def test_is_localhost(self):
self.assertTrue(is_localhost('127.0.0.1'))
self.assertTrue(is_localhost('localhost'))
self.assertTrue(is_localhost('127.0.0.1:21174'))
self.assertFalse(is_localhost('10.0.0.1'))
self.assertFalse(is_localhost('10.0.0.1:21174'))
def test_is_localhost(self):
self.assertTrue(is_localhost('127.0.0.1'))
self.assertTrue(is_localhost('localhost'))
self.assertTrue(is_localhost('127.0.0.1:21174'))
self.assertFalse(is_localhost('10.0.0.1'))
self.assertFalse(is_localhost('10.0.0.1:21174'))
def get(self):
message = self.get_argument('message', '')
level = self.get_argument('level', '')
user = self.current_user
analyses = user.shared_analyses | user.private_analyses
is_local_request = is_localhost(self.request.headers['host'])
gfi = partial(get_filepath_id, 'analysis')
dlop = partial(download_link_or_path, is_local_request)
mappings = {}
bioms = {}
for analysis in analyses:
_id = analysis.id
mapping = analysis.mapping_file
if mapping is not None:
mappings[_id] = dlop(mapping, gfi(mapping), 'mapping file')
else:
mappings[_id] = ''
links = [
dlop(f, gfi(f), l) for l, f in viewitems(analysis.biom_tables)
]
bioms[_id] = '\n'.join(links)
self.render("show_analyses.html",
analyses=analyses,
message=message,
level=level,
is_local_request=is_local_request,
mappings=mappings,
bioms=bioms)
def get(self):
message = self.get_argument('message', '')
level = self.get_argument('level', '')
user = self.current_user
analyses = user.shared_analyses | user.private_analyses
is_local_request = is_localhost(self.request.headers['host'])
gfi = partial(get_filepath_id, 'analysis')
dlop = partial(download_link_or_path, is_local_request)
mappings = {}
bioms = {}
tgzs = {}
for analysis in analyses:
_id = analysis.id
# getting mapping file
mapping = analysis.mapping_file
if mapping is not None:
mappings[_id] = dlop(mapping, gfi(mapping), 'mapping file')
else:
mappings[_id] = ''
# getting biom tables
links = [dlop(f, gfi(f), l)
for l, f in viewitems(analysis.biom_tables)]
bioms[_id] = '\n'.join(links)
# getting tgz file
tgz = analysis.tgz
if tgz is not None:
tgzs[_id] = dlop(tgz, gfi(tgz), 'tgz file')
else:
tgzs[_id] = ''
self.render("show_analyses.html", analyses=analyses, message=message,
level=level, is_local_request=is_local_request,
mappings=mappings, bioms=bioms, tgzs=tgzs)
def get(self):
message = self.get_argument('message', '')
level = self.get_argument('level', '')
user = self.current_user
analyses = user.shared_analyses | user.private_analyses
is_local_request = is_localhost(self.request.headers['host'])
dlop = partial(download_link_or_path, is_local_request)
mappings = {}
bioms = {}
tgzs = {}
for analysis in analyses:
_id = analysis.id
mappings[_id], bioms[_id], tgzs[_id] = '', '', ''
for fid, fp, fpt in retrieve_filepaths('analysis_filepath',
'analysis_id', _id):
if fpt == 'plain_text':
mappings[_id] = dlop(fp, fid, 'mapping file')
if fpt == 'biom':
bioms[_id] = dlop(fp, fid, 'biom file')
if fpt == 'tgz':
tgzs[_id] = dlop(fp, fid, 'tgz file')
self.render("list_analyses.html",
analyses=analyses,
message=message,
level=level,
is_local_request=is_local_request,
mappings=mappings,
bioms=bioms,
tgzs=tgzs)
def render(self, study):
study_info = study.info
id = study.id
abstract = study_info['study_abstract']
description = study_info['study_description']
pmids = ", ".join([pubmed_linkifier([pmid]) for pmid in study.pmids])
princ_inv = StudyPerson(study_info['principal_investigator_id'])
pi_link = study_person_linkifier((princ_inv.email, princ_inv.name))
number_samples_promised = study_info['number_samples_promised']
number_samples_collected = study_info['number_samples_collected']
metadata_complete = study_info['metadata_complete']
data_types = sorted(viewitems(get_data_types()), key=itemgetter(1))
