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427ac0c8c1
Resolves: https://github.com/alphagov/notifications-admin/pull/3980#discussion_r692919874 Previously it was unclear what kinds of areas this method returned, and whether there would be any duplicates (due to the hierarchy of areas we work with). This clarifies that. In addition, the areas returned may not overlap with the custom one [1], so we should reword to avoid falsely implying that. We could do the overlap check as part of the method as an alternative, but that would create extra work when calculating the ratio of intersection. We could always add "overlapping areas" as a complementary method to this one in future. [1]: https://github.com/alphagov/notifications-admin/pull/3980#discussion_r692919874
393 lines
10 KiB
Python
393 lines
10 KiB
Python
from math import isclose
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import pytest
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from custom_polygons import BRISTOL, SKYE
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from app.broadcast_areas.models import (
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BroadcastAreasRepository,
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CustomBroadcastArea,
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broadcast_area_libraries,
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)
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from app.broadcast_areas.populations import (
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CITY_OF_LONDON,
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estimate_number_of_smartphones_for_population,
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)
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def close_enough(a, b):
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return isclose(a, b, rel_tol=0.001) # Within 0.1% difference
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def test_loads_libraries():
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assert [
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(library.id, library.name, library.is_group) for library in sorted(broadcast_area_libraries)
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] == [
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(
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'ctry19',
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'Countries',
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False,
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),
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(
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'demo',
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'Demo areas',
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False,
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),
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(
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'wd20-lad20-ctyua19',
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'Local authorities',
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True,
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),
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(
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'test',
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'Test areas',
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False,
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),
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]
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def test_loads_areas_from_library():
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assert [
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(area.id, area.name) for area in sorted(
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broadcast_area_libraries.get('ctry19')
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)
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] == [
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('ctry19-E92000001', 'England'),
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('ctry19-N92000002', 'Northern Ireland'),
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('ctry19-S92000003', 'Scotland'),
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('ctry19-W92000004', 'Wales'),
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]
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def test_examples():
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countries = broadcast_area_libraries.get('ctry19').get_examples()
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assert countries == 'England, Northern Ireland, Scotland and Wales'
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wards = broadcast_area_libraries.get('wd20-lad20-ctyua19').get_examples()
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assert wards == 'Aberdeen City, Aberdeenshire, Adur and 391 more…'
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@pytest.mark.parametrize('id', (
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'ctry19-E92000001',
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'ctry19-N92000002',
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'ctry19-S92000003',
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'ctry19-W92000004',
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pytest.param('mercia', marks=pytest.mark.xfail(raises=KeyError)),
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))
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def test_loads_areas_from_libraries(id):
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assert (
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broadcast_area_libraries.get('ctry19').get(id)
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) == (
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broadcast_area_libraries.get_areas([id])[0]
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)
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def test_get_names_of_areas():
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areas = broadcast_area_libraries.get_areas([
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'ctry19-W92000004',
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'lad20-W06000014',
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'ctry19-E92000001',
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])
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assert [area.name for area in sorted(areas)] == [
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'England', 'Vale of Glamorgan', 'Wales',
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]
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def test_has_polygons():
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england = broadcast_area_libraries.get_areas(['ctry19-E92000001'])[0]
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scotland = broadcast_area_libraries.get_areas(['ctry19-S92000003'])[0]
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assert len(england.polygons) == 35
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assert len(scotland.polygons) == 195
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assert england.polygons.as_coordinate_pairs_lat_long[0][0] == [
