simulate spawns

sim_spawns.py

import random

def get_num_endermen(simulating, chunks):
    chunks = [{} for i in range(256)]
    num_mobs = 0
    MOB_CAP = 70
    num_endermen = 0
    MOB_CHOICES = ("spider", "zombie", "zombie_villager", "skeleton", "creeper", "slime", "enderman", "witch")
    MOB_WEIGHTS = (100, 95, 5, 100, 100, 100, 10, 5)

    while num_mobs < MOB_CAP:
        hit_chunk_cap = False
        for i in range(256):
            num_mobs_in_chunk = 0
            good_spawn = False
            if random.random() >= 0.0125:
                continue

            for j in range(3):
                random_lim = random.randint(1, 4)
                mob_type = random.choices(MOB_CHOICES, MOB_WEIGHTS)[0]
                y = 0
                for k in range(random_lim):
                    y += random.randint(0, 1) - random.randint(0, 1)
                    if y == 0:
                        if mob_type == "enderman":
                            num_endermen += 1
    
                        if mob_type in chunks[i]:
                            chunks[i][mob_type] += 1
                        else:
                            chunks[i][mob_type] = 1
    
                        num_mobs_in_chunk += 1
                        num_mobs += 1
                        if num_mobs_in_chunk >= 4:
                            hit_chunk_cap = True
                            break

                if hit_chunk_cap:
                    break

    if simulating:
        return num_endermen

    output = ""

    for i, chunk in enumerate(chunks):
        if len(chunk) != 0:
            output += f"{i:03d}: " + ", ".join(f"{key}: {item}" for key, item in chunk.items()) + "\n"

    output += f"num_endermen: {num_endermen}\nnum_mobs: {num_mobs}\n"
    print(output)

def main():
    num_endermen = 0
    chunks = [{} for i in range(256)]
    distribution = []

    max_endermen = 0
    for i in range(10000):
        cur_num_endermen = get_num_endermen(True, chunks)
        if cur_num_endermen >= len(distribution):
            distribution.extend([0] * (cur_num_endermen + 1 - len(distribution)))
        distribution[cur_num_endermen] += 1
        num_endermen += cur_num_endermen
        if cur_num_endermen > max_endermen:
            max_endermen = cur_num_endermen
        for i in range(256):
            chunks[i].clear()

    output = f"average_endermen: {num_endermen/10000}, max_endermen: {max_endermen}\n"
    for i, count in enumerate(distribution):
        output += f"{i:02d}: {count}\n"

    print(output)

if __name__ == "__main__":
    main()