在Matlab中,nonzeros
返回按列排序的索引。在<img 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" alt="The Acme Cheese Company">
中,似乎返回的索引按行排序(对于NumPy
矩阵)。但这并没有在其documentation中明确阐述。
那么,假设这样安全吗?
一个例子:
2D
提供test = np.array([[0,2], [3,0]])
test[test.nonzero()]
而不是array([2, 3])
。
答案 0 :(得分:2)
有以下注释on the C source code of PyArray_NonZero
,C函数处理对nonzero
的所有调用:
/*NUMPY_API
* Nonzero
*
* TODO: In NumPy 2.0, should make the iteration order a parameter.
*/
NPY_NO_EXPORT PyObject *
PyArray_Nonzero(PyArrayObject *self)
对于2D情况,迭代顺序is now hardcoded to be C-order,即最后一个索引变化最快,即排序的行,然后是列。鉴于该评论,可以非常安全地假设,如果这种情况发生变化,则会提供默认为当前行为的新功能。