Adjust float type of kernel functions used in propagate methods

[ckendrick]

This expands further on #57 to also change the float types of any device functions used inside a propagate function to prevent casting.

[mtbc]

It's certainly useful progress in its thinking. After some discussion and experimentation, a couple of issues:

1. It relies on DeviceFunction which is not available since numba 0.55 so we're going to have to find an alternative approach. I am having difficulty finding any official guidance on this matter.
2. change_floattype("float32") leaves our code still full of float64 because, for instance, y = x / 2 with a float32 x gives a float64 y. We appear to get the desired effect with y = x / float32(2) but (a) then we need a generic float caster for whichever's been configured and (b) to litter our code with it.

[mtbc]

From inspecting the inferred types, seems crucial to decorate literals with constructors too, unfortunately. Could be we define ones for int and float where, e.g., change_floattype("float32") means also that,

x = y / 2.0

becomes,

x = y / float32(2.0)

(after importing it from numba)

So, we probably have to adjust/clutter our propagation code with such a parameterizable constructor of literals unless there's some cunning way a Python decorator can implement code preprocessing. Might also need to address it for calc_reflectivity.