Ranks

import random
import numpy as np

key_info = [[5, 5, 0],
            [10, 5, 1],
            [15, 4, 1],
            [20, 3, 1],
            [25, 2, 1]]


def loss(rank, stars):
    if stars == 0:
        if rank < 20 and rank % 5 != 0:
            rank += 1
            stars = key_info[int((rank-1)/5)][1]-1
    else:
        stars -= 1

    winstreak = 0

    return rank, stars, winstreak


def win(rank, stars, winstreak):
    win_stars = 1
    winstreak += 1

    if winstreak >= 3:  # and rank > 5:
        win_stars = 2

    stars_needed = key_info[int((rank-1)/5)][1] - stars

    if stars_needed < win_stars:
        rank -= 1
        stars = win_stars - stars_needed

    else:
        stars += 1

    return rank, stars, winstreak

static_win_rate_list = [0.5, 0.55, 0.60, 0.65]
dynamic_win_rate_list = [0.5, 0.55, 0.6, 0.65]
static_list = [0, 1]

for static in static_list:
    for j in range(3):
        static_win_rate = static_win_rate_list[j]
        dynamic_win_rate = dynamic_win_rate_list[j]

        game_samples = []
        for i in range(100000):
            rank = 25
            stars = 0
            winstreak = 0
            games = 0

            while rank > 0:
                if static == 1:
                    if random.random() < static_win_rate:
                        rank, stars, winstreak = win(rank, stars, winstreak)
                    else:
                        rank, stars, winstreak = loss(rank, stars)
                else:
                    if random.random() < dynamic_win_rate + (rank-1)/100:
                        rank, stars, winstreak = win(rank, stars, winstreak)
                    else:
                        rank, stars, winstreak = loss(rank, stars)

                games += 1

                if games > 10**6:
                    print("fail")
                    continue

            game_samples.append(games)

        if static == 0:
            print(dynamic_win_rate + 0.25, dynamic_win_rate, np.mean(game_samples), np.std(game_samples))
        if static == 1:
            print(static_win_rate, static_win_rate, np.mean(game_samples), np.std(game_samples))