def _find_snp_position(snp_track, name):
if snp_track is None:
query = ElasticQuery.query_match("id", name)
elastic = Search(query, idx=ElasticSettings.idx('MARKER'))
snpResult = elastic.get_json_response()
if(len(snpResult['hits']['hits'])) > 0:
snp = snpResult['hits']['hits'][0]['_source']
chrom = snp['seqid'].replace('chr', "")
position = snp['start']
return {'chr': chrom, 'start': (position-1), 'end': position, 'name': name}
else:
mo = re.match(r"(.*)-(.*)", snp_track)
(group, track) = mo.group(1, 2)
try:
snp_track_idx = ElasticSettings.idx('CP_STATS_'+group.upper(), snp_track.upper())
except SettingsError:
snp_track_idx = ElasticSettings.idx('CP_STATS_'+group.upper())+"/"+track
query = ElasticQuery.query_match("name", name)
elastic = Search(query, idx=snp_track_idx)
snpResult = elastic.get_json_response()
if(len(snpResult['hits']['hits'])) > 0:
snp = snpResult['hits']['hits'][0]['_source']
chrom = snp['seqid'].replace('chr', "")
position = snp['start']
return {'chr': chrom, 'start': (position-1), 'end': position, 'name': name}
return {'error': 'Marker '+name+' does not exist in the currently selected dataset'}
def _find_snp_position(snp_track, name):
if snp_track is None:
query = ElasticQuery.query_match("id", name)
elastic = Search(query, idx=ElasticSettings.idx('MARKER'))
snpResult = elastic.get_json_response()
if(len(snpResult['hits']['hits'])) > 0:
snp = snpResult['hits']['hits'][0]['_source']
chrom = snp['seqid'].replace('chr', "")
position = snp['start']
return {'chr': chrom, 'start': (position-1), 'end': position, 'name': name}
else:
mo = re.match(r"(.*)-(.*)", snp_track)
(group, track) = mo.group(1, 2)
try:
snp_track_idx = ElasticSettings.idx('CP_STATS_'+group.upper(), snp_track.upper())
except SettingsError:
snp_track_idx = ElasticSettings.idx('CP_STATS_'+group.upper())+"/"+track
query = ElasticQuery.query_match("name", name)
elastic = Search(query, idx=snp_track_idx)
snpResult = elastic.get_json_response()
if(len(snpResult['hits']['hits'])) > 0:
snp = snpResult['hits']['hits'][0]['_source']
chrom = snp['seqid'].replace('chr', "")
position = snp['start']
return {'chr': chrom, 'start': (position-1), 'end': position, 'name': name}
return {'error': 'Marker '+name+' does not exist in the currently selected dataset'}
def filter_queryset(self, request, queryset, view):
''' Override this method to request just the documents required from elastic. '''
q_size = view.paginator.get_limit(request)
q_from = view.paginator.get_offset(request)
filterable = getattr(view, 'filter_fields', [])
filters = dict([(k, v) for k, v in request.GET.items()
if k in filterable])
search_filters = self._build_filters(filters=filters)
if search_filters is not None:
q = ElasticQuery.filtered(Query.match_all(), search_filters)
else:
q = ElasticQuery(Query.match_all())
s = Search(search_query=q,
idx=getattr(view, 'idx'),
size=q_size,
search_from=q_from)
json_results = s.get_json_response()
results = []
for result in json_results['hits']['hits']:
new_obj = ElasticObject(initial=result['_source'])
new_obj.uuid = result['_id']
results.append(new_obj)
view.es_count = json_results['hits']['total']
return results
def filter_queryset(self, request, queryset, view):
''' Override this method to request just the documents required from elastic. '''
q_size = view.paginator.get_limit(request)
q_from = view.paginator.get_offset(request)
filterable = getattr(view, 'filter_fields', [])
print(filterable)
print(request)
filters = dict([(k, v) for k, v in request.GET.items() if k in filterable])
criteria_idx = self._get_index(filters.get('feature_type', 'GENE_CRITERIA'))
idx = criteria_idx
if type(criteria_idx) == list:
idx = ','.join(ElasticSettings.idx(name) for name in criteria_idx)
else:
idx = ElasticSettings.idx(criteria_idx)
q = ElasticQuery(Query.match_all())
s = Search(search_query=q, idx=idx, size=q_size, search_from=q_from)
