Try to make use of QA data.
Fix typo.
Take into account QA values: ignore all 'other' quality.

Do a linear regression on the observed/modelled data.
Change how graphs are drawn in prepare.py.
Remove (almost) all graph plotting to new results.py.

Reason being that now results generation is separated
from analysis. Stats also handled by this new class.
Fixed a pernicious bug with masked arrays:
masked_arr[:, :] = 100
will get rid of entire mask!
Play around with some ideas for a slightly different model.
Experiment with different models (add in a delay function).

So far, it seems like this model behaves worse that the original
It should be able to perform at least as well, so see if changing
the optimization method helps.
Take out a different optimizer (fmin_bfgs) that hangs.
Add in ability to test  various models against eachother.

So far the simplest is still the best! exp_dec wins on most
metrics (r value, slope being close to 1 etc.).
Add in some precipitation data for catchment.
Include precipitation data from within the catchment area into a new model.

Improve some of the docs. Experiment with different optimization funcs.
Improve results graph drawing. Move project_settings.py to
default_settings.py.
Tidy up code: comments and documentation, lines < 80 chars.
Change path to creede.