meanlib 1.0.0

A Python package for calculating simple and weighted means, featuring classes for dynamic updates and sliding window functionality.

meanlib

meanlib is a Python library designed to facilitate the computation of various types of means, including simple means, rolling means, and weighted means. It provides easy-to-use classes and functions to update, compute, and retrieve means dynamically as new data becomes available.

Features

• SimpleMean: Calculate and update a simple arithmetic mean with each new value.
• Mean: Calculate a rolling mean with an optional limit on the number of values stored.
• Weighted Mean Function: Calculate the weighted mean of a list of values.

Usage

Here are some basic examples of how to use the library.

Simple Mean Calculation

from meanlib import SimpleMean

# Initialize the SimpleMean object
simple_mean = SimpleMean()

# Update the mean with new values
simple_mean.update(5)
simple_mean.update(10)
print(simple_mean.get_mean())  # Output: 7.5

Rolling Mean with a Maximum Limit

from meanlib import Mean

# Initialize the Mean object with a maximum of 3 values
mean = Mean(max_size=3)

# Update the mean with new values
mean.update(10)
mean.update(20)
mean.update(30)
print(mean.get_mean())  # Output: 20.0

# Adding another value, which will remove the oldest value (10)
mean.update(40)
print(mean.get_mean())  # Output: 30.0

Weighted Mean Calculation

from meanlib import weighted_mean

# Define values and their corresponding weights
values = [1, 2, 3, 4]
weights = [1, 2, 1, 1]

# Calculate the weighted mean
wm = weighted_mean(values, weights)
print(wm)  # Output: 2.5

API Reference

weighted_mean(values, weights)

Calculates the weighted mean of a list of values.

Parameters

• values (list or array-like): The list of values for which the weighted mean is to be calculated.
• weights (list or array-like): The list of weights associated with each value.

Returns

• float or complex: The calculated weighted mean.

Raises

• TypeError: If values or weights are not list or array-like.
• ValueError: If values and weights do not have the same length.
• ZeroDivisionError: If the total of values is zero.

class SimpleMean

A class for calculating a simple arithmetic mean that can be updated incrementally.

SimpleMean.__init__()

Initializes a SimpleMean object with initial sum and count set to zero.

SimpleMean.update(number)

Updates the mean with a new value.

Parameters:

• number (int, float, or complex): The new value to be added to the mean.

Returns:

• float or complex: The updated mean.

Raises:

• TypeError: If number is not of a compatible type.

SimpleMean.get_mean()

Returns the current mean.

Returns:

• float or complex: The current mean.
• None: If the count is zero.

class Mean

A class for calculating a rolling mean with an optional limit on the number of values stored.

Mean.__init__(max_size=None)

Initializes a Mean object.

Parameters:

• max_size (int or str, optional): The maximum number of values to store in the array. If None, there is no limit.

Raises:

• ValueError: If max_size is not an integer or a string of an integer.

Mean.update(number)

Updates the mean with a new value, maintaining the array size within the maximum limit.

Parameters:

• number (int, float, or complex): The new value to be added to the mean.

Returns:

• float or complex: The updated mean.

Raises:

• TypeError: If number is not of a compatible type.

Mean.update_list(_list)

Updates the mean with a list of values, maintaining the array size within the maximum limit.

Parameters:

• _list (list or tuple): The new value to be added to the mean.

Returns:

• float or complex: The updated mean.
• None: If the count is zero.

Raises:

• TypeError: If an element in _list is not of the correct type or if the value is not of a compatible type.

Mean.get_mean()

Returns the current mean.

Returns:

• float or complex: The current mean.
• None: If the count is zero.

License

This library is licensed under the MIT License.