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@sgratzl/chartjs-chart-boxplot
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@sgratzl/chartjs-chart-boxplot - npm Package Compare versions
Comparing version 3.6.0 to 3.7.0
@@ -20,35 +20,2 @@ /** | ||
| function gaussian(u) { | ||
| return (1 / Math.sqrt(2 * Math.PI)) * Math.exp(-0.5 * u * u); | ||
| } | ||
| function mean(x) { | ||
| if (x.length === 0) { | ||
| return Number.NaN; | ||
| } | ||
| return x.reduce((m, xi, i) => m + (xi - m) / (i + 1), 0); | ||
| } | ||
| function variance(x) { | ||
| const n = x.length; | ||
| if (n < 1) { | ||
| return Number.NaN; | ||
| } | ||
| if (n === 1) { | ||
| return 0; | ||
| } | ||
| const m = mean(x); | ||
| return x.reduce((acc, xi) => acc + (xi - m) * (xi - m), 0) / (x.length - 1); | ||
| } | ||
| function nrd(sample, quantiles) { | ||
| const q = quantiles(sample); | ||
| const h = (q.q3 - q.q1) / 1.34; | ||
| return 1.06 * Math.min(Math.sqrt(variance(sample)), h) * Math.pow(sample.length, -1 / 5); | ||
| } | ||
| function kde(points, sample, quantiles) { | ||
| const bw = nrd(sample, quantiles); | ||
| return points.map((v) => { | ||
| const y = sample.reduce((acc, s) => acc + gaussian((v - s) / bw), 0); | ||
| return { v, estimate: y / bw / sample.length }; | ||
| }); | ||
| } | ||
| function whiskers(boxplot, arr, coef = 1.5) { | ||
@@ -125,15 +92,6 @@ const iqr = boxplot.q3 - boxplot.q1; | ||
| } | ||
| function violinStats(arr, options) { | ||
| if (arr.length === 0) { | ||
| return undefined; | ||
| } | ||
| const items = arr.filter((v) => typeof v === 'number' && !Number.isNaN(v)).sort((a, b) => a - b); | ||
| const mean = items.reduce((acc, v) => acc + v, 0) / items.length; | ||
| const { quantiles } = determineStatsOptions(options); | ||
| const stats = quantiles(items); | ||
| const min = items[0]; | ||
| const max = items[items.length - 1]; | ||
| function computeSamples(min, max, points) { | ||
| const range = max - min; | ||
| const samples = []; | ||
| const inc = range / options.points; | ||
| const inc = range / points; | ||
| for (let v = min; v <= max && inc > 0; v += inc) { | ||
@@ -145,10 +103,20 @@ samples.push(v); | ||
| } | ||
| const coords = kde(items, samples, quantiles); | ||
| return samples; | ||
| } | ||
| function violinStats(arr, options) { | ||
| if (arr.length === 0) { | ||
| return undefined; | ||
| } | ||
| const stats = boxplots__default["default"](arr, determineStatsOptions(options)); | ||
| const samples = computeSamples(stats.min, stats.max, options.points); | ||
| const coords = samples.map((v) => ({ v, estimate: stats.kde(v) })); | ||
| const maxEstimate = coords.reduce((a, d) => Math.max(a, d.estimate), Number.NEGATIVE_INFINITY); | ||
| return { | ||
| ...stats, | ||
| min, | ||
| items, | ||
| mean, | ||
| max, | ||
| max: stats.max, | ||
| min: stats.min, | ||
| mean: stats.mean, | ||
| median: stats.median, | ||
| q1: stats.q1, | ||
| q3: stats.q3, | ||
| items: Array.from(stats.items), | ||
| coords, | ||
@@ -707,5 +675,5 @@ outliers: [], | ||
| } | ||
| outlierPositioner.id = 'averageInstance'; | ||
| outlierPositioner.id = 'average'; | ||
| outlierPositioner.register = () => { | ||
| chart_js.Tooltip.positioners.averageInstance = outlierPositioner; | ||
| chart_js.Tooltip.positioners.average = outlierPositioner; | ||
| return outlierPositioner; | ||
@@ -755,3 +723,3 @@ }; | ||
| plugins: { | ||
| tooltips: { | ||
| tooltip: { | ||
| position: outlierPositioner.register().id, | ||
@@ -758,0 +726,0 @@ callbacks: { |
@@ -12,35 +12,2 @@ /** | ||
| function gaussian(u) { | ||
| return (1 / Math.sqrt(2 * Math.PI)) * Math.exp(-0.5 * u * u); | ||
| } | ||
| function mean(x) { | ||
| if (x.length === 0) { | ||
| return Number.NaN; | ||
| } | ||
| return x.reduce((m, xi, i) => m + (xi - m) / (i + 1), 0); | ||
| } | ||
| function variance(x) { | ||
| const n = x.length; | ||
| if (n < 1) { | ||
| return Number.NaN; | ||
| } | ||
| if (n === 1) { | ||
| return 0; | ||
| } | ||
| const m = mean(x); | ||
| return x.reduce((acc, xi) => acc + (xi - m) * (xi - m), 0) / (x.length - 1); | ||
| } | ||
| function nrd(sample, quantiles) { | ||
| const q = quantiles(sample); | ||
| const h = (q.q3 - q.q1) / 1.34; | ||
| return 1.06 * Math.min(Math.sqrt(variance(sample)), h) * Math.pow(sample.length, -1 / 5); | ||
| } | ||
| function kde(points, sample, quantiles) { | ||
| const bw = nrd(sample, quantiles); | ||
| return points.map((v) => { | ||
| const y = sample.reduce((acc, s) => acc + gaussian((v - s) / bw), 0); | ||
| return { v, estimate: y / bw / sample.length }; | ||
| }); | ||
| } | ||
| function whiskers(boxplot, arr, coef = 1.5) { | ||
@@ -117,15 +84,6 @@ const iqr = boxplot.q3 - boxplot.q1; | ||
| } | ||
| function violinStats(arr, options) { | ||
| if (arr.length === 0) { | ||
| return undefined; | ||
| } | ||
| const items = arr.filter((v) => typeof v === 'number' && !Number.isNaN(v)).sort((a, b) => a - b); | ||
| const mean = items.reduce((acc, v) => acc + v, 0) / items.length; | ||
| const { quantiles } = determineStatsOptions(options); | ||
| const stats = quantiles(items); | ||
| const min = items[0]; | ||
| const max = items[items.length - 1]; | ||
| function computeSamples(min, max, points) { | ||
| const range = max - min; | ||
| const samples = []; | ||
| const inc = range / options.points; | ||
| const inc = range / points; | ||
| for (let v = min; v <= max && inc > 0; v += inc) { | ||
@@ -137,10 +95,20 @@ samples.push(v); | ||
| } | ||
| const coords = kde(items, samples, quantiles); | ||
| return samples; | ||
| } | ||
| function violinStats(arr, options) { | ||
| if (arr.length === 0) { | ||
| return undefined; | ||
| } | ||
| const stats = boxplots(arr, determineStatsOptions(options)); | ||
| const samples = computeSamples(stats.min, stats.max, options.points); | ||
| const coords = samples.map((v) => ({ v, estimate: stats.kde(v) })); | ||
| const maxEstimate = coords.reduce((a, d) => Math.max(a, d.estimate), Number.NEGATIVE_INFINITY); | ||
| return { | ||
| ...stats, | ||
| min, | ||
| items, | ||
| mean, | ||
| max, | ||
| max: stats.max, | ||
| min: stats.min, | ||
| mean: stats.mean, | ||
| median: stats.median, | ||
| q1: stats.q1, | ||
| q3: stats.q3, | ||
| items: Array.from(stats.items), | ||
| coords, | ||
@@ -699,5 +667,5 @@ outliers: [], | ||
| } | ||
| outlierPositioner.id = 'averageInstance'; | ||
| outlierPositioner.id = 'average'; | ||
| outlierPositioner.register = () => { | ||
| Tooltip.positioners.averageInstance = outlierPositioner; | ||
| Tooltip.positioners.average = outlierPositioner; | ||
| return outlierPositioner; | ||
@@ -747,3 +715,3 @@ }; | ||
| plugins: { | ||
| tooltips: { | ||
| tooltip: { | ||
| position: outlierPositioner.register().id, | ||
@@ -750,0 +718,0 @@ callbacks: { |
@@ -21,2 +21,30 @@ /** | ||
| const HELPER = Math.sqrt(2 * Math.PI); | ||
| function gaussian(u) { | ||
| return Math.exp(-0.5 * u * u) / HELPER; | ||
| } | ||
| function toSampleVariance(variance, len) { | ||
| return (variance * len) / (len - 1); | ||
| } | ||
| function nrd(iqr, variance, len) { | ||
| let s = Math.sqrt(toSampleVariance(variance, len)); | ||
| if (typeof iqr === 'number') { | ||
| s = Math.min(s, iqr / 1.34); | ||
| } | ||
| return 1.06 * s * Math.pow(len, -0.2); | ||
| } | ||
| function kde(stats) { | ||
