Markov-Boxing-Combos

The code in this repository simulates and generates random sequences of punches used in a boxing match. It does this by first calculating the probability distribution of the length of the sequences of punches in the data. It then creates a bin to count the occurrences of each punch in the data, and uses this to calculate the probability distribution of each punch. The code then creates a Markov matrix, which is a square matrix that shows the probabilities of transitioning from one punch to another. The code then uses this Markov matrix to generate a random sequence of punches that matches the length distribution of the original data.

Usage

To use this code, run the combo_generator() function, passing in the result of the punch_bin_counts() function and the original data as arguments. This will generate and print a random sequence of punches.

Dependencies

This code requires the following Python packages:

itertools
collections

Example

Here is an example of how to use this code to generate a random sequence of punches:

# Import necessary packages
from itertools import chain
from random import randrange
from random import choices
from collections import Counter

# Define the original data
data = [['Jab', 'Cross', 'Hook'], ['Jab', 'Cross', 'Cross', 'Hook'], ['Jab', 'Cross', 'Hook', 'Hook'], ['Jab', 'Jab', 'Cross'], ['Jab', 'Cross', 'Cross', 'Cross']]

# Calculate the probability distribution of the lengths of the sequences of punches
len_combo_probs = calc_len_combo_probs(data)

# Count the occurrences of each punch in the data
punch_counts = punch_bin_counts(result)

# Generate a random sequence of punches
combo_generator(result, data, matrix)