# Retrieve the files from the uploads folder, so the user can choose
# the sample template of the study. Filter them to only include the
# ones that ends with 'txt' or 'tsv'.
files = [f for _, f in get_files_from_uploads_folders(str(study.id))
if f.endswith(('txt', 'tsv'))]
# If the sample template exists, retrieve all its filepaths
if SampleTemplate.exists(study.id):
sample_templates = SampleTemplate(study.id).get_filepaths()
else:
# If the sample template does not exist, just pass an empty list
sample_templates = []
# Check if the request came from a local source
is_local_request = is_localhost(self.request.headers['host'])
# The user can choose the sample template only if the study is
# sandboxed or the current user is an admin
show_select_sample = (
study.status == 'sandbox' or self.current_user.level == 'admin')
# Ebi information
ebi_status = study.ebi_submission_status
ebi_accession = study.ebi_study_accession
if ebi_accession:
ebi_accession = (EBI_LINKIFIER.format(ebi_accession))
return self.render_string(
"study_description_templates/study_information_tab.html",
abstract=abstract,
description=description,
id=id,
pmids=pmids,
principal_investigator=pi_link,
number_samples_promised=number_samples_promised,
number_samples_collected=number_samples_collected,
metadata_complete=metadata_complete,
show_select_sample=show_select_sample,
files=files,
study_id=study.id,
sample_templates=sample_templates,
is_local_request=is_local_request,
data_types=data_types,
ebi_status=ebi_status,
ebi_accession=ebi_accession)
def render(self, study_id, processed_data, allow_approval,
approval_deny_msg):
user = self.current_user
# The request approval, approve processed data and make public buttons
# are mutually exclusive. Only one of them will be shown, depending on
# the current status of the processed data
status = processed_data.visibility
btn_to_show = None
if status == 'sandbox' and qiita_config.require_approval:
# The request approval button only appears if the processed data is
# sandboxed and the qiita_config specifies that the approval should
# be requested
btn_to_show = 'request_approval'
elif (user.level == 'admin' and status == 'awaiting_approval'
and qiita_config.require_approval):
# The approve processed data button only appears if the user is an
# admin, the processed data is waiting to be approved and the qiita
# config requires processed data approval
btn_to_show = 'approve'
elif status == 'private':
# The make public button only appears if the status is private
btn_to_show = 'make_public'
# The revert to sandbox button only appears if the processed data is
# not sandboxed or public
show_revert_btn = status not in {'sandbox', 'public'}
# process data can only have one preprocess_data
preprocessed_data_id = processed_data.parents[0].id
process_date = str(processed_data.timestamp)
filepaths = processed_data.filepaths
is_local_request = is_localhost(self.request.headers['host'])
return self.render_string(
"study_description_templates/processed_data_info_tab.html",
pd_id=processed_data.id,
preprocessed_data_id=preprocessed_data_id,
process_date=process_date,
filepaths=filepaths,
is_local_request=is_local_request,
btn_to_show=btn_to_show,
show_revert_btn=show_revert_btn,
allow_approval=allow_approval,
approval_deny_msg=approval_deny_msg)
def render(self, study_id, processed_data, allow_approval,
approval_deny_msg):
user = self.current_user
