Question

让我们假设有一个有着已知中心（Xo，Yo，Zo）和半径Ro的大球体。它包含数百万个粒子，每个粒子具有相同参考帧的已知质量和3d位置。在这个大球体内部，有十几个较小的假想球体随机分布在3d空间中，但其他已知的位置。我想计算每个较小球体内的粒子数量，从而计算出每个较小球体（容器）的最终质量，方法是计算每个球体内部的粒子。

这是我的MWE片段，其中我循环遍历各个粒子，看它们是否在每个较小的球体内，然后为每个球体单独计算它们，以便为每个较小的球体提供总质量： / p>

import numpy as np
from scipy.spatial.distance import euclidean 

### there is 10 small spheres inside Big Sphere each containing different number of particles and hence different masses
### small_sphere_id_array is the array of the IDs of the small spheres
### small_sphere_position_array is the array of the position of the center of small spheres
### small_sphere_radius_array is the array of the radii of small spheres
### small_sphere_mass_array is the array of the masses of small spheres
### particle_position_array is the array of the positions of particles inside the Big Sphere
### particle_mass_array is the array of the masses of particles inside the Big Sphere

for small_sphere_index in np.arange(0, 10)):

    for particle_index in np.arange(0, 6000000)):

        small_sphere_mass_array = []    
        small_sphere_mass = 0

        distances = euclidean(particle_position_array[particle_index], small_sphere_position_array[small_sphere_index])
        success_condition = (distances <= small_shpere_radius_array[small_sphere_index])

        while success_condition:
            small_sphere_mass += particle_mass_array[particle_index]         
            small_sphere_mass_array.append(small_sphere_mass)
            small_sphere_mass = np.sum(small_sphere_mass_array)

        else:
            break


    print('{}, {}'.format(small_sphere_id_array[small_sphere_index], small_sphere_mass))

我希望打印出10行（对应10个小球），首先是ID，然后是总质量。但是，这是我的输出：

some number, 0
some number, 0
some number, 0
some number, 0
some number, 0
some number, 0
some number, 0
some number, 0
some number, 0
some number, 0

特别是我无法获取while循环的结果并将其移动到外部for循环，因此循环遍历所有粒子，为每个小球体提供单个非零总质量。我似乎正确地循环了10个小球体但问题是质量最终为零，这意味着中间for环不能解释所有6000000个粒子。（提示：所有粒子做都有质量。）

Answer 1

我刚刚（通过我的一个朋友）了解到我在混合python和C ++之间的语法，这与C ++不同，C ++中变量的赋值不能从内循环到外循环，python是实际上只能通过循环之间的缩进来记住赋值。在python中（与C ++不同）一旦执行循环并且它的结束到达，那么通过一次缩进，python仍然可以回忆它正在计算的内容，因此可以访问循环的最终产品。因此，我应该使用while循环来确保已根据条件检查了所有粒子，而不是使用if循环。此外，变量 small_sphere_mass 和 small_sphere_mass_array 的初始化应该在内部循环之外进行，这样我就不会强制循环始终坚持第一个零值。 / p>

import numpy as np
from scipy.spatial.distance import euclidean 

### there is 10 small spheres inside Big Sphere each containing different number of particles and hence different masses
### small_sphere_id_array is the array of the IDs of the small spheres
### small_sphere_position_array is the array of the position of the center of small spheres
### small_sphere_radius_array is the array of the radii of small spheres
### small_sphere_mass_array is the array of the masses of small spheres
### particle_position_array is the array of the positions of particles inside the Big Sphere
### particle_mass_array is the array of the masses of particles inside the Big Sphere

for small_sphere_index in np.arange(0, 10)):

    small_sphere_mass_array = []    
    small_sphere_mass = 0

    for particle_index in np.arange(0, 6000000)):           
        distances = euclidean(particle_position_array[particle_index], small_sphere_position_array[small_sphere_index])

        if (distances <= small_shpere_radius_array[small_sphere_index]):
            part_particle=particle_mass_array[particle_index]
            small_sphere_mass +=  part_particle          
            small_sphere_mass_array.append(part_particle)


    print('{}, {}'.format(small_sphere_id_array[small_sphere_index], small_sphere_mass))

如何将值从最里面的while循环传递到python中的外部for循环？

1 个答案: