def get(self, request):
query_value = request.GET.get('search')
filters = request.GET
# Search collection
collection_results, \
site_results, \
fuzzy_search = GetCollectionAbstract.apply_filter(
query_value,
filters,
ignore_bbox=True)
try:
collection_ids = list(collection_results.values_list(
'model_pk', flat=True
))
records = BiologicalCollectionRecord.objects.filter(
pk__in=collection_ids
)
serializer = BioCollectionSerializer(
records,
many=True)
return Response(serializer.data)
except BiologicalCollectionRecord.DoesNotExist:
return HttpResponse(
'Object Does Not Exist',
status=status.HTTP_400_BAD_REQUEST
)
def get(self, request):
try:
allowed_taxon = AllowedTaxon()
taxon_list = allowed_taxon.get(request.user)
records = BiologicalCollectionRecord.objects.filter(
validated=False,
ready_for_validation=True,
taxon_gbif_id__in=taxon_list)
paginator = Paginator(records, self.page_limit)
page = request.GET.get('page')
try:
records = paginator.page(page)
current_page = int(page)
except PageNotAnInteger:
records = paginator.page(1)
current_page = 1
except EmptyPage:
records = paginator.page(paginator.num_pages)
current_page = paginator.num_pages
serializer = BioCollectionSerializer(records, many=True)
response_data = {
'data': serializer.data,
'pagination': {
'current_page': current_page,
'max_page': paginator.num_pages,
'page_limit': self.page_limit
}
}
return Response(response_data)
except BiologicalCollectionRecord.DoesNotExist:
return HttpResponse('Object Does Not Exist',
status=status.HTTP_400_BAD_REQUEST)
def get(self, request):
object_pk = request.GET.get('pk', None)
try:
object = BiologicalCollectionRecord.objects.get(pk=object_pk)
serializer = BioCollectionSerializer(object)
return Response(serializer.data)
except BiologicalCollectionRecord.DoesNotExist:
return HttpResponse('Object Does Not Exist',
status=status.HTTP_400_BAD_REQUEST)
def clustering_process(self, records, zoom, pix_x, pix_y):
"""
Iterate records and create point clusters
We use a simple method that for every point, that is not within any
cluster, calculate it's 'catchment' area and add it to the cluster
If a point is within a cluster 'catchment' area increase point
count for that cluster and recalculate clusters minimum bbox
:param records: list of records.
:type records: list
:param zoom: zoom level of map
:type zoom: int
:param pix_x: pixel x of icon
:type pix_x: int
:param pix_y: pixel y of icon
:type pix_y: int
"""
cluster_points = []
for record in records:
# get x,y of site
record = record.object
x = record.site.geometry_point.x
y = record.site.geometry_point.y
# check every point in cluster_points
for pt in cluster_points:
if 'minbbox' not in pt:
pt['minbbox'] = pt['bbox']
if within_bbox((x, y), pt['minbbox']):
# it's in the cluster 'catchment' area
pt['count'] += 1
pt['minbbox'] = update_min_bbox((x, y), pt['minbbox'])
break
else:
# point is not in the catchment area of any cluster
x_range, y_range = overlapping_area(zoom, pix_x, pix_y, y)
bbox = (x - x_range * 1.5, y - y_range * 1.5,
x + x_range * 1.5, y + y_range * 1.5)
serializer = BioCollectionSerializer(record)
new_cluster = {
'count': 1,
'bbox': bbox,
'coordinates': [x, y],
'record': serializer.data
}
cluster_points.append(new_cluster)
return cluster_points
def get(self, request):
filters = request.GET
search = CollectionSearch(filters)
# Search collection
collection_results = search.process_search()
try:
serializer = BioCollectionSerializer(collection_results, many=True)
return Response(serializer.data)
except BiologicalCollectionRecord.DoesNotExist:
return HttpResponse('Object Does Not Exist',
status=status.HTTP_400_BAD_REQUEST)