Time-series atmospheric data in -> optimized AOD and cloud thickness and spectrum out.
You'll want to have RTM set up to make use of any of this https://github.com/Queens-Applied-Sustainability/PyRTM
Create a directory some where.
You'll need to reate an info.yaml
file there containing global settings. At a bare minimum it should look like this:
latitude: 39.74
longitude: -105.18
Valid settings are any of those found in rtm.settings (https://github.com/Queens-Applied-Sustainability/PyRTM/blob/master/rtm/settings.py).
Settings in info.yaml
will be applied globally to the rtm models. Global settings take a low precedence and will be overridden by anything also defined in the time-series CSV.
Use nose, and for a quick check run nosetests -a '!slow'
.
nosetests
alone will run all tests including ones using sbdart
, which
takes ages.