What does -1 mean in numpy reshape?


numpy.reshape(a, newshape, order=‘C’)[source],参数newshape是啥意思?

根据Numpy文档的解释:

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)

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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)

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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。

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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)

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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.stackoverflow: What does -1 mean in numpy reshape?

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