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.
