假设自动线程scipy和numpy函数没有使用多个内核

import numpy as np
from scipy.integrate import quad
from concurrent.futures import ThreadPoolExecutor

def integrate_function(function, a, b):
    return quad(function, a, b)[0]

def integrate_function_parallel(function, a, b, num_threads):
    step = (b - a) / num_threads
    ranges = [(a + i * step, a + (i + 1) * step) for i in range(num_threads)]
    ranges[-1] = (ranges[-1][0], b)  # 修正最后一个范围的终点

    with ThreadPoolExecutor(max_workers=num_threads) as executor:
        results = list(executor.map(lambda r: integrate_function(function, r[0], r[1]), ranges))

    return np.sum(results)

# 示例函数
def example_function(x):
    return x ** 2

# 计算结果
result = integrate_function_parallel(example_function, 0, 1, 4)
print(f"Result: {result}")