# The request approval, approve processed data and make public buttons
# are mutually exclusive. Only one of them will be shown, depending on
# the current status of the processed data
status = processed_data.status
btn_to_show = None
if status == 'sandbox' and qiita_config.require_approval:
# The request approval button only appears if the processed data is
# sandboxed and the qiita_config specifies that the approval should
# be requested
btn_to_show = 'request_approval'
elif (user.level == 'admin' and status == 'awaiting_approval' and
qiita_config.require_approval):
# The approve processed data button only appears if the user is an
# admin, the processed data is waiting to be approved and the qiita
# config requires processed data approval
btn_to_show = 'approve'
elif status == 'private':
# The make public button only appears if the status is private
btn_to_show = 'make_public'
# The revert to sandbox button only appears if the processed data is
# not sandboxed or public
show_revert_btn = status not in {'sandbox', 'public'}
pd_id = processed_data.id
preprocessed_data_id = processed_data.preprocessed_data
process_date = processed_data.processing_info['processed_date']
filepaths = processed_data.get_filepaths()
is_local_request = is_localhost(self.request.headers['host'])
return self.render_string(
"study_description_templates/processed_data_info_tab.html",
pd_id=pd_id,
preprocessed_data_id=preprocessed_data_id,
process_date=process_date,
filepaths=filepaths,
is_local_request=is_local_request,
btn_to_show=btn_to_show,
show_revert_btn=show_revert_btn,
allow_approval=allow_approval,
approval_deny_msg=approval_deny_msg)
def get(self):
user = self.current_user
is_local_request = is_localhost(self.request.headers['host'])
uanalyses = user.shared_analyses | user.private_analyses
user_analysis_ids = set([a.id for a in uanalyses])
panalyses = Analysis.get_by_status('public')
public_analysis_ids = set([a.id for a in panalyses])
public_analysis_ids = public_analysis_ids - user_analysis_ids
user_analyses = generate_analysis_list(user_analysis_ids)
public_analyses = generate_analysis_list(public_analysis_ids, True)
dlop = partial(download_link_or_path, is_local_request)
messages = {'info': '', 'danger': ''}
for analysis_id in user_analysis_ids:
job_info = r_client.get('analysis_delete_%d' % analysis_id)
if job_info:
job_info = defaultdict(lambda: '', loads(job_info))
job_id = job_info['job_id']
job = ProcessingJob(job_id)
job_status = job.status
processing = job_status not in ('success', 'error')
if processing:
messages['info'] += ('Analysis %s is being deleted<br/>' %
analysis_id)
elif job_status == 'error':
messages['danger'] += (job.log.msg.replace('\n', '<br/>') +
'<br/>')
else:
if job_info['alert_type'] not in messages:
messages[job_info['alert_type']] = []
messages[job_info['alert_type']] += (
job.log.msg.replace('\n', '<br/>') + '<br/>')
self.render("list_analyses.html",
user_analyses=user_analyses,
public_analyses=public_analyses,
messages=messages,
dlop=dlop)
def get(self):
user = self.current_user
is_local_request = is_localhost(self.request.headers['host'])
uanalyses = user.shared_analyses | user.private_analyses
user_analysis_ids = set([a.id for a in uanalyses])
panalyses = Analysis.get_by_status('public')
public_analysis_ids = set([a.id for a in panalyses])
public_analysis_ids = public_analysis_ids - user_analysis_ids
user_analyses = generate_analysis_list(user_analysis_ids)