json_results = s.get_json_response()
results = []
for result in json_results['hits']['hits']:
new_obj = ElasticObject(initial=result['_source'])
new_obj.uuid = result['_id']
new_obj.criteria_type = result['_type']
results.append(new_obj)
view.es_count = json_results['hits']['total']
return results
def get_object(self):
q = ElasticQuery(Query.ids(self.kwargs[self.lookup_field]))
s = Search(search_query=q, idx=getattr(self, 'idx'))
try:
result = s.get_json_response()['hits']['hits'][0]
obj = ElasticObject(initial=result['_source'])
obj.uuid = result['_id']
# May raise a permission denied
self.check_object_permissions(self.request, obj)
return obj
except (TypeError, ValueError, IndexError):
raise Http404
def get_object(self):
q = ElasticQuery(Query.ids(self.kwargs[self.lookup_field]))
s = Search(search_query=q, idx=getattr(self, 'idx'))
try:
result = s.get_json_response()['hits']['hits'][0]
obj = ElasticObject(initial=result['_source'])
obj.uuid = result['_id']
obj.criteria_type = result['_type']
# May raise a permission denied
self.check_object_permissions(self.request, obj)
return obj
except (TypeError, ValueError, IndexError):
raise Http404
def post(self, request, *args, **kwargs):
ens_id = self.request.POST.get('ens_id')
marker = self.request.POST.get('marker')
markers = self.request.POST.getlist('markers[]')
if ens_id:
sfilter = Filter(Query.query_string(ens_id, fields=["genes"]).query_wrap())
elif marker:
sfilter = Filter(Query.query_string(marker, fields=["marker"]).query_wrap())
elif markers:
sfilter = Filter(Query.query_string(' '.join(markers), fields=["marker"]).query_wrap())
query = ElasticQuery.filtered(Query.match_all(), sfilter)
elastic = Search(query, idx=ElasticSettings.idx('REGION', 'STUDY_HITS'), size=500)
study_hits = elastic.get_json_response()['hits']
ens_ids = []
pmids = []
for hit in study_hits['hits']:
if 'pmid' in hit['_source']:
pmids.append(hit['_source']['pmid'])
if 'genes' in hit['_source']:
for ens_id in hit['_source']['genes']:
ens_ids.append(ens_id)
docs = utils.get_gene_docs_by_ensembl_id(ens_ids, ['symbol'])
pub_docs = PublicationDocument.get_pub_docs_by_pmid(pmids, sources=['authors.name', 'journal'])
for hit in study_hits['hits']:
genes = {}
if 'genes' in hit['_source']:
for ens_id in hit['_source']['genes']:
try:
genes[ens_id] = getattr(docs[ens_id], 'symbol')
except KeyError:
genes = {ens_id: ens_id}
hit['_source']['genes'] = genes
if 'pmid' in hit['_source']:
pmid = hit['_source']['pmid']
try:
authors = getattr(pub_docs[pmid], 'authors')
journal = getattr(pub_docs[pmid], 'journal')
hit['_source']['pmid'] = \
{'pmid': pmid,
'author': authors[0]['name'].rsplit(None, 1)[-1] if authors else "",
'journal': journal}
except KeyError:
hit['_source']['pmid'] = {'pmid': pmid}
return JsonResponse(study_hits)
def _build_frags_query(frags_idx, chrom, segmin, segmax):
query = ElasticQuery.filtered(Query.terms("seqid", [chrom, str("chr"+chrom)]),
Filter(RangeQuery("end", gte=segmin, lte=segmax)),
utils.bedFields)
fragsQuery = Search(search_query=query, search_from=0, size=10000, idx=frags_idx)
# fragsResult = fragsQuery.get_result()
# frags = fragsResult['data']
fragsResult = fragsQuery.get_json_response()
frags = []
for hit in fragsResult['hits']['hits']:
frags.append(hit['_source'])
frags = utils.makeRelative(int(segmin), int(segmax), ['start', 'end'], frags)
return frags
def _build_frags_query(frags_idx, chrom, segmin, segmax):
query = ElasticQuery.filtered(Query.terms("seqid", [chrom, str("chr"+chrom)]),
Filter(RangeQuery("end", gte=segmin, lte=segmax)),
utils.bedFields)
fragsQuery = Search(search_query=query, search_from=0, size=10000, idx=frags_idx)
# fragsResult = fragsQuery.get_result()
# frags = fragsResult['data']
fragsResult = fragsQuery.get_json_response()
frags = []
for hit in fragsResult['hits']['hits']:
