<p>我真的不能对网格的生成说什么,因为我不能完全确定您正在尝试做什么。
但就提高效率而言,使用三重for循环而不是使用广播会大大降低代码的速度</p>
<pre><code>import itertools
import numpy as np
from scipy.interpolate import RegularGridInterpolator
from time import time
target_size = 32
reduced_size = 5
small_shape = (reduced_size,reduced_size,reduced_size,3)
cube_small = np.random.randint(target_size, size=small_shape, dtype=np.uint8)
igrid = 3*[np.linspace(0, target_size-1, reduced_size)]
large_shape = (target_size, target_size, target_size,3)
cube_large = np.empty(large_shape)
def original_method():
t0 = time()
interpol = RegularGridInterpolator(igrid, cube_small)
for x in np.arange(target_size):
for y in np.arange(target_size):
for z in np.arange(target_size):
cube_large[x,y,z] = interpol([x,y,z])
print('ORIGINAL METHOD: ', time()-t0)
return cube_large
def improved_method():
t1 = time()
interpol = RegularGridInterpolator(igrid, cube_small)
arr = np.arange(target_size)
grid = np.array(list(itertools.product(arr, repeat=3)))
cube_large = interpol(grid).reshape(target_size, target_size, target_size, 3)
print('IMPROVED METHOD:', time() - t1)
return cube_large
c1 = original_method()
c2 = improved_method()
print('Is the result the same? ', np.all(c1 == c2))
</code></pre>
<p>输出</p>
<pre><code>ORIGINAL METHOD: 6.9040000438690186
IMPROVED METHOD: 0.026999950408935547
Is the result the same? True
</code></pre>