Perceptive Probability

perceptive.py

import numpy as np

def perceptive_probability(probability, average="median"):
    """ This function translates a probability [0;100] to a human readable string (phrase).

    The readable probabilities have been computed from data taken from the
    following github repository: https://github.com/zonination/perceptions/
    The repository contains a poll where people assigned a numerical probability
    to phrases. This data was used to find different types of averages of the
    distributions for each phrase.
    This function computes the 1 nearest neighbour of a probability to find its
    associated sentence.

    Args:
        probability (int): The probability from 0 to 100.
        method (string): The method for computing the average.
            Available options: ["mean", "median", "mode"]
    Returns (str):
        The closest phrase associated to the given probability.

    Example:
    >>> perceptive_probability(7)
    'Highly unlikely'

    >>> perceptive_probability(87, "mean")
    'Highly likely'
    """
    probabilities = {
        "mean":   np.array([5, 10, 14, 15, 18, 19, 27, 29, 49, 58, 68, 71, 72, 79, 86, 92]),
        "median": np.array([2,  5, 10, 15, 15, 20, 25, 26, 50, 60, 70, 70, 70, 80, 90, 95]),
        "mode":   np.array([5,  5, 10, 10, 10, 20, 25, 25, 50, 60, 70, 70, 80, 80, 90, 95])
    }
    phrases = [
        "Almost no chance", "Highly unlikely", "Chances are slight", "Little chance", 
        "Improbable", "Unlikely", "Doubtful", "Probably not",
        "About even", "Better than even", "Believable", "Probable",
        "Likely", "Very good chance", "Highly likely", "Almost certain"
    ]

    neighbours_dist = np.abs(probabilities[average] - probability)
    nearest_neighbour = np.argmin(neighbours_dist)
    return phrases[nearest_neighbour]