test_tear.py 文件源码

def test_make_norm_ndarray(self):
        ROW_SUBSET_FIELD = "pr_probe_normalization_group"
        COL_SUBSET_FIELD = "det_normalization_group_vector"
        row_df = pd.DataFrame(np.array([["8350", "1"], ["8350", "1"],
                                        ["8350", "2"], ["8350", "2"]]),
                              index=["r1", "r2", "r3", "r4"],
                              columns=["pr_gene_id", "pr_probe_normalization_group"])
        col_df = pd.DataFrame(np.array([["G-0022", "1,1"], ["G-0022", "1,1"], ["G-0022", "1,2"],
                                        ["G-0022", "2,2"], ["G-0022", "2,2"]]),
                              index=["c1", "c2", "c3", "c4", "c5"],
                              columns=["det_plate", "det_normalization_group_vector"])
        e_norm_ndarray = np.array([[1, 1, 1, 2, 2],
                                   [1, 1, 1, 2, 2],
                                   [1, 1, 2, 2, 2],
                                   [1, 1, 2, 2, 2]])
        norm_ndarray = tear.make_norm_ndarray(row_df, col_df, ROW_SUBSET_FIELD, COL_SUBSET_FIELD)
        self.assertTrue(np.array_equal(norm_ndarray, e_norm_ndarray),
                        ("\nExpected out:\n{} " +
                         "\nActual out:\n{}").format(e_norm_ndarray, norm_ndarray))