28:null 29:["$","title",null,{"children":"O | I001962 | Observable"}] 2e:T46e,message = { let i = 0; const text = "OODA Loop"; let message; while (i < text.length) { await Promises.delay(40); let span = html`${text.substr(i, 1)}`; span.style.color = d3.interpolateViridis(i / text.length); span.setAttribute("value", i); span.setAttribute("ascending", "ascending"); if (i == 0) { message = html`${span}`; } else { message = html`${message.innerHTML}${span}`; } i = i + 1; yield html`

${message}

`; } while (i >= text.length) { await Promises.delay(100); let current_message = html`

${message}

`; let current_spans = current_message.firstChild.children; for (let span of current_spans) { let v = +span.getAttribute("value"); if ((v == text.length) | (v == -1)) { span.toggleAttribute("ascending"); } span.hasAttribute("ascending") ? v-- : v++; span.setAttribute("value", v); span.style.color = d3.interpolateViridis(v / text.length); // span.style.fontSize = Math.sin(v / 10) + 20 + "px"; } i = i + 1; yield current_message; } }2f:T1c59,{ const visHeight = 2 * height + margin.top + margin.bottom; const red = 'firebrick', blue = 'steelblue'; const container = d3 .create('svg') .attr('width', width + margin.left + margin.right) .attr('height', visHeight); const defs = container.append('defs'); const clipRect = defs .append('clipPath') .attr('id', 'area-clip') .append("rect") .attr("x", 0) .attr("y", 0) .attr("width", xScale(startValue)) .attr("height", height); const lineChart = container .append('g') .attr('id', 'chart') .attr('transform', `translate(${margin.left}, ${margin.top})`); lineChart .append('g') .attr('class', 'axis axis_y') .call( d3 .axisLeft(qfYScale) .ticks(10) .tickFormat(d3.format(",.3f")) ); const curve = d3 .area() .x(d => xScale(d.x)) .y1(d => qfYScale(d.p_less_than_x)) .y0(qfYScale(0)); lineChart .append("path") .attr("d", curve(qfData)) .attr("fill", blue) .attr("stroke", blue); lineChart .append("path") .attr("d", curve(qfData)) .attr("fill", red) .attr("stroke", red) .attr("clip-path", 'url(#area-clip)'); const curveTicksG = container .append("g") .attr("transform", `translate(${margin.left}, ${margin.top})`); const dotplotTicksG = container.append("g"); curveTicksG .selectAll('.x-guideline') .data(quantiles) .enter() .append("line") .attr("class", "x-guideline") .attr("stroke", "lightgrey") .attr("stroke-width", "0.1px") .attr("stroke-dasharray", "5,2") .attr("x1", 0) .attr("y1", d => qfYScale(d.p_less_than_x)) .attr("x2", d => xScale(d.x)) .attr("y2", d => qfYScale(d.p_less_than_x)); curveTicksG .selectAll('.y-tick') .data(quantiles) .enter() .append("line") .attr("class", "y-guideline") .attr("stroke", "lightgrey") .attr("stroke-dasharray", "5,2") .attr("x1", d => xScale(d.x)) .attr("y1", d => yScale(0) - (yScale(0) - qfYScale(d.p_less_than_x))) .attr("x2", d => xScale(d.x)) .attr("y2", d => visHeight - (margin.top + margin.bottom)); const dotplotContainer = container .append('g') .attr("id", "dotplot-container") .attr("transform", `translate(${margin.left}, ${visHeight / 2})`); dotplotContainer .append('g') .attr('class', 'axis axis_x') .attr('transform', `translate(0, ${height})`) .call(d3.axisBottom(xScale)); const bins = dotplotContainer.selectAll(".gBin").data(qfStacks); const binContainerEnter = bins .enter() .append("g") .attr("class", "gBin") .attr("transform", d => `translate(${xScale(d.x)}, ${height})`) .attr("fill", d => (d.x - qBinwidth / 2 <= startValue ? red : blue)); binContainerEnter .selectAll("circle") .data(d => d.values.map((p, i) => { return { idx: i, value: p, radius: xScale(qBinwidth / 2) }; }) ) .enter() .append("circle") .attr("cx", 0) .attr("cy", d => -d.idx * 2 * d.radius - d.radius) .attr("r", d => d.radius) .attr("fill-opacity", 1); const lineG = container.append("g").attr("id", "q-line-g"); const lineY = lineG .append("line") .attr("id", "q-line-y") .attr("x1", xScale(startValue) + margin.left) .attr("x2", xScale(startValue) + margin.left) .attr("y1", visHeight - margin.top) .attr("y2", qfYScale(getPercentageForX(startValue) / 100) + margin.top) .attr("stroke", "black") .attr("stroke-width", "1px"); const lineX = lineG .append("line") .attr("id", "q-line-x") .attr("x1", margin.left) .attr("x2", xScale(startValue) + margin.left) .attr("y1", qfYScale(getPercentageForX(startValue) / 100) + margin.top) .attr("y2", qfYScale(getPercentageForX(startValue) / 100) + margin.top) .attr("stroke", "black") .attr("stroke-width", "1px"); lineG .append('text') .attr("x", xScale(startValue) + margin.left + 5) .attr("y", (visHeight + 100) / 2) .attr("id", "q-line-text") .attr("font-size", "10px") .text(`${getPercentageForX(startValue).toFixed(2)}%`); const