def test_make_template(self):
t_map = KeyTemplate(self.key_cols)
stern_df = pd.read_csv(self.stern_map_path, delimiter='\t', header=0)
t_map.update(stern_df)
df1 = t_map.make_template()
self.assertIsInstance(df1, pd.DataFrame,
"make_template should return a DataFrame")
self.assertEqual(
len(df1.columns), 1,
"make_template should return 1 column single key, no additional columns"
)
t_map2 = KeyTemplate(['event_type', 'type'])
t_map2.update(self.stern_map_path)
df2 = t_map2.make_template()
self.assertIsInstance(df2, pd.DataFrame,
"make_template should return a DataFrame")
self.assertEqual(
len(df2.columns), 2,
"make_template should return 2 columns w 2 keys, no additional columns"
)
df3 = t_map2.make_template(['bananas', 'pears', 'apples'])
self.assertIsInstance(df3, pd.DataFrame,
"make_template should return a DataFrame")
self.assertEqual(
len(df3.columns), 5,
"make_template should return 5 columns w 2 keys, 3 additional columns"
)
def test_update_map_missing_key(self):
keys = self.key_cols + ['another']
t_map = KeyTemplate(keys)
stern_df = pd.read_csv(self.stern_map_path, delimiter='\t', header=0)
t_map.update(stern_df)
self.assertEqual(len(t_map.col_map.columns),
len(self.key_cols) + 1,
"update should have all of the columns")
def test_print(self):
from io import StringIO
t_map = KeyTemplate(self.key_cols + self.target_cols)
t_map.update(self.stern_map_path)
t_map.update(self.stern_map_path)
with mock.patch('sys.stdout', new=StringIO()):
t_map.print()
print("This should be eaten by the StringIO")
def test_update_map_duplicate_keys(self):
t_map = KeyTemplate(self.key_cols)
stern_df = pd.read_csv(self.stern_test2_path, delimiter='\t', header=0)
t_map.update(stern_df)
self.assertEqual(
len(t_map.count_dict), len(t_map.map_dict),
"The count dictionary and key dictionary should have same number of values"
)
def test_update_map(self):
t_map = KeyTemplate(self.key_cols)
stern_df = pd.read_csv(self.stern_map_path, delimiter='\t', header=0)
t_map.update(stern_df)
df_map = t_map.col_map
df_dict = t_map.map_dict
self.assertEqual(len(df_map), len(stern_df),
"update map should contain all the entries")
self.assertEqual(len(df_dict.keys()), len(stern_df),
"update dictionary should contain all the entries")
def test_make_template_key_overlap(self):
t_map = KeyTemplate(['event_type', 'type'])
t_map.update(self.stern_map_path)
try:
t_map.make_template(['Bananas', 'type', 'Pears'])
except HedFileError:
pass
except Exception as ex:
self.fail(
f'make_template threw the wrong exception {ex} when additional columns overlapped keys'
)
else:
self.fail(
'KeyTemplate should have thrown a HedFileError exception when key overlap but threw none'
)
def test_key_hash_use(self):
t_map = KeyTemplate(['type'])
stern_df = pd.read_csv(self.stern_map_path,
delimiter='\t',
header=0,
keep_default_na=False,
na_values=",null")
t_map.update(stern_df)
t_col = t_map.col_map
for index, row in stern_df.iterrows():
key = get_row_hash(row, t_map.columns)
key_value = t_map.map_dict[key]
self.assertEqual(t_col.iloc[key_value]['type'], row['type'],
"The key should be looked up for same map")
stern_test1 = pd.read_csv(self.stern_test1_path,
delimiter='\t',
header=0)
for index, row in stern_test1.iterrows():
key = get_row_hash(row, t_map.columns)
key_value = t_map.map_dict[key]
self.assertEqual(t_col.iloc[key_value]['type'], row['type'],
"The key should be looked up for other file")
def test_update_map_not_unique(self):
t_map = KeyTemplate(self.target_cols)
stern_df = pd.read_csv(self.stern_map_path, delimiter='\t', header=0)
t_map.update(stern_df)
self.assertEqual(len(t_map.col_map.columns), 3,
"update should produce correct number of columns")
self.assertEqual(len(t_map.col_map),
len(stern_df) - 1,
"update should produce the correct number of rows")
for key, value in t_map.count_dict.items():
self.assertGreaterEqual(
value, 1, "update the counts should all be one for unique map")
t_map.update(stern_df)
for key, value in t_map.count_dict.items():
self.assertGreaterEqual(
value, 2,
"update the counts should all be one for second update with same map"
)
self.assertEqual(len(t_map.col_map.columns), 3,
"update should produce correct number of columns")
self.assertEqual(len(t_map.col_map),
len(stern_df) - 1,
"update should produce the correct number of rows")