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JGCRI / fldgen

Given a global mean temperature pathway, generate random global climate fields consistent with it and with spatial and temporal correlation derived from an ESM
https://jgcri.github.io/fldgen/
GNU General Public License v2.0
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downsized data sets to speed up testing #26

Open abigailsnyder opened 5 years ago

abigailsnyder commented 5 years ago

Currently devtools::test() takes a long time because our included sample data is large. At some point, we could figure out smaller sample data that works for the tests just as well.

rplzzz commented 5 years ago

The length of the test suite is a problem, but it looks like many of our travis timeouts (mostly on OS X, since the travis OS X instances are slow) are being caused by building the vignettes. I wonder if we could mitigate some of this by eliminating the tutorial1 vignette, which seems to be mostly obsolete.

The other question is, can we speed up the vignette processing? Reducing the resolution of the example data might help. If we halve the resolution in longitude, leaving latitude alone, we halve the size of a bunch of matrices, which could dramatically reduce the time required for some of the SVD and matrix multiplies dramatically (as I read it, for an m x n matrix, SVD is O(m^2*n + n^3) -- with n as the long dimension, that's effectively n^3).