tanguy-marchand/wph_quijote

wph_quijote's Issues

Advice for syntheses as in paper?

Hello, sorry to send this on the weekend; I am assuming you will look at it in the week if you want! I could use some guidance using the code. I have run run_syntheses.py,
which produced one batch of 2 syntheses. Unfortunately, unless I am missing or misunderstanding something, they do not look nearly as good as the syntheses in the paper. It created a folder result/first_result/1/, and created some synthesis_***.png files there, but they look only slightly non-Gaussian, not at all like LSS fields. There are some fields in folder result/first_result/1/original/original-?.png that look like LSS fields, but I am guessing those are training data. I did try to increase the number of samples used for training(?) from 3 to 6 (changing the relevant line in run_syntheses.py to
'filepaths': [os.path.join('data', 'quijote_fiducial_log_256', str(k), 'df_
z=0.npy') for k in range(6)],
-- by default, the last argument is 3), without a substantial improvement. Does that need to go all the way to 30? My GPU ran out of memory at 9.

If you have any advice on how to get fields somewhat like the ones in the paper, e.g. setting parameters, I would very much appreciate it. An alternative is if my CUDA environment is inadequately set up. I have attached the output of run_syntheses.py, in case it helps at all.

Thank you!!

output.txt