frags.append(hit['_source'])
frags = utils.makeRelative(int(segmin), int(segmax), ['start', 'end'], frags)
return frags
def get_criteria_details(cls, feature_id, idx, idx_type, criteria_id=None):
'''Function to get criteria details for a given feature_id. If criteria_id is given,
the result is restricted to that criteria
@type feature_id: string
@keyword feature_id: Id of the feature (gene => gene_id, region=>region_id)
@type criteria_id: string
@keyword criteria_id: criteria_id eg: cand_gene_in_study, gene_in_region
@type idx: string
@param idx: name of the index
@type idx_type: string
@param idx_type: name of the idx type, each criteria is an index type
'''
query = ElasticQuery(Query.term("qid", feature_id))
search = Search(query, idx=idx, idx_type=idx_type)
# elastic_docs = search.search().docs
criteria_hits = search.get_json_response()['hits']
return(criteria_hits)
def _build_hic_query(query, targetIdx, segmin=0, segmax=0):
hic = []
hicElastic = Search(query, idx=ElasticSettings.idx('CP_TARGET_'+targetIdx), search_from=0, size=2000)
# hicResult = hicElastic.get_result()
hicResult = hicElastic.get_json_response()
if "error" in hicResult:
return {'error': 'No search results found. Please try again.'}, segmin, segmax
if len(hicResult['hits']['hits']) > 0:
for hit in hicResult['hits']['hits']:
hic.append(hit['_source'])
if segmin == 0 or segmax == 0:
(segmin, segmax) = utils.segCoords(hic)
extension = int(0.05*(segmax-segmin))
segmin = segmin - extension
segmax = segmax + extension
hic = utils.makeRelative(int(segmin), int(segmax), ['baitStart', 'baitEnd', 'oeStart', 'oeEnd'], hic)
return hic, segmin, segmax
def _build_hic_query(query, targetIdx, segmin=0, segmax=0):
hic = []
hicElastic = Search(query, idx=ElasticSettings.idx('CP_TARGET_'+targetIdx), search_from=0, size=2000)
# hicResult = hicElastic.get_result()
hicResult = hicElastic.get_json_response()
if "error" in hicResult:
return {'error': 'No search results found. Please try again.'}, segmin, segmax
if len(hicResult['hits']['hits']) > 0:
for hit in hicResult['hits']['hits']:
hic.append(hit['_source'])
if segmin == 0 or segmax == 0:
(segmin, segmax) = utils.segCoords(hic)
extension = int(0.05*(segmax-segmin))
segmin = segmin - extension
segmax = segmax + extension
hic = utils.makeRelative(int(segmin), int(segmax), ['baitStart', 'baitEnd', 'oeStart', 'oeEnd'], hic)
return hic, segmin, segmax
def _build_exon_query(chrom, segmin, segmax, genes):
# get exonic structure for genes in this section
geneExons = dict()
query_bool = BoolQuery()
query_bool.must([Query.term("seqid", chrom)])
if len(genes) > 0:
for g in genes:
query = ElasticQuery.filtered_bool(Query.query_string(g["gene_id"], fields=["name"]),
query_bool, sources=utils.snpFields)
elastic = Search(query, idx=getattr(chicp_settings, 'CP_GENE_IDX')+'/exons/', search_from=0, size=2000)
# result = elastic.get_result()
# exons = result['data']
result = elastic.get_json_response()
exons = []
for hit in result['hits']['hits']:
exons.append(hit['_source'])
exons = utils.makeRelative(int(segmin), int(segmax), ['start', 'end'], exons)
geneExons[g["gene_id"]] = sorted(exons, key=operator.itemgetter("start"))
return geneExons
def _build_exon_query(chrom, segmin, segmax, genes):
# get exonic structure for genes in this section
geneExons = dict()
query_bool = BoolQuery()
query_bool.must([Query.term("seqid", chrom)])
if len(genes) > 0:
for g in genes:
query = ElasticQuery.filtered_bool(Query.query_string(g["gene_id"], fields=["name"]),
query_bool, sources=utils.snpFields)
elastic = Search(query, idx=getattr(chicp_settings, 'CP_GENE_IDX')+'/exons/', search_from=0, size=2000)
# result = elastic.get_result()
# exons = result['data']
result = elastic.get_json_response()
exons = []
for hit in result['hits']['hits']:
exons.append(hit['_source'])
exons = utils.makeRelative(int(segmin), int(segmax), ['start', 'end'], exons)
