Files

import random

import pandas as pd
import prairielearn as pl


def generate(data):
    # Generates number of events.
    x_events = random.randint(4, 7)

    # Control rounding
    n_digits = 2

    # Generate random integers up to a number
    r = [float(random.randint(1, 100)) for _ in range(x_events)]

    # Sum events
    s = sum(r)

    # Divide each value by sum to bring into [0, 1]
    # Round events
    a = [round(i / s, n_digits) for i in r]

    # Enforce probability summation constraint
    prob_sum = sum(a)
    capped_sum = round(1 - prob_sum, n_digits)

    # Truncate
    if not capped_sum.is_integer():
        max_val = max(a)
        max_ind = a.index(max_val)
        a[max_ind] += capped_sum

    d = {"P(X)": a}
    df = pd.DataFrame(data=d)

    data["params"]["df"] = pl.to_json(df)

    data["correct_answers"]["p_sum"] = sum(a)
    data["correct_answers"]["big_event"] = a.index(max(a))