Metadata-Version: 2.1
Name: aac-distributions
Version: 0.5
Summary: Gaussian and Binomial distributions
Home-page: UNKNOWN
Author: Alberto Armero
Author-email: alberto.armero86@gmail.com
License: UNKNOWN
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown

# aac-distributions package

# This package provides the Gaussian 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) - 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 of the Binomial distribution from p and n.
        
		calculate_stdev() - Function to calculate the standard deviation of the Binomial distribution 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 bar chart of the instance variable data using 
        matplotlib pyplot library.
        
		pdf(k) - Probability density function calculator for the binomial distribution.
            Args:
                x (float): point for calculating the probability density function
            Returns:
                float: probability density function output
            
		plot_bar_pdf() - Function that creates the bar chart that plots 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.
        
* -----------------------------------------------------------------------------------------------------        
* Distribution - Generic distribution class for calculating and visualizing a probability distribution, 
* from which Gaussian and Binary distributions inherit
* ----------------------------------------------------------------------------------------------------- 

    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.

    Methods:
    
		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.
      
# Files

* Generaldistribution.py -> contains the Distribution class, its attributes and methods being inherited by Gaussian and Binomial class.
* Gaussiandistribution.py -> contains the Gaussian class, its attributes and methods as described in aac-distributions package summary.
* Binomialdistribution.py -> contains the Binomial class, its attributes and methods as described in aac-distributions package summary.

# Installation

* Note: In __init__.py, notice that there's is a dot in front of the .py files when importing the Gaussian and Binomial classes.
* This dot is required in Python 3.X, but if you are working in Python 2.X, you shouldn't need it.

* The classes in this package make use of built-in Python libraries like:
		Math - provides access to mathematical functions
		matplotlib - provides data visualization and graphical plotting functionality
        
* To install the package, type pip install aac-distributions



