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198 lines
5.4 KiB
JavaScript
198 lines
5.4 KiB
JavaScript
'use strict';
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var deepMap = require('../../utils/collection/deepMap');
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var sign = require('../../utils/number').sign;
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function factory (type, config, load, typed) {
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/**
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* Compute the erf function of a value using a rational Chebyshev
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* approximations for different intervals of x.
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*
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* This is a translation of W. J. Cody's Fortran implementation from 1987
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* ( http://www.netlib.org/specfun/erf ). See the AMS publication
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* "Rational Chebyshev Approximations for the Error Function" by W. J. Cody
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* for an explanation of this process.
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*
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* For matrices, the function is evaluated element wise.
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*
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* Syntax:
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*
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* math.erf(x)
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*
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* Examples:
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*
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* math.erf(0.2); // returns 0.22270258921047847
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* math.erf(-0.5); // returns -0.5204998778130465
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* math.erf(4); // returns 0.9999999845827421
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*
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* @param {number | Array | Matrix} x A real number
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* @return {number | Array | Matrix} The erf of `x`
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*/
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var erf = typed('erf', {
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'number': function (x) {
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var y = Math.abs(x);
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if (y >= MAX_NUM) {
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return sign(x);
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}
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if (y <= THRESH) {
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return sign(x) * erf1(y);
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}
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if (y <= 4.0) {
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return sign(x) * (1 - erfc2(y));
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}
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return sign(x) * (1 - erfc3(y));
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},
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// TODO: Not sure if there's a way to guarantee some degree of accuracy here.
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// Perhaps it would be best to set the precision of the number to that which
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// is guaranteed by erf()
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'BigNumber': function (n) {
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return new type.BigNumber(erf(n.toNumber()));
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},
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'Array | Matrix': function (n) {
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return deepMap(n, erf);
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}
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// TODO: For complex numbers, use the approximation for the Faddeeva function
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// from "More Efficient Computation of the Complex Error Function" (AMS)
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});
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/**
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* Approximates the error function erf() for x <= 0.46875 using this function:
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* n
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* erf(x) = x * sum (p_j * x^(2j)) / (q_j * x^(2j))
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* j=0
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*/
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function erf1(y) {
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var ysq = y * y;
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var xnum = P[0][4]*ysq;
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var xden = ysq;
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var i;
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for (i = 0; i < 3; i += 1) {
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xnum = (xnum + P[0][i]) * ysq;
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xden = (xden + Q[0][i]) * ysq;
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}
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return y * (xnum + P[0][3]) / (xden + Q[0][3]);
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}
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/**
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* Approximates the complement of the error function erfc() for
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* 0.46875 <= x <= 4.0 using this function:
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* n
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* erfc(x) = e^(-x^2) * sum (p_j * x^j) / (q_j * x^j)
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* j=0
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*/
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function erfc2(y) {
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var xnum = P[1][8] * y;
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var xden = y;
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var i;
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for (i = 0; i < 7; i += 1) {
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xnum = (xnum + P[1][i]) * y;
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xden = (xden + Q[1][i]) * y;
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}
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var result = (xnum + P[1][7]) / (xden + Q[1][7]);
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var ysq = parseInt(y * 16) / 16;
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var del = (y - ysq) * (y + ysq);
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return Math.exp(-ysq*ysq) * Math.exp(-del) * result;
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}
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/**
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* Approximates the complement of the error function erfc() for x > 4.0 using
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* this function:
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*
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* erfc(x) = (e^(-x^2) / x) * [ 1/sqrt(pi) +
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* n
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* 1/(x^2) * sum (p_j * x^(-2j)) / (q_j * x^(-2j)) ]
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* j=0
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*/
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function erfc3(y) {
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var ysq = 1 / (y * y);
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var xnum = P[2][5] * ysq;
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var xden = ysq;
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var i;
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for (i = 0; i < 4; i += 1) {
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xnum = (xnum + P[2][i]) * ysq;
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xden = (xden + Q[2][i]) * ysq;
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}
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var result = ysq * (xnum + P[2][4]) / (xden + Q[2][4]);
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result = (SQRPI - result) / y;
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ysq = parseInt(y * 16) / 16;
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var del = (y - ysq) * (y + ysq);
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return Math.exp(-ysq*ysq) * Math.exp(-del) * result;
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}
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erf.toTex = {1: 'erf\\left(${args[0]}\\right)'};
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return erf;
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}
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/**
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* Upper bound for the first approximation interval, 0 <= x <= THRESH
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* @constant
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*/
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var THRESH = 0.46875;
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/**
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* Constant used by W. J. Cody's Fortran77 implementation to denote sqrt(pi)
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* @constant
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*/
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var SQRPI = 5.6418958354775628695e-1;
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/**
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* Coefficients for each term of the numerator sum (p_j) for each approximation
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* interval (see W. J. Cody's paper for more details)
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* @constant
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*/
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var P = [[
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3.16112374387056560e00, 1.13864154151050156e02,
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3.77485237685302021e02, 3.20937758913846947e03,
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1.85777706184603153e-1
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], [
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5.64188496988670089e-1, 8.88314979438837594e00,
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6.61191906371416295e01, 2.98635138197400131e02,
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8.81952221241769090e02, 1.71204761263407058e03,
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2.05107837782607147e03, 1.23033935479799725e03,
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2.15311535474403846e-8
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], [
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3.05326634961232344e-1, 3.60344899949804439e-1,
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1.25781726111229246e-1, 1.60837851487422766e-2,
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6.58749161529837803e-4, 1.63153871373020978e-2
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]];
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/**
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* Coefficients for each term of the denominator sum (q_j) for each approximation
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* interval (see W. J. Cody's paper for more details)
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* @constant
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*/
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var Q = [[
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2.36012909523441209e01, 2.44024637934444173e02,
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1.28261652607737228e03, 2.84423683343917062e03
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], [
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1.57449261107098347e01, 1.17693950891312499e02,
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5.37181101862009858e02, 1.62138957456669019e03,
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3.29079923573345963e03, 4.36261909014324716e03,
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3.43936767414372164e03, 1.23033935480374942e03
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], [
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2.56852019228982242e00, 1.87295284992346047e00,
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5.27905102951428412e-1, 6.05183413124413191e-2,
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2.33520497626869185e-3
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]];
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/**
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* Maximum/minimum safe numbers to input to erf() (in ES6+, this number is
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* Number.[MAX|MIN]_SAFE_INTEGER). erf() for all numbers beyond this limit will
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* return 1
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*/
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var MAX_NUM = Math.pow(2, 53);
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exports.name = 'erf';
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exports.factory = factory;
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