Re: [arts-users] ARTS OEM multiple inversions
Hi Patrick, Thanks for your quick answer. Simon's answer did clarify it and I believe his solution is quite close to what you suggest and what is done in Qpack. I'll try it out. Thanks, Eric De : Simon Pfreundschuh Envoyé : vendredi 4 juin 2021 14:55:24 À : Sauvageat, Eric (IAP); arts_users...@mailman.rrz.uni-hamburg.de Objet : Re: ARTS OEM multiple inversions Sorry, though the response would automatically go to the list. For completeness, here's my response from earlier. Just to clarify and confirm: > same sensors, same atmosphere, etc.. just different measurements vectors using > OEM from ARTS directly ? This is what ARTS currently does: It takes multiple observations and solves for a single atmospheric state. If I understand you correctly what you want to do is same sensors but different atmospheres (although they may be the same a priori). This kind of parallelism is not supported within ARTS so you'll have to do it sequentially. It's straight forward when you use the Python interface: After you have set up your calculation, you just call the OEM WSM multiple times in a loop. What you need to pay attention to is to reset the WSVs x, yf and jacobian before calling OEM a second time because those are both in- and outputs of the method. I not sure, however, how much you will gain from this computationally since this depends on your retrieval setup. Let me know if anything remains unclear. Kind regards, Simon From: arts_users.mi-boun...@mailman.rrz.uni-hamburg.de on behalf of eric.sauvag...@iap.unibe.ch Sent: Friday, June 4, 2021 12:03:12 PM To: arts_users...@mailman.rrz.uni-hamburg.de Subject: [arts-users] ARTS OEM multiple inversions Dear ARTS community, 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. 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 ? Thanks for your help, Eric ___ arts_users.mi mailing list arts_users.mi@lists.uni-hamburg.de https://mailman.rrz.uni-hamburg.de/mailman/listinfo/arts_users.mi
Re: [arts-users] ARTS OEM multiple inversions
Sorry, though the response would automatically go to the list. For completeness, here's my response from earlier. Just to clarify and confirm: > same sensors, same atmosphere, etc.. just different measurements vectors using > OEM from ARTS directly ? This is what ARTS currently does: It takes multiple observations and solves for a single atmospheric state. If I understand you correctly what you want to do is same sensors but different atmospheres (although they may be the same a priori). This kind of parallelism is not supported within ARTS so you'll have to do it sequentially. It's straight forward when you use the Python interface: After you have set up your calculation, you just call the OEM WSM multiple times in a loop. What you need to pay attention to is to reset the WSVs x, yf and jacobian before calling OEM a second time because those are both in- and outputs of the method. I not sure, however, how much you will gain from this computationally since this depends on your retrieval setup. Let me know if anything remains unclear. Kind regards, Simon From: arts_users.mi-boun...@mailman.rrz.uni-hamburg.de on behalf of eric.sauvag...@iap.unibe.ch Sent: Friday, June 4, 2021 12:03:12 PM To: arts_users...@mailman.rrz.uni-hamburg.de Subject: [arts-users] ARTS OEM multiple inversions Dear ARTS community, 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. 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 ? Thanks for your help, Eric ___ arts_users.mi mailing list arts_users.mi@lists.uni-hamburg.de https://mailman.rrz.uni-hamburg.de/mailman/listinfo/arts_users.mi
Re: [arts-users] ARTS OEM multiple inversions
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
[arts-users] ARTS OEM multiple inversions
Dear ARTS community, 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. 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 ? Thanks for your help, Eric ___ arts_users.mi mailing list arts_users.mi@lists.uni-hamburg.de https://mailman.rrz.uni-hamburg.de/mailman/listinfo/arts_users.mi