geneExons[g["gene_id"]] = sorted(exons, key=operator.itemgetter("start"))
return geneExons
def interaction_details(request):
""" Get interaction details for a given ensembl ID. """
ens_id = request.POST.get("ens_id")
query = ElasticQuery.has_parent("gene", Query.ids(ens_id))
elastic = Search(query, idx=ElasticSettings.idx("GENE", "INTERACTIONS"), size=500)
interaction_hits = elastic.get_json_response()["hits"]
ens_ids = []
for hit in interaction_hits["hits"]:
for interactor in hit["_source"]["interactors"]:
ens_ids.append(interactor["interactor"])
docs = _get_gene_docs_by_ensembl_id(ens_ids, ["symbol"])
for hit in interaction_hits["hits"]:
for interactor in hit["_source"]["interactors"]:
iid = interactor["interactor"]
try:
interactor["symbol"] = getattr(docs[iid], "symbol")
except KeyError:
interactor["symbol"] = iid
return JsonResponse(interaction_hits)
def interaction_details(request):
''' Get interaction details for a given ensembl ID. '''
ens_id = request.POST.get('ens_id')
query = ElasticQuery.has_parent('gene', Query.ids(ens_id))
elastic = Search(query, idx=ElasticSettings.idx('GENE', 'INTERACTIONS'), size=500)
interaction_hits = elastic.get_json_response()['hits']
ens_ids = []
for hit in interaction_hits['hits']:
for interactor in hit['_source']['interactors']:
ens_ids.append(interactor['interactor'])
docs = utils.get_gene_docs_by_ensembl_id(ens_ids, ['symbol'])
for hit in interaction_hits['hits']:
for interactor in hit['_source']['interactors']:
iid = interactor['interactor']
try:
interactor['symbol'] = getattr(docs[iid], 'symbol')
except KeyError:
interactor['symbol'] = iid
return JsonResponse(interaction_hits)
def studies_details(request):
""" Get studies for a given ensembl ID. """
ens_id = request.POST.get("ens_id")
sfilter = Filter(Query.query_string(ens_id, fields=["genes"]).query_wrap())
query = ElasticQuery.filtered(Query.match_all(), sfilter)
elastic = Search(query, idx=ElasticSettings.idx("REGION", "STUDY_HITS"), size=500)
study_hits = elastic.get_json_response()["hits"]
ens_ids = []
pmids = []
for hit in study_hits["hits"]:
if "pmid" in hit["_source"]:
pmids.append(hit["_source"]["pmid"])
for ens_id in hit["_source"]["genes"]:
ens_ids.append(ens_id)
docs = _get_gene_docs_by_ensembl_id(ens_ids, ["symbol"])
pub_docs = _get_pub_docs_by_pmid(pmids, sources=["authors.name", "journal"])
for hit in study_hits["hits"]:
genes = {}
for ens_id in hit["_source"]["genes"]:
try:
genes[ens_id] = getattr(docs[ens_id], "symbol")
except KeyError:
genes = {ens_id: ens_id}
hit["_source"]["genes"] = genes
if "pmid" in hit["_source"]:
pmid = hit["_source"]["pmid"]
try:
authors = getattr(pub_docs[pmid], "authors")
journal = getattr(pub_docs[pmid], "journal")
hit["_source"]["pmid"] = {
"pmid": pmid,
"author": authors[0]["name"].rsplit(None, 1)[-1],
"journal": journal,
}
except KeyError:
hit["_source"]["pmid"] = {"pmid": pmid}
return JsonResponse(study_hits)
def genesets_details(request):
''' Get pathway gene sets for a given ensembl ID. '''
ens_id = request.POST.get('ens_id')
geneset_filter = Filter(Query.query_string(ens_id, fields=["gene_sets"]).query_wrap())
query = ElasticQuery.filtered(Query.match_all(), geneset_filter)
elastic = Search(query, idx=ElasticSettings.idx('GENE', 'PATHWAY'), size=500)
genesets_hits = elastic.get_json_response()['hits']
ens_ids = []
for hit in genesets_hits['hits']:
for ens_id in hit['_source']['gene_sets']:
ens_ids.append(ens_id)
docs = utils.get_gene_docs_by_ensembl_id(ens_ids, ['symbol'])
for hit in genesets_hits['hits']:
genesets = {}
for ens_id in hit['_source']['gene_sets']:
try:
genesets[ens_id] = getattr(docs[ens_id], 'symbol')
except KeyError:
genesets[ens_id] = ens_id
hit['_source']['gene_sets'] = genesets
return JsonResponse(genesets_hits)
def genesets_details(request):
""" Get pathway gene sets for a given ensembl ID. """
