如何以蟒蛇般的方式将微小的球体放入大球体中

Question

我有一个具有一些已知特征(id、半径、质量和位置(的球体列表，其中ids、半径和质量是形状为(511，(的1D阵列，而位置则是3D阵列0,1,0(半径为distance_max。

hal_ids_data = np.array([19895, 19896, ..., 24249])                   
hal_radiuss_data = np.array([1.047, 1.078, ..., 3.263])                 
hal_masss_data = np.array([2.427e+06, 8.268e+06, ..., 8.954e+07]     
hal_positions_data = np.array([np.array([-33.78, 10.4, 33.83]), np.array([-33.61, 6.34, 35.64]), ..., np.array([-0.4014, 4.121, 33.05])])

我想在大球体内的整个体积中随机放置这些小球，同时保持它们的个体特征不变，这意味着只有它们的位置需要根据下面显示的两个约束进行洗牌。

for hal_id, hal_position, hal_radius, hal_mass in zip(hal_ids_data, hal_positions_data, hal_radiuss_data, hal_masss_data):
# check if 1) any one of the small spheres are above some mass threshold AND 2) inside the big sphere
if ((np.sqrt(pow(hal_position[0], 2)+pow(hal_position[1], 2)+pow(hal_position[2], 2)) < distance_max) and (log10(hal_mass)>=1e8)):
# if so, then do the following stuff down here but to the shuffled populations of small spheres meeting the conditions above rather than to the original population

在最后一个if statement下打乱我的球体，然后再对它们做一些事情，最快、最短的方法是什么？(我确实需要我的原始人口信息，以便以后使用，所以我不能忽略它(

Answer 1

最好的方法是以矢量化格式计算约束(这在numpy中非常有效(，而不是使用for循环。然后生成一个与约束匹配的索引数组，然后打乱这些索引。

因此，使用上面的示例数据：

import numpy as np
distance_max = 49 #I chose this so that we have some matching items
hal_ids_data = np.array([19895, 19896, 24249])                   
hal_radius_data = np.array([1.047, 1.078, 3.263])                 
hal_mass_data = np.array([2.427e+06, 8.268e+06, 8.954e+07])     
hal_positions_data = np.array([np.array([-33.78, 10.4, 33.83]), np.array([-33.61, 6.34, 35.64]), np.array([-0.4014, 4.121, 33.05])])
# Compute the conditions for every sphere at the same time instead of for loop
within_max = np.sqrt(pow(hal_positions_data[:,0],2) + pow(hal_positions_data[:,1],2) + pow(hal_positions_data[:,2],2)) < distance_max
mass_contraint = np.log10(hal_mass_data) >= 1 #I chose this so that we have some matching items
matched_spheres = within_max & mass_contraint
# Get indexes of matching spheres
idx = np.where(matched_spheres)[0] # create array of indexes
np.random.shuffle(idx) #shuffle array of indexes in place
# Generate shuffled data by applying the idx to the original arrays and saving to new 's_' arrays
s_hal_ids_data = hal_ids_data[idx]
s_hal_radius_data = hal_radius_data[idx]
s_hal_mass_data = hal_mass_data[idx]
s_hal_positions_data = hal_positions_data[idx]
# Do stuff with shuffled population of small spheres