def test_linear_mixed_effects_taxa(self):
linear_mixed_effects(
output_dir=self.temp_dir.name, table=self.table_ecam_fp,
metadata=self.md_ecam_fp, state_column='month',
group_categories='delivery,diet,antiexposedall',
individual_id_column='studyid',
metric='e2c3ff4f647112723741aa72087f1bfa')
def test_linear_mixed_effects_singular_matrix_error(self):
with self.assertRaisesRegex(ValueError, "singular matrix error"):
linear_mixed_effects(
output_dir=self.temp_dir.name, table=None,
metadata=self.md_ecam_fp, state_column='month',
group_categories='diet,diet_3',
individual_id_column='studyid', metric='observed_otus')
def test_linear_mixed_effects_missing_metric(self):
with self.assertRaisesRegex(
ValueError, 'Must specify either a metric or a formula'):
linear_mixed_effects(
output_dir=self.temp_dir.name, table=None,
metadata=self.md_ecam_fp, state_column='month',
individual_id_column='studyid')
def test_linear_mixed_effects_dodge_patsy_error_ix0_is_digit(self):
linear_mixed_effects(
output_dir=self.temp_dir.name, table=self.table_ecam_fp,
metadata=self.md_ecam_fp, state_column='month',
group_columns='delivery',
individual_id_column='studyid',
metric='74923f4bbde849e27fc4eda25d757e2a')
def test_linear_mixed_effects(self):
linear_mixed_effects(output_dir=self.temp_dir.name,
table=None,
metadata=self.md_ecam_fp,
state_column='month',
group_categories='delivery,diet,antiexposedall',
individual_id_column='studyid',
metric='observed_otus')
def test_linear_mixed_effects_formula_missing_tilde(self):
with self.assertRaisesRegex(ValueError,
'metric ~ independent'):
linear_mixed_effects(
output_dir=self.temp_dir.name, table=None,
metadata=self.md_ecam_fp, state_column='month',
individual_id_column='studyid',
formula='delivery * diet * antiexposedall')
def test_linear_mixed_effects_formula_missing_state_column(self):
with self.assertRaisesRegex(ValueError,
'must contain the "state_column"'):
linear_mixed_effects(
output_dir=self.temp_dir.name, table=None,
metadata=self.md_ecam_fp, state_column='month',
individual_id_column='studyid',
formula='observed_otus ~ delivery * diet * antiexposedall')
def test_linear_mixed_effects_dodge_patsy_error_spacey_metrics(self):
peanuts_ugly_md = qiime2.Metadata(
self.md_ecam_fp.to_dataframe().rename(
columns={'observed_otus': 'observed otus'}))
linear_mixed_effects(
output_dir=self.temp_dir.name,
metadata=peanuts_ugly_md, state_column='month',
group_columns='delivery',
individual_id_column='studyid',
metric='observed otus')
def test_linear_mixed_effects_no_group_categories(self):
linear_mixed_effects(
output_dir=self.temp_dir.name, table=None,
metadata=self.md_ecam_fp, state_column='month',
individual_id_column='studyid', metric='observed_otus')
obs = pd.read_csv(
os.path.join(self.temp_dir.name, 'model_results.tsv'),
sep='\t', index_col=0)
exp = pd.read_csv(
self.get_data_path('linear_mixed_effects_no_group_categories.tsv'),
sep='\t', index_col=0)
pdt.assert_frame_equal(obs, exp)
def test_linear_mixed_effects_interaction_depth_operator(self):
formula = 'observed_otus~(month+delivery+diet)**2'
linear_mixed_effects(
output_dir=self.temp_dir.name, table=None,
metadata=self.md_ecam_fp, state_column='month',
individual_id_column='studyid', formula=formula)
obs = pd.read_csv(
os.path.join(self.temp_dir.name, 'model_results.tsv'),
sep='\t', index_col=0)
exp = pd.read_csv(
self.get_data_path('linear_mixed_effects_formula_depth.tsv'),
sep='\t', index_col=0)
pdt.assert_frame_equal(obs, exp)
def test_linear_mixed_effects_complex_formula(self):
formula = 'observed_otus~month*delivery+diet+month:diet-month:delivery'
linear_mixed_effects(
output_dir=self.temp_dir.name, table=None,
metadata=self.md_ecam_fp, state_column='month',
individual_id_column='studyid', formula=formula)
obs = pd.read_csv(
os.path.join(self.temp_dir.name, 'model_results.tsv'),
sep='\t', index_col=0)
exp = pd.read_csv(
self.get_data_path('linear_mixed_effects_complex_formula.tsv'),
sep='\t', index_col=0)
pdt.assert_frame_equal(obs, exp)
def test_linear_mixed_effects_taxa(self):
linear_mixed_effects(
output_dir=self.temp_dir.name, table=self.table_ecam_fp,
metadata=self.md_ecam_fp, state_column='month',
group_categories='delivery,diet,antiexposedall',
individual_id_column='studyid',
metric='e2c3ff4f647112723741aa72087f1bfa')
obs = pd.read_csv(
os.path.join(self.temp_dir.name, 'model_results.tsv'),
sep='\t', index_col=0)
exp = pd.read_csv(
self.get_data_path('linear_mixed_effects_taxa.tsv'),
sep='\t', index_col=0)
pdt.assert_frame_equal(obs, exp)
def test_linear_mixed_effects_with_multiple_random_effects(self):
linear_mixed_effects(
output_dir=self.temp_dir.name, table=None,
metadata=self.md_ecam_fp, state_column='month',
group_columns='delivery,diet,antiexposedall',
random_effects='month,studyid',
individual_id_column='studyid', metric='observed_otus')
obs = pd.read_csv(
os.path.join(self.temp_dir.name, 'model_results.tsv'),
sep='\t', index_col=0)
exp = pd.read_csv(self.get_data_path(
'linear_mixed_effects_with_multiple_random_effects.tsv'),
sep='\t', index_col=0)
pdt.assert_frame_equal(obs, exp)
