Gaussian and Binomial Distributions
Project description
gaus-bin-dist
This package contains modules for working with Gaussian and Binomial Distributions.
Files
gaus_bin_dist/
: Distributions packageBinomialdistribution.py
: Binomial classGaussiandistribution.py
: Gaussian classGeneraldistribution.py
: Distribution class__init__.py
: Initialization script
license.txt
: MIT licensenumbers.txt
: Test file for Gaussian classnumbers_binomial.txt
: Test file for Binomial classsetup.cfg
: Configuration file for code packagingsetup.py
: Script for code packagingtest.py
: Unit tests
Installation
Download on PyPi or use following command:
pip install gaus-bin-dist
Python Interpreter Example
Initialization
>>> from gaus_bin_dist import Gaussian, Binomial
>>> Gaussian(10, 7)
mean 10, standard deviation 7
>>> Binomial(0.4, 25)
mean 10.0, standard deviation 2.449489742783178, p 0.4, n 25
Addition
>>> gaussian_one = Gaussian(25, 3)
>>> gaussian_two = Gaussian(30, 4)
>>> gaussian_one + gaussian_two
mean 55, standard deviation 5.0
>>> binomial_one = Binomial(0.4, 20)
>>> binomial_two = Binomial(0.4, 60)
>>> binomial_one + binomial_two
mean 32.0, standard deviation 4.381780460041329, p 0.4, n 80
Probability Density Function
>>> gaussian_one.pdf(25) # gaussian_one PDF at x = 25
0.1329807601338109
>>> binomial_one.pdf(5) # binomial_one PDF at x = 5
0.07464701952887093
Gaussian Visualizations
>>> gaussian = Gaussian()
>>> gaussian.read_data_file('numbers.txt')
>>> gaussian.replace_stats_with_data() # returns (mean, stdev)
(78.0909090909091, 92.87459776004906)
>>> gaussian.plot_histogram()
>>> gaussian.plot_histogram_pdf()
Binomial Visualizations
>>> binomial = Binomial()
>>> binomial.read_data_file('numbers_binomial.txt')
>>> binomial.replace_stats_with_data() # returns (p, n)
(0.6153846153846154, 13)
>>> binomial.plot_histogram()
>>> binomial.plot_pdf()
Project details
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