Comments (4)
Once you have the dat file, you can do whatever you want. Paraview has so many filter to plot CSV file, but that is out of scope of this discussion. I personally use plt.imshow()
from a meshgrid and interpolation the values at those grids.
from deepxde.
dde.saveplot(losshistory, train_state, issave=True, isplot=False)
This will save the loss history in loss.dat
, the predicted solution with the best model in test.dat
. For plotting you can use matplotlib.
from deepxde.
Thank you very much, I know how to plot in matplotlib but I would like to know if there is a way to export the data and obtain a better plot in Praview.
from deepxde.
Thank you very much. I’ll try it
from deepxde.
Related Issues (20)
- Does PINN training require a reference solution to the training data points? HOT 1
- How to give different inputs for subnetworks in PFNN
- Polygon PeriodicBC Problem HOT 1
- Model doesnot converge even after trying everything HOT 2
- possible bug: 'targets' variable not used in PDE losses() method?
- Hyperelasticity HOT 2
- Boundary condition as input for branch net in PI DeepONet
- ImportError: cannot import name 'check_pandas_support' from 'sklearn.utils' HOT 1
- ImportError check_pandas_support HOT 4
- Operator prediction becomes constant
- PDE error evaluated on bc points in PDE.losses but not used by following codes
- Is there a demo/code/model available for Fourier-MIONet?
- PDE with additional parameters HOT 8
- Support for Data Loader HOT 1
- Setting Custom Initial Weights in a Neural Network
- Implementing a free slip BC on a cylinder HOT 1
- multiple inputs and mixed data inputs by DEEPXDE
- Save only the best model files
- boundary number error
- RuntimeError when importing deepxde in unrelated test
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