"},{"id":803,"value":"viewof position_result = Scrubber(Array.from({length: resultData.length - 9}, (_, i) => i), {initial: 0, autoplay: false, loop: false, delay: 220})","pinned":false,"hidden":false,"mode":"ojs"},{"id":1085,"value":"Inputs.bind(\n Inputs.button(\n [\n [\"<<\", (value) => 0],\n [\"<\", (value) => {\n if (value > 0) {\n return value - 1\n } return value\n }],\n [\">\", (value) => {\n if (value < resultData.length - 10) {\n return value + 1\n } return value\n }],\n [\">>\", (value) => resultData.length - 10]\n ],\n { label: \"Buttons:\", value: 0 }\n ),\n viewof position_result\n)","pinned":false,"hidden":false,"mode":"ojs"},{"id":969,"value":"$31","pinned":false,"hidden":false,"mode":"html"},{"id":528,"value":"### Position of Move Code","pinned":false,"hidden":false,"mode":"md"},{"id":1244,"value":"The pie chart is used to display the total number of times each moveCode has been activated in each dataset. The other charts aims to show the area where the moveCodes have been used the most, depending on the dataset being analyzed.","pinned":false,"hidden":false,"mode":"md"},{"id":652,"value":"#### Initial Data","pinned":false,"hidden":false,"mode":"md"},{"id":530,"value":"PieChart(get_values_field(initialData, \"moveCode\"), {\n name: d => d.field,\n value: d => d.count,\n width,\n height: 500\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":532,"value":"Plot.plot({\n width: 1200,\n color: {\n scheme: \"Tableau10\",\n legend: true\n },\n marks: [\n Plot.voronoi(initialData, {x: \"EnemyX\", y: \"EnemyY\", fill: \"moveCode\", tip: true}),\n ]\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":1221,"value":"Plot.plot({\n width: 1200,\n color: {\n scheme: \"Tableau10\",\n legend: true\n },\n marks: [\n Plot.hull(initialData, {x: \"EnemyX\", y: \"EnemyY\", fill: \"moveCode\", fillOpacity: 0.5, tip: true}),\n ]\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":1109,"value":"Plot.plot({\n width: 1200,\n color: {\n scheme: \"Tableau10\",\n legend: true\n },\n marks: [\n Plot.hull(initialData, {x: \"EnemyX\", y: \"EnemyY\", fill: \"moveCode\", fy: \"moveCode\", fillOpacity: 1, tip: true}),\n Plot.frame()\n ]\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":654,"value":"#### Train Data","pinned":false,"hidden":false,"mode":"md"},{"id":404,"value":"PieChart(get_values_field(trainData, \"moveCode\"), {\n name: d => d.field,\n value: d => d.count,\n width,\n height: 500\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":245,"value":"Plot.plot({\n width: 1200,\n color: {\n scheme: \"Tableau10\",\n legend: true\n },\n marks: [\n Plot.voronoi(trainData, {x: \"EnemyX\", y: \"EnemyY\", fill: \"moveCode\", tip: true})\n ]\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":1206,"value":"Plot.plot({\n width: 1200,\n color: {\n scheme: \"Tableau10\",\n legend: true\n },\n marks: [\n Plot.hull(trainData, {x: \"EnemyX\", y: \"EnemyY\", fill: \"moveCode\", fillOpacity: 0.5, tip: true})\n ]\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":1224,"value":"Plot.plot({\n width: 1200,\n color: {\n scheme: \"Tableau10\",\n legend: true\n },\n marks: [\n Plot.hull(trainData, {x: \"EnemyX\", y: \"EnemyY\", fill: \"moveCode\", fy: \"moveCode\", fillOpacity: 1, tip: true}),\n Plot.frame()\n ]\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":659,"value":"#### Result Data","pinned":false,"hidden":false,"mode":"md"},{"id":586,"value":"PieChart(get_values_field(resultData, \"moveCode\"), {\n name: d => d.field,\n value: d => d.count,\n width,\n height: 500\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":593,"value":"Plot.plot({\n width: 1200,\n color: {\n scheme: \"Tableau10\",\n legend: true\n },\n marks: [\n Plot.voronoi(resultData, {x: \"EnemyX\", y: \"EnemyY\", fill: \"moveCode\", tip: true})\n ]\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":1210,"value":"Plot.plot({\n