| const len = stats.items.length; | ||
| const bandwidth = nrd(stats.iqr, stats.variance, len); | ||
| return (x) => { | ||
| let i = 0; | ||
| let sum = 0; | ||
| for (i = 0; i < len; i++) { | ||
| const v = stats.items[i]; | ||
| sum += gaussian((x - v) / bandwidth); | ||
| } | ||
| return sum / bandwidth / len; | ||
| }; | ||
| } | ||
| function quantilesInterpolate(arr, length, interpolate) { | ||
@@ -70,9 +98,6 @@ const n1 = length - 1; | ||
| function createSortedData(data) { | ||
| let min = Number.POSITIVE_INFINITY; | ||
| let max = Number.NEGATIVE_INFINITY; | ||
| let sum = 0; | ||
| let valid = 0; | ||
| const length = data.length; | ||
| const { length } = data; | ||
| const vs = data instanceof Float64Array ? new Float64Array(length) : new Float32Array(length); | ||
| for (let i = 0; i < length; ++i) { | ||
| for (let i = 0; i < length; i += 1) { | ||
| const v = data[i]; | ||
@@ -83,10 +108,3 @@ if (v == null || Number.isNaN(v)) { | ||
| vs[valid] = v; | ||
| valid++; | ||
| if (v < min) { | ||
| min = v; | ||
| } | ||
| if (v > max) { | ||
| max = v; | ||
| } | ||
| sum += v; | ||
| valid += 1; | ||
| } | ||
@@ -96,5 +114,4 @@ const missing = length - valid; | ||
| return { | ||
| sum, | ||
| min, | ||
| max, | ||
| min: Number.NaN, | ||
| max: Number.NaN, | ||
| missing, | ||
@@ -104,10 +121,11 @@ s: [], | ||
| } | ||
| const s = valid === length ? vs : vs.subarray(0, valid); | ||
| s.sort((a, b) => (a === b ? 0 : a < b ? -1 : 1)); | ||
| const validData = valid === length ? vs : vs.subarray(0, valid); | ||
| validData.sort((a, b) => (a === b ? 0 : a < b ? -1 : 1)); | ||
| const min = validData[0]; | ||
| const max = validData[validData.length - 1]; | ||
| return { | ||
| sum, | ||
| min: s[0], | ||
| max: s[s.length - 1], | ||
| min, | ||
| max, | ||
| missing, | ||
| s, | ||
| s: validData, | ||
| }; | ||
@@ -118,3 +136,2 @@ } | ||
| return { | ||
| sum: Number.NaN, | ||
| min: Number.NaN, | ||
@@ -128,10 +145,3 @@ max: Number.NaN, | ||
| const max = data[data.length - 1]; | ||
| const red = (acc, v) => acc + v; | ||
| const sum = data instanceof Float32Array | ||
| ? data.reduce(red, 0) | ||
| : data instanceof Float64Array | ||
| ? data.reduce(red, 0) | ||
| : data.reduce(red, 0); | ||
| return { | ||
| sum, | ||
| min, | ||
@@ -143,31 +153,4 @@ max, | ||
| } | ||
| function boxplot(data, options = {}) { | ||
| const { quantiles, validAndSorted, coef, whiskersMode, eps } = Object.assign({ | ||
| coef: 1.5, | ||
| eps: 10e-3, | ||
| quantiles: quantilesType7, | ||
| validAndSorted: false, | ||
| whiskersMode: 'nearest', | ||
| }, options); | ||
| const { missing, s, min, max, sum } = validAndSorted ? withSortedData(data) : createSortedData(data); | ||
| const invalid = { | ||
| min: Number.NaN, | ||
| max: Number.NaN, | ||
| mean: Number.NaN, | ||
| missing, | ||
| iqr: Number.NaN, | ||
| count: data.length, | ||
| whiskerHigh: Number.NaN, | ||
| whiskerLow: Number.NaN, | ||
| outlier: [], | ||
| median: Number.NaN, | ||
| q1: Number.NaN, | ||
| q3: Number.NaN, | ||
| items: [], | ||
| }; | ||
| function computeWhiskers(s, valid, min, max, { eps, quantiles, coef, whiskersMode }) { | ||
| const same = (a, b) => Math.abs(a - b) < eps; | ||
| const valid = data.length - missing; | ||
| if (valid === 0) { | ||
| return invalid; | ||
| } | ||
| const { median, q1, q3 } = quantiles(s, valid); | ||
@@ -178,4 +161,4 @@ const iqr = q3 - q1; | ||
| let whiskerHigh = isCoefValid ? Math.min(max, q3 + coef * iqr) : max; | ||
| const outlier = []; | ||
| for (let i = 0; i < valid; ++i) { | ||
| const outlierLow = []; | ||
| for (let i = 0; i < valid; i += 1) { | ||
| const v = s[i]; | ||
@@ -188,8 +171,8 @@ if (v >= whiskerLow || same(v, whiskerLow)) { | ||
| } | ||
| if (outlier.length === 0 || !same(outlier[outlier.length - 1], v)) { | ||
| outlier.push(v); | ||
| if (outlierLow.length === 0 || !same(outlierLow[outlierLow.length - 1], v)) { | ||
| outlierLow.push(v); | ||
| } | ||
| } | ||
| const reversedOutliers = []; | ||
| for (let i = valid - 1; i >= 0; --i) { | ||
| const reversedOutlierHigh = []; | ||
| for (let i = valid - 1; i >= 0; i -= 1) { | ||
| const v = s[i]; | ||
@@ -202,16 +185,9 @@ if (v <= whiskerHigh || same(v, whiskerHigh)) { | ||
| } | ||
| if ((reversedOutliers.length === 0 || !same(reversedOutliers[reversedOutliers.length - 1], v)) && | ||
| (outlier.length === 0 || !same(outlier[outlier.length - 1], v))) { | ||
| reversedOutliers.push(v); | ||
| if ((reversedOutlierHigh.length === 0 || !same(reversedOutlierHigh[reversedOutlierHigh.length - 1], v)) && | ||
| (outlierLow.length === 0 || !same(outlierLow[outlierLow.length - 1], v))) { | ||
| reversedOutlierHigh.push(v); | ||
| } | ||
| } | ||
| const outlier = outlierLow.concat(reversedOutlierHigh.reverse()); | ||
| return { | ||
| min, | ||
| max, | ||
| count: data.length, | ||
| missing, | ||
| mean: sum / valid, | ||
| whiskerHigh, | ||
| whiskerLow, | ||
| outlier: outlier.concat(reversedOutliers.reverse()), | ||
| median, | ||
@@ -221,38 +197,70 @@ q1, | ||
| iqr, | ||
| items: s, | ||
| outlier, | ||
| whiskerHigh, | ||
| whiskerLow, | ||
| }; | ||
| } | ||
| function gaussian(u) { | ||
| return (1 / Math.sqrt(2 * Math.PI)) * Math.exp(-0.5 * u * u); | ||
| } | ||
| function mean(x) { | ||
| if (x.length === 0) { | ||
| return Number.NaN; | ||
| function computeStats(s, valid) { | ||
| let mean = 0; | ||
| for (let i = 0; i < valid; i++) { | ||
| const v = s[i]; | ||
| mean += v; | ||
| } | ||
| return x.reduce((m, xi, i) => m + (xi - m) / (i + 1), 0); | ||
| mean /= valid; | ||
| let variance = 0; | ||
| for (let i = 0; i < valid; i++) { | ||
| const v = s[i]; | ||
| variance += (v - mean) * (v - mean); | ||
| } | ||
| variance /= valid; | ||
| return { | ||
| mean, | ||
| variance, | ||
| }; | ||
| } | ||
| function variance(x) { | ||
| const n = x.length; | ||
| if (n < 1) { | ||
| return Number.NaN; | ||
| function boxplot(data, options = {}) { | ||
| const fullOptions = { | ||
| coef: 1.5, | ||
| eps: 10e-3, | ||
| quantiles: quantilesType7, | ||
| validAndSorted: false, | ||
| whiskersMode: 'nearest', | ||
| ...options, | ||
| }; | ||
| const { missing, s, min, max } = fullOptions.validAndSorted ? withSortedData(data) : createSortedData(data); | ||
| const invalid = { | ||
| min: Number.NaN, | ||
| max: Number.NaN, | ||
| mean: Number.NaN, | ||
| missing, | ||
| iqr: Number.NaN, | ||
| count: data.length, | ||
| whiskerHigh: Number.NaN, | ||
| whiskerLow: Number.NaN, | ||
| outlier: [], | ||
| median: Number.NaN, | ||
| q1: Number.NaN, | ||
| q3: Number.NaN, | ||
| variance: 0, | ||
| items: [], | ||
| kde: () => 0, | ||
| }; | ||
| const valid = data.length - missing; | ||
| if (valid === 0) { | ||
| return invalid; | ||
| } | ||
| if (n === 1) { | ||
| return 0; | ||
| } | ||
| const m = mean(x); | ||
| return x.reduce((acc, xi) => acc + (xi - m) * (xi - m), 0) / (x.length - 1); | ||
| const result = { | ||
| min, | ||
| max, | ||
| count: data.length, | ||
| missing, | ||
| items: s, | ||
| ...computeStats(s, valid), | ||
| ...computeWhiskers(s, valid, min, max, fullOptions), | ||
| }; | ||
| return { | ||
| ...result, | ||
| kde: kde(result), | ||
| }; | ||
| } | ||
| function nrd(sample, quantiles) { | ||
| const q = quantiles(sample); | ||
| const h = (q.q3 - q.q1) / 1.34; | ||