public_analyses = generate_analysis_list(public_analysis_ids, True)
dlop = partial(download_link_or_path, is_local_request)
messages = {'info': '', 'danger': ''}
for analysis_id in user_analysis_ids:
job_info = r_client.get('analysis_delete_%d' % analysis_id)
if job_info:
job_info = defaultdict(lambda: '', loads(job_info))
job_id = job_info['job_id']
job = ProcessingJob(job_id)
job_status = job.status
processing = job_status not in ('success', 'error')
if processing:
messages['info'] += (
'Analysis %s is being deleted<br/>' % analysis_id)
elif job_status == 'error':
messages['danger'] += (
job.log.msg.replace('\n', '<br/>') + '<br/>')
else:
if job_info['alert_type'] not in messages:
messages[job_info['alert_type']] = []
messages[job_info['alert_type']] += (
job.log.msg.replace('\n', '<br/>') + '<br/>')
self.render("list_analyses.html", user_analyses=user_analyses,
public_analyses=public_analyses, messages=messages,
dlop=dlop)
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 = is_localhost(self.request.headers['host'])
show_ebi_btn = user.level == "admin"
processing_status = convert_text_html(
preprocessed_data.processing_status)
processed_data = sorted(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 render(self, study, prep_template, full_access, ena_terms,
user_defined_terms):
user = self.current_user
is_local_request = is_localhost(self.request.headers['host'])
template_fps = []
qiime_fps = []
# Unfortunately, both the prep template and the qiime mapping files
# have the sample type. The way to differentiate them is if we have
# the substring 'qiime' in the basename
for id_, fp in prep_template.get_filepaths():
if 'qiime' in basename(fp):
qiime_fps.append(
download_link_or_path(
is_local_request, fp, id_, 'Qiime mapping'))
else:
template_fps.append(
download_link_or_path(
is_local_request, fp, id_, 'Prep template'))
# Since get_filepaths returns the paths sorted from newest to oldest,
# the first in both list is the latest one
current_template_fp = template_fps[0]
current_qiime_fp = qiime_fps[0]
if len(template_fps) > 1:
show_old_templates = True
old_templates = template_fps[1:]
else:
show_old_templates = False
old_templates = None
if len(qiime_fps) > 1:
show_old_qiime_fps = True
old_qiime_fps = qiime_fps[1:]
else:
show_old_qiime_fps = False
old_qiime_fps = None
filetypes = sorted(
((ft, ft_id, fp_type_by_ft[ft])
for ft, ft_id in viewitems(get_filetypes())),
key=itemgetter(1))
files = [f for _, f in get_files_from_uploads_folders(str(study.id))]
other_studies_rd = sorted(viewitems(
_get_accessible_raw_data(user)))
# A prep template can be modified if its status is sandbox
is_editable = prep_template.status == 'sandbox'
raw_data_id = prep_template.raw_data
preprocess_options = []
preprocessed_data = None
show_preprocess_btn = True
no_preprocess_msg = None
if raw_data_id:
rd = RawData(raw_data_id)
rd_ft = rd.filetype
# If the prep template has a raw data associated, it can be
# preprocessed. Retrieve the pre-processing parameters
if rd_ft in ('SFF', 'FASTA'):
param_iter = Preprocessed454Params.iter()
elif rd_ft == 'FASTQ':
param_iter = [pip for pip in PreprocessedIlluminaParams.iter()
if pip.values['barcode_type'] != 'not-barcoded']
elif rd_ft == 'per_sample_FASTQ':
param_iter = [pip for pip in PreprocessedIlluminaParams.iter()
if pip.values['barcode_type'] == 'not-barcoded']
else:
raise NotImplementedError(
"Pre-processing of %s files currently not supported."
