To count phones in a custom polygon we need to work out the percentage
of overlap with each known area. This means we need to get each known
area from the database to compare it.
At the moment we do this by running:
- one SQLite query to get the details of all matching areas
- a loop, which performs one SQLite query *per area* to get the polygons
This commit reduces the number of SQLite queries to one, which uses a
`JOIN` to get both the details of the areas and their polygons.
This gives a speed increase of about 25% for a big area like
Lincolnshire.
By using the simplified polygons instead of the full resolutions ones
we:
- query less data from SQLite
- pass less data around
- give Shapely a less complicated shape to do its calculations on
This makes it faster to calculate how much of each electoral ward a
custom area overlaps.
For the two areas in our tests:
Place represented by custom area | Before | After
---------------------------------|--------|--------
Bristol | 0.07s | 0.02s
Skye | 0.02s | 0.01s
Our current assumption is that the bleed area has the same population
density as the broadcast area.
This is particularly naïve when:
- the bleed area overlaps the sea – no-one lives in the sea
- the broadcast area is a village and the bleed area is the surrounding
countryside
- the broadcast area is adjacent to a densely populated area like a city
We can be smarter about this now that we have a way of determining the
number of phones in an arbitrary area, based on the known areas that we
have population data about.
Calculating the population in an overlap is a slightly more intensive
calculation. So we only doing it for areas which are smaller enough that
it doesn’t slow things down too much. For larger areas we still use the
more naïve algorithm.
Previously this was hidden away in an anonymous __init__.py file.
I did think about splitting the models into individual files, like
we do with the top-level models for the app. Since the models are
only imported in one place - i.e. are all used together - it didn't
seem worth the hassle, so I've kept them in one file.
