如何以 pythonic 方式在大球体中洗牌小球体？

Question

我有一个具有一些已知特征（ids、半径、质量和位置）的球体列表，其中 ids、radii、 masses 是 1D arrays with shape (511, ) and positions being 3D array with shape (511, 3) inside some big spherical volume with known center, (0, 0, 0) and radius, 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])])

我想将这些小球体随机放置在大球体的整个体积内，同时保持它们各自的特征完好无损，这意味着只需要调整它们的位置受下面所示的两个约束.

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

在对球体做一些事情之前，将我的球体洗牌到最后一个if statement下的最快和最短的方法是什么？（虽然我确实需要我的原始人口信息以备后用，所以我不能忽视它）

Answer 1

最好的方法是以向量化格式（这在 numpy 中非常有效）而不是使用 for 循环来计算约束。然后生成一个与您的约束相匹配的索引数组，然后将这些索引打乱。

所以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

如何以 pythonic 方式在大球体中洗牌小球体？

How to shuffle tiny spheres inside a big sphere in a pythonic way?

random

shuffle

python-3.x

pandas