| return 1.06 * Math.min(Math.sqrt(variance(sample)), h) * Math.pow(sample.length, -1 / 5); | ||
| } | ||
| function kde(points, sample, quantiles) { | ||
| const bw = nrd(sample, quantiles); | ||
| return points.map((v) => { | ||
| const y = sample.reduce((acc, s) => acc + gaussian((v - s) / bw), 0); | ||
| return { v, estimate: y / bw / sample.length }; | ||
| }); | ||
| } | ||
@@ -330,15 +338,6 @@ function whiskers(boxplot, arr, coef = 1.5) { | ||
| } | ||
| function violinStats(arr, options) { | ||
| if (arr.length === 0) { | ||
| return undefined; | ||
| } | ||
| const items = arr.filter((v) => typeof v === 'number' && !Number.isNaN(v)).sort((a, b) => a - b); | ||
| const mean = items.reduce((acc, v) => acc + v, 0) / items.length; | ||
| const { quantiles } = determineStatsOptions(options); | ||
| const stats = quantiles(items); | ||
| const min = items[0]; | ||
| const max = items[items.length - 1]; | ||
| function computeSamples(min, max, points) { | ||
| const range = max - min; | ||
| const samples = []; | ||
| const inc = range / options.points; | ||
| const inc = range / points; | ||
| for (let v = min; v <= max && inc > 0; v += inc) { | ||
@@ -350,10 +349,20 @@ samples.push(v); | ||
| } | ||
| const coords = kde(items, samples, quantiles); | ||
| return samples; | ||
| } | ||
| function violinStats(arr, options) { | ||
| if (arr.length === 0) { | ||
| return undefined; | ||
| } | ||
| const stats = boxplot(arr, determineStatsOptions(options)); | ||
| const samples = computeSamples(stats.min, stats.max, options.points); | ||
| const coords = samples.map((v) => ({ v, estimate: stats.kde(v) })); | ||
| const maxEstimate = coords.reduce((a, d) => Math.max(a, d.estimate), Number.NEGATIVE_INFINITY); | ||
| return { | ||
| ...stats, | ||
| min, | ||
| items, | ||
| mean, | ||
| max, | ||
| max: stats.max, | ||
| min: stats.min, | ||
| mean: stats.mean, | ||
| median: stats.median, | ||
| q1: stats.q1, | ||
| q3: stats.q3, | ||
| items: Array.from(stats.items), | ||
| coords, | ||
@@ -463,5 +472,5 @@ outliers: [], | ||
| } | ||
| outlierPositioner.id = 'averageInstance'; | ||
| outlierPositioner.id = 'average'; | ||
| outlierPositioner.register = () => { | ||
| chart_js.Tooltip.positioners.averageInstance = outlierPositioner; | ||
| chart_js.Tooltip.positioners.average = outlierPositioner; | ||
| return outlierPositioner; | ||
@@ -511,3 +520,3 @@ }; | ||
| plugins: { | ||
| tooltips: { | ||
| tooltip: { | ||
| position: outlierPositioner.register().id, | ||
@@ -514,0 +523,0 @@ callbacks: { |
@@ -1,2 +0,2 @@ | ||
| !function(t,e){"object"==typeof exports&&"undefined"!=typeof module?e(exports,require("chart.js"),require("chart.js/helpers")):"function"==typeof define&&define.amd?define(["exports","chart.js","chart.js/helpers"],e):e((t="undefined"!=typeof globalThis?globalThis:t||self).ChartBoxPlot={},t.Chart,t.Chart.helpers)}(this,(function(t,e,r){"use strict";function i(t,e,r){const i=e-1,o=e=>{const o=e*i,n=Math.floor(o),s=o-n,a=t[n];return 0===s?a:r(a,t[Math.min(n+1,i)],s)};return{q1:o(.25),median:o(.5),q3:o(.75)}}function o(t,e=t.length){return i(t,e,((t,e,r)=>t+r*(e-t)))}function n(t,e=t.length){return i(t,e,((t,e,r)=>t+(e-t)*r))}function s(t,e=t.length){return i(t,e,(t=>t))}function a(t,e=t.length){return i(t,e,((t,e)=>e))}function l(t,e=t.length){return i(t,e,((t,e,r)=>r<.5?t:e))}function u(t,e=t.length){return i(t,e,((t,e)=>.5*(t+e)))}function h(t,e=t.length){const r=e,i=Math.floor((r+3)/2)/2,o=e=>.5*(t[Math.floor(e)-1]+t[Math.ceil(e)-1]);return{q1:o(i),median:o((r+1)/2),q3:o(r+1-i)}}function d(t,e=t.length){return h(t,e)}function m(t,e={}){const{quantiles:r,validAndSorted:i,coef:n,whiskersMode:s,eps:a}=Object.assign({coef:1.5,eps:.01,quantiles:o,validAndSorted:!1,whiskersMode:"nearest"},e),{missing:l,s:u,min:h,max:d,sum:m}=i?function(t){if(0===t.length)return{sum:Number.NaN,min:Number.NaN,max:Number.NaN,missing:0,s:[]};const e=t[0],r=t[t.length-1],i=(t,e)=>t+e;return{sum:(t instanceof Float32Array||Float64Array,t.reduce(i,0)),min:e,max:r,missing:0,s:t}}(t):function(t){let e=Number.POSITIVE_INFINITY,r=Number.NEGATIVE_INFINITY,i=0,o=0;const n=t.length,s=t instanceof Float64Array?new Float64Array(n):new Float32Array(n);for(let a=0;a<n;++a){const n=t[a];null==n||Number.isNaN(n)||(s[o]=n,o++,n<e&&(e=n),n>r&&(r=n),i+=n)}const a=n-o;if(0===o)return{sum:i,min:e,max:r,missing:a,s:[]};const l=o===n?s:s.subarray(0,o);return l.sort(((t,e)=>t===e?0:t<e?-1:1)),{sum:i,min:l[0],max:l[l.length-1],missing:a,s:l}}(t),c={min:Number.NaN,max:Number.NaN,mean:Number.NaN,missing:l,iqr:Number.NaN,count:t.length,whiskerHigh:Number.NaN,whiskerLow:Number.NaN,outlier:[],median:Number.NaN,q1:Number.NaN,q3:Number.NaN,items:[]},f=(t,e)=>Math.abs(t-e)<a,g=t.length-l;if(0===g)return c;const{median:p,q1:x,q3:y}=r(u,g),b=y-x,w="number"==typeof n&&n>0;let q=w?Math.max(h,x-n*b):h,k=w?Math.min(d,y+n*b):d;const N=[];for(let t=0;t<g;++t){const e=u[t];if(e>=q||f(e,q)){"nearest"===s&&(q=e);break}0!==N.length&&f(N[N.length-1],e)||N.push(e)}const C=[];for(let t=g-1;t>=0;--t){const e=u[t];if(e<=k||f(e,k)){"nearest"===s&&(k=e);break}0!==C.length&&f(C[C.length-1],e)||0!==N.length&&f(N[N.length-1],e)||C.push(e)}return{min:h,max:d,count:t.length,missing:l,mean:m/g,whiskerHigh:k,whiskerLow:q,outlier:N.concat(C.reverse()),median:p,q1:x,q3:y,iqr:b,items:u}}function c(t){const e=t.length;if(e<1)return Number.NaN;if(1===e)return 0;const r=function(t){return 0===t.length?Number.NaN:t.reduce(((t,e,r)=>t+(e-t)/(r+1)),0)}(t);return t.reduce(((t,e)=>t+(e-r)*(e-r)),0)/(t.length-1)}function f(t,e,r){const i=function(t,e){const r=e(t),i=(r.q3-r.q1)/1.34;return 1.06*Math.min(Math.sqrt(c(t)),i)*Math.pow(t.length,-.2)}(e,r);return t.map((t=>{const r=e.reduce(((e,r)=>{return e+(o=(t-r)/i,1/Math.sqrt(2*Math.PI)*Math.exp(-.5*o*o));var o}),0);return{v:t,estimate:r/i/e.length}}))}const g={coef:1.5,quantiles:7};function p(t){const e=null==t||"number"!=typeof t.coef?g.coef:t.coef,r=function(t){return"function"==typeof t?t:{hinges:d,fivenum:h,7:o,quantiles:o,linear:n,lower:s,higher:a,nearest:l,midpoint:u}[t]||o}(null==t||null==t.quantiles?o:t.quantiles);return{coef:e,quantiles:r}}function x(t,e){if(t){if("number"==typeof t.median&&"number"==typeof t.q1&&"number"==typeof t.q3){if(void 0===t.whiskerMin){const{coef:r}=p(e),{whiskerMin:i,whiskerMax:o}=function(t,e,r=1.5){const i=t.q3-t.q1,o="number"==typeof r&&r>0;let n=o?Math.max(t.min,t.q1-r*i):t.min,s=o?Math.min(t.max,t.q3+r*i):t.max;if(Array.isArray(e)){for(let t=0;t<e.length;t+=1){const r=e[t];if(r>=n){n=r;break}}for(let t=e.length-1;t>=0;t-=1){const r=e[t];if(r<=s){s=r;break}}}return{whiskerMin:n,whiskerMax:s}}(t,Array.isArray(t.items)?t.items.slice().sort(((t,e)=>t-e)):null,r);t.whiskerMin=i,t.whiskerMax=o}return t}if(Array.isArray(t))return function(t,e){const r=m(t,p(e));return{items:Array.from(r.items),outliers:r.outlier,whiskerMax:r.whiskerHigh,whiskerMin:r.whiskerLow,max:r.max,median:r.median,mean:r.mean,min:r.min,q1:r.q1,q3:r.q3}}(t,e)}}function y(t,e){if(t){if("number"==typeof t.median&&Array.isArray(t.coords))return t;if(Array.isArray(t))return function(t,e){if(0===t.length)return;const r=t.filter((t=>"number"==typeof t&&!Number.isNaN(t))).sort(((t,e)=>t-e)),i=r.reduce(((t,e)=>t+e),0)/r.length,{quantiles:o}=p(e),n=o(r),s=r[0],a=r[r.length-1],l=[],u=(a-s)/e.points;for(let t=s;t<=a&&u>0;t+=u)l.push(t);l[l.length-1]!