mouseOverlay = container .append("rect") .attr("x", margin.left) .attr("y", margin.top) .attr("width", width) .attr("height", visHeight - margin.top - margin.bottom + 10) .attr("fill", "yellow") .attr("opacity", 0.0); container.append("g").attr("id", "explanation-g"); explainResults(container.select("#explanation-g"), qfStacks, startValue); mouseOverlay.on("click", event => { var coords = d3.pointer(event); console.log(xScale(18)); console.log(coords[0]); const xValue = xScale.invert(coords[0] - margin.left); console.log(xValue); mutable startValue = xValue; }); /* mouseOverlay.on("click", function() { var coords = d3.mouse(this); console.log(xScale(18)); console.log(coords[0]); const xValue = xScale.invert(coords[0] - margin.left); console.log(xValue); mutable startValue = xValue; }); */ function explainResults(group, stacks, xValue) { const selDots = qfStacks.filter(c => c.x - qBinwidth / 2 <= xValue); console.log(selDots, xValue, qBinwidth); const lastStackX = selDots.length == 0 ? 0 : selDots[selDots.length - 1].x; group.html( getSVGText( selDots.map(c => c.values.length).reduce((acc, val) => val + acc, 0), n_quantiles, lastStackX, getPercentageForX(xValue), xValue, minTommss(qBinwidth / 2, true) ) ); } function getPercentageForX(xValue) { const insertIdx = d3.bisectLeft(x, xValue); const perc = (((xValue - qfData[insertIdx - 1].x) / (qfData[insertIdx].x - qfData[insertIdx - 1].x)) * (qfData[insertIdx].p_less_than_x - qfData[insertIdx - 1].p_less_than_x) + qfData[insertIdx - 1].p_less_than_x) * 100; return perc; } function getSVGText(dots, totalDots, dotsX, percent, xValue, timeWidth) { return ` TODO UPDATE THIS - and cursor % -- The dotplot says: "You will miss the bus ${dots} out of ${totalDots} times (${( (dots * 100) / totalDots ).toFixed( 2 )}%) if you arrive in approximately (±${timeWidth}) ${minTommss( dotsX )}" The CDF says: "You will miss the bus ${Math.ceil( percent )} out of 100 times (${percent.toFixed( 2 )}%) if you arrive in exactly ${minTommss( xValue )}" `; } function minTommss(minutes, short) { var min = Math.floor(Math.abs(minutes)); var sec = Math.floor((Math.abs(minutes) * 60) % 60); if (short) return `${min}m:${sec}s`; else return `${min} minutes and ${sec} seconds`; } return container.node(); }30:[] 2c:{"id":"77f73ea23a1c6189","slug":"ooda-loop","title":"O","thumbnail":"44e79fb2fd73472ffeea73aa54b1dfc05958707023e7a28679b5e76c585fee42","access_level":"public","create_time":"$D2020-12-27T22:32:56.309Z","update_time":"$D2020-12-29T22:25:35.771Z","view_time":null,"first_public_time":"$D2020-12-29T03:08:47.146Z","has_unpublished_edits":null,"fork":false,"stars":0,"starred":false,"owner":{"type":"team","id":"436acea24096daff","login":"i001962","name":"I001962","avatar_url":"https://avatars-next.observableusercontent.com/7212e15f56a82fc2cc6f6e4457694ecaa8dc7341f61c1244b492e2649b21ddc8","tier":"starter_2024"},"version":720,"publish_version":720,"role":null,"authored":false,"authors":[{"type":"individual","id":"3f12d775ca68a2fb","login":"i001962","name":"I001962","avatar_url":"https://avatars-next.observableusercontent.com/7212e15f56a82fc2cc6f6e4457694ecaa8dc7341f61c1244b492e2649b21ddc8","tier":null}],"members":[{"type":"individual","id":"3f12d775ca68a2fb","login":"i001962","name":"I001962","avatar_url":"https://avatars-next.observableusercontent.com/7212e15f56a82fc2cc6f6e4457694ecaa8dc7341f61c1244b492e2649b21ddc8","tier":null,"role":"editor"}],"comments":[],"custom_thumbnail":false,"trashed":false,"lapsed":null,"subscribed":null,"forks":1,"collection":null,"type":"notebook","body":{"title":"O","cells":[{"id":0,"value":"$2e","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":719,"value":"md` \n### Collect new Observations, Orient (with existing knowledge), Decide and Act...`","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":208,"value":"md`## Observation\nSlide the slider to generate input observations. Move it around until you think you have about 100 observations`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":25,"value":"viewof uniSlider = slider({\n min: 1,\n max: 100,\n step: 1,\n value: 1,\n format: \",\",\n description: \"Load histogram by sliding\"\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":215,"value":"md`## Orient\nNew observations are added to the shape of the previous observations. `","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":624,"value":"viewof b1 = button({\n value: \"Generate histogram from observations.\",\n description:\n \"While the collection of observations from the slider is reactive, we are saving your browser by forcing a button click to simulate from the observations.