fixes.py 文件源码

def _min_or_max_axis(X, axis, min_or_max):
        N = X.shape[axis]
        if N == 0:
            raise ValueError("zero-size array to reduction operation")
        M = X.shape[1 - axis]
        mat = X.tocsc() if axis == 0 else X.tocsr()
        mat.sum_duplicates()
        major_index, value = _minor_reduce(mat, min_or_max)
        not_full = np.diff(mat.indptr)[major_index] < N
        value[not_full] = min_or_max(value[not_full], 0)
        mask = value != 0
        major_index = np.compress(mask, major_index)
        value = np.compress(mask, value)

        from scipy.sparse import coo_matrix
        if axis == 0:
            res = coo_matrix((value, (np.zeros(len(value)), major_index)),
                             dtype=X.dtype, shape=(1, M))
        else:
            res = coo_matrix((value, (major_index, np.zeros(len(value)))),
                             dtype=X.dtype, shape=(M, 1))
        return res.A.ravel()