==a&&l.push(a);const h=f(r,l,o),d=h.reduce(((t,e)=>Math.max(t,e.estimate)),Number.NEGATIVE_INFINITY);return{...n,min:s,items:r,mean:i,max:a,coords:h,outliers:[],maxEstimate:d}}(t,e)}}const b={number:(t,e,r)=>t===e||null==t?e:null==e?t:t+(e-t)*r};function w(t,e,r){return"number"==typeof t&&"number"==typeof e?b.number(t,e,r):Array.isArray(t)&&Array.isArray(e)?e.map(((e,i)=>b.number(t[i],e,r))):e}function q(t){const e=t.formattedValue,r=this;e&&null!=r._tooltipOutlier&&t.datasetIndex===r._tooltipOutlier.datasetIndex&&(e.hoveredOutlierIndex=r._tooltipOutlier.index)}function k(t,e){if(!t.length)return!1;let r=0,i=0,o=0;for(let n=0;n<t.length;n+=1){const s=t[n].element;if(s&&s.hasValue()){const t=s.tooltipPosition(e,this);r+=t.x,i+=t.y,o+=1}}return{x:r/o,y:i/o}}function N(t){const e=["borderColor","backgroundColor"].concat(t.filter((t=>t.endsWith("Color"))));return{animations:{numberArray:{fn:w,properties:["outliers","items"]},colors:{type:"color",properties:e}},transitions:{show:{animations:{colors:{type:"color",properties:e,from:"transparent"}}},hide:{animations:{colors:{type:"color",properties:e,to:"transparent"}}}},minStats:"min",maxStats:"max",...g}}function C(){return{plugins:{tooltips:{position:k.register().id,callbacks:{beforeLabel:q}}}}}k.id="averageInstance",k.register=()=>(e.Tooltip.positioners.averageInstance=k,k);class M extends e.BarController{_transformStats(t,e,r){for(const i of["min","max","median","q3","q1","mean"]){const o=e[i];"number"==typeof o&&(t[i]=r(o))}for(const i of["outliers","items"])Array.isArray(e[i])&&(t[i]=e[i].map(r))}getMinMax(t,e){const r=t.axis,i=this.options;t.axis=i.minStats;const{min:o}=super.getMinMax(t,e);t.axis=i.maxStats;const{max:n}=super.getMinMax(t,e);return t.axis=r,{min:o,max:n}}parsePrimitiveData(t,e,r,i){const o=t.vScale,n=t.iScale,s=n.getLabels(),a=[];for(let t=0;t<i;t+=1){const i=t+r,l={};l[n.axis]=n.parse(s[i],i);const u=this._parseStats(null==e?null:e[i],this.options);u&&(Object.assign(l,u),l[o.axis]=u.median),a.push(l)}return a}parseArrayData(t,e,r,i){return this.parsePrimitiveData(t,e,r,i)}parseObjectData(t,e,r,i){return this.parsePrimitiveData(t,e,r,i)}getLabelAndValue(t){const e=super.getLabelAndValue(t),{vScale:r}=this._cachedMeta,i=this.getParsed(t);if(!r||!i||"NaN"===e.value)return e;e.value={raw:i,hoveredOutlierIndex:-1},this._transformStats(e.value,i,(t=>r.getLabelForValue(t)));const o=this._toStringStats(e.value.raw);return e.value.toString=function(){return this.hoveredOutlierIndex>=0?`(outlier: ${this.outliers[this.hoveredOutlierIndex]})`:o},e}_toStringStats(t){const e=t=>null==t?"NaN":r.formatNumber(t,this.chart.options.locale,{});return`(min: ${e(t.min)}, 25% quantile: ${e(t.q1)}, median: ${e(t.median)}, mean: ${e(t.mean)}, 75% quantile: ${e(t.q3)}, max: ${e(t.max)})`}updateElement(t,e,r,i){const o="reset"===i,n=this._cachedMeta.vScale,s=this.getParsed(e),a=n.getBasePixel();r._datasetIndex=this.index,r._index=e,this._transformStats(r,s,(t=>o?a:n.getPixelForValue(t,e))),super.updateElement(t,e,r,i)}}const v={borderWidth:1,outlierStyle:"circle",outlierRadius:2,outlierBorderWidth:1,itemStyle:"circle",itemRadius:0,itemBorderWidth:0,meanStyle:"circle",meanRadius:3,meanBorderWidth:1,hitPadding:2,outlierHitRadius:4},_={outlierBackgroundColor:"backgroundColor",outlierBorderColor:"borderColor",itemBackgroundColor:"backgroundColor",itemBorderColor:"borderColor",meanBackgroundColor:"backgroundColor",meanBorderColor:"borderColor"},B=Object.keys(v).concat(Object.keys(_));class S extends e.Element{isVertical(){return!this.horizontal}_drawItems(t){const e=this.isVertical(),i=this.getProps(["x","y","items","width","height","outliers"]),{options:o}=this;if(o.itemRadius<=0||!i.items||i.items.length<=0)return;t.save(),t.strokeStyle=o.itemBorderColor,t.fillStyle=o.itemBackgroundColor,t.lineWidth=o.itemBorderWidth;const n=function(t=Date.now()){let e=t;return()=>(e=(9301*e+49297)%233280,e/233280)}(1e3*this._datasetIndex+this._index),s={pointStyle:o.itemStyle,radius:o.itemRadius,borderWidth:o.itemBorderWidth},a=new Set(i.outliers||[]);e?i.items.forEach((e=>{a.has(e)||r.drawPoint(t,s,i.x-i.width/2+n()*i.width,e)})):i.items.forEach((e=>{a.has(e)||r.drawPoint(t,s,e,i.y-i.height/2+n()*i.height)})),t.restore()}_drawOutliers(t){const e=this.isVertical(),i=this.getProps(["x","y","outliers"]),{options:o}=this;if(o.outlierRadius<=0||!i.outliers||0===i.outliers.length)return;t.save(),t.fillStyle=o.outlierBackgroundColor,t.strokeStyle=o.outlierBorderColor,t.lineWidth=o.outlierBorderWidth;const n={pointStyle:o.outlierStyle,radius:o.outlierRadius,borderWidth:o.outlierBorderWidth};e?i.outliers.forEach((e=>{r.drawPoint(t,n,i.x,e)})):i.outliers.forEach((e=>{r.drawPoint(t,n,e,i.y)})),t.restore()}_drawMeanDot(t){const e=this.isVertical(),i=this.getProps(["x","y","mean"]),{options:o}=this;if(o.meanRadius<=0||null==i.mean||Number.isNaN(i.mean))return;t.save(),t.fillStyle=o.meanBackgroundColor,t.strokeStyle=o.meanBorderColor,t.lineWidth=o.meanBorderWidth;const n={pointStyle:o.meanStyle,radius:o.meanRadius,borderWidth:o.meanBorderWidth};e?r.drawPoint(t,n,i.x,i.mean):r.drawPoint(t,n,i.mean,i.y),t.restore()}_getBounds(t){return{left:0,top:0,right:0,bottom:0}}_getHitBounds(t){const e=this.options.hitPadding,r=this._getBounds(t);return{left:r.left-e,top:r.top-e,right:r.right+e,bottom:r.bottom+e}}inRange(t,e,r){return(!Number.isNaN(this.x)||!Number.isNaN(this.y))&&(this._boxInRange(t,e,r)||this._outlierIndexInRange(t,e,r)>=0)}inXRange(t,e){const r=this._getHitBounds(e);return t>=r.left&&t<=r.right}inYRange(t,e){const r=this._getHitBounds(e);return t>=r.top&&t<=r.bottom}_outlierIndexInRange(t,e,r){const i=this.getProps(["x","y"],r),o=this.options.outlierHitRadius,n=this._getOutliers(r),s=this.isVertical();if(s&&Math.abs(t-i.x)>o||!s&&Math.abs(e-i.y)>o)return-1;const a=s?e:t;for(let t=0;t<n.length;t+=1)if(Math.abs(n[t]-a)<=o)return t;return-1}_boxInRange(t,e,r){const i=this._getHitBounds(r);return t>=i.left&&t<=i.right&&e>=i.top&&e<=i.bottom}getCenterPoint(t){const e=this.getProps(["x","y"],t);return{x:e.x,y:e.y}}_getOutliers(t){return this.getProps(["outliers"],t).outliers||[]}tooltipPosition(t,e){if(!t||"boolean"==typeof t)return this.getCenterPoint();e&&delete e._tooltipOutlier;const r=this.getProps(["x","y"]),i=this._outlierIndexInRange(t.x,t.y);return i<0||!e?this.getCenterPoint():(e._tooltipOutlier={index:i,datasetIndex:this._datasetIndex},this.isVertical()?{x:r.x,y:this._getOutliers()[i]}:{x:this._getOutliers()[i],y:r.y})}}const P=B.concat(["medianColor","lowerBackgroundColor"]);class T extends S{draw(t){t.save(),t.fillStyle=this.options.backgroundColor,t.strokeStyle=this.options.borderColor,t.lineWidth=this.options.borderWidth,this._drawBoxPlot(t),this._drawOutliers(t),this._drawMeanDot(t),t.restore(),this._drawItems(t)}_drawBoxPlot(t){this.isVertical()?this._drawBoxPlotVertical(t):this._drawBoxPlotHorizontal(t)}_drawBoxPlotVertical(t){const{options:e}=this,r=this.getProps(["x","width","q1","q3","median","whiskerMin","whiskerMax"]),{x:i}=r,{width:o}=r,n=i-o/2;r.q3>r.q1?t.fillRect(n,r.q1,o,r.q3-r.q1):t.fillRect(n,r.q3,o,r.q1-r.q3),t.save(),e.medianColor&&"transparent"!==e.medianColor&&"#0000"!==e.medianColor&&(t.strokeStyle=e.medianColor),t.beginPath(),t.moveTo(n,r.median),t.lineTo(n+o,r.median),t.closePath(),t.stroke(),t.restore(),t.save(),e.lowerBackgroundColor&&"transparent"!