\"\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":693,"value":"md`Go ahead and move the slider again and see the shape of the distribution change. `","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":200,"value":"histogram(simulatedDist, 600, 300, 'Simulated metalog', 30)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":700,"value":"md`\nIn the cell below you will see that a few quantiles and parameters are being calculate and stored. These parameters will be input into the metalog function which simulates n trials to fit the historical observations. This is handy way to reduce the amount of information needed to share a distribution.`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":626,"value":"metaLogParams = {\n b1;\n var metaLogParams = buildMetalogParams(histogram1);\n return metaLogParams;\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":237,"value":"md`### Decide\nWhat is the chance of *x* or less?`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":241,"value":"viewof chanceOfSlider = slider({\n min: 1,\n max: 100,\n step: 1,\n value: 1,\n format: \",\",\n description:\n \"Chance of a New Observation being less than or equal (value of this slider) based on historical slider usage.\"\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":244,"value":"chanceOf = d3.quantile(simulatedDist, chanceOfSlider / 100)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":350,"value":"quantiles = p_less_than_x.map(d => ({\n p_less_than_x: d,\n x: metalog(d, metaLogParams)\n}))\n","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":335,"value":"viewof n_quantiles = slider({\n min: 10,\n max: 200,\n step: 1,\n value: 20,\n title: \"Number of quantiles\"\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":568,"value":"$2f","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":620,"value":"md`Caution clicking of the chart isn't quite working. You'll need to eyeball this to get correct y-axis value.`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":684,"value":"md`## Act\nIn an OODA loop after observing, orienting and deciding it's time to take action. For this notebook your action could be to enter another data point into the slider above to represent the result of your action. A bit abstract (I know, I know) yet a feedback loop here could create an infinite loop.`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":682,"value":"md`# Code Details in no special order`","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":29,"value":"histogram1.summary","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":622,"value":"import { button } from \"@jashkenas/inputs\"","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":62,"value":"createMetalogDist = function(arrayOfUnis, metaLogParams) {\n var arrayLength = arrayOfUnis.length;\n var newArray = [];\n for (var i = 0; i < arrayLength; i++) {\n // loop through array of unis\n newArray[i] = metalog(arrayOfUnis[i], metaLogParams); // get metalog value and put into dist vector\n }\n return newArray;\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":64,"value":"function buildMetalogParams(histogramIn) {\n var obj = {};\n\n Object.assign(obj, { lowProb: 0.1 }); // fixed for now\n Object.assign(obj, { lowerBound: histogramIn.minNonZeroValue }); // histogram lib only postives > 0\n Object.assign(obj, { lowValue: histogramIn.getValueAtPercentile(10) }); // this is the value at lowProb misleading name!\n Object.assign(obj, { median: histogramIn.getValueAtPercentile(50) });\n Object.assign(obj, { highValue: histogramIn.getValueAtPercentile(90) }); // this is the value at 1- lowProb\n Object.assign(obj, { upperBound: histogramIn.maxValue });\n Object.assign(obj, { boundedness: \"b\" }); // fixed for now\n return obj;\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":95,"value":"//simulatedDist = createMetalogDist(seededUniform, metaLogParams)\n\nsimulatedDist = {\n var a = createMetalogDist(seededUniform, metaLogParams);\n a.sort(function(x, y) {\n return d3.ascending(x, y);\n });\n\n return a;\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":87,"value":"seededUniform = {\n var a = generateSeededUniform(trials, 1234);\n a.sort(function(x, y) {\n return d3.ascending(x, y);\n });\n\n return a;\n}\n//x = jStat.seq(0.01, 30, 1000)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":343,"value":"p_less_than_x = jStat.seq(1/n_quantiles / 2, 1 - (1/n_quantiles / 2), n_quantiles)","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":17,"value":"histogram1.recordValue(uniSlider)","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":6,"value":"histogram1 = JSHistogram.build({\n bitBucketSize: 32, // may be 8, 16, 32, 64 or 'packed'\n autoResize: true, // default value is true\n lowestDiscernibleValue: 1, // default value is also 1\n highestTrackableValue: 100, // can increase up to Number.MAX_SAFE_INTEGER\n numberOfSignificantValueDigits: 3 // Number between 1 and 5 (inclusive)\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":81,"value":"function generateSeededUniform(trials, seedIn) {\n var samples = new Array(trials);\n for (var distTrials = 0; distTrials < trials; distTrials++) {\n samples[distTrials] = HDRando(seedIn, distTrials);\n }\n return samples;\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":79,"value":"HDRando(1234, 0)","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":198,"value":"import { histogram } from '@jonhelfman/histogram'","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":165,"value":"JSHistogram = require('https://bundle.run/hdr-histogram-js@2.0.1')","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":57,"value":"import { metalog, HDRando } from '@i001962/correlated-metalog-using-copulas'","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":10,"value":"import {slider} from \"@jashkenas/inputs\"\n","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":99,"value":"Plotly = require(\"https://cdn.plot.ly/plotly-latest.min.js\")","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":247,"value":"// d3 = require(\"d3\", \"d3-array@^2.2\")\nd3 = require(\"d3@6\", \"d3-array@^2.2\")","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":595,"value":"import { kde, epanechnikov } from \"@d3/kernel-density-estimation\"","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":314,"value":"margin = {\n return {\n top: 50,\n right: 50,\n bottom: 50,\n left: 100\n };\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":316,"value":"width = 600","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":317,"value":"height = 200","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":323,"value":"xScale = d3\n .scaleLinear()\n .domain(d3.extent(quantiles, d => d.x))\n .rangeRound([0, width])\n .nice()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":325,"value":"yScale = d3\n .scaleLinear()\n .domain(d3.extent(quantiles, d => d.y))\n .rangeRound([height, 0])","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":331,"value":"jStat = require('//cdn.jsdelivr.net/npm/jstat@latest/dist/jstat.min.js')","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":361,"value":"qfYScale = d3\n .scaleLinear()\n .domain(d3.extent(qfData, d => d.p_less_than_x))\n .range([height, 0])","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":362,"value":"qfData = simulatedDist.map((d, i) => ({\n x: d,\n p_less_than_x: seededUniform[i]\n}))\n\n/* \nqfData = seededUniform.map(d => ({\n x: d,\n p_less_than_x: metalog(d, metaLogParams)\n}))\n*/","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":369,"value":"qBinwidth = 1.25 * Math.sqrt(150 / n_quantiles)","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":371,"value":"function generateDotplotStacks(data, binwidth) {\n data = data.sort((a, b) => a - b);\n const stacks = [];\n for (let i = 0; i < data.length; ) {\n const threshold = data[i] + binwidth;\n\n const stack = [data[i]];\n let j = i + 1;\n\n while (data[j] < threshold) {\n stack.push(data[j++]);\n }\n let v = (stack[stack.length - 1] - stack[0]) / 2;\n const diff = data[i] - data[i - 1];\n // if (diff > binwidth || i == 0) { // X_0 = -inf in the original algorithm\n // v = (stack[stack.length - 1] - stack[0]) / 2;\n // }\n\n stacks.push({\n values: stack,\n // \"x\": jStat.median(stack),\n // \"x\": (stack[0] + stack[stack.length - 1]) / 2\n x: stack[0] + v,\n v: v,\n diff: diff,\n threshold: threshold\n });\n i = j;\n }\n return stacks;\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":373,"value":"mutable startValue = 20","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":367,"value":"qfStacks = generateDotplotStacks(quantiles.map(c => c.x), qBinwidth)","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":421,"value":"x = jStat.seq(0.01, 100, trials)","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":537,"value":"trials = 100","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":708,"value":"md`### Credits and acknowledgements\n- https://observablehq.com/@ale0xb/quantile-dotplots \n- http://www.metalogdistributions.com/home.html \n- https://hubbardresearch.com/ \n- https://fs.blog/2018/01/john-boyd-ooda-loop/`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"}],"files":"$W30","stdlib":"1","titling":"auto"}} 2d:"$2c:body"