sparse.py 文件源码

 复制代码def csc_matvec(mat_csc, vec, dense_output=True, dtype=None):
    v_nnz = vec.indices
    v_val = vec.data

    m_val = mat_csc.data
    m_ind = mat_csc.indices
    m_ptr = mat_csc.indptr

    res_dtype = dtype or np.result_type(mat_csc.dtype, vec.dtype)
    if dense_output:
        res = np.zeros((mat_csc.shape[0],), dtype=res_dtype)
        matvec2dense(m_ptr, m_ind, m_val, v_nnz, v_val, res)
    else:
        sizes = m_ptr.take(v_nnz+1) - m_ptr.take(v_nnz)
        sizes = np.concatenate(([0], np.cumsum(sizes)))
        n = sizes[-1]
        data = np.empty((n,), dtype=res_dtype)
        indices = np.empty((n,), dtype=np.intp)
        indptr = np.array([0, n], dtype=np.intp)
        matvec2sparse(m_ptr, m_ind, m_val, v_nnz, v_val, sizes, indices, data)
        res = sp.sparse.csr_matrix((data, indices, indptr), shape=(1, mat_csc.shape[0]), dtype=res_dtype)
        res.sum_duplicates() # expensive operation
    return res