Gaussian and Binomial distributions
Project description
Prayikta
By using Prayikta module you can calculate Gaussian distribution, Binomial Probability, pdf and can visualization of them.
Classes
- Gaussian Class
- Binomial Class
Gaussian Class
# Example Fuctions
>>> from prayikta import Gaussian
# It has two arguments mean and standard daviation default (mean = 0 and stdev = 1)
>>> gaussian = Gaussian()
>>> gaussian.mean
>>> gaussian.stdev
# Read data from file and calculate mean and standard deviation
>>> gaussian.read_data_file('filename.txt')
>>> gaussian.calculate_mean()
>>> gaussian.calculate_stdev()
# Plot histogram of data
>>> gaussian.plot_histogram()
# Calculate probability density function and visualise it.
>>> gaussian.pdf() # takes one argument
>>> gaussian.plot_histogram_pdf()
# Add to gaussian functions
>>> gaussian_a = Gaussian(25,0)
>>> gaussian_b = Gaussian(5,2)
>>> gaussian_c = gaussian_a + gaussian_b
Binomial Class
# Example Fuctions
>>> from prayikta import Binomial
# It takes two arguments mean and standard daviation default (probability = 0.5 and size = 20)
>>> binomial = Binomial()
>>> binomial.calculate_mean()
>>> binomial.calculate_stdev()
# Plot bar
>>> binomial.plot_bar()
# Calculate pdf and visualise it.
>>> binomial.pdf() # takes one argument
>>> binomial.plot_bar_pdf()
# Add to binomial functions
>>> binomial_a = Binomial(0.5,10)
>>> binomial_b = Binomial(0.25,20)
>>> binomial_c = binomial_a + binomial_b
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