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+// Copyright (c) 2019-2021 Alexander Medvednikov. All rights reserved.
+// Use of this source code is governed by an MIT license
+// that can be found in the LICENSE file.
+module dist
+
+import math
+import rand
+
+fn check_probability_range(p f64) {
+	if p < 0 || p > 1 {
+		panic('$p is not a valid probability value.')
+	}
+}
+
+// bernoulli returns true with a probability p. Note that 0 <= p <= 1.
+pub fn bernoulli(p f64) bool {
+	check_probability_range(p)
+	return rand.f64() <= p
+}
+
+// binomial returns the number of successful trials out of n when the
+// probability of success for each trial is p.
+pub fn binomial(n int, p f64) int {
+	check_probability_range(p)
+	mut count := 0
+	for _ in 0 .. n {
+		if bernoulli(p) {
+			count++
+		}
+	}
+	return count
+}
+
+// Configuration struct for the `normal_pair` function. The default value for
+// `mu` is 0 and the default value for `sigma` is 1.
+pub struct NormalConfigStruct {
+	mu    f64 = 0.0
+	sigma f64 = 1.0
+}
+
+// normal_pair returns a pair of normally distributed random numbers with the mean mu
+// and standard deviation sigma. If not specified, mu is 0 and sigma is 1. Intended usage is
+// `x, y := normal_pair(mu: mean, sigma: stdev)`, or `x, y := normal_pair()`.
+pub fn normal_pair(config NormalConfigStruct) (f64, f64) {
+	if config.sigma <= 0 {
+		panic('The standard deviation has to be positive.')
+	}
+	// This is an implementation of the Marsaglia polar method
+	// See: https://doi.org/10.1137%2F1006063
+	// Also: https://en.wikipedia.org/wiki/Marsaglia_polar_method
+	for {
+		u := rand.f64_in_range(-1, 1)
+		v := rand.f64_in_range(-1, 1)
+
+		s := u * u + v * v
+		if s >= 1 || s == 0 {
+			continue
+		}
+		t := math.sqrt(-2 * math.log(s) / s)
+		x := config.mu + config.sigma * t * u
+		y := config.mu + config.sigma * t * v
+		return x, y
+	}
+	return config.mu, config.mu
+}
+
+// normal returns a normally distributed random number with the mean mu and standard deviation
+// sigma. If not specified, mu is 0 and sigma is 1. Intended usage is
+// `x := normal(mu: mean, sigma: etdev)` or `x := normal()`.
+// **NOTE:** If you are generating a lot of normal variates, use `the normal_pair` function
+// instead. This function discards one of the two variates generated by the `normal_pair` function.
+pub fn normal(config NormalConfigStruct) f64 {
+	x, _ := normal_pair(config)
+	return x
+}
+
+// exponential returns an exponentially distributed random number with the rate paremeter
+// lambda. It is expected that lambda is positive.
+pub fn exponential(lambda f64) f64 {
+	if lambda <= 0 {
+		panic('The rate (lambda) must be positive.')
+	}
+	// Use the inverse transform sampling method
+	return -math.log(rand.f64()) / lambda
+}