I have successfully trained a model using Fourcastnet. I have been using the inferencer.py code to capture the true and recursive_pred output of a trained model. The input is on128x64 grid.
When I plot the output of both the true and predicted data I seem to have two 64x64 versions of the full grid in the 128x64 output data. I am expecting a 128x64 output grid matching the input?
I have verified that the input data is the correct 128x64 field without duplicates.
Is this an issue with a setting or a bug?
The figure shows the two 64x64 grids in the 128x64 output array produced by the model. The lines at 180 degrees are an artefact of the plotting (no wrap points included).
Here is the input data:-
This is the code that I use to extract the data:-
surft_p[nsave, tstep,:,:] = pred_recursive[0,:,:].cpu().detach().numpy()
surft_t[nsave, tstep,:,:] = true[0,:,:].cpu().detach().numpy()