Numpy reshape 更改数组的维度

temp = np.zeros([2,3,4])
print("temp",temp)
temp_new = temp.reshape([4,6])  # 元素的总个数(2*3*4=24)不变的情况下进行reshape
print("temp",temp)
print("temp_new",temp_new)
print(id(temp),id(temp_new))
print("-----------------")
temp_new = temp.reshape([4,7])  # 这样做就会报错，ValueError！

temp [[[0. 0. 0. 0.]
  [0. 0. 0. 0.]
  [0. 0. 0. 0.]]

 [[0. 0. 0. 0.]
  [0. 0. 0. 0.]
  [0. 0. 0. 0.]]]
temp [[[0. 0. 0. 0.]
  [0. 0. 0. 0.]
  [0. 0. 0. 0.]]

 [[0. 0. 0. 0.]
  [0. 0. 0. 0.]
  [0. 0. 0. 0.]]]
temp_new [[0. 0. 0. 0. 0. 0.]
 [0. 0. 0. 0. 0. 0.]
 [0. 0. 0. 0. 0. 0.]
 [0. 0. 0. 0. 0. 0.]]
140319658903952 140319660464768
-----------------
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-27-784dd88cae99> in <module>()
      6 print(id(temp),id(temp_new))
      7 print("-----------------")
----> 8 temp_new = temp.reshape([4,7])  # 元素的总个数不变的情况下进行reshape

ValueError: cannot reshape array of size 24 into shape (4,7)

help(np.array([]).reshape)

Help on built-in function reshape:

reshape(...) method of numpy.ndarray instance
    a.reshape(shape, order='C')
    
    Returns an array containing the same data with a new shape.
    
    Refer to `numpy.reshape` for full documentation.
    
    See Also
    --------
    numpy.reshape : equivalent function
    
    Notes
    -----
    Unlike the free function `numpy.reshape`, this method on `ndarray` allows
    the elements of the shape parameter to be passed in as separate arguments.
    For example, ``a.reshape(10, 11)`` is equivalent to
    ``a.reshape((10, 11))``.