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// Returns the value at a given percentile in a sorted numeric array. | |
// "Linear interpolation between closest ranks" method | |
function percentile(arr, p) { | |
if (arr.length === 0) return 0; | |
if (typeof p !== 'number') throw new TypeError('p must be a number'); | |
if (p <= 0) return arr[0]; | |
if (p >= 1) return arr[arr.length - 1]; | |
var index = (arr.length - 1) * p, | |
lower = Math.floor(index), | |
upper = lower + 1, | |
weight = index % 1; | |
if (upper >= arr.length) return arr[lower]; | |
return arr[lower] * (1 - weight) + arr[upper] * weight; | |
} | |
// Returns the percentile of the given value in a sorted numeric array. | |
function percentRank(arr, v) { | |
if (typeof v !== 'number') throw new TypeError('v must be a number'); | |
for (var i = 0, l = arr.length; i < l; i++) { | |
if (v <= arr[i]) { | |
while (i < l && v === arr[i]) i++; | |
if (i === 0) return 0; | |
if (v !== arr[i-1]) { | |
i += (v - arr[i-1]) / (arr[i] - arr[i-1]); | |
} | |
return i / l; | |
} | |
} | |
return 1; | |
} |
@ityoung2016 Agreed, but 21/2 is 10.5, not 11.5. If line 9 is changed to: var index = (arr.length - 1) * p,
then it passes both your tests.
Alternative percentile rank, closer to python's scipy.stats.percentileofscore
function percentRank(array, n) {
var L = 0;
var S = 0;
var N = array.length
for (var i = 0; i < array.length; i++) {
if (array[i] < n) {
L += 1
} else if (array[i] === n) {
S += 1
} else {
}
}
var pct = (L + (0.5 * S)) / N
return pct
}
Hi,
Thanks for your valuable contribution to writing such a nice code. I had found an issue when we calculate Percentile of decimal values. It's not calculated accurately because resulted value is not matched with Excel resulted value. We need to sort the array before going to perform operations on it. I had added sorting functionality in the following code. Now resulted value is matched with Excel value.
function percentile(arr, p) {
if (arr.length === 0) return 0;
if (typeof p !== 'number') throw new TypeError('p must be a number');
if (p <= 0) return arr[0];
if (p >= 1) return arr[arr.length - 1];
arr.sort(function (a, b) { return a - b; });
var index = (arr.length - 1) * p
lower = Math.floor(index),
upper = lower + 1,
weight = index % 1;
if (upper >= arr.length) return arr[lower];
return arr[lower] * (1 - weight) + arr[upper] * weight;
}
I've ported the function rank
method from numpy's percentileofscore
.
You need to have ramda
as dependency, but chances are if you need this function, you already use ramda
to facilitate functional programming:
const R = require('ramda')
const percentileOfScore = (array, value) => {
let originalLength = array.length
let a = [...array]
let alen
const equalsValue = v => v === value
if (!R.any(equalsValue, array)) {
a.push(value)
alen = range(a.length)
} else {
alen = range(a.length + 1)
}
const sortedArray = R.sort((a, b) => a - b, array)
const idx = R.map(equalsValue, sortedArray)
const alenTrue = R.filter((v, i) => {
return idx[alen.indexOf(v)] === true
}, alen)
const mean = R.mean(alenTrue)
const percent = mean / originalLength
return percent
}
@superzadeh Thanks for the function! Here's modified version that uses Lodash (to get the mean) and it expects array to be already sorted (to avoid n * sorting):
const percentileOfScore = (array, value) => {
const originalLength = array.length;
const a = [...array];
let alen;
const equalsValue = v => v === value;
if (!array.some(equalsValue)) {
a.push(value);
alen = range(a.length)
} else {
alen = range(a.length + 1)
}
const idx = array.map(equalsValue);
const alenTrue = alen.filter((v) => idx[alen.indexOf(v)]);
const meanVal = mean(alenTrue);
const percent = meanVal / originalLength;
return Math.round( percent * 100) / 100;
};
I don't know why I didn't see all these comments for years, but thanks for the contributions. I updated line 9.
// sort + filter by open interest
{
filteredBacktestResults.sort((a, b) => a.open_interest - b.open_interest)
const values = filteredBacktestResults.map(backtestResult => backtestResult.open_interest)
for (let i = 0; i < filteredBacktestResults.length; ++i) {
filteredBacktestResults[i].open_interest_rank_percentile = percentRank(values, filteredBacktestResults[i].open_interest)
}
filteredBacktestResults = filteredBacktestResults.filter(backtestResult => {
const openInterestTooLow = backtestResult.open_interest_rank_percentile <= 0.25 // bottom 25%
if (openInterestTooLow === true) {
return false
}
return true
})
}
hopefully this example helps somebody else on Google of how to use this, thank you @IceCreamYou + others who helped make it better
There seems to be a real bug in this program. Use arr = [1,2,3,18,19,27] and p = ½. The result should be 21/2 = 11.5 but the program gives 18. Then try arr = [1,2,3,18,19,22,27] with p = ½. The answer should be 18 but the program gives 18.5.