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starting from the usual destriper, and out of its results starting the more comprehensive model to mitigate the atmospheric structures during the maps reconstruction.
@savaroskij check it out! It could be a really sensible theme for a doctorate proposal....
The text was updated successfully, but these errors were encountered:
With the PR #9 the program is able to solve large linear problems with the PCG algorithm. The default preconditioner is the Jacobi preconditioner, that in genera represents a smart solution for this problems. In case of the atmosphere is not so easy. The stantards models and the jacoby preconditioner seem that don't work.
Btw, so far, the program can solve a problem with a maximum likelihood approach using the PCG. Let's start the fun in searching the correct model to mitigate the atmosphere.
Use step/by/step approach
Implement a good filter for remove the atmosphere contribute from 1h of data, and than pass to the 1 day of data and so on
mapmaking/src/lib.rs
Line 173 in 3abfd53
starting from the usual destriper, and out of its results starting the more comprehensive model to mitigate the atmospheric structures during the maps reconstruction.
@savaroskij check it out! It could be a really sensible theme for a doctorate proposal....
The text was updated successfully, but these errors were encountered: