np.empty()——依据给定形状和类型(shape,[dtype, order])返回一个新的空数组

官方解释：

np.empty()返回一个随机元素的矩阵，所以使用的时候要小心。需要手工把每一个值重新定义，否则该值是接近零的随机数。

gauss = np.empty((5, 64, 64), dtype=np.float64)
print(gauss)

结果：

[[[7.18634390e-312 7.19311879e-312 0.00000000e+000 ... 0.00000000e+000
   0.00000000e+000 0.00000000e+000]
  [0.00000000e+000 0.00000000e+000 0.00000000e+000 ... 0.00000000e+000
   0.00000000e+000 0.00000000e+000]
  [0.00000000e+000 0.00000000e+000 0.00000000e+000 ... 0.00000000e+000
   0.00000000e+000 0.00000000e+000]
  ...
  [0.00000000e+000 0.00000000e+000 0.00000000e+000 ... 0.00000000e+000
   0.00000000e+000 0.00000000e+000]
  [0.00000000e+000 0.00000000e+000 0.00000000e+000 ... 0.00000000e+000
   0.00000000e+000 0.00000000e+000]
  [0.00000000e+000 0.00000000e+000 0.00000000e+000 ... 0.00000000e+000
   0.00000000e+000 0.00000000e+000]]

 [[0.00000000e+000 0.00000000e+000 0.00000000e+000 ... 0.00000000e+000
   0.00000000e+000 0.00000000e+000]
  [0.00000000e+000 0.00000000e+000 0.00000000e+000 ... 0.00000000e+000
   0.00000000e+000 0.00000000e+000]
  [0.00000000e+000 0.00000000e+000 0.00000000e+000 ... 0.00000000e+000
   0.00000000e+000 0.00000000e+000]
  ...
  [0.00000000e+000 0.00000000e+000 0.00000000e+000 ... 0.00000000e+000
   0.00000000e+000 0.00000000e+000]
  [0.00000000e+000 0.00000000e+000 0.00000000e+000 ... 0.00000000e+000
   0.00000000e+000 0.00000000e+000]
  [0.00000000e+000 0.00000000e+000 0.00000000e+000 ... 0.00000000e+000
   0.00000000e+000 0.00000000e+000]]

 [[0.00000000e+000 0.00000000e+000 0.00000000e+000 ... 0.00000000e+000
   0.00000000e+000 0.00000000e+000]
  [0.00000000e+000 0.00000000e+000 0.00000000e+000 ... 0.00000000e+000
   0.00000000e+000 0.00000000e+000]
  [0.00000000e+000 0.00000000e+000 0.00000000e+000 ... 0.00000000e+000
   0.00000000e+000 0.00000000e+000]
  ...
  [0.00000000e+000 0.00000000e+000 0.00000000e+000 ... 0.00000000e+000
   0.00000000e+000 0.00000000e+000]
  [0.00000000e+000 0.00000000e+000 0.00000000e+000 ... 0.00000000e+000
   0.00000000e+000 0.00000000e+000]
  [0.00000000e+000 0.00000000e+000 0.00000000e+000 ... 0.00000000e+000
   0.00000000e+000 0.00000000e+000]]

 [[0.00000000e+000 0.00000000e+000 0.00000000e+000 ... 0.00000000e+000
   0.00000000e+000 0.00000000e+000]
  [0.00000000e+000 0.00000000e+000 0.00000000e+000 ... 0.00000000e+000
   0.00000000e+000 0.00000000e+000]
  [0.00000000e+000 0.00000000e+000 0.00000000e+000 ... 0.00000000e+000
   0.00000000e+000 0.00000000e+000]
  ...
  [0.00000000e+000 0.00000000e+000 0.00000000e+000 ... 0.00000000e+000
   0.00000000e+000 0.00000000e+000]
  [0.00000000e+000 0.00000000e+000 0.00000000e+000 ... 0.00000000e+000
   0.00000000e+000 0.00000000e+000]
  [0.00000000e+000 0.00000000e+000 0.00000000e+000 ... 0.00000000e+000
   0.00000000e+000 0.00000000e+000]]

 [[0.00000000e+000 0.00000000e+000 0.00000000e+000 ... 0.00000000e+000
   0.00000000e+000 0.00000000e+000]
  [0.00000000e+000 0.00000000e+000 0.00000000e+000 ... 0.00000000e+000
   0.00000000e+000 0.00000000e+000]
  [0.00000000e+000 0.00000000e+000 0.00000000e+000 ... 0.00000000e+000
   0.00000000e+000 0.00000000e+000]
  ...
  [0.00000000e+000 0.00000000e+000 0.00000000e+000 ... 0.00000000e+000
   0.00000000e+000 0.00000000e+000]
  [0.00000000e+000 0.00000000e+000 0.00000000e+000 ... 0.00000000e+000
   0.00000000e+000 0.00000000e+000]
  [0.00000000e+000 0.00000000e+000 0.00000000e+000 ... 0.00000000e+000
   0.00000000e+000 0.00000000e+000]]]

参考：
http://www.30daydo.com/article/376