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55.811085, -2.034358 # https://goo.gl/maps/wsf2LUWzYinwydMk8
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]
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def test_polygons_are_enclosed():
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england = broadcast_area_libraries.get('ctry19').get('ctry19-E92000001')
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first_polygon = england.polygons.as_coordinate_pairs_lat_long[0]
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assert first_polygon[0] != first_polygon[1] != first_polygon[2]
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assert first_polygon[0] == first_polygon[-1]
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def test_lat_long_order():
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england = broadcast_area_libraries.get_areas(['ctry19-E92000001'])[0]
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lat_long = england.polygons.as_coordinate_pairs_lat_long
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long_lat = england.polygons.as_coordinate_pairs_long_lat
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assert len(lat_long[0]) == len(long_lat[0]) == 2082 # Coordinates in polygon
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assert len(lat_long[0][0]) == len(long_lat[0][0]) == 2 # Axes in coordinates
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assert lat_long[0][0] == list(reversed(long_lat[0][0]))
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def test_includes_electoral_wards():
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areas = broadcast_area_libraries.get_areas(['wd20-E05009289'])
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assert len(areas) == 1
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def test_electoral_wards_are_groupable_cardiff():
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areas = broadcast_area_libraries.get_areas(['lad20-W06000015'])
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assert len(areas) == 1
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cardiff = areas[0]
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assert len(cardiff.sub_areas) == 29
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def test_electoral_wards_are_groupable_ealing():
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areas = broadcast_area_libraries.get_areas(['lad20-E09000009'])
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assert len(areas) == 1
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ealing = areas[0]
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assert len(ealing.sub_areas) == 23
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def test_repository_has_all_libraries():
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repo = BroadcastAreasRepository()
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libraries = repo.get_libraries()
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assert len(libraries) == 4
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assert [
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('Countries', 'country'),
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('Demo areas', 'demo area'),
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('Test areas', 'test area'),
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('Local authorities', 'local authority'),
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] == [(name, name_singular) for _, name, name_singular, _is_group in libraries]
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@pytest.mark.parametrize('library', (
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broadcast_area_libraries
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))
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def test_every_area_has_count_of_phones(library):
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for area in library:
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if library.id == 'test':
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assert area.count_of_phones == 0
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else:
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assert area.count_of_phones > 0
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@pytest.mark.parametrize('area_id, area_name, expected_count', (
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# Unitary authority
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('ctyua19-E10000014', 'Hampshire', 853_594.48),
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# District
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('lad20-E07000087', 'Fareham', 81_970.06),
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# Ward
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('wd20-E05004516', 'Fareham East', 5_684.9),
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# Unitary authority
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('lad20-E09000012', 'Hackney', 222_578.0),
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# Ward
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('wd20-E05009373', 'Hackney Downs', 11_321.169999999998),
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# Special case: ward with hard-coded population
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('wd20-E05011090', 'Bryher', 76.44),
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# Areas with missing data
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('lad20-E07000008', 'Cambridge', 0),
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('lad20-E07000084', 'Basingstoke and Deane', 0),
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('lad20-E07000118', 'Chorley', 0),
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('lad20-E07000178', 'Oxford', 0),
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))
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def test_count_of_phones_for_all_levels(area_id, area_name, expected_count):
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area = broadcast_area_libraries.get_areas([area_id])[0]
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assert area.name == area_name
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assert area.count_of_phones == expected_count
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def test_city_of_london_counts_are_not_derived_from_population():
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city_of_london = broadcast_area_libraries.get_areas(['lad20-E09000001'])[0]
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assert city_of_london.name == 'City of London'
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assert len(city_of_london.sub_areas) == len(CITY_OF_LONDON.WARDS) == 25
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for ward in city_of_london.sub_areas:
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# The population of the whole City of London is 9,401, so an
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# average of 300 per ward. What we’re asserting here is that the
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# count of phones is much larger, because it isn’t derived from
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# the resident population.