% rd_ft)
preprocess_options = []
for param in param_iter:
text = ("<b>%s:</b> %s" % (k, v)
for k, v in viewitems(param.values))
preprocess_options.append((param.id,
param.name,
'<br>'.join(text)))
preprocessed_data = prep_template.preprocessed_data
# Check if the template have all the required columns for
# preprocessing
raw_data_files = rd.get_filepaths()
if len(raw_data_files) == 0:
show_preprocess_btn = False
no_preprocess_msg = (
"Preprocessing disabled because there are no files "
"linked with the Raw Data")
else:
if prep_template.data_type() in TARGET_GENE_DATA_TYPES:
raw_forward_fps = [fp for _, fp, ftype in raw_data_files
if ftype == 'raw_forward_seqs']
key = ('demultiplex_multiple' if len(raw_forward_fps) > 1
else 'demultiplex')
missing_cols = prep_template.check_restrictions(
[PREP_TEMPLATE_COLUMNS_TARGET_GENE[key]])
if rd_ft == 'per_sample_FASTQ':
show_preprocess_btn = 'run_prefix' not in missing_cols
else:
show_preprocess_btn = len(missing_cols) == 0
no_preprocess_msg = None
if not show_preprocess_btn:
no_preprocess_msg = (
"Preprocessing disabled due to missing columns in "
"the prep template: %s" % ', '.join(missing_cols))
preprocessing_status = prep_template.preprocessing_status
return self.render_string(
"study_description_templates/prep_template_info_tab.html",
pt_id=prep_template.id,
study_id=study.id,
raw_data=raw_data_id,
current_template_fp=current_template_fp,
current_qiime_fp=current_qiime_fp,
show_old_templates=show_old_templates,
old_templates=old_templates,
show_old_qiime_fps=show_old_qiime_fps,
old_qiime_fps=old_qiime_fps,
filetypes=filetypes,
files=files,
other_studies_rd=other_studies_rd,
prep_template=prep_template,
study=study,
ena_terms=ena_terms,
user_defined_terms=user_defined_terms,
investigation_type=prep_template.investigation_type,
is_editable=is_editable,
preprocess_options=preprocess_options,
preprocessed_data=preprocessed_data,
preprocessing_status=preprocessing_status,
show_preprocess_btn=show_preprocess_btn,
no_preprocess_msg=no_preprocess_msg)
def render(self, study):
study_info = study.info
id = study.id
abstract = study_info['study_abstract']
description = study_info['study_description']
publications = []
for doi, pmid in study.publications:
if doi is not None:
publications.append(doi_linkifier([doi]))
if pmid is not None:
publications.append(pubmed_linkifier([pmid]))
publications = ", ".join(publications)
princ_inv = StudyPerson(study_info['principal_investigator_id'])
pi_link = study_person_linkifier((princ_inv.email, princ_inv.name))
number_samples_promised = study_info['number_samples_promised']
number_samples_collected = study_info['number_samples_collected']
metadata_complete = study_info['metadata_complete']
data_types = sorted(viewitems(get_data_types()), key=itemgetter(1))
# Retrieve the files from the uploads folder, so the user can choose
# the sample template of the study. Filter them to only include the
# ones that ends with 'txt' or 'tsv'.
files = [
f for _, f in get_files_from_uploads_folders(str(study.id))
if f.endswith(('txt', 'tsv'))
]
# If the sample template exists, retrieve all its filepaths
if SampleTemplate.exists(study.id):
sample_templates = SampleTemplate(study.id).get_filepaths()
else:
# If the sample template does not exist, just pass an empty list
sample_templates = []
# Check if the request came from a local source
is_local_request = is_localhost(self.request.headers['host'])
# The user can choose the sample template only if the study is
# sandboxed or the current user is an admin
show_select_sample = (study.status == 'sandbox'
or self.current_user.level == 'admin')
# EBI information
ebi_status = study.ebi_submission_status
ebi_accession = study.ebi_study_accession
if ebi_accession:
ebi_accession = (EBI_LINKIFIER.format(ebi_accession))
return self.render_string(
"study_description_templates/study_information_tab.html",
abstract=abstract,
description=description,
id=id,
publications=publications,
principal_investigator=pi_link,
number_samples_promised=number_samples_promised,
