Closed lberti closed 1 year ago
@prudhomm Locally I was not able to check if the notebook is correctly generated. I tested the code blocks, and they run. However, for some reason, the errors don't seem to be correctly computed in this example.
Which error type did you used? Do you have the log of the offline code? Have you tried to make it parabolic? Can you plug external temperature from meteo data?
Error type: residual scm
Offline code: the error estimation that is displayed during the offline part is of the order 1e-7, and when the fem solution is also computed, the error is of the order 1e-10; it's only in the online part that the error is not properly computed
Parabolic: no, it's just the stationary part, as it was implemented in the example thermalbuilding.
I needed to document it to check what the model was like. I am working on the parabolic one
External temperature: the fifth parameter is the external temperature, involved in the computation of heat fluxes through the walls and the door. I did not add the possibility to read the external temperature from a meteo file.
Regarding the last point, i made a remark in the course notes regarding input signals over time at the end. We have to train with dirac signal at initial time. Initial condition are already handled
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@lberti here is the page: https://deploy-preview-258--adoring-edison-f92f3c.netlify.app/mor/latest/thermalbuilding/
unfortunately since feelpp cannot be installed on netlify images we cannot check the results of the python code
@prudhomm In any case the Python code needs the developments contained in branch feelpp/2143-clean-mor to run the reduced model with the fpp archive.
Add Python code for the online execution of the thermalbuilding model.