Probabilistic Calculations for Any Array

This functionality enables probabilistic calculations on arrays of any length, which proves particularly valuable when computing information entropy. The implementation involves counting the frequency of each element's occurrence within the array to establish probability distributions. Key algorithmic steps include traversing the array to record element frequencies, then normalizing these frequencies to obtain probability values. These calculated probabilities serve as inputs for information entropy computation, which measures the uncertainty level of the array data. The entropy calculation follows the standard formula: H(X) = -Σ p(x)log₂p(x), where p(x) represents the probability of each distinct element. By quantifying the array's information entropy, we gain deeper insights into its characteristics and extract meaningful information patterns, making this approach essential for data analysis tasks and informed decision-making processes.