def query(self, term, symptoms_side, dominant_hemisphere):
path = semiology_dict_path if term in all_semiology_terms else None
query_semiology_result, num_query_lat, num_query_loc = QUERY_SEMIOLOGY(
mega_analysis_df,
semiology_term=term,
semiology_dict_path=path,
)
if query_semiology_result is None:
return None
all_combined_gifs, num_QL_lat, num_QL_CL, num_QL_IL, num_QL_BL, num_QL_DomH, num_QL_NonDomH = QUERY_LATERALISATION(
query_semiology_result,
mega_analysis_df,
one_map,
gif_lat_file,
side_of_symptoms_signs=symptoms_side.value,
pts_dominant_hemisphere_R_or_L=dominant_hemisphere.value,
)
if all_combined_gifs is None:
pivot_result = melt_then_pivot_query(
mega_analysis_df,
query_semiology_result,
term,
)
all_combined_gifs = pivot_result_to_one_map(pivot_result, one_map)
return all_combined_gifs
def query(self, term):
path = semiology_dict_path if term in all_semiology_terms else None
inspect_result, num_query_lat, num_query_loc = QUERY_SEMIOLOGY(
mega_analysis_df,
semiology_term=term,
semiology_dict_path=path,
)
return path, inspect_result
def test_parenthesis_and_caps_QUERY_SEMIOLOGY_with_dictionary(self):
query, num_query_lat, num_query_loc = QUERY_SEMIOLOGY(
self.df,
# see dummy_SemioDict: equivalent to "Aphasia"
semiology_term='dummy_test_link_aphasia',
ignore_case=False,
# in QUERY_SEMIO re.IGNORECASE is used for dictionary anyway
semiology_dict_path=dummy_semiology_dict_path,
col1='Reported Semiology',
col2='Semiology Category',
)
assert (query['Localising'].sum() == 14)
assert (query['Lateralising'].sum() == 6)
def test_parenthesis_and_caps_QUERY_SEMIOLOGY_regex_pickup(self):
"""
default QUERY_SEMIOLOGY doesn't exclude paed cases
"""
query, num_query_lat, num_query_loc = QUERY_SEMIOLOGY(
self.df,
semiology_term=['aphasia'],
ignore_case=True,
semiology_dict_path=None,
col1='Reported Semiology',
col2='Semiology Category',
)
assert (query['Localising'].sum() == 14)
assert (query['Lateralising'].sum() == 6)
def test_caps_QUERY_SEMIOLOGY_regex_pickup(self):
"""
when ignore case is false, it won't pick up case mismatches.
so sum is slightly less.
"""
query, num_query_lat, num_query_loc = QUERY_SEMIOLOGY(
self.df,
semiology_term=['aphasia'],
ignore_case=False,
semiology_dict_path=None,
col1='Reported Semiology',
col2='Semiology Category',
)
assert (query['Localising'].sum() == 13)
assert (query['Lateralising'].sum() == 6)
def test_only_postictal_cases(self):
"""
Include only the single postictal aphasia. Note Dominant in dummy data.
cf test_postictal_exclusions
"""
# Low level test
df_postictal = only_postictal_cases(self.df)
query, num_query_lat, num_query_loc = QUERY_SEMIOLOGY(
df_postictal,
semiology_term=['aphasia'],
ignore_case=True,
semiology_dict_path=None,
col1='Reported Semiology',
col2='Semiology Category',
)
assert (query['Localising'].sum() == 1)
assert (query['Lateralising'].sum() == 1)
# High level test
patient = Semiology('aphasia',
Laterality.NEUTRAL,
dominant_hemisphere=Laterality.LEFT)
patient.data_frame = self.df
patient.include_postictals = True
patient.include_only_postictals = True
patient.granular = True
lat_allgifs = patient.query_lateralisation(one_map_dummy)
lat_allgifs = lat_allgifs[['Gif Parcellations', 'pt #s']].astype({
'Gif Parcellations':
'int32',
'pt #s':
'int32'
})
lat_allgifs.set_index('Gif Parcellations', inplace=True)
# note that dominant_hemisphere == Laterality.LEFT as set above. Just to clarify results change if dominace changes. Also 1's become 2's if not granular.
assert (lat_allgifs.loc[164, 'pt #s'] == 1)
assert (lat_allgifs.loc[166, 'pt #s'] == 1)
assert (lat_allgifs.loc[163, 'pt #s'] == 0)
assert (lat_allgifs.loc[165, 'pt #s'] == 0)
lat_allgifs = lat_allgifs.loc[lat_allgifs['pt #s'] != 0, :]
SVT_output, _ = patient.get_num_datapoints_dict(method='minmax')
assert SVT_output == dict((lat_allgifs)['pt #s'])
def test_postictal_exclusion(self):
"""
Exclude the single postictal aphasia.
After update in June, default is to exclude postictals.
So the result of this should be the same as query_semiology()
"""
df_excl = exclusions(self.df)
query, num_query_lat, num_query_loc = QUERY_SEMIOLOGY(
df_excl,
semiology_term=['aphasia'],
ignore_case=True,
semiology_dict_path=None,
col1='Reported Semiology',
col2='Semiology Category',
)
assert (query['Localising'].sum() == 13)
assert (query['Lateralising'].sum() == 5)
print('\n2.2 postictal\n')