==e.lowerBackgroundColor&&"#0000"!==e.lowerBackgroundColor&&(t.fillStyle=e.lowerBackgroundColor,r.q3>r.q1?t.fillRect(n,r.median,o,r.q3-r.median):t.fillRect(n,r.median,o,r.q1-r.median)),t.restore(),r.q3>r.q1?t.strokeRect(n,r.q1,o,r.q3-r.q1):t.strokeRect(n,r.q3,o,r.q1-r.q3),t.beginPath(),t.moveTo(n,r.whiskerMin),t.lineTo(n+o,r.whiskerMin),t.moveTo(i,r.whiskerMin),t.lineTo(i,r.q1),t.moveTo(n,r.whiskerMax),t.lineTo(n+o,r.whiskerMax),t.moveTo(i,r.whiskerMax),t.lineTo(i,r.q3),t.closePath(),t.stroke()}_drawBoxPlotHorizontal(t){const{options:e}=this,r=this.getProps(["y","height","q1","q3","median","whiskerMin","whiskerMax"]),{y:i}=r,{height:o}=r,n=i-o/2;r.q3>r.q1?t.fillRect(r.q1,n,r.q3-r.q1,o):t.fillRect(r.q3,n,r.q1-r.q3,o),t.save(),e.medianColor&&"transparent"!==e.medianColor&&(t.strokeStyle=e.medianColor),t.beginPath(),t.moveTo(r.median,n),t.lineTo(r.median,n+o),t.closePath(),t.stroke(),t.restore(),t.save(),e.lowerBackgroundColor&&"transparent"!==e.lowerBackgroundColor&&(t.fillStyle=e.lowerBackgroundColor,r.q3>r.q1?t.fillRect(r.median,n,r.q3-r.median,o):t.fillRect(r.median,n,r.q1-r.median,o)),t.restore(),r.q3>r.q1?t.strokeRect(r.q1,n,r.q3-r.q1,o):t.strokeRect(r.q3,n,r.q1-r.q3,o),t.beginPath(),t.moveTo(r.whiskerMin,n),t.lineTo(r.whiskerMin,n+o),t.moveTo(r.whiskerMin,i),t.lineTo(r.q1,i),t.moveTo(r.whiskerMax,n),t.lineTo(r.whiskerMax,n+o),t.moveTo(r.whiskerMax,i),t.lineTo(r.q3,i),t.closePath(),t.stroke()}_getBounds(t){const e=this.isVertical();if(null==this.x)return{left:0,top:0,right:0,bottom:0};if(e){const{x:e,width:r,whiskerMax:i,whiskerMin:o}=this.getProps(["x","width","whiskerMin","whiskerMax"],t),n=e-r/2;return{left:n,top:i,right:n+r,bottom:o}}const{y:r,height:i,whiskerMax:o,whiskerMin:n}=this.getProps(["y","height","whiskerMin","whiskerMax"],t),s=r-i/2;return{left:n,top:s,right:o,bottom:s+i}}}T.id="boxandwhiskers",T.defaults={...e.BarElement.defaults,...v,medianColor:"transparent",lowerBackgroundColor:"transparent"},T.defaultRoutes={...e.BarElement.defaultRoutes,..._};class A extends S{draw(t){t.save(),t.fillStyle=this.options.backgroundColor,t.strokeStyle=this.options.borderColor,t.lineWidth=this.options.borderWidth;const e=this.getProps(["x","y","width","height","min","max","coords","maxEstimate"]);r.drawPoint(t,{pointStyle:"rectRot",radius:5,borderWidth:this.options.borderWidth},e.x,e.y),e.coords&&e.coords.length>0&&this._drawCoords(t,e),this._drawOutliers(t),this._drawMeanDot(t),t.restore(),this._drawItems(t)}_drawCoords(t,e){if(t.beginPath(),this.isVertical()){const{x:r,width:i}=e,o=i/2/e.maxEstimate;t.moveTo(r,e.min),e.coords.forEach((e=>{t.lineTo(r-e.estimate*o,e.v)})),t.lineTo(r,e.max),t.moveTo(r,e.min),e.coords.forEach((e=>{t.lineTo(r+e.estimate*o,e.v)})),t.lineTo(r,e.max)}else{const{y:r,height:i}=e,o=i/2/e.maxEstimate;t.moveTo(e.min,r),e.coords.forEach((e=>{t.lineTo(e.v,r-e.estimate*o)})),t.lineTo(e.max,r),t.moveTo(e.min,r),e.coords.forEach((e=>{t.lineTo(e.v,r+e.estimate*o)})),t.lineTo(e.max,r)}t.closePath(),t.stroke(),t.fill()}_getBounds(t){if(this.isVertical()){const{x:e,width:r,min:i,max:o}=this.getProps(["x","width","min","max"],t),n=e-r/2;return{left:n,top:o,right:n+r,bottom:i}}const{y:e,height:r,min:i,max:o}=this.getProps(["y","height","min","max"],t),n=e-r/2;return{left:i,top:n,right:o,bottom:n+r}}}function I(t,r,i,o=[],n=[]){e.registry.addControllers(i),Array.isArray(o)?e.registry.addElements(...o):e.registry.addElements(o),Array.isArray(n)?e.registry.addScales(...n):e.registry.addScales(n);const s=r;return s.type=t,s}A.id="violin",A.defaults={...e.BarElement.defaults,...v},A.defaultRoutes={...e.BarElement.defaultRoutes,..._};class R extends M{_parseStats(t,e){return x(t,e)}_transformStats(t,e,r){super._transformStats(t,e,r);for(const i of["whiskerMin","whiskerMax"])t[i]=r(e[i])}}R.id="boxplot",R.defaults=r.merge({},[e.BarController.defaults,N(P),{animations:{numbers:{type:"number",properties:e.BarController.defaults.animations.numbers.properties.concat(["q1","q3","min","max","median","whiskerMin","whiskerMax","mean"],P.filter((t=>!t.endsWith("Color"))))}},dataElementType:T.id}]),R.overrides=r.merge({},[e.BarController.overrides,C()]);class E extends e.Chart{constructor(t,r){super(t,I("boxplot",r,R,T,[e.LinearScale,e.CategoryScale]))}}E.id=R.id;class W extends M{_parseStats(t,e){return y(t,e)}_transformStats(t,e,r){super._transformStats(t,e,r),t.maxEstimate=e.maxEstimate,Array.isArray(e.coords)&&(t.coords=e.coords.map((t=>({...t,v:r(t.v)}))))}}W.id="violin",W.defaults=r.merge({},[e.BarController.defaults,N(B),{points:100,animations:{numbers:{type:"number",properties:e.BarController.defaults.animations.numbers.properties.concat(["q1","q3","min","max","median","maxEstimate"],B.filter((t=>!t.endsWith("Color"))))},kdeCoords:{fn:function(t,e,r){return Array.isArray(t)&&Array.isArray(e)?e.map(((e,i)=>({v:b.number(t[i]?t[i].v:null,e.v,r),estimate:b.number(t[i]?t[i].estimate:null,e.estimate,r)}))):e},properties:["coords"]}},dataElementType:A.id}]),W.overrides=r.merge({},[e.BarController.overrides,C()]);class V extends e.Chart{constructor(t,r){super(t,I("violin",r,W,A,[e.LinearScale,e.CategoryScale]))}}V.id=W.id,e.registry.addControllers(R,W),e.registry.addElements(T,A),t.BoxAndWiskers=T,t.BoxPlotChart=E,t.BoxPlotController=R,t.StatsBase=S,t.Violin=A,t.ViolinChart=V,t.ViolinController=W,Object.defineProperty(t,"__esModule",{value:!0})})); | ||
| !function(t,e){"object"==typeof exports&&"undefined"!=typeof module?e(exports,require("chart.js"),require("chart.js/helpers")):"function"==typeof define&&define.amd?define(["exports","chart.js","chart.js/helpers"],e):e((t="undefined"!=typeof globalThis?globalThis:t||self).ChartBoxPlot={},t.Chart,t.Chart.helpers)}(this,(function(t,e,r){"use strict";const i=Math.sqrt(2*Math.PI);function o(t){const e=t.items.length,r=function(t,e,r){let i=Math.sqrt(function(t,e){return t*e/(e-1)}(e,r));return"number"==typeof t&&(i=Math.min(i,t/1.34)),1.06*i*Math.pow(r,-.2)}(t.iqr,t.variance,e);return o=>{let n=0,s=0;for(n=0;n<e;n++){const e=t.items[n];s+=(a=(o-e)/r,Math.exp(-.5*a*a)/i)}var a;return s/r/e}}function n(t,e,r){const i=e-1,o=e=>{const o=e*i,n=Math.floor(o),s=o-n,a=t[n];return 0===s?a:r(a,t[Math.min(n+1,i)],s)};return{q1:o(.25),median:o(.5),q3:o(.75)}}function s(t,e=t.length){return n(t,e,((t,e,r)=>t+r*(e-t)))}function a(t,e=t.length){return n(t,e,((t,e,r)=>t+(e-t)*r))}function l(t,e=t.length){return n(t,e,(t=>t))}function u(t,e=t.length){return n(t,e,((t,e)=>e))}function d(t,e=t.length){return n(t,e,((t,e,r)=>r<.5?t:e))}function m(t,e=t.length){return n(t,e,((t,e)=>.5*(t+e)))}function h(t,e=t.length){const r=e,i=Math.floor((r+3)/2)/2,o=e=>.5*(t[Math.floor(e)-1]+t[Math.ceil(e)-1]);return{q1:o(i),median:o((r+1)/2),q3:o(r+1-i)}}function c(t,e=t.length){return h(t,e)}function f(t,e,r,i,{eps:o,quantiles:n,coef:s,whiskersMode:a}){const l=(t,e)=>Math.abs(t-e)<o,{median:u,q1:d,q3:m}=n(t,e),h=m-d,c="number"==typeof s&&s>0;let f=c?Math.max(r,d-s*h):r,g=c?Math.min(i,m+s*h):i;const p=[];for(let r=0;r<e;r+=1){const e=t[r];if(e>=f||l(e,f)){"nearest"===a&&(f=e);break}0!==p.length&&l(p[p.length-1],e)||p.push(e)}const x=[];for(let r=e-1;r>=0;r-=1){const e=t[r];if(e<=g||l(e,g)){"nearest"===a&&(g=e);break}0!==x.length&&l(x[x.length-1],e)||0!