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assert ward.count_of_phones > 5_000
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@pytest.mark.parametrize('population, expected_estimate', (
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# Upper and lower bounds of each age range
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(
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[(0, 100)], 50,
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),
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(
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[(16, 100)], 100
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),
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(
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[(24, 100)], 100,
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),
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(
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[(25, 100)], 97,
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),
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(
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[(34, 100)], 97,
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),
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(
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[(35, 100)], 91
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),
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(
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[(44, 100)], 91,
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),
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(
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[(45, 100)], 88
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),
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(
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[(54, 100)], 88,
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),
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(
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[(55, 100)], 73
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),
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(
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[(64, 100)], 73,
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),
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(
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[(65, 100)], 40
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),
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(
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[(999, 100)], 40,
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),
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# Multiple different ages in a single popualtion
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(
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[(16, 100), (54, 100)], 188
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),
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(
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[(1, 1000), (66, 100)], 540
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),
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))
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def test_estimate_number_of_smartphones_for_population(
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population, expected_estimate,
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):
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assert estimate_number_of_smartphones_for_population(
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population
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) == expected_estimate
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@pytest.mark.parametrize('area, expected_phones_per_square_mile', (
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(
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# Islington (most dense in UK)
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'lad20-E09000019', 21_348
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),
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(
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# Cordwainer Ward (City of London)
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# This is higher than Islington because we inflate the
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# popualtion to account for daytime workers
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'wd20-E05009300', 310_674
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),
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(
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# Crewe East
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'wd20-E05008621', 2_078),
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(
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# Eden (Cumbria, least dense in England)
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'lad20-E07000030', 25.57
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),
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(
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# Highland (least dense in UK)
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'lad20-S12000017', 4.40
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),
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))
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def test_phone_density(
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area, expected_phones_per_square_mile,
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):
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assert close_enough(
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broadcast_area_libraries.get_areas([area])[0].phone_density,
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expected_phones_per_square_mile,
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)
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@pytest.mark.parametrize('area, expected_bleed_in_m, expected_bleed_in_degrees', (
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(
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# Islington (most dense in UK)
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'lad20-E09000019', 500, 0.00449
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),
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(
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# Cordwainer Ward (City of London)
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# Special case because of inflated daytime population
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'wd20-E05009300', 500, 0.00449
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),
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(
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# Crewe East
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'wd20-E05008621', 1_752, 0.01574
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),
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(
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# Eden (Cumbria, least dense in England)
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'lad20-E07000030', 4_140, 0.0372
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),
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(
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# Highland (least dense in UK)
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'lad20-S12000017', 5_000, 0.0449
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),
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(
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# No population data available
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'test-santa-claus-village-rovaniemi-a', 1_500, 0.01347
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)
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))
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def test_estimated_bleed(
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area, expected_bleed_in_m, expected_bleed_in_degrees,
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):
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assert close_enough(
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broadcast_area_libraries.get_areas([area])[0].estimated_bleed_in_m,
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expected_bleed_in_m,
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)
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assert close_enough(
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broadcast_area_libraries.get_areas([area])[0].estimated_bleed_in_degrees,
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expected_bleed_in_degrees,
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)
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@pytest.mark.parametrize('polygon, expected_possible_overlaps, expected_count_of_phones', (
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(
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BRISTOL,
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[
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'Ashley',
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'Bedminster',
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'Central',
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'Clifton',
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'Clifton Down',
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'Cotham',
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'Hotwells and Harbourside',
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'Knowle',
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'Lawrence Hill',
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'Southville',
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'Stoke Bishop',
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'Windmill Hill',
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],
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73_119,
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),
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(
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SKYE,
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[
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'Caol and Mallaig',
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'Eilean á Chèo',
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'Na Hearadh agus Ceann a Deas nan Loch',
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'Wester Ross, Strathpeffer and Lochalsh',
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],
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3_534,
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),
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))
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def test_count_of_phones_for_custom_area(
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polygon,
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expected_possible_overlaps,
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expected_count_of_phones,
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):
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area = CustomBroadcastArea(
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name='Example',
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polygons=[polygon],
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)
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assert sorted(
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overlap.name for overlap in area.nearby_electoral_wards
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) == expected_possible_overlaps
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assert close_enough(area.count_of_phones, expected_count_of_phones)
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