casio-calculator/distribution.py

import math


def bnd(x, n, p):
	"""
	Computes the binomial distribution.
	:param x: Number of successes.
	:param n: Number of trials.
	:param p: Probability of success.
	:return: Returns the probability of getting x successes in n trials.
	"""
	return math.comb(n, x) * p ** x * (1 - p) ** (n - x)


def bnd_mean(n, p):
	"""
	Computes the mean of the binomial distribution.
	:param n: Number of trials.
	:param p: Probability of success.
	:return: Returns the mean of the binomial distribution.
	"""
	return n * p


def bnd_var(n, p):
	"""
	Computes the variance of the binomial distribution.
	:param n: Number of trials.
	:param p: Probability of success.
	:return: Returns the variance of the binomial distribution.
	"""
	return n * p * (1 - p)


def bnd_std(n, p):
	"""
	Computes the standard deviation of the binomial distribution.
	:param n: Number of trials.
	:param p: Probability of success.
	:return: Returns the standard deviation of the binomial distribution.
	"""
	return bnd_var(n, p) ** 0.5


def bnd_upto(x, n, p):
	"""
	Computes the cumulative probability of getting upto x successes in n trials.
	:param x: Number of successes.
	:param n: Number of trials.
	:param p: Probability of success.
	:return: Returns the cumulative probability of getting upto x successes in n trials.
	"""
	return sum(bnd(i, n, p) for i in range(x + 1))


def bnd_from(x, n, p):
	"""
	Computes the cumulative probability of getting from x successes in n trials.
	:param x: Number of successes.
	:param n: Number of trials.
	:param p: Probability of success.
	:return: Returns the cumulative probability of getting from x successes in n trials.
	"""
	return 1 - bnd_upto(x - 1, n, p)


def gd(x, p, q=None):
	"""
	Computes the geometric distribution.
	:param x: Number of trials until the first success.
	:param p: Probability of success.
	:param q: Probability of failure.
	:return: Returns the probability of getting the first success on the xth trial.
	"""
	if q is None:
		q = 1 - p
	return q ** (x - 1) * p


def gd_mean(p):
	"""
	Computes the mean of the geometric distribution.
	:param p: Probability of success.
	:return: Returns the mean of the geometric distribution.
	"""
	return 1 / p


def gd_var(p):
	"""
	Computes the variance of the geometric distribution.
	:param p: Probability of success.
	:return: Returns the variance of the geometric distribution.
	"""
	return (1 - p) / p ** 2


def gd_std(p):
	"""
	Computes the standard deviation of the geometric distribution.
	:param p: Probability of success.
	:return: Returns the standard deviation of the geometric distribution.
	"""
	return gd_var(p) ** 0.5


def gd_upto(x, p, q=None):
	"""
	Computes the cumulative probability of getting upto x trials until the first success.
	:param x: Number of trials until the first success.
	:param p: Probability of success.
	:param q: Probability of failure.
	:return: Returns the cumulative probability of getting upto x trials until the first success.
	"""
	if q is not None:
		return sum(gd(i, p, q) for i in range(1, x + 1))
	return sum(gd(i, p) for i in range(1, x + 1))


def gd_from(x, p, q=None):
	"""
	Computes the cumulative probability of getting from x trials until the first success.
	:param x: Number of trials until the first success.
	:param p: Probability of success.
	:param q: Probability of failure.
	:return: Returns the cumulative probability of getting from x trials until the first success.
	"""
	if q is not None:
		return 1 - gd_upto(x - 1, p, q)
	return 1 - gd_upto(x - 1, p)


def hgd(x, N, n, k):
	"""
	Computes the hyper geometric distribution.
	:param x: Number of successes in the sample.
	:param N: Number of items in the population.
	:param n: Number of draws.
	:param k: Number of successes in the population.
	:return: Returns the probability of getting x successes in n draws from a population of size N with k successes.
	"""
	return (math.comb(k, x) * math.comb(N - k, n - x)) / math.comb(N, n)


def hgd_mean(N, n, k):
	"""
	Computes the mean of the hyper geometric distribution.
	:param N: Number of items in the population.
	:param n: Number of draws.
	:param k: Number of successes in the population.
	:return: Returns the mean of the hyper geometric distribution.
	"""
	return n * (k / N)


def hgd_var(N, n, k):
	"""
	Computes the variance of the hyper geometric distribution.
	:param N: Number of items in the population.
	:param n: Number of draws.
	:param k: Number of successes in the population.
	:return: Returns the variance of the hyper geometric distribution.
	"""
	return (n * k * (N - k) * (N - n)) / (N ** 2 * (N - 1))


