31:T1162,chart = { // define parameters const width = 1000; const height = 500; const margin = 30; const radius = (height-(margin*2)) / 2; const dotRadius = 4; const axisCircles = 4; const axisLabelFactor = 1.12; const wrapWidth = 60; const radarLine = d3.lineRadial() .curve(d3["curveLinearClosed"]) .radius(d => rScale(d)) .angle((d, i) => -angleSlice*i); const rScale = d3.scaleLinear() .domain([0, maxValue]) .range([0, radius]) const svg = d3.select(DOM.svg(width, height+(margin*2))) .style('preserveAspectRatio', "xMinYMin met"); const containerWidth = width-(margin*2); const containerHeight = height-(margin*2); const container = svg.append('g') .attr("width", containerWidth) .attr("height", containerHeight) .attr('transform', `translate(${(width/3)+margin}, ${(height/2)+margin})`); // draw the grid var axisGrid = container.append("g") .attr("class", "axisWrapper"); axisGrid.selectAll(".levels") .data(d3.range(1,(axisCircles+1)).reverse()) .enter() .append("circle") .attr("class", "gridCircle") .attr("r", (d, i) => radius/axisCircles*d) .style("fill", "#CDCDCD") .style("stroke", "#CDCDCD") .style("fill-opacity", 0.1); // draw scale at circles var gridGraduation = container.append("g") .attr("class", "gridGraduation"); gridGraduation.selectAll(".levels") .data(d3.range(1,(axisCircles+1)).reverse()) .enter() .append("text") .attr("class", "graduation") .style("font-size", "11px") .attr("text-anchor", "middle") .attr("font-family", "monospace") .attr("fill","gray") .attr("dy", "0.35em") .attr("x", (d, i) => 0) .attr("y", (d, i) => 0 - radius/axisCircles*d) .text(d => String(Math.round(d*maxValue/axisCircles*10)/10)); // draw the axes and labels const axis = axisGrid.selectAll(".axis") .data(axesDomain) .enter() .append("g") .attr("class", "axis"); axis.append("line") .attr("x1", 0) .attr("y1", 0) .attr("x2", (d, i) => rScale(maxValue) * Math.cos(-angleSlice*i - Math.PI/2)) .attr("y2", (d, i) => rScale(maxValue) * Math.sin(-angleSlice*i - Math.PI/2)) .attr("class", "line") .style("stroke", "#CDCDCD") .style("stroke-width", "2px"); axis.append("text") .attr("class", "legend") .style("font-size", "11px") .attr("text-anchor", "middle") .attr("font-family", "monospace") .attr("dy", "0.35em") .attr("x", (d, i) => rScale(maxValue * axisLabelFactor) * Math.cos(-angleSlice*i - Math.PI/2)) .attr("y", (d, i) => rScale(maxValue * axisLabelFactor) * Math.sin(-angleSlice*i - Math.PI/2)) .text(d => bias_dimension_labels_to_show[d]); // draw the lines const plots = container.append('g') .selectAll('g') .data(formattedData) .join('g') // .attr("data-name", (d, i) => type(i)) // .attr("fill", "none") // .attr("stroke", "steelblue"); plots.append('path') .attr("d", d => radarLine(d.map(v => v.value))) .data(selected_monitor_sets) .attr("fill", (d, i) => color[d]) .attr("fill-opacity", 0.1) .attr("stroke", (d, i) => color[d]) .attr("stroke-width", 2); // plots.selectAll("circle") // .data(d => d) // .join("circle") // .attr("r", dotRadius) // .attr("cx", (d,i) => rScale(d.value) * Math.cos(-angleSlice*(i)-Math.PI/2)) // .attr("cy", (d,i) => rScale(d.value) * Math.sin(-angleSlice*(i)-Math.PI/2)) // .style("fill-opacity", 0.8); //legend const labels = selected_monitor_sets const maxword = d3.max(labels, d =>d.length) const r = width/110 const x = width/2.3 - 8*r - 4*maxword; const y = -height/2 +4*r ;//cfg.h / 2 + 100; var legend = container.selectAll("mydots") .data(labels) .enter() .append("circle") .attr("cx", x) .attr("cy", function(d,i){ return y + i*25}) // 100 is where the first dot appears. 25 is the distance between dots .attr("r", r) .style("fill", (d,i) => color[d]) // .style("filter", "url(#glow)"); container.selectAll("mydots") .data(labels) .enter() .append("text") .attr("x", x + 15) .attr("y", function(d,i){ return y + i*25}) // 100 is where the first dot appears. 