Skip to main content

Gaussian and Bionomial distributions

Project description

Introduction

Probability Distributions

A probability distribution is a statistical function that describes all the possible values and likelihoods that a random variable can take within a given range. This package includes two commonly used probability distributions, namely Gaussian distribution (or normal distribution) and Binomial Distribution.

How to install

you can install this package directly from the pypi repository using pip install: pip install Gaus_Binom_probability

How to import and use the package

Open python or in your main python code import Gaussian and/or Binomial distributions from the package and use them as follows:

  • from Gaus_Binom_probability import Gaussian, Binomial

  • The to make a Gaussian distribution you need to have the mean valu and the standard deviation value:

    • Gaussian(mean_value, stdev_value)
  • to read data that is generated by gaussian dist and to find their mean and stdev:

    • gaussian_1 = Gaussian(mean, stdev) #initialise your gaussian distribution
    • gaussian_1.read_data_file(Folder_address+filename) #read your data
    • gaussian_1.calculate_mean() #to calculate the mean
    • gaussian_1.calculate_stdev() #to calculate the stdev
    • gaussian_1.plot_histogram() #to plot a histogram of your data
    • gaussian_1.pdf(x) #to calculate the probability density function
    • gaussian_1.plot_histogram_pdf(number_of_data_points) #to plot the normalized histogram of the data and a plot of the probability density function along the same range
    • gaussian_1 + gaussian_2 #to add two gaussian functions (meaning add means and update the stdev)
  • To make a bionomial distribution you need to have the probability of the occurence of your event (for example probability of getting head in coin flipping) and the number of your tries or the size of your data:

    • Binomial(probability_of_occurence, size_of_data)
  • to read data and to find their mean and stdev:

    • binomial_1 = Binomial(p, n) #initialise your Binomial distribution
    • binomial_1.read_data_file(Folder_address+filename) #read your data
    • binomial_1.calculate_mean() #to calculate the mean
    • binomial_1.calculate_stdev() #to calculate the stdev
    • binomial_1.replace_stats_with_data() #to calculate p and n from the data set
    • binomial_1.plot_bar() #to plot a histogram of your data
    • binomial_1.pdf(x) #to calculate the probability density function
    • binomial_1.plot_pdf(number_of_data_points) #to plot the pdf of the binomial distribution
    • gaussian_1 + gaussian_2 #to add two Binomial functions (Note: p values of the two distributions should be the same.

Licensing

You can find info regarding the licensing in the license.txt file where the package is installed.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

GausBinom_probability_Dist-0.3.tar.gz (4.1 kB view details)

Uploaded Source

File details

Details for the file GausBinom_probability_Dist-0.3.tar.gz.

File metadata

  • Download URL: GausBinom_probability_Dist-0.3.tar.gz
  • Upload date:
  • Size: 4.1 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.8.0 pkginfo/1.9.6 readme-renderer/34.0 requests/2.25.1 requests-toolbelt/0.9.1 urllib3/1.26.17 tqdm/4.64.1 importlib-metadata/3.7.0 keyring/23.4.1 rfc3986/1.5.0 colorama/0.4.5 CPython/3.6.3

File hashes

Hashes for GausBinom_probability_Dist-0.3.tar.gz
Algorithm Hash digest
SHA256 c31f687263b8d1b2ae616c4262bce95d8034b4f5e1071981f1596274faf621d4
MD5 6ebaad8a85c96d43fdad8a1d1e0d76c8
BLAKE2b-256 f2876e269227efd2ad7b3b87a2c10646ab507fc5789937eb9fc29ef74ded61f3

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page