Various Functions and Methods for sample distributions
Project description
kavanaghdistributions
kavanaghdistributions is a python package for generating samples from Normal, Poisson and Binomial Distributions.
Installation
Use the package manager pip to install kavanaghdistributions.
pip install kavanaghdistributions
Usage
from kavanaghdistributions.functions import random_draw
from kavanaghdistributions.classes import NormalDistribution, PoissonDistribution, BinomialDistribution
#random_draw function
random_draw(sample_shape=5, distribution='normal', mean=1, sd=2)
# generates: array([1.82261281, 0.81926903, 3.06892213, 1.62636623, 2.05127246])
random_draw(sample_shape=5, distribution='poisson', lam=10)
# generates: array([12, 8, 7, 14, 8])
random_draw(sample_shape=(2,2), distribution='binomial', num=2, prob=0.3)
#generates: array([[0, 0],
# [1, 0]])
#NormalDistribution
nd = NormalDistribution(mean=3, sd=1, sample_shape=5)
nd.draw()
#generates array([3.59149631, 3.13146966, 3.98872244, 3.59125381, 4.36412151])
nd.summarise()
#generates:
#Min: 3.1314696620512454
#Max: 4.3641215077437945
#Mean: 3.733412745193425
#Standard Deviation: 0.41609169604466906
#PoissonDistribution
pd = PoissonDistribution(lam=(2,3,2), sample_shape=[2,2,3])
pd.draw()
#generates:
#array([[[0, 0, 2],
# [2, 1, 1]],
#
# [[3, 3, 1],
# [2, 1, 3]]])
pd.summarise()
#generates:
#Min: 0
#Max: 3
#Mean: 1.5833333333333333
#Standard Deviation: 1.0374916331657276
#BinomialDistribution
bd = BinomialDistribution(num=4, prob=0.5, sample_shape=6)
bd.draw()
#generates: array([2, 3, 2, 1, 1, 1])
bd.summarise()
#generates:
#Min: 1
#Max: 3
#Mean: 1.6666666666666667
#Standard Deviation: 0.74535599249993
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