25 is the distance between dots .style("fill", (d,i) => color[d]) .style("font-size", "11px") .text(d => d) .attr("text-anchor", "left") .style("alignment-baseline", "middle"); return svg.node(); }32:T46b,async function createData() { // const d = new Date(); // const t0 = d.getTime(); const ids = ["Atlas", "RIS", "RouteViews", "RIS&RouteViews"]; // Array of ids let bias = {}; const responses = await Promise.all( ids.map(async id => { bias[id] = await get_imp_bias(id); // Send request for each id }) ); let dataNew = []; for (let i=0; ie.xlabel == bias_dimension_labels_new[bias_dimensions_selection])[0]; const data_to_plot_filtered = {}; data_to_plot_filtered['feature'] = data_to_plot['feature']; data_to_plot_filtered['xlabel'] = data_to_plot['xlabel']; data_to_plot_filtered['ylabel'] = data_to_plot['ylabel']; if (data_to_plot['bars'] !== undefined) { data_to_plot_filtered['bars'] = {}; let filtered_test_data = Object.keys(data_to_plot['bars']).filter(e => selected_monitor_sets_mapped.includes(e)); for (let i=0; i selected_monitor_sets_mapped.includes(e)); for (let i=0; i { for (let i=0; i< Object.keys(colors).length; i++){ if (key.includes(Object.keys(colors)[i])) { selected_colors[Object.keys(colors)[i]] = colors[Object.keys(colors)[i]] } } }); if (data_to_plot_filtered["bars"] !== undefined) { return Plot.plot({ width: 1200, x: {axis: null}, y: {tickFormat: "s", domain: [0, 1]}, color: {domain: Object.keys(selected_colors), range: Object.values(selected_colors), legend: true}, marks: [ Plot.barY(dist_plot_data_formatted_filtered, { x: "AS", y: "value", fill: d => selected_colors[d["AS"]], fx: d => d[bias_dimensions_selection], // show value when hovered in bar plot title: d => d.value, sort: {x: null, fx: "y", order: "descending"},//, reduce: "max"} }), Plot.axisX({ tickFormat: d => d[bias_dimensions_selection], // tickRotate: -45, label: bias_dimensions_selection, }), Plot.ruleY([0]), ], }) } else { return Plot.plot({ width: 1200, marginBottom: 60, color: {domain: Object.keys(selected_colors), range: Object.values(selected_colors), legend: true}, x: { type: "log", tickRotate: -45, tickFormat: (d) => { const exponent = Math.floor(Math.log10(d)); const base = d / 10 ** exponent; return base.toFixed(1) + "e" + exponent; }, // tickFormat: (d, i, ticks) => { // const exponent = Math.floor(Math.log10(d)); // const base = d / 10 ** exponent; // const multiples = [0, 1, 2, 9, 10, 30, 200, 900, 1000, 2000, 9000, 10000, ]; // if (multiples.includes(i)) { // return base.toFixed(1) + "e" + exponent; // } // return null; // }, }, y: { grid: true, label: `↑ ${data_to_plot_filtered['ylabel']}` }, marks: [ Plot.ruleY([0]), Plot.lineY(dist_plot_data_formatted_filtered, {x: data_to_plot_filtered['xlabel'], y: data_to_plot_filtered['ylabel'], z: "AS", stroke: "AS", sort: {x: null, color: null, z: "AS"} }) ] }) } }34:T649,dist_plot_data_formatted = { let data_to_plot = data_fetched_joined.filter(e=>e.xlabel == bias_dimension_labels_new[bias_dimensions_selection])[0]; let dataArr = []; if (data_to_plot["bars"] !== undefined) { let data_to_plot_bars = data_to_plot['bars']; for (let j=0; j { distr[id] = (id.startsWith("My"))? await get_dist_plots_custom(custom_sets_dict[id], set_numbers_type): await get_dist_plots_imps(id) ; // Send request for each id }) ); let dist_plots_fetched_data_custom = distr["My 1st Custom Set"] let dist_plots_fetched_data_custom1 = distr["My 2nd Custom Set"] let dist_plots_fetched_data_custom2 = distr["My 3rd Custom Set"] let dist_plots_fetched_data_all = distr["all"] let dist_plots_fetched_data_ATLAS = distr["Atlas"] let dist_plots_fetched_data_RIS = distr["RIS"] let dist_plots_fetched_data_RouteViews = distr["RouteViews"] let dist_plots_fetched_data_RISRouteViews = distr["RIS&RouteViews"] for (let i=0; i response.json()); } else if (monitor == 'My 1st Custom Set') { (custom_set.length > 0) ? arr = fetch("https://ai4netmon.csd.auth.gr/api/bias/cause/"+mtype+"/?"