[英]How to reshape 2D arrays?
I would like to reshape four 2D arrays : A, B, C and D (i have split before a "big array" in order to minimize function...and these arrays are the analytical results of the minimization) in a specific order : 我想重塑四个2D数组:A,B,C和D(为了最小化功能,我在“大数组”之前拆分了...这些数组是最小化的分析结果)按特定顺序排列:
AB AB
CD 光盘
I try with np.reshape or vectorize then concatenate but impossible to get this order as you can see of the picture below, all is mixed. 我尝试使用np.reshape或vectorize然后进行连接,但是无法获得此顺序,如您在下面的图片中所见,所有内容都是混合的。 I should have a result homogeneous
我应该得到均匀的结果
Thanks for answer, it works well by this way! 感谢您的回答,通过这种方式效果很好!
And i must apply that on a great number of subarrays, so i would like to automize the reshape of the array, as example below, the case of 4 arrays. 而且我必须将其应用于大量的子数组,因此我想自动化数组的重塑,如下例所示(4个数组的情况)。 As you can see i try with loops for but it doesnt work and perhaps by this way it could be not very fast...
如您所见,我尝试使用循环,但它不起作用,也许通过这种方式可能不是很快...
test_reshape = np.empty([20,20])
test_reshape[0:10,0:10] = frametemperature[0,:,:]
test_reshape[0:10,10:10*2.] = frametemperature[1,:,:]
test_reshape[10:10*2.,0:10] = frametemperature[2,:,:]
test_reshape[10:10*2.,10:10*2.] = frametemperature[3,:,:]
for i in range(frametemperature.shape[0]/2):
for j in range(frametemperature.shape[0]/2):
for k in range(frametemperature.shape[0]):
test_reshape[i*10:10*(i+1),j*10:10*(j+1)] = frametemperature[k,:,:]
So you've got 4 2d arrays that you want to combine back into one 2d array. 因此,您有4个2d阵列要合并回一个2d阵列。
1) create a empty 2d array to store them in 1) 创建一个空的2d数组将其存储在
import numpy as np
blank = np.empty([4,4])
2) assign the arrays according to their location instead of concatenating 2)根据其位置分配数组,而不是串联
A = np.ones([2,2])
B = np.ones([2,2]) * 2
C = np.ones([2,2]) * 3
D = np.ones([2,2]) * 4
blank[0:2,0:2] = a
blank[0:2,2:4] = b
blank[2:4,0:2] = c
blank[2:4,2:4] = d
blank
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