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/*********************************************************************
* NAN - Native Abstractions for Node.js
*
* Copyright (c) 2018 NAN contributors
*
* MIT License <https://github.com/nodejs/nan/blob/master/LICENSE.md>
********************************************************************/
#include <cstdlib>
#include "pi_est.h" // NOLINT(build/include_subdir)
/*
Estimate the value of π by using a Monte Carlo method.
Take `points` samples of random x and y values on a
[0,1][0,1] plane. Calculating the length of the diagonal
tells us whether the point lies inside, or outside a
quarter circle running from 0,1 to 1,0. The ratio of the
number of points inside to outside gives us an
approximation of π/4.
See https://en.wikipedia.org/wiki/File:Pi_30K.gif
for a visualization of how this works.
*/
inline int randall(unsigned int *p_seed) {
// windows has thread safe rand()
#ifdef _WIN32
return rand(); // NOLINT(runtime/threadsafe_fn)
#else
return rand_r(p_seed);
#endif
}
double Estimate (int points) {
int i = points;
int inside = 0;
unsigned int randseed = 1;
#ifdef _WIN32
srand(randseed);
#endif
// unique seed for each run, for threaded use
unsigned int seed = randall(&randseed);
#ifdef _WIN32
srand(seed);
#endif
while (i-- > 0) {
double x = randall(&seed) / static_cast<double>(RAND_MAX);
double y = randall(&seed) / static_cast<double>(RAND_MAX);
// x & y and now values between 0 and 1
// now do a pythagorean diagonal calculation
// `1` represents our 1/4 circle
if ((x * x) + (y * y) <= 1)
inside++;
}
// calculate ratio and multiply by 4 for π
return (inside / static_cast<double>(points)) * 4;
}
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