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。
转自：https://blog.csdn.net/qq_38409301/article/details/88559889