本文由腾讯云 社区自动同步，原文地址 https://stackoverflow.club/article/python_reshape/
按行reshape order=’C’
按列reshape order=’F’
代码语言：txt复制temp = np.array([[1,2,3],[4,5,6]])
temp
# array([[1, 2, 3],
# [4, 5, 6]])
temp.reshape((3,2))
# array([[1, 2],
# [3, 4],
# [5, 6]])
temp.reshape((3,2),'F')
# Traceback (most recent call last):
# File "<stdin>", line 1, in <module>
# TypeError: 'tuple' object cannot be interpreted as an integer
temp.reshape((3,2),order='F')
# array([[1, 5],
# [4, 3],
# [2, 6]])
temp.reshape((3,2),order='A')
# array([[1, 2],
# [3, 4],
# [5, 6]])reshape(a, newshape, order=’C’)
代码语言：txt复制Gives a new shape to an array without changing its data.Parameters
----------
a : array_like
Array to be reshaped.
newshape : int or tuple of ints
The new shape should be compatible with the original shape. If
an integer, then the result will be a 1-D array of that length.
One shape dimension can be -1. In this case, the value is
inferred from the length of the array and remaining dimensions.
order : {'C', 'F', 'A'}, optional
Read the elements of `a` using this index order, and place the
elements into the reshaped array using this index order. 'C'
means to read / write the elements using C-like index order,
with the last axis index changing fastest, back to the first
axis index changing slowest. 'F' means to read / write the
elements using Fortran-like index order, with the first index
changing fastest, and the last index changing slowest. Note that
the 'C' and 'F' options take no account of the memory layout of
the underlying array, and only refer to the order of indexing.
'A' means to read / write the elements in Fortran-like index
order if `a` is Fortran *contiguous* in memory, C-like order
otherwise.