+mtype+"="+custom_set.replaceAll(",","&"+mtype+"=")).then((response) => response.json()) : null } else if (monitor == 'My 2nd Custom Set') { (custom_set1.length > 0) ? arr = fetch("https://ai4netmon.csd.auth.gr/api/bias/cause/"+mtype+"/?"+mtype+"="+custom_set1.replaceAll(",","&"+mtype+"=")).then((response) => response.json()) : null } else if (monitor == 'My 3rd Custom Set') { (custom_set2.length > 0) ? arr = fetch("https://ai4netmon.csd.auth.gr/api/bias/cause/"+mtype+"/?"+mtype+"="+custom_set2.replaceAll(",","&"+mtype+"=")).then((response) => response.json()) : null } return arr; }38:[{"id":"112091031385b262a953a7109f87cf7a1b72b7f85fd0e977493c1d8bd291ed531d9be38f892c37091b974e702ff430154ed64e04afbc2683444f25e37ff16191","href":"https://static.observableusercontent.com/files/112091031385b262a953a7109f87cf7a1b72b7f85fd0e977493c1d8bd291ed531d9be38f892c37091b974e702ff430154ed64e04afbc2683444f25e37ff16191","name":"Test_bias_values_for_radar@1.csv","type":"text/csv","lastModified":1646224654967.498,"size":614},{"id":"6d1d8050bceda5892e273de1412b3b478a45e77a2201ac851c98726777e7126c20063b9969806c2fda4513fca123547687bd61173d7be6ca3e943e83e87a51cf","href":"https://static.observableusercontent.com/files/6d1d8050bceda5892e273de1412b3b478a45e77a2201ac851c98726777e7126c20063b9969806c2fda4513fca123547687bd61173d7be6ca3e943e83e87a51cf","name":"bias_values_for_radar_custom.csv","type":"text/csv","lastModified":1666888068807.683,"size":705},{"id":"44b2c68585069158a1f27abbe5de91ad6d04fcce1acfc08a215faf78cb33ef158050f69eeae2f47b11707111d7de52470c43b438233fd17cf6f3c18fb0a2bcdc","href":"https://static.observableusercontent.com/files/44b2c68585069158a1f27abbe5de91ad6d04fcce1acfc08a215faf78cb33ef158050f69eeae2f47b11707111d7de52470c43b438233fd17cf6f3c18fb0a2bcdc","name":"bias_values_for_radar_custom@1.csv","type":"text/csv","lastModified":1666888848298.206,"size":704},{"id":"53f0c2dc556bb14bfa705f6e284e4474fd7ac3886c2637c046e62cbc59af867cc6f23f1f1b220403bac7001dd962723d76919ff547514ec4711db7228ca75849","href":"https://static.observableusercontent.com/files/53f0c2dc556bb14bfa705f6e284e4474fd7ac3886c2637c046e62cbc59af867cc6f23f1f1b220403bac7001dd962723d76919ff547514ec4711db7228ca75849","name":"bias_values_for_radar_custom@2.csv","type":"text/csv","lastModified":1666889379944.997,"size":723},{"id":"6ce260f7e010c13e41a560c0286b276105e5ad12370211b35d132920ffe1f4322188498f8e91b561a792cafc82939fa75a1558079e7cd12cb17be44e5970e980","href":"https://static.observableusercontent.com/files/6ce260f7e010c13e41a560c0286b276105e5ad12370211b35d132920ffe1f4322188498f8e91b561a792cafc82939fa75a1558079e7cd12cb17be44e5970e980","name":"Test_bias_values_for_radar_custom.csv","type":"text/csv","lastModified":1661073279689.938,"size":720}] 2f:{"title":"Bias in Internet Measurement Platforms","cells":[{"id":0,"value":"# Bias in Internet Measurement Platforms\n\nThis notebook visualizes the bias in Internet measurement platforms, based on the analyses of the [AI4NetMon](https://sermpezis.github.io/ai4netmon/) project. For an introduction on the bias of Internet measurement platforms see the [RIPE Labs article](https://labs.ripe.net/author/pavlos_sermpezis/bias-in-internet-measurement-infrastructure/).