number_samples_collected=number_samples_collected,
metadata_complete=metadata_complete,
show_select_sample=show_select_sample,
files=files,
study_id=study.id,
sample_templates=sample_templates,
is_local_request=is_local_request,
data_types=data_types,
ebi_status=ebi_status,
ebi_accession=ebi_accession)
def render(self, study_id, preprocessed_data):
user = self.current_user
ppd_id = preprocessed_data.id
vamps_status = preprocessed_data.is_submitted_to_vamps
filepaths = preprocessed_data.filepaths
is_local_request = is_localhost(self.request.headers['host'])
show_ebi_btn = user.level == "admin"
processing_status, processing_status_msg = \
get_artifact_processing_status(preprocessed_data)
processed_data = sorted([pd.id for pd in preprocessed_data.children])
# 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']
# ppd can only have 1 prep template
prep_template = preprocessed_data.prep_templates[0]
# this block might seem wrong but is here due to a possible
# pathological case that we used to have in the system: preprocessed
# data without valid prep_templates
prep_templates = preprocessed_data.prep_templates
if len(prep_templates) == 1:
prep_template_id = prep_template.id
raw_data_id = prep_template.artifact.id
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 Command(3).default_parameter_sets
}
# We just need to provide an ID for the default parameters,
# so we can initialize the interface
default_params = min(process_params.keys())
ebi_link = None
if preprocessed_data.is_submitted_to_ebi:
ebi_link = EBI_LINKIFIER.format(
Study(study_id).ebi_study_accession)
return self.render_string(
"study_description_templates/preprocessed_data_info_tab.html",
ppd_id=ppd_id,
show_ebi_btn=show_ebi_btn,
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.id,
processing_status=processing_status,
processing_status_msg=processing_status_msg,
processed_data=processed_data,
ebi_link=ebi_link)
def render(self, study, prep_template, full_access, ena_terms,
user_defined_terms):
user = self.current_user
is_local_request = is_localhost(self.request.headers['host'])
template_fps = []
qiime_fps = []
# Unfortunately, both the prep template and the qiime mapping files
# have the sample type. The way to differentiate them is if we have
# the substring 'qiime' in the basename
for id_, fp in prep_template.get_filepaths():
if 'qiime' in basename(fp):
qiime_fps.append(
download_link_or_path(is_local_request, fp, id_,
'Qiime mapping'))
else:
template_fps.append(
download_link_or_path(is_local_request, fp, id_,
'Prep template'))
# Since get_filepaths returns the paths sorted from newest to oldest,
# the first in both list is the latest one
current_template_fp = template_fps[0]
current_qiime_fp = qiime_fps[0]
if len(template_fps) > 1:
show_old_templates = True
old_templates = template_fps[1:]
else:
show_old_templates = False
old_templates = None
if len(qiime_fps) > 1:
show_old_qiime_fps = True
old_qiime_fps = qiime_fps[1:]
else:
show_old_qiime_fps = False
old_qiime_fps = None
filetypes = sorted(((ft, ft_id, fp_type_by_ft[ft])
for ft, ft_id in viewitems(get_artifact_types())),
key=itemgetter(1))
files = [f for _, f in get_files_from_uploads_folders(str(study.id))]
other_studies_rd = sorted(viewitems(_get_accessible_raw_data(user)))
# A prep template can be modified if its status is sandbox
is_editable = prep_template.status == 'sandbox'
raw_data = prep_template.artifact
preprocess_options = []
preprocessed_data = None
show_preprocess_btn = True
no_preprocess_msg = None
preprocessing_status = 'Not processed'
preprocessing_status_msg = ""
if raw_data:
raw_data_ft = raw_data.artifact_type
# If the prep template has a raw data associated, it can be
# preprocessed. Retrieve the pre-processing parameters
# Hardcoding the command ids until the interface is refactored
if raw_data_ft in ('SFF', 'FASTA'):
param_iter = Command(2).default_parameter_sets
elif raw_data_ft == 'FASTQ':
param_iter = [
p for p in Command(1).default_parameter_sets
if p.values['barcode_type'] != 'not-barcoded'
]
elif raw_data_ft == 'per_sample_FASTQ':
