I am trying to optimize the speed of r.sun to compute shadowed area on a DTM at 1m resolution. My current area is 3.39 km² but my final area will be 450 km².
The r.sun wiki say that pre-computing horizons as well as lat/lon increase the model, but the opposite happen on my computer (GRASS 7.0.1RC2, Windows7 64 bits [although r.sun run in 32 bits mode], 4 CPU, 8 threads)
Here is an example:
npartitions are different on the 2 examples (I have no choice), but this parameter has not a big impact on the computing time.
If anyone has an idea why it has this behavior, it will be much appreciated.
Testing on Grass 6.4, using horizons allows me to decrease computation time from 42-50s to 32s.
Another question is: Is there a possibility to avoid the computation of the sun angles for each cell ? Providing a single value for the whole area would be ok for me, and I can compute it by myself
أكثر...
The r.sun wiki say that pre-computing horizons as well as lat/lon increase the model, but the opposite happen on my computer (GRASS 7.0.1RC2, Windows7 64 bits [although r.sun run in 32 bits mode], 4 CPU, 8 threads)
Here is an example:
r.sun elevation=MNEcomplet@ShadowProject day=88 time=7 incidout=incidoutD88T07 --overwrite npartitions=2 distance_step=1
==> 38 sec
r.sun elevation=MNEcomplet@ShadowProject horizon_basename=horizon horizon_step=30 day=88 time=7 incidout=incidoutD88T07 --overwrite npartitions=2 distance_step=1.0 lat=MNEcomplet.lat long=MNEcomplet.lon
==> between 56 sec and 1min7s
npartitions are different on the 2 examples (I have no choice), but this parameter has not a big impact on the computing time.
If anyone has an idea why it has this behavior, it will be much appreciated.
Testing on Grass 6.4, using horizons allows me to decrease computation time from 42-50s to 32s.
Another question is: Is there a possibility to avoid the computation of the sun angles for each cell ? Providing a single value for the whole area would be ok for me, and I can compute it by myself
أكثر...