ens_id = request.POST.get("ens_id")
geneset_filter = Filter(Query.query_string(ens_id, fields=["gene_sets"]).query_wrap())
query = ElasticQuery.filtered(Query.match_all(), geneset_filter)
elastic = Search(query, idx=ElasticSettings.idx("GENE", "PATHWAY"), size=500)
genesets_hits = elastic.get_json_response()["hits"]
ens_ids = []
for hit in genesets_hits["hits"]:
for ens_id in hit["_source"]["gene_sets"]:
ens_ids.append(ens_id)
docs = _get_gene_docs_by_ensembl_id(ens_ids, ["symbol"])
for hit in genesets_hits["hits"]:
genesets = {}
for ens_id in hit["_source"]["gene_sets"]:
try:
genesets[ens_id] = getattr(docs[ens_id], "symbol")
except KeyError:
genesets[ens_id] = ens_id
hit["_source"]["gene_sets"] = genesets
return JsonResponse(genesets_hits)
def _build_snp_query(snp_track, chrom, segmin, segmax):
snps = []
snpMeta = {}
maxScore = -1
if snp_track and snp_track != 'None':
# get SNPs based on this segment
mo = re.match(r"(.*)-(.*)", snp_track)
(group, track) = mo.group(1, 2)
try:
snp_track_idx = ElasticSettings.idx('CP_STATS_'+group.upper(), snp_track.upper())
except SettingsError:
snp_track_idx = ElasticSettings.idx('CP_STATS_'+group.upper())+"/"+track
query = ElasticQuery.filtered(Query.terms("seqid", [chrom, str("chr"+chrom)]),
Filter(RangeQuery("end", gte=segmin, lte=segmax)),
utils.snpFields)
snpQuery = Search(search_query=query, search_from=0, size=10000, idx=snp_track_idx)
# snpResult = snpQuery.get_result()
# snps = snpResult['data']
snpResult = snpQuery.get_json_response()
snps = []
for hit in snpResult['hits']['hits']:
snps.append(hit['_source'])
snps = utils.makeRelative(int(segmin), int(segmax), ['start', 'end'], snps)
data_type = ElasticSettings.get_label('CP_STATS_'+group.upper(), None, "data_type")
snpSettings = getattr(chicp_settings, 'STUDY_DEFAULTS').get(data_type)
for s in snps:
if float(s['score']) > maxScore:
maxScore = float(s['score'])
snpSettings['max'] = maxScore
snpMeta = snpSettings
return snps, snpMeta
def _build_snp_query(snp_track, chrom, segmin, segmax):
snps = []
snpMeta = {}
maxScore = -1
if snp_track and snp_track != 'None':
# get SNPs based on this segment
mo = re.match(r"(.*)-(.*)", snp_track)
(group, track) = mo.group(1, 2)
try:
snp_track_idx = ElasticSettings.idx('CP_STATS_'+group.upper(), snp_track.upper())
except SettingsError:
snp_track_idx = ElasticSettings.idx('CP_STATS_'+group.upper())+"/"+track
query = ElasticQuery.filtered(Query.terms("seqid", [chrom, str("chr"+chrom)]),
Filter(RangeQuery("end", gte=segmin, lte=segmax)),
utils.snpFields)
snpQuery = Search(search_query=query, search_from=0, size=10000, idx=snp_track_idx)
# snpResult = snpQuery.get_result()
# snps = snpResult['data']
snpResult = snpQuery.get_json_response()
snps = []
for hit in snpResult['hits']['hits']:
snps.append(hit['_source'])
snps = utils.makeRelative(int(segmin), int(segmax), ['start', 'end'], snps)
data_type = ElasticSettings.get_label('CP_STATS_'+group.upper(), None, "data_type")
snpSettings = getattr(chicp_settings, 'STUDY_DEFAULTS').get(data_type)
for s in snps:
if float(s['score']) > maxScore:
maxScore = float(s['score'])
snpSettings['max'] = maxScore
snpMeta = snpSettings
return snps, snpMeta
def get_all_criteria_disease_tags(cls, qids, idx, idx_type):
if qids is None:
query = ElasticQuery(Query.match_all(), sources=['disease_tags', 'qid'])
# search = Search(query, idx=idx, idx_type=idx_type, size=30000)
else:
query = ElasticQuery(Query.terms("qid", qids), sources=['disease_tags', 'qid'])
# search = Search(query, idx=idx, idx_type=idx_type)
search = Search(query, idx=idx, idx_type=idx_type)
criteria_hits = search.get_json_response()['hits']
hits = criteria_hits['hits']
meta_info = {}
criteria_disease_tags = {}
for hit in hits:
if idx == hit['_index']:
qid = hit['_source']['qid']
meta_desc = cls.get_meta_desc(idx, [hit['_type']])
