Krypton-GD 1.0.1
A small package to add up two gaussian distributions together
Requires Python: >=3.6

Project description
# Krypton-GD package

This package provides the Gaussian distribution and Binomial distribution classes.

* Gaussian - Gaussian distribution class for calculating and visualizing a Gaussian distribution.
Attributes:
mean (float) - representing the mean value of the distribution.
stdev (float) - representing the standard deviation of the distribution.
data_list (list of floats) - a list of floats extracted from the data file.

## Methods:
calculate_mean() - Function to calculate the mean of the data set.
calculate_stdev() - Function to calculate the standard deviation of the data set.
plot_histogram() - Function to output a histogram of the instance variable data using matplotlib pyplot library.
read_data_file(filename) - Function to read in data from a txt file. The txt file should have one number (float) per line. The numbers are stored in the data attribute.
pdf(x) - Probability density function calculator for the gaussian distribution
Args:
x (float): point for calculating the probability density function
Returns:
float: probability density function output
plot_histogram_pdf(n_spaces = 50) - Function to plot the normalized histogram of the data and a plot of the probability density function along the same range
Args:
n_spaces (int): number of data points
Returns:
list: x values for the pdf plot
list: y values for the pdf plot
__add__(other) - Function to add together two Gaussian distributions
Args:
other (Gaussian): Gaussian instance
Returns:
Gaussian: Gaussian distribution
__repr__() - Function to output the characteristics of the Gaussian instance


* Binomial - Binomial distribution class for calculating and visualizing a Binomial distribution.
Attributes:
mean (float) representing the mean value of the distribution
stdev (float) representing the standard deviation of the distribution
data_list (list of floats) a list of floats to be extracted from the data file
p (float) representing the probability of an event occurring
n (int) number of trials

## Methods:
calculate_mean() - Function to calculate the mean from p and n
calculate_stdev() - Function to calculate the standard deviation from p and n.
read_data_file(filename) - Function to read in data from a txt file. The txt file should have one number (float) per line. The numbers are stored in the data attribute.
replace_stats_with_data() - Function to calculate p and n from the data set
Args:
None
Returns:
float: the p value
float: the n value
plot_bar() - Function to output a histogram of the instance variable data using matplotlib pyplot library.
pdf(k) - Probability density function calculator for the gaussian distribution.
Args:
x (float): point for calculating the probability density function
Returns:
float: probability density function output
plot_bar_pdf() - Function to plot the pdf of the binomial distribution
Args:
None
Returns:
list: x values for the pdf plot
list: y values for the pdf plot
__add__(other) - Function to add together two Binomial distributions with equal p
Args:
other (Binomial): Binomial instance
Returns:
Binomial: Binomial distribution
__repr__() - Function to output the characteristics of the Binomial instance.



## Files

* Generaldistribution.py - contains Distribution class, its attributes and methods being inherited by Gaussian and Binomial class.
* Gaussiandistribution.py - contains Gaussian class, its attributes and methods stated above in udc-dsnd-distributions package summary.
* Binomialdistribution.py - contains Binomial class, its attributes and methods stated above in udc-dsnd-distributions package summary.

## Installation
* The code should run with no issues using Python versions 3.*.
* No extra besides the built-in libraries from Anaconda needed to run this project
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