def test_FP_options(self):
'''
Creating amplicon FPs logic is independent of creating sample FPs logic
'''
with self.subTest():
ret = config.get_serviceImpl().run_picrust2_pipeline(
config.ctx, {
**config.get_ws(),
'amplicon_matrix_upa': enigma50by30,
'fp_options': {
'create_amplicon_fps': False,
'create_sample_fps': False,
},
'output_name': 'an_output_name',
})
assert len(Var.objects_created) == 2, Var.objects_created
with self.subTest():
ret = config.get_serviceImpl().run_picrust2_pipeline(
config.ctx, {
**config.get_ws(),
'amplicon_matrix_upa': enigma50by30,
'fp_options': {
'create_amplicon_fps': True,
'create_sample_fps': True,
},
'output_name': 'an_output_name',
})
assert len(Var.objects_created) == 8, Var.objects_created
def test_nonePass_succeedCor(self):
# get obj with all 1s
with patch.dict('OTUSampleMetadataCorrelation.util.kbase_obj.Var',
values={'dfu': get_mock_dfu('enigma50by30')}):
obj = AmpliconMatrix(enigma50by30).obj
obj['data']['values'] = [[1 for j in range(30)]
for i in range(50)] # all 1s
# integreate all-1s version into mock dfu
dfu = get_mock_dfu('enigma50by30', replace_obj={enigma50by30: obj})
# run with all-1s-obj patched in
with patch(
'OTUSampleMetadataCorrelation.OTUSampleMetadataCorrelationImpl.DataFileUtil',
new=lambda *a, **kw: dfu):
ret = cfg.get_serviceImpl().run_OTUSampleMetadataCorrelation(
cfg.ctx, {
"amp_mat_upa": enigma50by30,
"sample_metadata": sample_metadata_50by30,
"amp_params": {
"val_cutoff": None,
"sd_cutoff": None,
"tax_rank": None,
"tax_field": None,
},
"cor_params": {
"cor_cutoff": 0,
"cor_method": "pearson",
"p_adj_method": "bonferroni",
"p_adj_cutoff": 1
},
'workspace_name': self.wsName,
})
def test_has_row_AttributeMapping_create_all(self):
ret = config.get_serviceImpl().run_picrust2_pipeline(
config.ctx, {
**config.get_ws(),
'amplicon_matrix_upa': enigma50by30,
'output_name': 'an_output_name',
})
assert len(Var.objects_created) == 8, Var.objects_created
def test_has_no_row_AttributeMapping(self):
'''
Will not update/create row AttributeMapping if already none
Default is to create all the FPs
'''
ret = config.get_serviceImpl().run_picrust2_pipeline(
config.ctx, {
**config.get_ws(),
'amplicon_matrix_upa': enigma50by30_noAttrMaps_noSampleSet,
'output_name': 'an_output_name',
})
assert len(Var.objects_created) == 6, Var.objects_created
def test_large_dataset(self):
'''
'''
ret = config.get_serviceImpl().run_picrust2_pipeline(
config.ctx, {
**config.get_ws(),
'amplicon_matrix_upa': enigma17770by511,
'fp_options': {
'create_amplicon_fps': 1,
'create_sample_fps': 1,
},
'output_name': 'an_output_name',
})
assert len(Var.objects_created) == 8, Var.objects_created
def test_userTest_data(self):
ret = config.get_serviceImpl().run_picrust2_pipeline(
config.ctx, {
**config.get_ws(),
'amplicon_matrix_upa': userTest,
'functions': {
'cog': 1,
'pfam': 1,
'tigrfam': 1,
'pheno': 1,
},
'fp_options': {
'create_amplicon_fps': 1,
'create_sample_fps': 1,
},
'output_name': 'an_output_name',
})
assert len(Var.objects_created) == 14, Var.objects_created
def test_nonePass_filterPAdj(self):
ret = cfg.get_serviceImpl().run_OTUSampleMetadataCorrelation(
