Metadata-Version: 2.1
Name: blaze-distributions
Version: 0.2
Summary: A Binomial and Gaussian Distribution Package
Home-page: UNKNOWN
Author: Toluwalope Oluyipe
Author-email: kingtoluwalope@gmail.com
License: UNKNOWN
Description: This package provides methods for Gaussian distribution and Binomial distribution classes.
        
        # Gaussian
        This package contains 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 
        Contains 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.
        
        
        The code should run with no issues using Python versions >= 3.6.
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown
