Add tests for the population calculations

Now that this function is split out we can unit test it to make sure
that the expected numbers are coming out of it.

tests/app/broadcast_areas/test_broadcast_area.py

@@ -4,7 +4,10 @@ from app.broadcast_areas import (
     BroadcastAreasRepository,
     broadcast_area_libraries,
 )
-from app.broadcast_areas.populations import CITY_OF_LONDON
+from app.broadcast_areas.populations import (
+    CITY_OF_LONDON,
+    estimate_number_of_smartphones_for_population,
+)
 
 
 def test_loads_libraries():
@@ -176,3 +179,60 @@ def test_city_of_london_counts_are_not_derived_from():
         # count of phones is much larger, because it isn’t derived from
         # the resident population.
         assert ward.count_of_phones > 5_000
+
+
+@pytest.mark.parametrize('population, expected_estimate', (
+    # Upper and lower bounds of each age range
+    (
+        [(0, 100)], 50,
+    ),
+    (
+        [(16, 100)], 100
+    ),
+    (
+        [(24, 100)], 100,
+    ),
+    (
+        [(25, 100)], 97,
+    ),
+    (
+        [(34, 100)], 97,
+    ),
+    (
+        [(35, 100)], 91
+    ),
+    (
+        [(44, 100)], 91,
+    ),
+    (
+        [(45, 100)], 88
+    ),
+    (
+        [(54, 100)], 88,
+    ),
+    (
+        [(55, 100)], 73
+    ),
+    (
+        [(64, 100)], 73,
+    ),
+    (
+        [(65, 100)], 40
+    ),
+    (
+        [(999, 100)], 40,
+    ),
+    # Multiple different ages in a single popualtion
+    (
+        [(16, 100), (54, 100)], 188
+    ),
+    (
+        [(1, 1000), (66, 100)], 540
+    ),
+))
+def test_estimate_number_of_smartphones_for_population(
+    population, expected_estimate,
+):
+    assert estimate_number_of_smartphones_for_population(
+        population
+    ) == expected_estimate