Develop functionality to show occurrence data per month (#3650)

* Add chart data by month for site dashboard

* Implement switch dashboard frequency in frontend

bims/api_views/download_request.py

@@ -1,5 +1,8 @@
 from preferences import preferences
 import ast
+
+from rest_framework import status
+
 from bims.download.csv_download import send_new_csv_notification
 from bims.models.taxonomy import Taxonomy
 
@@ -30,6 +33,11 @@ def post(self, request):
         input, creates the download request, and sends a notification email if
         successful.
         """
+        if not request.user.is_authenticated:
+            return Response(
+                {'error': 'User needs to be logged in first'},
+                status=status.HTTP_401_UNAUTHORIZED)
+
         resource_name = request.POST.get('resource_name')
         resource_type = request.POST.get('resource_type')
         purpose = request.POST.get('purpose')

bims/api_views/location_site.py

@@ -59,6 +59,10 @@
 from bims.tasks.email_csv import send_csv_via_email
 from bims.tasks.collection_record import download_gbif_ids
 from bims.enums.ecosystem_type import ECOSYSTEM_WETLAND
+from bims.api_views.location_site_dashboard import (
+    PER_YEAR_FREQUENCY,
+    PER_MONTH_FREQUENCY
+)
 
 
 class LocationSiteList(APIView):
@@ -173,15 +177,23 @@ def generate(self, filters, search_process):
         collection_results = search.process_search()
         site_id = filters['siteId']
 
+        # Indicates whether to show occurrence data per year (y) or per month (m)
+        data_frequency = filters.get('d', PER_YEAR_FREQUENCY)
+
         self.iucn_category = dict(
             (x, y) for x, y in IUCNStatus.CATEGORY_CHOICES)
 
         self.origin_name_list = dict(
             (x, y) for x, y in Taxonomy.CATEGORY_CHOICES
         )
 
-        taxa_occurrence = self.site_taxa_occurrences_per_year(
-            collection_results)
+        if data_frequency == PER_MONTH_FREQUENCY:
+            taxa_occurrence = self.site_taxa_occurrences_per_date(
+                collection_results
+            )
+        else:
+            taxa_occurrence = self.site_taxa_occurrences_per_year(
+                collection_results)
 
         category_summary = collection_results.exclude(
             taxonomy__origin=''
@@ -403,6 +415,27 @@ def site_taxa_occurrences_per_year(self, collection_results):
         result['occurrences_line_chart']['title'] = 'Occurrences'
         return result
 
+    def site_taxa_occurrences_per_date(self, collection_results):
+        """
+        Get occurrence data for charts based on the date sampled
+        :param collection_results: collection record queryset
+        :return: dict of taxa occurrence data for line graph
+        """
+        taxa_occurrence_data = collection_results.values('collection_date').annotate(
+            count=Count('collection_date')
+        ).order_by('collection_date')
+        result = dict()
+        result['occurrences_line_chart'] = {
+            'values': [],
+            'keys': [],
+            'title': 'Occurrences per Date Sampled'
+        }
+        for data in taxa_occurrence_data:
+            formatted_date = data['collection_date'].strftime('%Y-%m-%d')
+            result['occurrences_line_chart']['keys'].append(formatted_date)
+            result['occurrences_line_chart']['values'].append(data['count'])
+        return result
+
     def get_biodiversity_data(self, collection_results):
         biodiversity_data = {}
         biodiversity_data['species'] = {}

bims/api_views/location_site_dashboard.py

@@ -1,45 +1,46 @@
 from bims.models.taxonomy import Taxonomy
 from rest_framework.views import APIView, Response
-from django.db.models import Case, F, Count, Value, When
-from django.db.models.functions import ExtractYear
+from django.db.models import Case, F, Count, Value, When, CharField
+from django.db.models.functions import ExtractYear, ExtractMonth, Concat, LPad, Cast
 from bims.api_views.search import CollectionSearch
 
+PER_YEAR_FREQUENCY = 'y'
+PER_MONTH_FREQUENCY = 'm'
+
 
 class ChartDataApiView(APIView):
+    data_frequency = PER_YEAR_FREQUENCY
 
     def format_data(self, collection_data, categories):
         chart_data = {
-            'dataset_labels': [],
+            'dataset_labels': categories,
             'labels': [],
-            'data': {}
+            'data': {category: [] for category in categories}
         }
-        year_labels = []
-        category_with_data = dict()
-        for category in categories:
-            category_with_data[category] = []
 