\n\nThe following radar plot shows: \n- the bias; from 0 (low bias, center of the circle) to 1 (high bias, far from center)\n- for each selected set of monitors (lines/areas of different colors)\n- along different bias dimensions (each radius of the circle)\n\nYou can upload any custom set of monitors to compare their bias, and select which sets of monitors / bias dimensions to visualize.","pinned":false,"hidden":false,"mode":"md"},{"id":599,"value":"[Optional] Select a **custom set** of vantage points. In the box below, add a list of ASNs (only numbers, separated with commas, no spaces; e.g., 174,1299,3333)","pinned":false,"hidden":false,"mode":"md"},{"id":758,"value":"viewof set_numbers_type = {\n const types_array = [\"ASNs\", \"probe IDs\"];\n const set_numbers_type = Inputs.radio(types_array, {label: \"Select the type of list of numbers\", value: types_array[0]});\n set_numbers_type.style.width = \"100%\";\n return set_numbers_type;\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":601,"value":"viewof custom_set = {\n const custom_set = Inputs.text({label: `Custom Set #1 (${set_numbers_type})`});\n custom_set.style.width = \"100%\";\n return custom_set;\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":741,"value":"viewof custom_set1 = {\n const custom_set1 = Inputs.text({label: `Custom Set #2 (${set_numbers_type})`});\n custom_set1.style.width = \"100%\";\n return custom_set1;\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":763,"value":"viewof custom_set2 = {\n const custom_set2 = Inputs.text({label: `Custom Set #3 (${set_numbers_type})`});\n custom_set2.style.width = \"100%\";\n return custom_set2;\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":592,"value":"Select the sets of vantage points to visualize","pinned":false,"hidden":false,"mode":"md"},{"id":578,"value":"viewof checkboxes_monitor_sets = {\n const checkboxes_monitor_sets = Inputs.checkbox(monitor_sets, {label: \"Vantage point sets\", value: monitor_sets});\n checkboxes_monitor_sets.style.width = \"100%\";\n return checkboxes_monitor_sets;\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":597,"value":"Select the bias dimensions to visualize","pinned":false,"hidden":false,"mode":"md"},{"id":494,"value":"viewof checkboxes_bias_dimensions = {\n const checkboxes_bias_dimensions = Inputs.checkbox(Object.keys(bias_dimension_labels_new), {label: \"Bias dimensions\", value: Object.keys(bias_dimension_labels_new)});\n checkboxes_bias_dimensions.style.width = \"100%\";\n return checkboxes_bias_dimensions;\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":104,"value":"$31","pinned":false,"hidden":false,"mode":"ojs"},{"id":164,"value":"### Data","pinned":false,"hidden":false,"mode":"md"},{"id":769,"value":"$32","pinned":false,"hidden":false,"mode":"ojs"},{"id":1038,"value":"function get_imp_bias(imp) {\n return fetch(\"https://ai4netmon.csd.auth.gr/api/bias/\"+imp).then((response) => response.json())\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":1040,"value":"function get_custom_bias(arg_custom_set, arg_set_numbers_type) {\n let custom_data;\n if (arg_custom_set.length > 0){\n let mtype = (arg_set_numbers_type === \"ASNs\") ? \"asn\" : \"probe\";\n custom_data = fetch(\"https://ai4netmon.csd.auth.gr/api/bias/\"+mtype+\"/?\"+mtype+\"=\"+arg_custom_set.replaceAll(\",\",\"&\"+mtype+\"=\")).then((response) => response.json());\n }\n return custom_data\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":771,"value":"data_fetched = createData()","pinned":false,"hidden":false,"mode":"ojs"},{"id":773,"value":"formattedData = selected_monitor_sets.map(m => (data_custom_new.filter(e => bias_dimensions.includes(e.tag)).map(e => ({axis:e.tag, value:e[m]}))))","pinned":false,"hidden":false,"mode":"ojs"},{"id":775,"value":"data_custom_new = {\n let x = JSON.parse(JSON.stringify(data_fetched));\n\n const custom_sets_dict = {\"My 1st Custom Set\": custom_set, \n \"My 2nd Custom Set\": custom_set1, \n \"My 3rd Custom Set\": custom_set2\n }; \n const ids = [\"My 1st Custom Set\", \"My 2nd Custom Set\", \"My 3rd Custom Set\"];\n let bias = {};\n const responses = await Promise.all(\n \tids.map(async id => {\n \t\tbias[id] = await