我想知道是否有更pythonic /更有效的方法将我的2d数组重塑为3d数组?这是以下工作代码:
def mousePressEvent(self, event):
w = 16.0
x = int(event.x()*1.0/w)
y = int(event.y()*1.0/w)
s1, s2 = self.grid.shape
# verify
if 0 <= y < s1 and 0 <= x < s2:
self.grid[x][y] = -self.grid[x][y]
self.viewport().update()
这是原始预期输出:
import numpy as np
#
# Declaring the dimensions
n_ddl = 2
N = 3
n_H = n_ddl*N
#
# Typical 2D array to reshape
x_tilde_2d = np.array([[111,112,121,122,131,132],[211,212,221,222,231,232],[311,312,321,322,331,332]])
x_tilde_2d = x_tilde_2d.T
#
# Initialization of the output 3D array
x_tilde_reshaped_3d = np.zeros((N,x_tilde_2d.shape[1],n_ddl))
for i in range(0,x_tilde_2d.shape[1],1):
x_tilde_sol = x_tilde_2d[:,i]
x_tilde_sol_reshape = x_tilde_sol.reshape((N,n_ddl))
for j in range(0,n_ddl,1):
x_tilde_reshaped_3d[:,i,j] = x_tilde_sol_reshape[:,j]
和相同的输出,沿轴= 2:
array([[[111., 112.],
[211., 212.],
[311., 312.]],
[[121., 122.],
[221., 222.],
[321., 322.]],
[[131., 132.],
[231., 232.],
[331., 332.]]])
任何建议将不胜感激。谢谢。
答案 0 :(得分:2)
为什么不直接做一个reshape
。似乎不需要首先初始化一个零的3d矩阵,然后按维度对其进行填充。
可以使用swapaxes(0, 1)
修改后的答案
x_tilde_2d = np.array([[111,112,121,122,131,132],[211,212,221,222,231,232],[311,312,321,322,331,332]])
x_tilde_reshaped_3d = x_tilde_2d.reshape(N, x_tilde_2d.T.shape[1], n_ddl).swapaxes(0, 1)
print (x_tilde_reshaped_3d)
输出
[[[111 112]
[211 212]
[311 312]]
[[121 122]
[221 222]
[321 322]]
[[131 132]
[231 232]
[331 332]]]
答案 1 :(得分:2)
In [337]: x=np.array([[111,112,121,122,131,132],[211,212,221,222,231,232],[311,3
...: 12,321,322,331,332]])
In [338]: x.shape
Out[338]: (3, 6)
In [339]: x
Out[339]:
array([[111, 112, 121, 122, 131, 132],
[211, 212, 221, 222, 231, 232],
[311, 312, 321, 322, 331, 332]])
使最后一个尺寸保持正确顺序的唯一重塑是:
In [340]: x.reshape(3,3,2)
Out[340]:
array([[[111, 112],
[121, 122],
[131, 132]],
[[211, 212],
[221, 222],
[231, 232]],
[[311, 312],
[321, 322],
[331, 332]]])
现在只需交换前两个维度:
In [341]: x.reshape(3,3,2).transpose(1,0,2)
Out[341]:
array([[[111, 112],
[211, 212],
[311, 312]],
[[121, 122],
[221, 222],
[321, 322]],
[[131, 132],
[231, 232],
[331, 332]]])