Merge pull request #3941 from alphagov/use-custom-polygon-to-estimate-phones-in-bleed-area

Use `CustomBroadcastArea` to estimate number of phones in bleed area

app/broadcast_areas/models.py

@@ -144,6 +144,10 @@ class CustomBroadcastArea(BaseBroadcastArea):
         self.name = name
         self._polygons = polygons or []
 
+    @classmethod
+    def from_polygon_objects(cls, polygon_objects):
+        return cls(name=None, polygons=polygon_objects.as_coordinate_pairs_lat_long)
+
     @property
     def polygons(self):
         return Polygons(

app/models/broadcast_message.py

@@ -7,6 +7,7 @@ from orderedset import OrderedSet
 from werkzeug.utils import cached_property
 
 from app.broadcast_areas.models import (
+    CustomBroadcastArea,
     CustomBroadcastAreas,
     broadcast_area_libraries,
 )
@@ -17,6 +18,10 @@ from app.notify_client.broadcast_message_api_client import (
     broadcast_message_api_client,
 )
 
+ESTIMATED_AREA_OF_LARGEST_UK_COUNTY = broadcast_area_libraries.get_areas(
+    'ctyua19-E10000023'  # North Yorkshire
+)[0].polygons.estimated_area
+
 
 class BroadcastMessage(JSONModel):
 
@@ -176,12 +181,25 @@ class BroadcastMessage(JSONModel):
 
     @property
     def count_of_phones_likely(self):
-        area_estimate = self.simple_polygons.estimated_area
+        estimated_area = self.simple_polygons.estimated_area
-        bleed_area_estimate = self.simple_polygons_with_bleed.estimated_area - area_estimate
+
-        return round_to_significant_figures(
+        if estimated_area > ESTIMATED_AREA_OF_LARGEST_UK_COUNTY:
-            self.count_of_phones + (self.count_of_phones * bleed_area_estimate / area_estimate),
+            # For large areas, use a naïve but computationally less
-            1
+            # expensive way of counting the number of phones in the
-        )
+            # bleed area
+            count = self.count_of_phones * (
+                self.simple_polygons_with_bleed.estimated_area / estimated_area
+            )
+        else:
+            # For smaller areas, where the computation can be done in
+            # a second or less (approximately) calculate the number of
+            # phones based on the ammount of overlap with areas for
+            # which we have population data
+            count = CustomBroadcastArea.from_polygon_objects(
+                self.simple_polygons_with_bleed
+            ).count_of_phones
+
+        return round_to_significant_figures(count, 1)
 
     def get_areas(self, areas):
         return broadcast_area_libraries.get_areas(

tests/app/main/views/test_broadcast.py

@@ -830,7 +830,7 @@ def test_broadcast_page(
     ], [
         'An area of 6.3 square miles Will get the alert',
         'An extra area of 22.6 square miles is Likely to get the alert',
-        '9,000 to 40,000 phones',
+        '9,000 to 10,000 phones',
     ]),
     ([
         'lad20-E09000019',
@@ -839,7 +839,26 @@ def test_broadcast_page(
     ], [
         'An area of 9.7 square miles Will get the alert',
         'An extra area of 4.7 square miles is Likely to get the alert',
-        '200,000 to 300,000 phones',
+        '200,000 to 500,000 phones',
+    ]),
+    ([
+        'ctyua19-E10000019',
+    ], [
+        'Lincolnshire remove',
+    ], [
+        'An area of 3,986.6 square miles Will get the alert',
+        'An extra area of 599.4 square miles is Likely to get the alert',
+        '500,000 to 600,000 phones',
+    ]),
+    ([
+        'ctyua19-E10000019',
+        'ctyua19-E10000023'
+    ], [
+        'Lincolnshire remove', 'North Yorkshire remove',
+    ], [
+        'An area of 9,776.2 square miles Will get the alert',
+        'An extra area of 1,654.6 square miles is Likely to get the alert',
+        '1,000,000 phones estimated',
     ]),
 ))
 def test_preview_broadcast_areas_page(
@@ -907,7 +926,7 @@ def test_preview_broadcast_areas_page(
         [
             'An area of 3,205.0 square miles Will get the alert',
             'An extra area of 763.4 square miles is Likely to get the alert',
-            '4,000 to 5,000 phones',
+            '4,000 phones estimated',
         ]
     ),
 ))