1af61eee76fc63e98ba5ad85ad82fbd18111b8e9,scipy/sparse/data.py,_minmax_mixin,_min_or_max_axis,#_minmax_mixin#Any#Any#,106

Before Change

        row = out_mat.rows[0]
        data = out_mat.data[0]

        for i, (start, stop) in enumerate(izip(mat.indptr, mat.indptr[1:])):
            if start == stop:
                continue
            val = min_or_max(mat.data[start:stop])

After Change

        // can"t use indices > data length with reduceat`
        trunc = np.searchsorted(indptr, indptr[-1])
        min_or_max.reduceat(mat.data, indptr[:trunc], out=out[:trunc])
        nnz = np.diff(indptr)
        min_or_max(out, zero, where=nnz < N, out=out)
        out[nnz == 0] = zero

        out = lil_matrix(out, dtype=self.dtype)

Instances