get_custom_bias(custom_sets_dict[id], set_numbers_type); // Send request for each id\n \t})\n );\n\n for (let id=0; id 0){ \n for (var i = 0; i < data_fetched.length; i++) {\n let tt = data_fetched[i][\"tag\"];\n let tk = bias_dimension_labels_new[tt];\n let bias_dict;\n bias_dict = bias[current_custom_set][\"bias\"]\n x[i][current_custom_set] = bias_dict[tk]\n } \n }\n }\n \n return x;\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":777,"value":"##### Monitor Sets","pinned":false,"hidden":false,"mode":"md"},{"id":779,"value":"monitor_sets = [\"RIPE RIS\", \"RIPE Atlas\", \"RouteViews\", \"RIS&RouteViews\", \"My 1st Custom Set\", \"My 2nd Custom Set\", \"My 3rd Custom Set\"]//data.columns.slice(1)","pinned":false,"hidden":false,"mode":"ojs"},{"id":781,"value":"selected_monitor_sets = monitor_sets.filter(e => checkboxes_monitor_sets.includes(e))","pinned":false,"hidden":false,"mode":"ojs"},{"id":783,"value":"##### Bias dimensions","pinned":false,"hidden":false,"mode":"md"},{"id":258,"value":"bias_dimensions = data_fetched.map(o=>o.tag).filter(e => checkboxes_bias_dimensions.includes(bias_dimension_labels_to_show[e]))","pinned":false,"hidden":false,"mode":"ojs"},{"id":787,"value":"bias_dimension_labels_to_show = ({\n \"RIR region\": \"RIR region\",\n \"Country\": \"Country\",\n \"Continent\": \"Continent\",\n \"Customer cone (#ASNs)\": \"Customer cone (#ASNs)\",\n \"Customer cone (#pfxs)\": \"Customer cone (#pfxs)\",\n \"Customer cone (#addresses)\": \"Customer cone (#addresses)\",\n \"AS Hegemony\": \"AS Hegemony\",\n \"CTI origin\": \"CTI origin\",\n \"CTI top\": \"CTI top\",\n \"#neighbors (total)\": \"#neighbors (total)\",\n \"#peers\": \"#peers\",\n \"#customers\": \"#customers\",\n \"#providers\": \"#providers\",\n \"#IXPs\": \"#IXPs\",\n \"#facilities\": \"#facilities\",\n \"Peering policy\": \"Peering policy\",\n \"ASDB C1L1\": \"ASDB C1L1\",\n \"ASDB C1L2\": \"ASDB C1L2\",\n \"Net. type\": \"Net. type\",\n \"Traffic ratio\": \"Traffic ratio\",\n \"Traffic volume\": \"Traffic volume\",\n \"Scope\": \"Scope\",\n \"Personal ASN\": \"Personal ASN\"\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":792,"value":"bias_dimension_labels_new = ({\n \"RIR region\": \"RIR region\",\n \"Country\": \"Location (country)\",\n \"Continent\": \"Location (continent)\",\n \"Customer cone (#ASNs)\": \"Customer cone (#ASNs)\",\n \"Customer cone (#pfxs)\": \"Customer cone (#prefixes)\",\n \"Customer cone (#addresses)\": \"Customer cone (#addresses)\",\n \"AS Hegemony\": \"AS hegemony\",\n \"CTI origin\": \"Country influence (CTI origin)\",\n \"CTI top\": \"Country influence (CTI top)\",\n \"#neighbors (total)\": \"#neighbors (total)\",\n \"#peers\": \"#neighbors (peers)\",\n \"#customers\": \"#neighbors (customers)\",\n \"#providers\": \"#neighbors (providers)\",\n \"#IXPs\": \"#IXPs (PeeringDB)\",\n \"#facilities\": \"#facilities (PeeringDB)\",\n \"Peering policy\": \"Peering policy (PeeringDB)\",\n \"ASDB C1L1\": \"ASDB C1L1\",\n \"ASDB C1L2\": \"ASDB C1L2\",\n \"Net. type\": \"Network type (PeeringDB)\",\n \"Traffic ratio\": \"Traffic ratio (PeeringDB)\",\n \"Traffic volume\": \"Traffic volume (PeeringDB)\",\n \"Scope\": \"Scope (PeeringDB)\",\n \"Personal ASN\": \"Personal ASN\"\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":794,"value":"bias_dimension_labels_chart = {\n const bias_dimension_labels_chart = {};\n for (let i=0; i Math.max(...Object.values(o).filter(v => typeof v === 'number'))))","pinned":false,"hidden":false,"mode":"ojs"},{"id":162,"value":"### Plotting","pinned":false,"hidden":false,"mode":"md"},{"id":270,"value":"##### Plotting functions","pinned":false,"hidden":false,"mode":"md"},{"id":95,"value":"// radarLine = d3.lineRadial()\n// .curve(d3[\"curveLinear\"])\n// .radius(d => rScale(d))\n// .angle((d, i) => -angleSlice*i)","pinned":false,"hidden":false,"mode":"ojs"},{"id":100,"value":"// rScale = d3.scaleLinear()\n// .domain([0, maxValue])\n// .range([0, radius])","pinned":false,"hidden":false,"mode":"ojs"},{"id":102,"value":"// color = d3.scaleOrdinal()\n// .range([\"#EDC951\",\"#CC333F\",\"#00A0B0\",\"#ab3da9\",\"#a6d75b\", \"#115f9a\"])\ncolor = Object({\n 'RIPE Atlas': \"#EDC951\",\n 'RIPE RIS': \"#CC333F\",\n 'RouteViews': \"#00A0B0\",\n 'RIS&RouteViews': \"#0F8C79\",\n 'My 1st Custom Set': \"#ab3da9\",\n 'My 2nd Custom Set': \"#a6d75b\",\n 'My 3rd Custom Set': \"#115f9a\",\n })","pinned":false,"hidden":false,"mode":"ojs"},{"id":225,"value":"##### Plotting parameters","pinned":false,"hidden":false,"mode":"md"},{"id":10,"value":"axesDomain = bias_dimensions","pinned":false,"hidden":false,"mode":"ojs"},{"id":30,"value":"// axisLabelFactor = 1.12","pinned":false,"hidden":false,"mode":"ojs"},{"id":29,"value":"// wrapWidth = 60","pinned":false,"hidden":false,"mode":"ojs"},{"id":43,"value":"\nmaxValue = Math.ceil(max_bias*10)/10 \n","pinned":false,"hidden":false,"mode":"ojs"},{"id":97,"value":"angleSlice = 2*Math.PI/bias_dimensions.length","pinned":false,"hidden":false,"mode":"ojs"},{"id":32,"value":"axisCircles = maxValue*10","pinned":false,"hidden":false,"mode":"ojs"},{"id":20,"value":"axesLength = bias_dimensions.length\n","pinned":false,"hidden":false,"mode":"ojs"},{"id":34,"value":"// dotRadius = 4","pinned":false,"hidden":false,"mode":"ojs"},{"id":36,"value":"// radius = (height-(margin*2)) / 2","pinned":false,"hidden":false,"mode":"ojs"},{"id":40,"value":"// height = 600","pinned":false,"hidden":false,"mode":"ojs"},{"id":38,"value":"// margin = 30","pinned":false,"hidden":false,"mode":"ojs"},{"id":840,"value":"### Distribution Plots","pinned":false,"hidden":false,"mode":"md"},{"id":844,"value":"viewof bias_dimensions_selection = {\n // delete Country from bias dimensions list\n const biasArr = Object.keys(bias_dimension_labels_new);\n biasArr.splice(biasArr.findIndex(e => e === \"Country\"),1);\n biasArr.splice(biasArr.findIndex(e => e === \"ASDB C1L2\"),1);\n const select = Inputs.select(biasArr, {label: \"Bias dimensions\", value: biasArr});\n\n select.style.width = \"100%\";\n return select;\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":847,"value":"#### Plots","pinned":false,"hidden":false,"mode":"md"},{"id":849,"value":"$33","pinned":false,"hidden":false,"mode":"ojs"},{"id":852,"value":"#### Data","pinned":false,"hidden":false,"mode":"md"},{"id":1339,"value":"monitor_sets_Obj = Object({\n \"RIPE Atlas\": \"Atlas\",\n \"RIPE RIS\": \"RIS\",\n \"RouteViews\": \"RouteViews\",\n \"RIS&RouteViews\": \"RIS&RouteViews\",\n \"My 1st Custom Set\": \"My 1st Custom Set\",\n \"My 2nd Custom Set\": \"My 2nd Custom Set\",\n \"My 3rd Custom Set\": \"My 3rd Custom Set\"\n })","pinned":false,"hidden":false,"mode":"ojs"},{"id":1342,"value":"selected_monitor_sets_mapped = {\n const newArr = [];\n newArr.push(\"All ASes\");\n for (let i=0; i selected_monitor_sets_mapped.includes(e['AS']))","pinned":false,"hidden":false,"mode":"ojs"},{"id":854,"value":"$34","pinned":false,"hidden":false,"mode":"ojs"},{"id":858,"value":"##### All Data","pinned":false,"hidden":false,"mode":"md"},{"id":998,"value":"$35","pinned":false,"hidden":false,"mode":"ojs"},{"id":1001,"value":"async function get_dist_plots_imps(imp){\n const data = await fetch(\"https://ai4netmon.csd.auth.gr/api/distributions/\"+imp).then((response) => response.json());\n return data[0]\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":1003,"value":"async function get_dist_plots_custom(arg_custom_set, arg_set_numbers_type){\n if (arg_custom_set.length>0){\n let mtype = (arg_set_numbers_type === \"ASNs\")? \"asn\":\"probe\"\n // console.log(mtype)\n let data = await fetch(\"https://ai4netmon.csd.auth.gr/api/distributions/custom/\"+mtype+\"/?