Metadata-Version: 2.1
Name: essdistributions
Version: 1.2
Summary: Gaussian&Binomial distributions
Home-page: https://github.com/esraahisham753/Gaussian_Binomial_package
Author: Esraa Abduallah
Author-email: esraahisham753@gmail.com
License: UNKNOWN
Description: # Gaussian and Binomial distribution
        ## Gaussian Class:
        ### 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:
        * __init__(self, mean=0, stdev=1)
        
        * read_data_file(self, file_name)
        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.		
        		Args:
        			file_name (string): name of a file to read from		
        		Returns:
        			None
        
        * calculate_mean(self)
        Function to calculate the mean of the data set.		
        		Args: 
        			None
        		
        		Returns: 
        			float: mean of the data set
        
        * calculate_stdev(self, sample=True)
        Function to calculate the standard deviation of the data set.		
        		Args: 
        			sample (bool): whether the data represents a sample or population	
        		Returns: 
        			float: standard deviation of the data set
        
        * plot_histogram(self)
        Function to output a histogram of the instance variable data using 
        		matplotlib pyplot library.
        		Args:
        			None	
        		Returns:
        			None
        
        * pdf(self, 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(self, 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__(self, other)
        Function to add together two Gaussian distributions
        		Args:
        			other (Gaussian): Gaussian instance	
        		Returns:
        			Gaussian: Gaussian distribution
        
        * __repr__(self)
        Function to output the characteristics of the Gaussian instance
        		Args:
        			None
        		Returns:
        			string: characteristics of the Gaussian
        
        ## Binomial class
        ### 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.
        * p (float) representing the probability of an event occurring
        * n (int) the total number of trials
        
        ### Methods
        * __init__(self, p=.5, n=20)
        
        * calculate_mean(self):
        Function to calculate the mean from p and n
        Args: 
            None
        Returns: 
            float: mean of the data set
        
        * calculate_stdev(self):
        Function to calculate the standard deviation from p and n.
        Args: 
            None
        Returns: 
            float: standard deviation of the data set
        
        * replace_stats_with_data(self):    
        Function to calculate p and n from the data set
        Args: 
            None
        Returns: 
            float: the p value
            float: the n value
        
        * plot_bar(self):
        Function to output a histogram of the instance variable data using 
        matplotlib pyplot library.
        Args:
            None   
        Returns:
            None
        
        * pdf(self, k):
        Probability density function calculator for the gaussian distribution.
        Args:
            k (float): point for calculating the probability density function
        Returns:
            float: probability density function output
        
        * plot_bar_pdf(self):
        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__(self, other):        
        Function to add together two Binomial distributions with equal p
        Args:
            other (Binomial): Binomial instance
        Returns:
            Binomial: Binomial distribution
        
        * __repr__(self):    
        Function to output the characteristics of the Binomial instance
        Args:
            None
        Returns:
            string: characteristics of the Gaussian
        
        
        
        
        
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.0
Description-Content-Type: text/markdown
