Eric,
I am performing strato-mesospheric ozone retrievals with the OEM
implemented directly in ARTS (using the python interface).
As my sensor is not changing much with time, I am wondering if there is
a way (and if this is worth in terms of computation speed) to reuse the
sensor_response matrix (FFT channel response, unbinned) for different
measurements which I think was quite straightforward with Qpack.
In Qpack some stuff is made behind the scene. Yes, it can be avoided to
recalculate the sensor response. But you need save a number of
variables. At least these ones:
sensor_response
sensor_response_f
sensor_response_pol
sensor_response_dlos,
sensor_response_f_grid, sensor_response_pol_grid,
sensor_response_dlos_grid
Maybe also good to save
mblock_dlos_grid
stokes_dim
And then you just need to import these for a new calculation (or just
keep them in memory).
I was trying to write multiple calibrated spectra within the y vector as
well as multiple meas. error cov. (Se and inv) blocks before running the
OEM which I thought might be the way to go but it seems to treat them as
multiple measurements of the same ozone profiles instead. Could somebody
confirmed if this is expected and if yes, is there another way to do
this kind of parallel OEM retrievals: same sensors, same atmosphere,
etc.. just different measurements vectors using OEM from ARTS directly ?
There is no clear cut way inside ARTS to do batch OEM inversions. I am
not using Python myself, but is this part not easy to setup on the
python side?
Bye,
Patrick
_______________________________________________
arts_users.mi mailing list
arts_users.mi@lists.uni-hamburg.de
https://mailman.rrz.uni-hamburg.de/mailman/listinfo/arts_users.mi
