Martin De Kauwe wrote:
> Note I have cross posted this as I have only just found this mailing list
> and perhaps it is the more appropriate place (I am not sure)?
I think your question is appropriate for both lists, it just wasn't sexy
enough for anyone on c.l.py to answer ;)
> I have been working on re-writing a model in python. However I am not sure
> how easy on the eye my final structure is and would appreciate any
> constructive comments/suggestions. So broadly the model estimates how
> plants grow using a number of related sub functions which I have grouped
> into classes and they all live in separate files. My main issue at the
> moment is I think I have a lot of verbose class instances but I really
> can't see a better way to do it. Is there a better way? How do other
> people do similar things? I am talking largely about the instances in the
> method run_sim
Random remarks:
> pg = PlantGrowth(self.control, self.params, self.state,
> self.fluxes, self.met_data)
I'd prefer your code to be even more verbose here; no two-letter variables
for anything that is non-generic.
> # plant growth
> pg.grow(project_day, self.date, leafnc)
With the construction in mind that is actually
> # plant growth
> plant_growth.grow(project_day, self.date, leafnc)
but plant_grows.grow() does not make a lot of sense, and the comment is
superfluous as it just undoes the abbreviation instead of explaining what is
going on.
> for i in self.met_data.doy:
> project_day = i - 1
> self.increment_date()
I'd iterate over the project_day-s directly if possible
for project_day in self.project_days():
...
> # calculate model decay rates
> dc.decay_rates()
A lot of methods don't take any arguments and return nothing. I'm guessing
that they modify the state that you passed to the initializer. I prefer
these modifications to be explicit if feasible, e. g.
state = dc.decay_rates(state)
where of course state is a placeholder for the actual variables that are
necessary to do the calculations.
The big picture? I'll leave that for someone else.
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