python中的reshape中参数-1的作用
来源链接：https://www.zhihu.com/question/52684594/answer/157491724
numpy.reshape(a, newshape, order='C')[source]，参数`newshape`是啥意思？
根据Numpy文档(https://docs.scipy.org/doc/numpy/reference/generated/numpy.reshape.html#numpy-reshape)的解释：
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**.
大意是说，数组新的shape属性应该要与原来的配套，如果等于-1的话，那么Numpy会根据剩下的维度计算出数组的另外一个shape属性值。
举几个例子或许就清楚了，有一个数组z，它的shape属性是(4, 4)
-
z = np.array([[
1,
2,
3,
4],
-
[
5, 6, 7, 8],
-
[
9, 10, 11, 12],
-
[
13, 14, 15, 16]])
-
z.shape
-
(
4,
4)
z.reshape(-1)
-
z
.reshape(
-1)
-
array(
[ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16])
z.reshape(-1, 1)
也就是说，先前我们不知道z的shape属性是多少，但是想让z变成只有一列，行数不知道多少，通过`z.reshape(-1,1)`，Numpy自动计算出有12行，新的数组shape属性为(16, 1)，与原来的(4, 4)配套。
-
z
.reshape(
-1,1)
-
array(
[[ 1],
-
[ 2],
-
[ 3],
-
[ 4],
-
[ 5],
-
[ 6],
-
[ 7],
-
[ 8],
-
[ 9],
-
[10],
-
[11],
-
[12],
-
[13],
-
[14],
-
[15],
-
[16]])
-
z.reshape(-1, 2)
newshape等于-1，列数等于2，行数未知，reshape后的shape等于(8, 2)
-
z
.reshape(
-1, 2)
-
array(
[[ 1, 2],
-
[ 3, 4],
-
[ 5, 6],
-
[ 7, 8],
-
[ 9, 10],
-
[11, 12],
-
[13, 14],
-
[15, 16]])
-
同理，只给定行数，newshape等于-1，Numpy也可以自动计算出新数组的列数。
----------
参考
1.http://stackoverflow.com/questions/18691084/what-does-1-mean-in-numpy-reshape