+        if self.data_frequency == PER_MONTH_FREQUENCY:
+            year_labels = sorted({data['year'] for data in collection_data},
+                                 key=lambda x: (x.split('-')[1], x.split('-')[0]))
+        else:
+            year_labels = sorted({data['year'] for data in collection_data})
+
+        data_counts = {
+            year: {category: 0 for category in categories}
+            for year in year_labels}
         for data in collection_data:
-            new_data = False
-            if data['year'] not in year_labels:
-                new_data = True
-                year_labels.append(data['year'])
-
-            if new_data and len(year_labels) > 1:
-                # Add 0 to previous
-                for category in categories:
-                    if len(category_with_data[category]) < len(
-                            year_labels) - 1:
-                        category_with_data[category].insert(
-                            len(year_labels) - 2, 0)
-
-            category_with_data[data['name']].append(data['count'])
-
-        chart_data['dataset_labels'] = categories
+            data_counts[data['year']][data['name']] += data['count']
+        for year in year_labels:
+            for category in categories:
+                chart_data['data'][category].append(
+                    data_counts[year][category])
+
         chart_data['labels'] = year_labels
-        chart_data['data'] = category_with_data
 
         return chart_data
 
+    def chart_data_per_month(self, collection_results):
+        raise NotImplementedError
+
     def chart_data(self, collection_results):
         raise NotImplementedError
 
@@ -48,9 +49,16 @@ def categories(self, collection_results):
 
     def get(self, request):
         filters = request.GET.dict()
+
+        self.data_frequency = filters.get('d', PER_YEAR_FREQUENCY)
+
         search = CollectionSearch(filters)
         collection_results = search.process_search()
-        chart_data = self.chart_data(collection_results)
+        if self.data_frequency == PER_YEAR_FREQUENCY:
+            chart_data = self.chart_data(collection_results)
+        else:
+            chart_data = self.chart_data_per_month(collection_results)
+
         categories = self.categories(collection_results)
         result = self.format_data(
             chart_data,
@@ -63,25 +71,47 @@ class OccurrencesChartData(ChartDataApiView):
     """
     Get occurrence data categorized by origin for chart
     """
+
     def categories(self, collection_results):
         return list(collection_results.annotate(
             name=Case(
-                    When(taxonomy__origin='', then=Value('Unknown')),
-                    When(taxonomy__origin__icontains='unknown',
-                         then=Value('Unknown')),
-                      default=F('taxonomy__origin'))
+                When(taxonomy__origin='', then=Value('Unknown')),
+                When(taxonomy__origin__icontains='unknown',
+                     then=Value('Unknown')),
+                default=F('taxonomy__origin'))
         ).values_list(
             'name', flat=True
         ).distinct('name'))
 
+    def chart_data_per_month(self, collection_results):
+        return collection_results.annotate(
+            y=ExtractYear('collection_date'),
+            m=LPad(Cast(ExtractMonth('collection_date'), CharField()), 2, Value('0')),
+            year=Concat(
+                'm', Value('-'), 'y',
+                output_field=CharField()
+            ),
+            name=Case(
+                When(taxonomy__origin='', then=Value('Unknown')),
+                When(taxonomy__origin__icontains='unknown',
+                     then=Value('Unknown')),
+                default=F('taxonomy__origin'))
+        ).values(
+            'year', 'name'
+        ).annotate(
+            count=Count('year'),
+        ).values(
+            'year', 'name', 'count'
+        ).order_by('collection_date')
+
     def chart_data(self, collection_results):
         return collection_results.annotate(
             year=ExtractYear('collection_date'),
             name=Case(
-                    When(taxonomy__origin='', then=Value('Unknown')),
-                    When(taxonomy__origin__icontains='unknown',
-                         then=Value('Unknown')),
-                      default=F('taxonomy__origin'))
+                When(taxonomy__origin='', then=Value('Unknown')),
+                When(taxonomy__origin__icontains='unknown',
+                     then=Value('Unknown')),
+                default=F('taxonomy__origin'))
         ).values(
             'year', 'name'
         ).annotate(
@@ -105,6 +135,25 @@ def categories(self, collection_results):
             'name', flat=True
         ).distinct('name'))
 