\"+mtype+\"=\"+arg_custom_set.replaceAll(\",\",\"&\"+mtype+\"=\")).then((response) => response.json());\n // console.log(data[0])\n return data[0];\n } else {\n return null; \n }\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":1386,"value":"#### old do not use","pinned":false,"hidden":false,"mode":"md"},{"id":860,"value":"$36","pinned":false,"hidden":false,"mode":"ojs"},{"id":862,"value":"dist_plots_fetched_data_ATLAS = {\n \n const data = await fetch(\"https://ai4netmon.csd.auth.gr/api/distributions/Atlas\").then((response) => response.json());\n const data_returned = data[0];\n return data_returned;\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":864,"value":"dist_plots_fetched_data_RIS = {\n const data = await fetch(\"https://ai4netmon.csd.auth.gr/api/distributions/RIS\").then((response) => response.json());\n const data_returned = data[0];\n return data_returned;\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":866,"value":"dist_plots_fetched_data_RouteViews = {\n const data = await fetch(\"https://ai4netmon.csd.auth.gr/api/distributions/RouteViews\").then((response) => response.json());\n const data_returned = data[0];\n return data_returned;\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":868,"value":"dist_plots_fetched_data_custom = {\n // if (custom_set_formatted !== \"\" && checkboxes_monitor_sets.filter(e => e == \"My 1st Custom Set\").length !== 0) {\n // let data;\n // if (set_numbers_type === \"ASNs\") {\n // data = await fetch(\"https://ai4netmon.csd.auth.gr/api/distributions/custom/asn/?asn=\"+custom_set_formatted).then((response) => response.json());\n // } else {\n // data = await fetch(\"https://ai4netmon.csd.auth.gr/api/distributions/custom/probe/?probe=\"+custom_set_formatted).then((response) => response.json());\n // }\n // const data_returned = data[0];\n // return data_returned;\n // } else return null;\n return get_dist_plots_custom(custom_set, set_numbers_type)\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":870,"value":"dist_plots_fetched_data_custom1 = {\n // if (custom_set_formatted1 !== \"\" && checkboxes_monitor_sets.filter(e => e == \"My 2nd Custom Set\").length !== 0) {\n // let data;\n // if (set_numbers_type === \"ASNs\") {\n // data = await fetch(\"https://ai4netmon.csd.auth.gr/api/distributions/custom/asn/?asn=\"+custom_set_formatted1).then((response) => response.json());\n // } else {\n // data = await fetch(\"https://ai4netmon.csd.auth.gr/api/distributions/custom/probe/?probe=\"+custom_set_formatted1).then((response) => response.json());\n // }\n // const data_returned = data[0];\n // return data_returned;\n // } else return null;\n return get_dist_plots_custom(custom_set1, set_numbers_type)\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":872,"value":"dist_plots_fetched_data_custom2 = {\n // if (custom_set_formatted2 !== \"\" && checkboxes_monitor_sets.filter(e => e == \"My 3rd Custom Set\").length !== 0) {\n // let data;\n // if (set_numbers_type === \"ASNs\") {\n // data = await fetch(\"https://ai4netmon.csd.auth.gr/api/distributions/custom/asn/?asn=\"+custom_set_formatted2).then((response) => response.json());\n // } else {\n // data = await fetch(\"https://ai4netmon.csd.auth.gr/api/distributions/custom/probe/?probe=\"+custom_set_formatted2).then((response) => response.json());\n // }\n // const data_returned = data[0];\n // return data_returned;\n // } else return null;\n return get_dist_plots_custom(custom_set2, set_numbers_type)\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":947,"value":"### Recommendations","pinned":false,"hidden":false,"mode":"md"},{"id":1520,"value":"monitors_index = Object({\n \"RIPE RIS\": \"RIS\",\n \"RIPE Atlas\": \"Atlas\",\n \"RouteViews\": \"RouteViews\",\n \"RIS&RouteViews\": \"RIS&RouteViews\",\n \"My 1st Custom Set\": \"My 1st Custom Set\",\n \"My 2nd Custom Set\": \"My 2nd Custom Set\",\n \"My 3rd Custom Set\": \"My 3rd Custom Set\"\n })","pinned":false,"hidden":false,"mode":"ojs"},{"id":1486,"value":"viewof monitor_set_selection = {\n const select = Inputs.select(monitor_sets, {label: \"Vantage point set\", value: monitor_sets});\n\n select.style.width = \"100%\";\n return select;\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":1469,"value":"viewof searched_data = {\n const search_field = Inputs.search(data_monitor_set_formatted, {label: 'Filter by: Bias Dimension, Value or Difference'});\n\n search_field.style.width = \"100%\";\n return search_field;\n}\n// viewof searched_data = Inputs.search(data_monitor_set_formatted, {label: 'Filter by: Bias Dimension, Value or Difference'});","pinned":false,"hidden":false,"mode":"ojs"},{"id":966,"value":"viewof table_monitor_set = Inputs.table(searched_data, {\n \n // sort: \"TOTAL bias (selected)\",\n width: {\n \"Bias Dimension\": \"40%\",\n \"Value\": \"30%\",\n \"Difference\": \"30%\"\n },\n align: {\n \"Bias Dimension\": \"left\",\n \"Value\": \"left\",\n \"Difference\": \"left\"\n },\n \n columns: [\n \"Bias Dimension\",\n \"Value\",\n \"Difference\"\n ],\n \n header: {\n \"Bias Dimension\": \"Bias Dimension\",\n \"Value\": \"Value\",\n \"Difference\": \"Difference %\"\n },\n\n // format: {\n // \"Bias Dimension\": d => d['Bias Dimension'],\n // \"Value\": d => Object.keys(d),\n // \"Difference\": d => Object.values(d),\n // }\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":955,"value":"#### Data","pinned":false,"hidden":false,"mode":"md"},{"id":1439,"value":"// format data for table input\ndata_monitor_set_formatted = {\n let dataArr = [];\n const data_fetched_table = (monitor_set_selection.includes(\"My\")) ? ((Object.keys(data_fetched_monitor_set).length > 0) ? data_fetched_monitor_set[\"Custom list\"] : 0 ) : data_fetched_monitor_set[monitors_index[monitor_set_selection]];\n for (let i=0; i el['Difference']);","pinned":true,"hidden":false,"mode":"ojs"},{"id":1725,"value":"smallest_diff_widget = {\n if (diff_only_arr.length !== 0) {\n return html`\n

The characteristic ${data_monitor_set_formatted.map(el => el['Difference'] == Math.min(...diff_only_arr) ? el['Bias Dimension'] : '')} with value ${data_monitor_set_formatted.map(el => el['Difference'] == Math.min(...diff_only_arr) ? el['Value'] : '')} is the most underrepresented in the selected set, by a percentage of ${Math.min(...diff_only_arr)} %

\n `\n } else {\n return html`\n

No results

\n `\n }\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":1697,"value":"largest_diff_widget = {\n if (diff_only_arr.length !== 0) {\n return html`\n

The characteristic ${data_monitor_set_formatted.map(el => el['Difference'] == Math.max(...diff_only_arr) ? el['Bias Dimension'] : '')} with value ${data_monitor_set_formatted.map(el => el['Difference'] == Math.max(...diff_only_arr) ? el['Value'] : '')} is the most overrepresented in the selected set, by a percentage of ${Math.max(...diff_only_arr)} %

\n `\n } else {\n return html`\n

No results

\n `\n }\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":159,"value":"### Dependencies","pinned":false,"hidden":false,"mode":"md"},{"id":45,"value":"import {select} from \"@jashkenas/inputs\"\n","pinned":false,"hidden":false,"mode":"ojs"},{"id":46,"value":"import {curveTypes} from \"@palewire/d3-curves-inputs\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":49,"value":"_ = require(\"underscore\")","pinned":false,"hidden":false,"mode":"ojs"},{"id":51,"value":"d3 = require(\"d3@5\")","pinned":false,"hidden":false,"mode":"ojs"}],"files":"$W38","stdlib":"1","titling":"auto"}