==p.length&&l(p[p.length-1],e)||x.push(e)}return{median:u,q1:d,q3:m,iqr:h,outlier:p.concat(x.reverse()),whiskerHigh:g,whiskerLow:f}}function g(t,e){let r=0;for(let i=0;i<e;i++){r+=t[i]}r/=e;let i=0;for(let o=0;o<e;o++){const e=t[o];i+=(e-r)*(e-r)}return i/=e,{mean:r,variance:i}}function p(t,e={}){const r={coef:1.5,eps:.01,quantiles:s,validAndSorted:!1,whiskersMode:"nearest",...e},{missing:i,s:n,min:a,max:l}=r.validAndSorted?function(t){return 0===t.length?{min:Number.NaN,max:Number.NaN,missing:0,s:[]}:{min:t[0],max:t[t.length-1],missing:0,s:t}}(t):function(t){let e=0;const{length:r}=t,i=t instanceof Float64Array?new Float64Array(r):new Float32Array(r);for(let o=0;o<r;o+=1){const r=t[o];null==r||Number.isNaN(r)||(i[e]=r,e+=1)}const o=r-e;if(0===e)return{min:Number.NaN,max:Number.NaN,missing:o,s:[]};const n=e===r?i:i.subarray(0,e);return n.sort(((t,e)=>t===e?0:t<e?-1:1)),{min:n[0],max:n[n.length-1],missing:o,s:n}}(t),u={min:Number.NaN,max:Number.NaN,mean:Number.NaN,missing:i,iqr:Number.NaN,count:t.length,whiskerHigh:Number.NaN,whiskerLow:Number.NaN,outlier:[],median:Number.NaN,q1:Number.NaN,q3:Number.NaN,variance:0,items:[],kde:()=>0},d=t.length-i;if(0===d)return u;const m={min:a,max:l,count:t.length,missing:i,items:n,...g(n,d),...f(n,d,a,l,r)};return{...m,kde:o(m)}}const x={coef:1.5,quantiles:7};function y(t){const e=null==t||"number"!=typeof t.coef?x.coef:t.coef,r=function(t){return"function"==typeof t?t:{hinges:c,fivenum:h,7:s,quantiles:s,linear:a,lower:l,higher:u,nearest:d,midpoint:m}[t]||s}(null==t||null==t.quantiles?s:t.quantiles);return{coef:e,quantiles:r}}function b(t,e){if(t){if("number"==typeof t.median&&"number"==typeof t.q1&&"number"==typeof t.q3){if(void 0===t.whiskerMin){const{coef:r}=y(e),{whiskerMin:i,whiskerMax:o}=function(t,e,r=1.5){const i=t.q3-t.q1,o="number"==typeof r&&r>0;let n=o?Math.max(t.min,t.q1-r*i):t.min,s=o?Math.min(t.max,t.q3+r*i):t.max;if(Array.isArray(e)){for(let t=0;t<e.length;t+=1){const r=e[t];if(r>=n){n=r;break}}for(let t=e.length-1;t>=0;t-=1){const r=e[t];if(r<=s){s=r;break}}}return{whiskerMin:n,whiskerMax:s}}(t,Array.isArray(t.items)?t.items.slice().sort(((t,e)=>t-e)):null,r);t.whiskerMin=i,t.whiskerMax=o}return t}if(Array.isArray(t))return function(t,e){const r=p(t,y(e));return{items:Array.from(r.items),outliers:r.outlier,whiskerMax:r.whiskerHigh,whiskerMin:r.whiskerLow,max:r.max,median:r.median,mean:r.mean,min:r.min,q1:r.q1,q3:r.q3}}(t,e)}}function w(t,e){if(t){if("number"==typeof t.median&&Array.isArray(t.coords))return t;if(Array.isArray(t))return function(t,e){if(0===t.length)return;const r=p(t,y(e)),i=function(t,e,r){const i=[],o=(e-t)/r;for(let r=t;r<=e&&o>0;r+=o)i.push(r);return i[i.length-1]!==e&&i.push(e),i}(r.min,r.max,e.points).map((t=>({v:t,estimate:r.kde(t)}))),o=i.reduce(((t,e)=>Math.max(t,e.estimate)),Number.NEGATIVE_INFINITY);return{max:r.max,min:r.min,mean:r.mean,median:r.median,q1:r.q1,q3:r.q3,items:Array.from(r.items),coords:i,outliers:[],maxEstimate:o}}(t,e)}}const q={number:(t,e,r)=>t===e||null==t?e:null==e?t:t+(e-t)*r};function k(t,e,r){return"number"==typeof t&&"number"==typeof e?q.number(t,e,r):Array.isArray(t)&&Array.isArray(e)?e.map(((e,i)=>q.number(t[i],e,r))):e}function C(t){const e=t.formattedValue,r=this;e&&null!=r._tooltipOutlier&&t.datasetIndex===r._tooltipOutlier.datasetIndex&&(e.hoveredOutlierIndex=r._tooltipOutlier.index)}function M(t,e){if(!t.length)return!1;let r=0,i=0,o=0;for(let n=0;n<t.length;n+=1){const s=t[n].element;if(s&&s.hasValue()){const t=s.tooltipPosition(e,this);r+=t.x,i+=t.y,o+=1}}return{x:r/o,y:i/o}}function v(t){const e=["borderColor","backgroundColor"].concat(t.filter((t=>t.endsWith("Color"))));return{animations:{numberArray:{fn:k,properties:["outliers","items"]},colors:{type:"color",properties:e}},transitions:{show:{animations:{colors:{type:"color",properties:e,from:"transparent"}}},hide:{animations:{colors:{type:"color",properties:e,to:"transparent"}}}},minStats:"min",maxStats:"max",...x}}function B(){return{plugins:{tooltip:{position:M.register().id,callbacks:{beforeLabel:C}}}}}M.id="average",M.register=()=>(e.Tooltip.positioners.average=M,M);class _ extends e.BarController{_transformStats(t,e,r){for(const i of["min","max","median","q3","q1","mean"]){const o=e[i];"number"==typeof o&&(t[i]=r(o))}for(const i of["outliers","items"])Array.isArray(e[i])&&(t[i]=e[i].map(r))}getMinMax(t,e){const r=t.axis,i=this.options;t.axis=i.minStats;const{min:o}=super.getMinMax(t,e);t.axis=i.maxStats;const{max:n}=super.getMinMax(t,e);return t.axis=r,{min:o,max:n}}parsePrimitiveData(t,e,r,i){const o=t.vScale,n=t.iScale,s=n.getLabels(),a=[];for(let t=0;t<i;t+=1){const i=t+r,l={};l[n.axis]=n.parse(s[i],i);const u=this._parseStats(null==e?null:e[i],this.options);u&&(Object.assign(l,u),l[o.axis]=u.median),a.push(l)}return a}parseArrayData(t,e,r,i){return this.parsePrimitiveData(t,e,r,i)}parseObjectData(t,e,r,i){return this.parsePrimitiveData(t,e,r,i)}getLabelAndValue(t){const e=super.getLabelAndValue(t),{vScale:r}=this._cachedMeta,i=this.getParsed(t);if(!r||!i||"NaN"===e.value)return e;e.value={raw:i,hoveredOutlierIndex:-1},this._transformStats(e.value,i,(t=>r.getLabelForValue(t)));const o=this._toStringStats(e.value.raw);return e.value.toString=function(){return this.hoveredOutlierIndex>=0?`(outlier: ${this.outliers[this.hoveredOutlierIndex]})`:o},e}_toStringStats(t){const e=t=>null==t?"NaN":r.formatNumber(t,this.chart.options.locale,{});return`(min: ${e(t.min)}, 25% quantile: ${e(t.q1)}, median: ${e(t.median)}, mean: ${e(t.mean)}, 75% quantile: ${e(t.q3)}, max: ${e(t.max)})`}updateElement(t,e,r,i){const o="reset"===i,n=this._cachedMeta.vScale,s=this.getParsed(e),a=n.getBasePixel();r._datasetIndex=this.index,r._index=e,this._transformStats(r,s,(t=>o?a:n.getPixelForValue(t,e))),super.updateElement(t,e,r,i)}}const N={borderWidth:1,outlierStyle:"circle",outlierRadius:2,outlierBorderWidth:1,itemStyle:"circle",itemRadius:0,itemBorderWidth:0,meanStyle:"circle",meanRadius:3,meanBorderWidth:1,hitPadding:2,outlierHitRadius:4},S={outlierBackgroundColor:"backgroundColor",outlierBorderColor:"borderColor",itemBackgroundColor:"backgroundColor",itemBorderColor:"borderColor",meanBackgroundColor:"backgroundColor",meanBorderColor:"borderColor"},P=Object.keys(N).concat(Object.keys(S));class A extends e.Element{isVertical(){return!this.horizontal}_drawItems(t){const e=this.isVertical(),i=this.getProps(["x","y","items","width","height","outliers"]),{options:o}=this;if(o.itemRadius<=0||!i.items||i.items.length<=0)return;t.save(),t.strokeStyle=o.itemBorderColor,t.fillStyle=o.itemBackgroundColor,t.lineWidth=o.itemBorderWidth;const n=function(t=Date.now()){let e=t;return()=>(e=(9301*e+49297)%233280,e/233280)}(1e3*this._datasetIndex+this._index),s={pointStyle:o.itemStyle,radius:o.itemRadius,borderWidth:o.itemBorderWidth},a=new Set(i.outliers||[]);e?i.items.forEach((e=>{a.has(e)||r.drawPoint(t,s,i.x-i.width/2+n()*i.width,e)})):i.items.forEach((e=>{a.has(e)||r.drawPoint(t,s,e,i.y-i.height/2+n()*i.height)})),t.restore()}_drawOutliers(t){const e=this.isVertical(),i=this.getProps(["x","y","outliers"]),{options:o}=this;if(o.outlierRadius<=0||!i.outliers||0===i.outliers.length)return;t.save(),t.fillStyle=o.outlierBackgroundColor,t.strokeStyle=o.outlierBorderColor,t.lineWidth=o.outlierBorderWidth;const n={pointStyle:o.outlierStyle,radius:o.outlierRadius,borderWidth:o.outlierBorderWidth};e?i.outliers.forEach((e=>{r.drawPoint(t,n,i.x,e)})):i.outliers.forEach((e=>{r.drawPoint(t,n,e,i.y)})),t.restore()}_drawMeanDot(t){const e=this.isVertical(),i=this.getProps(["x","y","mean"]),{options:o}=this;if(o.meanRadius<=0||null==i.mean||Number.isNaN(i.mean))return;t.save(),t.fillStyle=o.meanBackgroundColor,t.strokeStyle=o.meanBorderColor,t.lineWidth=o.meanBorderWidth;const n={pointStyle:o.meanStyle,radius:o.meanRadius,borderWidth:o.meanBorderWidth};e?r.drawPoint(t,n,i.x,i.mean):r.drawPoint(t,n,i.mean,i.y),t.restore()}_getBounds(t){return{left:0,top:0,right:0,bottom:0}}_getHitBounds(t){const e=this.options.hitPadding,r=this._getBounds(t);return{left:r.left-e,top:r.top-e,right:r.right+e,bottom:r.bottom+e}}inRange(t,e,r){return(!Number.isNaN(this.x)||!Number.isNaN(this.y))&&(this._boxInRange(t,e,r)||this._outlierIndexInRange(t,e,r)>=0)}inXRange(t,e){const r=this._getHitBounds(e);return t>=r.left&&t<=r.right}inYRange(t,e){const r=this._getHitBounds(e);return t>=r.top&&t<=r.bottom}_outlierIndexInRange(t,e,r){const i=this.getProps(["x","y"],r),o=this.options.outlierHitRadius,n=this._getOutliers(r),s=this.isVertical();if(s&&Math.abs(t-i.x)>o||!s&&Math.abs(e-i.y)>o)return-1;const a=s?e:t;for(let t=0;t<n.length;t+=1)if(Math.abs(n[t]-a)<=o)return t;return-1}_boxInRange(t,e,r){const i=this._getHitBounds(r);return t>=i.left&&t<=i.right&&e>=i.top&&e<=i.bottom}getCenterPoint(t){const e=this.getProps(["x","y"],t);return{x:e.x,y:e.y}}_getOutliers(t){return this.getProps(["outliers"],t).outliers||[]}tooltipPosition(t,e){if(!t||"boolean"==typeof t)return this.getCenterPoint();e&&delete e._tooltipOutlier;const r=this.getProps(["x","y"]),i=this._outlierIndexInRange(t.x,t.y);return i<0||!e?this.getCenterPoint():(e._tooltipOutlier={index:i,datasetIndex:this._datasetIndex},this.isVertical()?{x:r.x,y:this._getOutliers()[i]}:{x:this._getOutliers()[i],y:r.y})}}const T=P.concat(["medianColor","lowerBackgroundColor"]);class R extends A{draw(t){t.save(),t.fillStyle=this.options.backgroundColor,t.strokeStyle=this.options.borderColor,t.lineWidth=this.options.borderWidth,this._drawBoxPlot(t),this._drawOutliers(t),this._drawMeanDot(t),t.restore(),this._drawItems(t)}_drawBoxPlot(t){this.isVertical()?this._drawBoxPlotVertical(t):this._drawBoxPlotHorizontal(t)}_drawBoxPlotVertical(t){const{options:e}=this,r=this.getProps(["x","width","q1","q3","median","whiskerMin","whiskerMax"]),{x:i}=r,{width:o}=r,n=i-o/2;r.q3>r.q1?t.fillRect(n,r.q1,o,r.q3-r.q1):t.fillRect(n,r.q3,o,r.q1-r.q3),t.save(),e.medianColor&&"transparent"!==e.medianColor&&"#0000"!==e.medianColor&&(t.strokeStyle=e.medianColor),t.beginPath(),t.moveTo(n,r.median),t.lineTo(n+o,r.median),t.closePath(),t.stroke(),t.restore(),t.save(),e.lowerBackgroundColor&&"transparent"!==e.lowerBackgroundColor&&"#0000"!==e.lowerBackgroundColor&&(t.fillStyle=e.lowerBackgroundColor,r.q3>r.q1?t.fillRect(n,r.median,o,r.q3-r.median):t.fillRect(n,r.median,o,r.q1-r.median)),t.restore(),r.q3>r.q1?t.strokeRect(n,r.q1,o,r.q3-r.q1):t.strokeRect(n,r.q3,o,r.q1-r.q3),t.beginPath(),t.moveTo(n,r.whiskerMin),t.lineTo(n+o,r.whiskerMin),t.moveTo(i,r.whiskerMin),t.lineTo(i,r.q1),t.moveTo(n,r.whiskerMax),t.lineTo(n+o,r.whiskerMax),t.moveTo(i,r.whiskerMax),t.lineTo(i,r.q3),t.closePath(),t.stroke()}_drawBoxPlotHorizontal(t){const{options:e}=this,r=this.getProps(["y","height","q1","q3","median","whiskerMin","whiskerMax"]),{y:i}=r,{height:o}=r,n=i-o/2;r.q3>r.q1?t.fillRect(r.q1,n,r.q3-r.q1,o):t.fillRect(r.q3,n,r.q1-r.q3,o),t.save(),e.medianColor&&"transparent"!==e.medianColor&&(t.strokeStyle=e.medianColor),t.beginPath(),t.moveTo(r.median,n),t.lineTo(r.median,n+o),t.closePath(),t.stroke(),t.restore(),t.save(),e.lowerBackgroundColor&&"transparent"!==e.lowerBackgroundColor&&(t.fillStyle=e.lowerBackgroundColor,r.q3>r.q1?t.fillRect(r.median,n,r.q3-r.median,o):t.fillRect(r.median,n,r.q1-r.median,o)),t.restore(),r.q3>r.q1?t.strokeRect(r.q1,n,r.q3-r.q1,o):t.strokeRect(r.q3,n,r.q1-r.q3,o),t.beginPath(),t.moveTo(r.whiskerMin,n),t.lineTo(r.whiskerMin,n+o),t.moveTo(r.whiskerMin,i),t.lineTo(r.q1,i),t.moveTo(r.whiskerMax,n),t.lineTo(r.whiskerMax,n+o),t.moveTo(r.whiskerMax,i),t.lineTo(r.q3,i),t.closePath(),t.stroke()}_getBounds(t){const e=this.isVertical();if(null==this.x)return{left:0,top:0,right:0,bottom:0};if(e){const{x:e,width:r,whiskerMax:i,whiskerMin:o}=this.getProps(["x","width","whiskerMin","whiskerMax"],t),n=e-r/2;return{left:n,top:i,right:n+r,bottom:o}}const{y:r,height:i,whiskerMax:o,whiskerMin:n}=this.getProps(["y","height","whiskerMin","whiskerMax"],t),s=r-i/2;return{left:n,top:s,right:o,bottom:s+i}}}R.id="boxandwhiskers",R.defaults={...e.BarElement.defaults,...N,medianColor:"transparent",lowerBackgroundColor:"transparent"},R.defaultRoutes={...e.BarElement.defaultRoutes,...S};class E extends A{draw(t){t.save(),t.fillStyle=this.options.backgroundColor,t.strokeStyle=this.options.borderColor,t.lineWidth=this.options.borderWidth;const e=this.getProps(["x","y","width","height","min","max","coords","maxEstimate"]);r.drawPoint(t,{pointStyle:"rectRot",radius:5,borderWidth:this.options.borderWidth},e.x,e.y),e.coords&&e.coords.length>0&&this._drawCoords(t,e),this._drawOutliers(t),this._drawMeanDot(t),t.restore(),this._drawItems(t)}_drawCoords(t,e){if(t.beginPath(),this.isVertical()){const{x:r,width:i}=e,o=i/2/e.maxEstimate;t.moveTo(r,e.min),e.coords.forEach((e=>{t.lineTo(r-e.estimate*o,e.v)})),t.lineTo(r,e.max),t.moveTo(r,e.min),e.coords.forEach((e=>{t.lineTo(r+e.estimate*o,e.v)})),t.lineTo(r,e.max)}else{const{y:r,height:i}=e,o=i/2/e.maxEstimate;t.moveTo(e.min,r),e.coords.forEach((e=>{t.lineTo(e.v,r-e.estimate*o)})),t.lineTo(e.max,r),t.moveTo(e.min,r),e.coords.forEach((e=>{t.lineTo(e.v,r+e.estimate*o)})),t.lineTo(e.max,r)}t.closePath(),t.stroke(),t.fill()}_getBounds(t){if(this.isVertical()){const{x:e,width:r,min:i,max:o}=this.getProps(["x","width","min","max"],t),n=e-r/2;return{left:n,top:o,right:n+r,bottom:i}}const{y:e,height:r,min:i,max:o}=this.getProps(["y","height","min","max"],t),n=e-r/2;return{left:i,top:n,right:o,bottom:n+r}}}function I(t,r,i,o=[],n=[]){e.registry.addControllers(i),Array.isArray(o)?e.registry.addElements(...o):e.registry.addElements(o),Array.isArray(n)?e.registry.addScales(...n):e.registry.addScales(n);const s=r;return s.type=t,s}E.id="violin",E.defaults={...e.BarElement.defaults,...N},E.defaultRoutes={...e.BarElement.defaultRoutes,...S};class W extends _{_parseStats(t,e){return b(t,e)}_transformStats(t,e,r){super._transformStats(t,e,r);for(const i of["whiskerMin","whiskerMax"])t[i]=r(e[i])}}W.id="boxplot",W.defaults=r.merge({},[e.BarController.defaults,v(T),{animations:{numbers:{type:"number",properties:e.BarController.defaults.animations.numbers.properties.concat(["q1","q3","min","max","median","whiskerMin","whiskerMax","mean"],T.filter((t=>!t.endsWith("Color"))))}},dataElementType:R.id}]),W.overrides=r.merge({},[e.BarController.overrides,B()]);class V extends e.Chart{constructor(t,r){super(t,I("boxplot",r,W,R,[e.LinearScale,e.CategoryScale]))}}V.id=W.id;class O extends _{_parseStats(t,e){return w(t,e)}_transformStats(t,e,r){super._transformStats(t,e,r),t.maxEstimate=e.maxEstimate,Array.isArray(e.coords)&&(t.coords=e.coords.map((t=>({...t,v:r(t.v)}))))}}O.id="violin",O.defaults=r.merge({},[e.BarController.defaults,v(P),{points:100,animations:{numbers:{type:"number",properties:e.BarController.defaults.animations.numbers.properties.concat(["q1","q3","min","max","median","maxEstimate"],P.filter((t=>!t.endsWith("Color"))))},kdeCoords:{fn:function(t,e,r){return Array.isArray(t)&&Array.isArray(e)?e.map(((e,i)=>({v:q.number(t[i]?t[i].v:null,e.v,r),estimate:q.number(t[i]?t[i].estimate:null,e.estimate,r)}))):e},properties:["coords"]}},dataElementType:E.id}]),O.overrides=r.merge({},[e.BarController.overrides,B()]);class H extends e.Chart{constructor(t,r){super(t,I("violin",r,O,E,[e.LinearScale,e.CategoryScale]))}}H.id=O.id,e.registry.addControllers(W,O),e.registry.addElements(R,E),t.BoxAndWiskers=R,t.BoxPlotChart=V,t.BoxPlotController=W,t.StatsBase=A,t.Violin=E,t.ViolinChart=H,t.ViolinController=O,Object.defineProperty(t,"__esModule",{value:!0})})); | ||