+    def chart_data_per_month(self, collection_results):
+        return collection_results.annotate(
+            y=ExtractYear('collection_date'),
+            m=LPad(Cast(ExtractMonth('collection_date'), CharField()), 2, Value('0')),
+            year=Concat(
+                'm', Value('-'), 'y',
+                output_field=CharField()
+            ),
+            name=Case(When(taxonomy__iucn_status__category__isnull=False,
+                           then=F('taxonomy__iucn_status__category')),
+                      default=Value('NE')),
+        ).values(
+            'year', 'name'
+        ).annotate(
+            count=Count('year'),
+        ).values(
+            'year', 'name', 'count'
+        ).order_by('collection_date')
+
     def chart_data(self, collection_results):
         return collection_results.annotate(
             year=ExtractYear('collection_date'),
@@ -124,6 +173,7 @@ class LocationSitesTaxaChartData(ChartDataApiView):
     """
     """
     taxa = None
+
     def categories(self, collection_results):
         if not self.taxa:
             self.taxa = Taxonomy.objects.filter(
@@ -138,6 +188,30 @@ def categories(self, collection_results):
             'name', flat=True
         ).distinct('name'))
 
+    def chart_data_per_month(self, collection_results):
+        if not self.taxa:
+            self.taxa = Taxonomy.objects.filter(
+                biologicalcollectionrecord__id__in=
+                collection_results.values_list('id', flat=True)
+            ).distinct()[:25]
+        return collection_results.filter(
+            taxonomy__in=self.taxa
+        ).annotate(
+            y=ExtractYear('collection_date'),
+            m=LPad(Cast(ExtractMonth('collection_date'), CharField()), 2, Value('0')),
+            year=Concat(
+                'm', Value('-'), 'y',
+                output_field=CharField()
+            ),
+            name=F('taxonomy__scientific_name'),
+        ).values(
+            'year', 'name'
+        ).annotate(
+            count=Count('year'),
+        ).values(
+            'year', 'name', 'count'
+        ).order_by('collection_date')
+
     def chart_data(self, collection_results):
         if not self.taxa:
             self.taxa = Taxonomy.objects.filter(
@@ -162,6 +236,7 @@ class LocationSitesEndemismChartData(ChartDataApiView):
     """
     Return data for endemism bar chart.
     """
+
     def categories(self, collection_results):
         return list(collection_results.annotate(
             name=Case(When(taxonomy__endemism__isnull=False,
@@ -171,6 +246,25 @@ def categories(self, collection_results):
             'name', flat=True
         ).distinct('name'))
 
+    def chart_data_per_month(self, collection_results):
+        return collection_results.annotate(
+            y=ExtractYear('collection_date'),
+            m=LPad(Cast(ExtractMonth('collection_date'), CharField()), 2, Value('0')),
+            year=Concat(
+                'm', Value('-'), 'y',
+                output_field=CharField()
+            ),
+            name=Case(When(taxonomy__endemism__isnull=False,
+                           then=F('taxonomy__endemism__name')),
+                      default=Value('Unknown'))
+        ).values(
+            'year', 'name'
+        ).annotate(
+            count=Count('year'),
+        ).values(
+            'year', 'name', 'count'
+        ).order_by('collection_date')
+
     def chart_data(self, collection_results):
         return collection_results.annotate(
             year=ExtractYear('collection_date'),

bims/static/js/non_requirejs/download_request_popup.js

@@ -36,8 +36,14 @@ function showDownloadPopup(resource_type, resource_name, callback, auto_approved
         callback(data['download_request_id']);
         $downloadPopup.modal('hide');
         $submitDownloadPopup.prop('disabled', false);
-      }, error: function () {
-        alert('Error submitting download request');
+      }, error: function (jqXHR, textStatus, errorThrown) {
+        let errorMessage = "Error submitting download request.";
+        if (jqXHR.responseJSON && jqXHR.responseJSON.error) {
+          errorMessage += " " + jqXHR.responseJSON.error;
+        } else if (textStatus) {
+          errorMessage += " " + textStatus;
+        }
+        alert(errorMessage);
         $downloadPopup.modal('hide');
         $submitDownloadPopup.prop('disabled', false);
       }