/Gaussian_Binomial_package

Pip package for Gaussian and Binomial main functionalities like plotting, adding and computing statistics like mean and standard deviation

Primary LanguagePythonMIT LicenseMIT

Gaussian and Binomial distribution

Installation

pip install essdistributions

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