| //# sourceMappingURL=index.umd.min.js.map |
| { | ||
| "name": "@sgratzl/chartjs-chart-boxplot", | ||
| "description": "Chart.js module for charting boxplots and violin charts", | ||
| "version": "3.6.0", | ||
| "version": "3.7.0", | ||
| "publishConfig": { | ||
@@ -53,3 +53,3 @@ "access": "public" | ||
| "peerDependencies": { | ||
| "chart.js": "^3.6.0" | ||
| "chart.js": "^3.7.0" | ||
| }, | ||
@@ -62,40 +62,40 @@ "browserslist": [ | ||
| "dependencies": { | ||
| "@sgratzl/boxplots": "^1.2.2" | ||
| "@sgratzl/boxplots": "^1.3.0" | ||
| }, | ||
| "devDependencies": { | ||
| "@rollup/plugin-commonjs": "^21.0.1", | ||
| "@rollup/plugin-node-resolve": "^13.0.6", | ||
| "@rollup/plugin-replace": "^3.0.0", | ||
| "@rollup/plugin-node-resolve": "^13.1.3", | ||
| "@rollup/plugin-replace": "^3.0.1", | ||
| "@rollup/plugin-typescript": "^8.3.0", | ||
| "@types/jest": "^27.0.2", | ||
| "@types/jest": "^27.4.0", | ||
| "@types/jest-image-snapshot": "^4.3.1", | ||
| "@types/node": "^16.11.6", | ||
| "@typescript-eslint/eslint-plugin": "^5.3.0", | ||
| "@typescript-eslint/parser": "^5.3.0", | ||
| "@types/node": "^17.0.16", | ||
| "@typescript-eslint/eslint-plugin": "^5.11.0", | ||
| "@typescript-eslint/parser": "^5.11.0", | ||
| "@yarnpkg/sdks": "^2.5.0", | ||
| "canvas": "^2.8.0", | ||
| "canvas": "^2.9.0", | ||
| "canvas-5-polyfill": "^0.1.5", | ||
| "chart.js": "^3.6.0", | ||
| "eslint": "^8.1.0", | ||
| "eslint-config-airbnb-typescript": "^14.0.1", | ||
| "chart.js": "^3.7.0", | ||
| "eslint": "^8.8.0", | ||
| "eslint-config-airbnb-typescript": "^16.1.0", | ||
| "eslint-config-prettier": "^8.3.0", | ||
| "eslint-config-react-app": "^6.0.0", | ||
| "eslint-config-react-app": "^7.0.0", | ||
| "eslint-plugin-flowtype": "^8.0.3", | ||
| "eslint-plugin-import": "^2.25.2", | ||
| "eslint-plugin-jsx-a11y": "^6.4.1", | ||
| "eslint-plugin-import": "^2.25.4", | ||
| "eslint-plugin-jsx-a11y": "^6.5.1", | ||
| "eslint-plugin-prettier": "^4.0.0", | ||
| "eslint-plugin-react": "^7.26.1", | ||
| "eslint-plugin-react-hooks": "^4.2.0", | ||
| "jest": "^27.3.1", | ||
| "eslint-plugin-react": "^7.28.0", | ||
| "eslint-plugin-react-hooks": "^4.3.0", | ||
| "jest": "^27.5.1", | ||
| "jest-image-snapshot": "^4.5.1", | ||
| "prettier": "^2.4.1", | ||
| "prettier": "^2.5.1", | ||
| "rimraf": "^3.0.2", | ||
| "rollup": "^2.59.0", | ||
| "rollup": "^2.67.1", | ||
| "rollup-plugin-cleanup": "^3.2.1", | ||
| "rollup-plugin-dts": "^4.0.0", | ||
| "rollup-plugin-dts": "^4.1.0", | ||
| "rollup-plugin-terser": "^7.0.2", | ||
| "ts-jest": "^27.0.7", | ||
| "ts-jest": "^27.1.3", | ||
| "tslib": "^2.3.1", | ||
| "typedoc": "^0.22.7", | ||
| "typescript": "^4.4.4" | ||
| "typedoc": "^0.22.11", | ||
| "typescript": "^4.5.5" | ||
| }, | ||
@@ -121,7 +121,7 @@ "scripts": { | ||
| "dependenciesMeta": { | ||
| "chart.js@3.6.0": { | ||
| "chart.js@3.7.0": { | ||
| "unplugged": true | ||
| } | ||
| }, | ||
| "packageManager": "yarn@3.1.0" | ||
| "packageManager": "yarn@3.1.1" | ||
| } |
@@ -86,7 +86,7 @@ # Chart.js Box and Violin Plot | ||
| ```js | ||
| import Chart from 'chart.js'; | ||
| import { BoxPlotController } from '@sgratzl/chartjs-chart-boxplot'; | ||
| import Chart, { LinearScale, CategoryScale } from 'chart.js'; | ||
| import { BoxPlotController, BoxAndWiskers } from '@sgratzl/chartjs-chart-boxplot'; | ||
| // register controller in chart.js and ensure the defaults are set | ||
| Chart.register(BoxPlotController); | ||
| Chart.register(BoxPlotController, BoxAndWiskers, LinearScale, CategoryScale); | ||
| ... | ||
@@ -93,0 +93,0 @@ |
@@ -49,3 +49,3 @@ import { BarController, Element, ChartMeta, LinearScale, Scale, UpdateMode } from 'chart.js'; | ||
| plugins: { | ||
| tooltips: { | ||
| tooltip: { | ||
| position: outlierPositioner.register().id, | ||
@@ -52,0 +52,0 @@ callbacks: { |
@@ -11,3 +11,2 @@ import boxplots, { | ||
| } from '@sgratzl/boxplots'; | ||
| import kde from './kde'; | ||
@@ -200,21 +199,7 @@ export { | ||
| export function violinStats(arr: readonly number[], options: IViolinOptions): IViolin | undefined { | ||
| // console.assert(Array.isArray(arr)); | ||
| if (arr.length === 0) { | ||
| return undefined; | ||
| } | ||
| const items = arr.filter((v) => typeof v === 'number' && !Number.isNaN(v)).sort((a, b) => a - b); | ||
| const mean = items.reduce((acc, v) => acc + v, 0) / items.length; | ||
| const { quantiles } = determineStatsOptions(options); | ||
| const stats = quantiles(items); | ||
| const min = items[0]; | ||
| const max = items[items.length - 1]; | ||
| function computeSamples(min: number, max: number, points: number) { | ||
| // generate coordinates | ||
| const range = max - min; | ||
| const samples = []; | ||
| const inc = range / options.points; | ||
| const samples: number[] = []; | ||
| const inc = range / points; | ||
| for (let v = min; v <= max && inc > 0; v += inc) { | ||
@@ -226,11 +211,25 @@ samples.push(v); | ||
| } | ||
| const coords = kde(items, samples, quantiles); | ||
| return samples; | ||
| } | ||
| export function violinStats(arr: readonly number[], options: IViolinOptions): IViolin | undefined { | ||
| // console.assert(Array.isArray(arr)); | ||
| if (arr.length === 0) { | ||
| return undefined; | ||
| } | ||
| const stats = boxplots(arr, determineStatsOptions(options)); | ||
| // generate coordinates | ||
| const samples = computeSamples(stats.min, stats.max, options.points); | ||
| const coords = samples.map((v) => ({ v, estimate: stats.kde(v) })); | ||
| const maxEstimate = coords.reduce((a, d) => Math.max(a, d.estimate), Number.NEGATIVE_INFINITY); | ||
| return { | ||
| ...stats, | ||
| min, | ||
| items, | ||
| mean, | ||
| max, | ||
| max: stats.max, | ||
| min: stats.min, | ||
| mean: stats.mean, | ||
| median: stats.median, | ||
| q1: stats.q1, | ||
| q3: stats.q3, | ||
| items: Array.from(stats.items), | ||
| coords, | ||
@@ -237,0 +236,0 @@ outliers: [], // items.filter((d) => d < stats.q1 || d > stats.q3), |
@@ -48,6 +48,6 @@ import { InteractionItem, TooltipItem, Tooltip, TooltipModel } from 'chart.js'; | ||
| outlierPositioner.id = 'averageInstance'; | ||
| outlierPositioner.id = 'average'; | ||
| outlierPositioner.register = () => { | ||
| Tooltip.positioners.averageInstance = outlierPositioner as any; | ||
| Tooltip.positioners.average = outlierPositioner as any; | ||
| return outlierPositioner; | ||
| }; |
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No alert changes
Worsened metrics
- Total package byte prevSize
- decreased by-1.18%
349058
- Number of package files
- decreased by-3.12%
31
- Lines of code
- decreased by-1.73%
5228
Dependency changes
Updated@sgratzl/boxplots@^1.3.0