import numpy as np
import math


def softmax(scores: list[float]) -> list[float]:
    exp_scores = []
    for s in scores:
        exp_scores.append(math.e ** s)
    probabilities = []
    for e in exp_scores:
        probabilities.append(round(e / np.sum(exp_scores),4))
    return probabilities


if __name__ == "__main__":
    scores = np.array(eval(input()))
    print(softmax(scores))