stats-lite - npm Package Compare versions

Comparing version 2.0.4 to 2.1.0

package.json

		{
		"name": "stats-lite",
		"version": "2.0.4",
		"version": "2.1.0",
		"description": "A light statistical package that operates on numeric Arrays.",
		@@ -43,2 +43,3 @@ "main": "stats.js",
		"devDependencies": {
		"dice": "0.0.2",
		"tape": "~4.6.3"
		@@ -45,0 +46,0 @@ },

README.md

		@@ -30,2 +30,3 @@ stats-lite
		console.log("85th percentile: %s", stats.percentile(rolls, 0.85))
		console.log("histogram:", stats.histogram(rolls))

		@@ -40,2 +41,6 @@ /* Your exact numbers may vary, but they should be pretty similar:
		85th percentile: 10
		histogram { values: [ 86, 159, 253, 335, 907, 405, 339, 270, 146, 100 ],
		bins: 10,
		binWidth: 1.05,
		binLimits: [ 1.75, 12.25 ] }
		*/
		@@ -101,2 +106,16 @@

		`histogram(vals[, bins])`
		---

		Build a histogram representing the distribution of the data in the provided number of `bins`. If `bins` is not set, it will choose one based on `Math.sqrt(vals.length)`. Data will look like:
		```
		histogram {
		values: [ 86, 159, 253, 335, 907, 405, 339, 270, 146, 100 ],
		bins: 10,
		binWidth: 1.05,
		binLimits: [ 1.75, 12.25 ]
		}
		```
		Where `values` are the bins and the counts of the original values falling in that range. The ranges can be calculated from the `binWidth` and `binLimits`. For example, the first bin `values[0]` in this example is from `1.75 < value <= 2.8`. The third bin `values[2]` would be `1.75 + (1.05 * 2) < value <= 1.75 + (1.05 * 3)` or `3.85 < value <= 4.9`.

		LICENSE
		@@ -103,0 +122,0 @@ =======

stats.js

		@@ -11,2 +11,3 @@ "use strict";
		module.exports.percentile = percentile
		module.exports.histogram = histogram

		@@ -131,1 +132,56 @@ var isNumber = require("isnumber")
		}

		function histogram (vals, bins) {
		if (vals == null) {
		return null
		}
		vals = nsort(numbers(vals))
		if (vals.length === 0) {
		return null
		}
		if (bins == null) {
		// pick bins by simple method: Math.sqrt(n)
		bins = Math.sqrt(vals.length)
		}
		bins = Math.round(bins)
		if (bins < 1) {
		bins = 1
		}

		var min = vals[0]
		var max = vals[vals.length - 1]
		if (min === max) {
		// fudge for non-variant data
		min = min - 0.5
		max = max + 0.5
		}

		var range = (max - min)
		// make the bins slightly larger by expanding the range about 10%
		// this helps with dumb floating point stuff
		var binWidth = (range + (range * 0.05)) / bins
		var midpoint = (min + max) / 2
		// even bin count, midpoint makes an edge
		var leftEdge = midpoint - (binWidth * Math.floor(bins / 2))
		if (bins % 2 !== 0) {
		// odd bin count, center middle bin on midpoint
		var leftEdge = (midpoint - (binWidth / 2)) - (binWidth * Math.floor(bins / 2))
		}

		var hist = {
		values: Array(bins).fill(0),
		bins: bins,
		binWidth: binWidth,
		binLimits: [leftEdge, leftEdge + (binWidth * bins)]
		}

		var binIndex = 0
		for (var i = 0; i < vals.length; i++) {
		while (vals[i] > (((binIndex + 1) * binWidth) + leftEdge)) {
		binIndex++
		}
		hist.values[binIndex]++
		}

		return hist
		}

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