def hgd_std(N, n, k):
	"""
	Computes the standard deviation of the hyper geometric distribution.
	:param N: Number of items in the population.
	:param n: Number of draws.
	:param k: Number of successes in the population.
	:return: Returns the standard deviation of the hyper geometric distribution.
	"""
	return hgd_var(N, n, k) ** 0.5


def hgd_upto(x, N, n, k):
	"""
	Computes the cumulative probability of getting upto x successes in n draws from a population of size N with k successes.
	:param x: Number of successes in the sample.
	:param N: Number of items in the population.
	:param n: Number of draws.
	:param k: Number of successes in the population.
	:return: Returns the cumulative probability of getting upto x successes in n draws from a population of size N with k successes.
	"""
	return sum(hgd(i, N, n, k) for i in range(x + 1))


def hgd_from(x, N, n, k):
	"""
	Computes the cumulative probability of getting from x successes in n draws from a population of size N with k successes.
	:param x: Number of successes in the sample.
	:param N: Number of items in the population.
	:param n: Number of draws.
	:param k: Number of successes in the population.
	:return: Returns the cumulative probability of getting from x successes in n draws from a population of size N with k successes.
	"""
	return 1 - hgd_upto(x - 1, N, n, k)


def pd(x, l):
	"""
	Computes the poisson distribution.
	:param x: Number of occurrences.
	:param l: Average number of occurrences.
	:return: Returns the probability of getting x occurrences.
	"""
	return (l ** x * math.e ** -l) / math.factorial(x)


def pd_mean(l):
	"""
	Computes the mean of the poisson distribution.
	:param l: Average number of occurrences.
	:return: Returns the mean of the poisson distribution.
	"""
	return l


def pd_var(l):
	"""
	Computes the variance of the poisson distribution.
	:param l: Average number of occurrences.
	:return: Returns the variance of the poisson distribution.
	"""
	return l


def pd_std(l):
	"""
	Computes the standard deviation of the poisson distribution.
	:param l: Average number of occurrences.
	:return: Returns the standard deviation of the poisson distribution.
	"""
	return l ** 0.5


def pd_upto(x, l):
	"""
	Computes the cumulative probability of getting upto x occurrences.
	:param x: Number of occurrences.
	:param l: Average number of occurrences.
	:return: Returns the cumulative probability of getting upto x occurrences.
	"""
	return sum(pd(i, l) for i in range(x + 1))


def pd_from(x, l):
	"""
	Computes the cumulative probability of getting from x occurrences.
	:param x: Number of occurrences.
	:param l: Average number of occurrences.
	:return: Returns the cumulative probability of getting from x occurrences.
	"""
	return 1 - pd_upto(x - 1, l)


def man():
	"""
	Prints the manual for the module.
	"""
	print(
		"""
This module contains functions for computing the total probability of events.
The functions are:
bnd(x, n, p) - The binomial distribution
bnd_mean(n, p) - The mean of the binomial distribution
bnd_var(n, p) - The variance of the binomial distribution
bnd_std(n, p) - The standard deviation of the binomial distribution
bnd_upto(x, n, p) - The cumulative probability of getting upto x successes in n trials
bnd_from(x, n, p) - The cumulative probability of getting from x successes in n trials
gd(x, p, q) - The geometric distribution
gd_mean(p) - The mean of the geometric distribution
gd_var(p) - The variance of the geometric distribution
gd_std(p) - The standard deviation of the geometric distribution
gd_upto(x, p, q) - The cumulative probability of getting upto x trials until the first success
gd_from(x, p, q) - The cumulative probability of getting from x trials until the first success
hgd(x, N, n, k) - The hyper geometric distribution
hgd_mean(N, n, k) - The mean of the hyper geometric distribution
hgd_var(N, n, k) - The variance of the hyper geometric distribution
hgd_std(N, n, k) - The standard deviation of the hyper geometric distribution
hgd_upto(x, N, n, k) - The cumulative probability of getting upto x successes in n draws from a population of size N with k successes
hgd_from(x, N, n, k) - The cumulative probability of getting from x successes in n draws from a population of size N with k successes
pd(x, l) - The poisson distribution
pd_mean(l) - The mean of the poisson distribution
pd_var(l) - The variance of the poisson distribution
pd_std(l) - The standard deviation of the poisson distribution
pd_upto(x, l) - The cumulative probability of getting upto x occurrences
pd_from(x, l) - The cumulative probability of getting from x occurrences
""")