width: 1200,\n color: {\n scheme: \"Tableau10\",\n legend: true\n },\n marks: [\n Plot.hull(resultData, {x: \"EnemyX\", y: \"EnemyY\", fill: \"moveCode\", fillOpacity: 0.5, tip: true})\n ]\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":1227,"value":"Plot.plot({\n width: 1200,\n color: {\n scheme: \"Tableau10\",\n legend: true\n },\n marks: [\n Plot.hull(resultData, {x: \"EnemyX\", y: \"EnemyY\", fill: \"moveCode\", fy: \"moveCode\", fillOpacity: 1, tip: true}),\n Plot.frame()\n ]\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":51,"value":"## Data transformation","pinned":false,"hidden":false,"mode":"md"},{"id":787,"value":"// Get values with id\ninitial_values_data = getListValues(initialData, position_initial);","pinned":false,"hidden":false,"mode":"ojs"},{"id":740,"value":"// Get values with id\ntrain_values_data = getListValues(trainData, position_train);","pinned":false,"hidden":false,"mode":"ojs"},{"id":789,"value":"// Get values with id\nresult_values_data = getListValues(resultData, position_result);","pinned":false,"hidden":false,"mode":"ojs"},{"id":931,"value":"function findImageByField(fieldName, player) {\n return images.find(image => image.Field === fieldName) || \n images.find(image => image.Field.includes(player + fieldName)) ||\n images.find(image => image.Field == player);\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":759,"value":"function getListValues(data, position) {\n const list = [];\n for(var i=position; i {\n if (!valuesField[row[field]]) {\n valuesField[row[field]] = 0;\n }\n valuesField[row[field]] += 1;\n });\n\n return Object.entries(valuesField).map(([field, count]) => ({ field, count }));\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":86,"value":"fields = {\n const not_fields = [\"X\", \"Y\", \"EnemyX\", \"EnemyY\", \"Distance\", \"moveCode\"]\n const train_set = new Set();\n\n trainData.forEach(object => {\n Object.keys(object).forEach(key => {\n if (!not_fields.includes(key)) {\n train_set.add(key);\n }\n })\n });\n\n return Array.from(train_set).reduce((a, v) => ({ ...a, [v]: v}), {}) \n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":420,"value":"move_codes = {\n const moveCodeSet = new Set();\n\n trainData.forEach(row => {\n moveCodeSet.add(row.moveCode);\n });\n\n return Array.from(moveCodeSet).reduce((a, v) => ({ ...a, [v]: v}), {})\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":451,"value":"## Tables","pinned":false,"hidden":false,"mode":"md"},{"id":457,"value":"SELECT * FROM \"initialData\"","pinned":false,"hidden":false,"mode":"sql","output":"data","database":"var:initialData"},{"id":465,"value":"Select * From trainData","pinned":false,"hidden":false,"mode":"sql","output":"","database":"var:trainData"},{"id":580,"value":"Select * From resultData","pinned":false,"hidden":false,"mode":"sql","output":"data1","database":"var:resultData"},{"id":7,"value":"## Datasets","pinned":false,"hidden":false,"mode":"md"},{"id":446,"value":"initialData = FileAttachment(\"initial2024-04-22_12-43-42.json\").json()","pinned":false,"hidden":false,"mode":"ojs"},{"id":34,"value":"trainData = FileAttachment(\"train2024-04-27_07-55-41@1.json\").json()","pinned":false,"hidden":false,"mode":"ojs"},{"id":558,"value":"resultData = FileAttachment(\"results2024-04-27_12-49-07@3.json\").json()","pinned":false,"hidden":false,"mode":"ojs"},{"id":897,"value":"$32","pinned":false,"hidden":false,"mode":"ojs"},{"id":46,"value":"## Libraries and others","pinned":false,"hidden":false,"mode":"md"},{"id":48,"value":"$33","pinned":false,"hidden":false,"mode":"ojs"},{"id":494,"value":"import {toc} from \"@nebrius/indented-toc\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":1011,"value":"import {Scrubber} from \"@mbostock/scrubber\"","pinned":false,"hidden":false,"mode":"ojs"}],"files":"$W34","stdlib":"1","titling":"auto"}