def test_to_file(self):
params = ProcessedSortmernaParams(1)
fd, fp = mkstemp()
close(fd)
with open(fp, 'w') as f:
params.to_file(f)
with open(fp, 'U') as f:
obs = f.read()
self.assertEqual(obs, EXP_SMR_PARAMS_FILE)
def test_get_process_target_gene_cmd(self):
preprocessed_data = PreprocessedData(1)
params = ProcessedSortmernaParams(1)
obs_cmd, obs_output_dir = _get_process_target_gene_cmd(
preprocessed_data, params)
_, ref_dir = get_mountpoint('reference')[0]
_, preprocessed_dir = get_mountpoint('preprocessed_data')[0]
exp_cmd = ("pick_closed_reference_otus.py -i {}1_seqs.fna -r "
"{}GreenGenes_13_8_97_otus.fasta -o {} -p placeholder -t "
"{}GreenGenes_13_8_97_otu_taxonomy.txt".format(
preprocessed_dir, ref_dir, obs_output_dir, ref_dir))
obs_tokens = obs_cmd.split()[::-1]
exp_tokens = exp_cmd.split()[::-1]
self.assertEqual(len(obs_tokens), len(exp_tokens))
while obs_tokens:
o_t = obs_tokens.pop()
e_t = exp_tokens.pop()
if o_t == '-p':
# skip parameters file
obs_tokens.pop()
exp_tokens.pop()
else:
self.assertEqual(o_t, e_t)
def test_generate_param_str(self):
params = ProcessedSortmernaParams(1)
obs = generate_param_str(params)
exp = ("<b>Reference:</b> Greengenes 13_8<br/>"
"<b>similarity:</b> 0.97<br/>"
"<b>sortmerna_e_value:</b> 1.0<br/>"
"<b>sortmerna_max_pos:</b> 10000<br/>"
"<b>threads:</b> 1<br/>"
"<b>sortmerna_coverage:</b> 0.97")
self.assertEqual(obs, exp)
def test_insert_processed_data_target_gene(self):
fd, fna_fp = mkstemp(suffix='_seqs.fna')
close(fd)
fd, qual_fp = mkstemp(suffix='_seqs.qual')
close(fd)
filepaths = [
(fna_fp, convert_to_id('preprocessed_fasta', 'filepath_type')),
(qual_fp, convert_to_id('preprocessed_fastq', 'filepath_type'))
]
preprocessed_data = PreprocessedData.create(
Study(1),
"preprocessed_sequence_illumina_params",
1,
filepaths,
data_type="18S")
params = ProcessedSortmernaParams(1)
pick_dir = mkdtemp()
path_builder = partial(join, pick_dir)
db_path_builder = partial(join, get_mountpoint('processed_data')[0][1])
# Create a placeholder for the otu table
with open(path_builder('otu_table.biom'), 'w') as f:
f.write('\n')
# Create a placeholder for the directory
mkdir(path_builder('sortmerna_picked_otus'))
# Create the log file
fd, fp = mkstemp(dir=pick_dir, prefix='log_', suffix='.txt')
close(fd)
with open(fp, 'w') as f:
f.write('\n')
_insert_processed_data_target_gene(preprocessed_data, params, pick_dir)
new_id = get_count('qiita.processed_data')
# Check that the files have been copied
db_files = [
db_path_builder("%s_otu_table.biom" % new_id),
db_path_builder("%s_sortmerna_picked_otus" % new_id),
db_path_builder("%s_%s" % (new_id, basename(fp)))
]
for fp in db_files:
self.assertTrue(exists(fp))
# Check that a new preprocessed data has been created
self.assertTrue(
self.conn_handler.execute_fetchone(
"SELECT EXISTS(SELECT * FROM qiita.processed_data WHERE "
"processed_data_id=%s)", (new_id, ))[0])
def render(self, study_id, preprocessed_data):
user = self.current_user
ppd_id = preprocessed_data.id
ebi_status = preprocessed_data.submitted_to_insdc_status()
ebi_study_accession = preprocessed_data.ebi_study_accession
ebi_submission_accession = preprocessed_data.ebi_submission_accession
vamps_status = preprocessed_data.submitted_to_vamps_status()
filepaths = preprocessed_data.get_filepaths()
is_local_request = self._is_local()
show_ebi_btn = user.level == "admin"
processing_status = preprocessed_data.processing_status
processed_data = preprocessed_data.processed_data
# Get all the ENA terms for the investigation type
ontology = Ontology(convert_to_id('ENA', 'ontology'))
# make "Other" show at the bottom of the drop down menu
ena_terms = []
for v in sorted(ontology.terms):
if v != 'Other':
ena_terms.append('<option value="%s">%s</option>' % (v, v))
ena_terms.append('<option value="Other">Other</option>')
# New Type is for users to add a new user-defined investigation type
user_defined_terms = ontology.user_defined_terms + ['New Type']
if PrepTemplate.exists(preprocessed_data.prep_template):
prep_template_id = preprocessed_data.prep_template
prep_template = PrepTemplate(prep_template_id)
raw_data_id = prep_template.raw_data
inv_type = prep_template.investigation_type or "None Selected"
else:
prep_template_id = None
raw_data_id = None
inv_type = "None Selected"
process_params = {param.id: (generate_param_str(param), param.name)
for param in ProcessedSortmernaParams.iter()}
# We just need to provide an ID for the default parameters,
# so we can initialize the interface
default_params = 1
return self.render_string(
"study_description_templates/preprocessed_data_info_tab.html",
ppd_id=ppd_id,
show_ebi_btn=show_ebi_btn,
ebi_status=ebi_status,
ebi_study_accession=ebi_study_accession,
ebi_submission_accession=ebi_submission_accession,
filepaths=filepaths,
is_local_request=is_local_request,
prep_template_id=prep_template_id,
raw_data_id=raw_data_id,
inv_type=inv_type,
ena_terms=ena_terms,
vamps_status=vamps_status,
user_defined_terms=user_defined_terms,
process_params=process_params,
default_params=default_params,
study_id=preprocessed_data.study,
processing_status=processing_status,
processed_data=processed_data)
def test_to_str(self):
params = ProcessedSortmernaParams(1)
obs = params.to_str()
exp = ("--similarity 0.97 --sortmerna_coverage 0.97 "
"--sortmerna_e_value 1.0 --sortmerna_max_pos 10000 --threads 1")
self.assertEqual(obs, exp)