param_iter = [
p for p in Command(1).default_parameter_sets
if p.values['barcode_type'] == 'not-barcoded'
]
else:
raise NotImplementedError(
"Pre-processing of %s files currently not supported." %
raw_data_ft)
preprocess_options = []
for param in param_iter:
text = ("<b>%s:</b> %s" % (k, v)
for k, v in viewitems(param.values))
preprocess_options.append(
(param.id, param.name, '<br>'.join(text)))
preprocessed_data = raw_data.children
# Check if the template have all the required columns for
# preprocessing
raw_data_files = raw_data.filepaths
if len(raw_data_files) == 0:
show_preprocess_btn = False
no_preprocess_msg = (
"Preprocessing disabled because there are no files "
"linked with the Raw Data")
else:
if prep_template.data_type() in TARGET_GENE_DATA_TYPES:
raw_forward_fps = [
fp for _, fp, ftype in raw_data_files
if ftype == 'raw_forward_seqs'
]
key = ('demultiplex_multiple'
if len(raw_forward_fps) > 1 else 'demultiplex')
missing_cols = prep_template.check_restrictions(
[PREP_TEMPLATE_COLUMNS_TARGET_GENE[key]])
if raw_data_ft == 'per_sample_FASTQ':
show_preprocess_btn = 'run_prefix' not in missing_cols
else:
show_preprocess_btn = len(missing_cols) == 0
no_preprocess_msg = None
if not show_preprocess_btn:
no_preprocess_msg = (
"Preprocessing disabled due to missing columns in "
"the prep template: %s" % ', '.join(missing_cols))
# Check the processing status
preprocessing_status, preprocessing_status_msg = \
get_artifact_processing_status(raw_data)
ebi_link = None
if prep_template.is_submitted_to_ebi:
ebi_link = EBI_LINKIFIER.format(study.ebi_study_accession)
return self.render_string(
"study_description_templates/prep_template_info_tab.html",
raw_data=raw_data,
current_template_fp=current_template_fp,
current_qiime_fp=current_qiime_fp,
show_old_templates=show_old_templates,
old_templates=old_templates,
show_old_qiime_fps=show_old_qiime_fps,
old_qiime_fps=old_qiime_fps,
filetypes=filetypes,
files=files,
other_studies_rd=other_studies_rd,
prep_template=prep_template,
study=study,
ena_terms=ena_terms,
user_defined_terms=user_defined_terms,
investigation_type=prep_template.investigation_type,
is_editable=is_editable,
preprocess_options=preprocess_options,
preprocessed_data=preprocessed_data,
preprocessing_status=preprocessing_status,
preprocessing_status_message=preprocessing_status_msg,
show_preprocess_btn=show_preprocess_btn,
no_preprocess_msg=no_preprocess_msg,
ebi_link=ebi_link)
def render(self, study_id, preprocessed_data):
user = self.current_user
ppd_id = preprocessed_data.id
vamps_status = preprocessed_data.is_submitted_to_vamps
filepaths = preprocessed_data.filepaths
is_local_request = is_localhost(self.request.headers['host'])
show_ebi_btn = user.level == "admin"
processing_status, processing_status_msg = \
get_artifact_processing_status(preprocessed_data)
processed_data = sorted([pd.id for pd in preprocessed_data.children])
# 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']
# ppd can only have 1 prep template
prep_template = preprocessed_data.prep_templates[0]
# this block might seem wrong but is here due to a possible
# pathological case that we used to have in the system: preprocessed
# data without valid prep_templates
prep_templates = preprocessed_data.prep_templates
if len(prep_templates) == 1:
prep_template_id = prep_template.id
raw_data_id = prep_template.artifact.id
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 Command(3).default_parameter_sets}
# We just need to provide an ID for the default parameters,
# so we can initialize the interface
default_params = min(process_params.keys())
ebi_link = None
if preprocessed_data.is_submitted_to_ebi:
ebi_link = EBI_LINKIFIER.format(
Study(study_id).ebi_study_accession)
return self.render_string(
"study_description_templates/preprocessed_data_info_tab.html",
ppd_id=ppd_id,
show_ebi_btn=show_ebi_btn,
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.id,
processing_status=processing_status,
processing_status_msg=processing_status_msg,
processed_data=processed_data,
ebi_link=ebi_link)