cfg.ctx, {
"amp_mat_upa": enigma50by30,
"sample_metadata": sample_metadata_50by30,
"amp_params": {
"val_cutoff": None,
"sd_cutoff": None,
"tax_rank": None,
"tax_field": None,
},
"cor_params": {
"cor_cutoff": 0,
"cor_method": "pearson",
"p_adj_method": "BH",
"p_adj_cutoff": 0
},
'workspace_name': self.wsName,
})
def _test_wTax(self, amp_mat_upa, sample_metadata, tax_rank, tax_field):
ret = cfg.get_serviceImpl().run_OTUSampleMetadataCorrelation(
cfg.ctx,
{
"amp_mat_upa": amp_mat_upa,
"sample_metadata": sample_metadata,
"amp_params": {
"val_cutoff": None,
"sd_cutoff": None,
"tax_rank": tax_rank,
"tax_field": tax_field, # can be listed or not
},
"cor_params": {
"cor_cutoff": 0.1,
"cor_method": "kendall",
"p_adj_method": "BH",
"p_adj_cutoff": 0.9
},
'workspace_name': self.wsName,
})
def test_small_3_results(self):
'''
'''
ret = cfg.get_serviceImpl().run_OTUSampleMetadataCorrelation(
cfg.ctx, {
"amp_mat_upa": enigma50by30,
"sample_metadata": sample_metadata_50by30,
"amp_params": {
"val_cutoff": 1,
"sd_cutoff": 1,
"tax_rank": 'genus',
"tax_field": ['taxonomy'],
},
"cor_params": {
"cor_cutoff": 0.503,
"cor_method": "kendall",
"p_adj_method": "bonferroni",
"p_adj_cutoff": 1,
},
'workspace_name': self.wsName,
})
def test_large_defaultParams(self):
'''
'''
ret = cfg.get_serviceImpl().run_OTUSampleMetadataCorrelation(
cfg.ctx, {
"amp_mat_upa": enigma17770by511,
"sample_metadata": sample_metadata_17770by511,
"amp_params": {
"val_cutoff": None,
"sd_cutoff": None,
"tax_rank": None,
"tax_field": None,
},
"cor_params": {
"cor_cutoff": 0.5,
"cor_method": "kendall",
"p_adj_method": "BH",
"p_adj_cutoff": 0.05,
},
'workspace_name': self.wsName,
})
def test_small(self):
'''
'''
ret = cfg.get_serviceImpl().run_OTUSampleMetadataCorrelation(
cfg.ctx, {
"amp_mat_upa": enigma50by30,
"sample_metadata": sample_metadata_50by30,
"amp_params": {
"val_cutoff": None,
"sd_cutoff": None,
"tax_rank": 'genus',
"tax_field": ['taxonomy'],
},
"cor_params": {
"cor_cutoff": 0.01,
"cor_method": "pearson",
"p_adj_method": "BH",
"p_adj_cutoff": 0.9,
},
'workspace_name': self.wsName,
})
def test_func_options(self):
with self.subTest():
ret = config.get_serviceImpl().run_picrust2_pipeline(
config.ctx, {
**config.get_ws(),
'amplicon_matrix_upa': enigma50by30,
'functions': {
'cog': 1,
'pfam': 1,
'tigrfam': 1,
'pheno': 1,
},
'fp_options': {
'create_amplicon_fps': 1,
'create_sample_fps': 1,
},
'output_name': 'an_output_name',
})
assert len(Var.objects_created) == 16, Var.objects_created
'''
def test_nonePass_prelimFilter(self):
'''
All amplicons filtered out by value/sd
(Taxonomy can't eliminate all amplicons)
'''
ret = cfg.get_serviceImpl().run_OTUSampleMetadataCorrelation(
cfg.ctx, {
"amp_mat_upa": enigma50by30,
"sample_metadata": sample_metadata_50by30,
"amp_params": {
"val_cutoff": 1e9,
"sd_cutoff": 1e9,
"tax_rank": None,
"tax_field": None,
},
"cor_params": {
"cor_cutoff": 0.5,
"cor_method": "kendall",
"p_adj_method": "BH",
"p_adj_cutoff": 0.05
},
'workspace_name': self.wsName,
})
def test_dup_GenomeSet(self):
ret = config.get_serviceImpl().run_FAPROTAX(
config.ctx, {
**self.ws,
'input_upa': refseq_dup,
})