meta_info[hit['_type']] = meta_desc[idx][hit['_type']]
criteria_desc = hit['_type']
if qid not in criteria_disease_tags:
criteria_disease_tags[qid] = {}
criteria_disease_tags[qid][criteria_desc] = hit['_source']['disease_tags']
disease_tags_all = []
for fid, fvalue in criteria_disease_tags.items():
disease_tags_all = cls.get_all_criteria_disease_tags_aggregated(qid, fvalue)
criteria_disease_tags[fid]['all'] = disease_tags_all
criteria_disease_tags[fid]['meta_info'] = meta_info
return(criteria_disease_tags)
def _add_diseases():
''' Add diseases dictionary to a context '''
query = ElasticQuery(Query.match_all())
elastic_disease = Search(search_query=query, size=100, idx='disease')
return elastic_disease.get_json_response()['hits']['hits']
def pub_details(request):
''' Get PMID details. '''
pmids = request.POST.getlist("pmids[]")
query = ElasticQuery(Query.ids(pmids))
elastic = Search(query, idx=ElasticSettings.idx('PUBLICATION', 'PUBLICATION'), size=len(pmids))
return JsonResponse(elastic.get_json_response()['hits'])
def _add_diseases():
''' Add diseases dictionary to a context '''
query = ElasticQuery(Query.match_all())
elastic_disease = Search(search_query=query, size=100, idx='disease')
return elastic_disease.get_json_response()['hits']['hits']
def filter_queryset(self, request, queryset, view):
''' Override this method to request just the documents required from elastic. '''
q_size = view.paginator.get_limit(request)
q_from = view.paginator.get_offset(request)
filterable = getattr(view, 'filter_fields', [])
filters = dict([(k, v) for k, v in request.GET.items() if k in filterable])
criteria_idx = self._get_index(filters.get('feature_type', 'GENE_CRITERIA'))
feature_type = filters.get('feature_type')
feature_id = filters.get('feature_id')
aggregate = filters.get('aggregate')
detail = filters.get('detail')
idx = criteria_idx
if type(criteria_idx) == list:
idx = ','.join(ElasticSettings.idx(name) for name in criteria_idx)
else:
idx = ElasticSettings.idx(criteria_idx)
results = []
if feature_id and aggregate == 'true':
disease_doc_tags = Criteria.get_disease_tags(feature_id, idx=idx)
disease_tags = [getattr(d, 'code') for d in disease_doc_tags]
new_obj = ElasticObject()
new_obj.qid = feature_id
new_obj.disease_tags = disease_tags
new_obj.criteria_type = None
results.append(new_obj)
return results
elif feature_id and detail == 'true':
(idx, idx_types) = Criteria.get_feature_idx_n_idxtypes(feature_type.lower())
criteria_details = Criteria.get_criteria_details(feature_id, idx=idx, idx_type=idx_types)
criteria_list = idx_types.split(',')
criteria_details_expanded = Criteria.add_meta_info(idx, criteria_list, criteria_details)
feature_details = self._get_feature_details(criteria_details_expanded)
for criteria, details in feature_details.items():
print(criteria)
new_obj = ElasticObject()
new_obj.qid = details['qid']
new_obj.criteria_type = criteria
disease_tags = details['disease_tags']
fdetails = list(details['fdetails'])
print('+++++++++++++++')
print(disease_tags)
print(fdetails)
print('+++++++++++++++')
new_obj.disease_tags = disease_tags
new_obj.feature_details = fdetails
results.append(new_obj)
return results
else:
q = ElasticQuery(Query.match_all())
s = Search(search_query=q, idx=idx, size=q_size, search_from=q_from)
json_results = s.get_json_response()
for result in json_results['hits']['hits']:
new_obj = ElasticObject(initial=result['_source'])
new_obj.uuid = result['_id']
new_obj.criteria_type = result['_type']
results.append(new_obj)
view.es_count = json_results['hits']['total']
return results
def pub_details(request):
""" Get PMID details. """
pmids = request.POST.getlist("pmids[]")
query = ElasticQuery(Query.ids(pmids))
elastic = Search(query, idx=ElasticSettings.idx("PUBLICATION", "PUBLICATION"), size=len(pmids))
return JsonResponse(elastic.get_json_response()["hits"])
