essdistributions 1.2

Gaussian&Binomial distributions

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