def apply_filter(query_value, filters, ignore_bbox=False, only_site=False):
"""
Apply filter and do the search to biological collection
record and location site
:param query_value: str
:param filters: dict
:param ignore_bbox: bool
:returns:
- collection_results : results from bio collection record
- site_results : results from location site
- fuzzy_search : if results from search is fuzzy search
"""
fuzzy_search = False
user_boundaries = None
filter_mode = False
sqs = SearchQuerySet()
settings.ELASTIC_MIN_SCORE = 0
# All filters
taxon = filters.get('taxon', None)
bbox = filters.get('bbox', None)
query_collector = filters.get('collector', None)
boundary = filters.get('boundary', None)
user_boundary = filters.get('userBoundary', None)
query_category = filters.get('category', None)
reference_category = filters.get('referenceCategory', None)
reference = filters.get('reference', None)
year_from = filters.get('yearFrom', None)
year_to = filters.get('yearTo', None)
months = filters.get('months', None)
site_id = filters.get('siteId', None)
endemic = filters.get('endemic', None)
conservation_status = filters.get('conservationStatus', None)
river_catchments = filters.get('riverCatchment', None)
if (
taxon or
query_collector or
boundary or user_boundary or
query_category or reference_category or
year_from or year_to or
months or reference or
conservation_status or
river_catchments or
site_id or endemic):
filter_mode = True
if query_value:
clean_query = sqs.query.clean(query_value)
results = sqs.filter(
SQ(original_species_name_exact__contains=clean_query) |
SQ(taxon_scientific_name_exact__contains=clean_query) |
SQ(vernacular_names__contains=clean_query),
validated=True
).models(BiologicalCollectionRecord)
if len(results) > 0:
fuzzy_search = False
else:
fuzzy_search = True
# Set min score bigger for fuzzy search
settings.ELASTIC_MIN_SCORE = 2
results = sqs.filter(
SQ(original_species_name=clean_query),
validated=True
).models(BiologicalCollectionRecord)
settings.ELASTIC_MIN_SCORE = 0
else:
if filter_mode:
results = sqs.all().models(
BiologicalCollectionRecord)
results = results.filter(validated=True)
else:
results = []
if taxon:
results = sqs.filter(
taxonomy=taxon
).models(BiologicalCollectionRecord)
# get by bbox
if not ignore_bbox:
if bbox:
bbox_array = bbox.split(',')
downtown_bottom_left = Point(
float(bbox_array[1]),
float(bbox_array[0]))
downtown_top_right = Point(
float(bbox_array[3]),
float(bbox_array[2]))
results = results.within(
'location_center',
downtown_bottom_left,
downtown_top_right)
# additional filters
# query by collectors
if query_collector:
qs_collector = SQ()
qs = json.loads(query_collector)
for query in qs:
qs_collector.add(SQ(collector=query), SQ.OR)
results = results.filter(qs_collector)
if boundary:
qs_collector = SQ()
qs = json.loads(boundary)
for query in qs:
query = '_' + query + '_'
qs_collector.add(SQ(boundary__contains=query), SQ.OR)
results = results.filter(qs_collector)
if user_boundary:
qs = json.loads(user_boundary)
user_boundaries = UserBoundary.objects.filter(
pk__in=qs
)
for user_boundary in user_boundaries:
for geom in user_boundary.geometry:
results = results.polygon(
'location_center',
geom
)
# query by category
if query_category:
qs_category = SQ()
qs = json.loads(query_category)
for query in qs:
qs_category.add(SQ(category=query), SQ.OR)
results = results.filter(qs_category)
# query by endemic
if endemic:
qs_endemism = SQ()
qs = json.loads(endemic)
for query in qs:
qs_endemism.add(SQ(endemism=query), SQ.OR)
results = results.filter(qs_endemism)
# query by conservation status
if conservation_status:
qs_conservation_status = SQ()
qs = json.loads(conservation_status)
for query in qs:
qs_conservation_status.add(SQ(iucn_status=query), SQ.OR)
results = results.filter(qs_conservation_status)
# query by river catchment
if river_catchments:
qs_river_catchment = SQ()
qs = json.loads(river_catchments)
for query in qs:
query = '_' + query.replace(' ', '_') + '_'
qs_river_catchment.add(SQ(river_catchments__contains=query),
SQ.OR)
results = results.filter(qs_river_catchment)
# query by reference category
if reference_category:
qs_reference_category = SQ()
qs = json.loads(reference_category)
for query in qs:
qs_reference_category.add(SQ(reference_category=query), SQ.OR)
results = results.filter(qs_reference_category)
# query by reference category
if reference:
qs_reference = SQ()
qs = json.loads(reference)
for query in qs:
qs_reference.add(SQ(reference__exact=query),
SQ.OR)
results = results.filter(qs_reference)
# query by year from
if year_from:
clean_query_year_from = sqs.query.clean(year_from)
results = results.filter(
collection_date_year__gte=clean_query_year_from)
# query by year to
if year_to:
clean_query_year_to = sqs.query.clean(year_to)
results = results.filter(
collection_date_year__lte=clean_query_year_to)
# query by months
if months:
qs = months.split(',')
qs_month = SQ()
for month in qs:
clean_query_month = sqs.query.clean(month)
qs_month.add(
SQ(collection_date_month=clean_query_month), SQ.OR)
results = results.filter(qs_month)
# Search by site id
if site_id:
site_ids = site_id.split(',')
qs_site_id = SQ()
for site in site_ids:
qs_site_id.add(
SQ(site_id_indexed=site), SQ.OR
)
results = results.filter(
qs_site_id
).models(BiologicalCollectionRecord)
collection_results = results
# Search location site by name
location_site_search = EmptySearchQuerySet()
if query_value:
location_site_search = SearchQuerySet().filter(
site_name__contains=query_value
).models(LocationSite)
location_site_results = location_site_search
location_site_user_boundary = EmptySearchQuerySet()
if boundary:
qs_collector = SQ()
qs = json.loads(boundary)
for query in qs:
query = '_' + query + '_'
qs_collector.add(SQ(boundary__contains=query), SQ.OR)
if isinstance(location_site_results, SearchQuerySet):
location_site_results = location_site_results.filter(
qs_collector)
if user_boundaries and isinstance(location_site_search,
SearchQuerySet):
location_site_user_boundary = location_site_search
for user_boundary in user_boundaries:
for geom in user_boundary.geometry:
location_site_user_boundary = \
location_site_user_boundary.polygon(
'location_site_point',
geom)
site_results = GetCollectionAbstract.combine_search_query_results(
location_site_results,
location_site_user_boundary
)
if len(site_results) > 0 or isinstance(
location_site_user_boundary, SearchQuerySet):
# If there are fuzzy results from collection search but we
# got non fuzzy results from location site, then remove
# all the fuzzy results from collection
if fuzzy_search and \
len(collection_results) > 0:
collection_results = []
fuzzy_search = False
return collection_results, site_results, fuzzy_search
