Python simulate_model示例

示例#1

文件： 4_simulate_with_adaptive.py 项目： SenoritaSarker/openmc_workshop

def find_tbr(x):

    enrichment, thickness = x

    result = simulate_model(enrichment=enrichment, thickness=thickness)

    result["sample"] = "adaptive"

    filename = "outputs/" + str(uuid.uuid4()) + ".json"
    Path(filename).parent.mkdir(parents=True, exist_ok=True)
    with open(filename, mode="w", encoding="utf-8") as f:
        json.dump(result, f, indent=4)

    return result["TBR"]

示例#2

文件： 1_simulate_with_random_sample.py 项目： SenoritaSarker/openmc_workshop

import argparse

import numpy as np
from tqdm import tqdm

from openmc_model import simulate_model

parser = argparse.ArgumentParser()
parser.add_argument("-n",
                    "--number",
                    default=1,
                    type=int,
                    help="number of simulations to perform")
args = parser.parse_args()

print("running simulations with random sampling")

for i in tqdm(range(args.number)):

    enrichment = np.random.uniform(0, 100)
    thickness = np.random.uniform(1, 500)

    result = simulate_model(enrichment=enrichment, thickness=thickness)

    result["sample"] = "random"

    filename = "outputs/" + str(uuid.uuid4()) + ".json"
    Path(filename).parent.mkdir(parents=True, exist_ok=True)
    with open(filename, mode="w", encoding="utf-8") as f:
        json.dump(result, f, indent=4)