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
Metadata
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