def test_report_locs_from_same_seg():
diff_report_segs_dict = dict(REPORT_LOCS_DG1).update(
{'AL.3': 'allergen_code'})
with pytest.raises(ValueError):
tidy_segs(MSG_ID_LOCS, diff_report_segs_dict, MSGS)
diff_report_segs_lst = list(REPORT_LOCS_DG1) + ['AL.3']
with pytest.raises(ValueError):
tidy_segs(MSG_ID_LOCS, diff_report_segs_lst, MSGS)
def test_locs_not_empty():
# id locs
with pytest.raises(ValueError):
tidy_segs({}, {'DG1.1': 'report_loc_1'}, MSGS)
with pytest.raises(ValueError):
tidy_segs([], ['DG1.1'], MSGS)
# report locs
with pytest.raises(ValueError):
tidy_segs({'MSH.7': 'id_loc_1'}, {}, MSGS)
with pytest.raises(ValueError):
tidy_segs(['MSH.7'], [], MSGS)
# messages
with pytest.raises(ValueError):
tidy_segs(['MSH.7'], ['DG1.1'], [])
def test_df_vals():
# pylint: disable=invalid-name
def are_segs_equal(seg1, seg2):
def are_vals_equal(k):
return seg1[k][0] == seg2[k][0]
def are_vals_na(k):
return np.isnan(seg1[k][0]) and np.isnan(seg2[k][0])
are_keys_equal = set(seg1) == set(seg2)
are_all_vals_equal = all(
[are_vals_equal(key) or are_vals_na(key) for key in seg1])
return are_keys_equal and are_all_vals_equal
msg_1_seg_1 = {
'msg_date_time': ['20170515104040'],
'facility_code': ['123'],
'seg': [1.0],
'diag_dr': [np.nan],
'diag_type': ['AM'],
'diag_code': ['D53.9'],
}
msg_1_seg_2 = {
'msg_date_time': ['20170515104040'],
'facility_code': ['123'],
'seg': [2.0],
'diag_dr': [np.nan],
'diag_type': [np.nan],
'diag_code': [np.nan],
}
msg_2_seg_1 = {
'msg_date_time': ['20170711123256'],
'facility_code': ['456'],
'seg': [1.0],
'diag_dr': [np.nan],
'diag_type': ['AM'],
'diag_code': ['M43.16'],
}
msg_3_seg_1 = {
'msg_date_time': ['20170322123231'],
'facility_code': ['789'],
'seg': [np.nan],
'diag_dr': [np.nan],
'diag_type': [np.nan],
'diag_code': [np.nan],
}
df = tidy_segs(MSG_ID_LOCS, REPORT_LOCS_DG1, MSGS)
df_msg_1 = df.loc[df['msg_date_time'] == '20170515104040']
df_msg_1_seg_1 = df_msg_1.loc[df['seg'] == 1].to_dict('list')
df_msg_1_seg_2 = df_msg_1.loc[df['seg'] == 2].to_dict('list')
df_msg_2_seg_1 = df.loc[df['msg_date_time'] == '20170711123256'].to_dict(
'list')
df_msg_3_seg_1 = df.loc[df['msg_date_time'] == '20170322123231'].to_dict(
'list')
assert are_segs_equal(df_msg_1_seg_1, msg_1_seg_1) is True
assert are_segs_equal(df_msg_1_seg_2, msg_1_seg_2) is True
assert are_segs_equal(df_msg_2_seg_1, msg_2_seg_1) is True
assert are_segs_equal(df_msg_3_seg_1, msg_3_seg_1) is True
def test_id_loc_not_multi_vals():
with pytest.raises(RuntimeError):
tidy_segs(['DG1.3.2'], REPORT_LOCS_DG1, MSGS)
def test_id_loc_not_missing_seg():
with pytest.raises(RuntimeError):
tidy_segs(['EVN.2'], REPORT_LOCS_DG1, MSGS)
def test_id_loc_not_na():
with pytest.raises(RuntimeError):
tidy_segs(['PID.3.2'], REPORT_LOCS_DG1, MSGS)
def test_print_tidy_segs():
# pylint: disable=invalid-name
df = tidy_segs(MSG_ID_LOCS, REPORT_LOCS_DG1, MSGS)
print('\n\n')
print(df)
def test_df_cols_renamed():
# pylint: disable=invalid-name
df = tidy_segs(MSG_ID_LOCS, REPORT_LOCS_DG1, MSGS)
col_names = (list(MSG_ID_LOCS.values()) + list(REPORT_LOCS_DG1.values()) +
['seg'])
assert all([col in df.columns.values for col in col_names]) is True