aguinot
commented
2 years ago In addition to the comment I let on the code, here are some comments on the notebooks:
- Dataset.ipynb:
- Why you do not use the function in
galaxy.py? - Also we should discuss about the tests we want to make because having a fix SNR and a flux that vary is not very realistic. Basically, if the SNR is fixed varying the flux will not change anything in the results I think.
- In
Real Images - II feel like some galaxies looks "weird", maybe it is juste me.. The noise looks strange as well. - In
Real Images III feel like there is some patterns in the noise?
- Why you do not use the function in
- metacal_comparison.ipynb:
- In
Test GalFlow Deconv/Reconvare the residual actually small? what is the maximum pixel value in your original image? Because if the flux is 1, like it is in your default, this is actually not that "small" a few percent. But maybe it is expected? - In
GalFlow vs GalSimsame comment ^^^^^ - I don't understand those plots:
reconv w/ same psf noshear - In
Simple Ellipticity MeasurementsI don't like what I see here. The value you measure are "far" from the expected one. Maybe this is because of the step size, could you re-try with step=0.01? - When you print the calibrated e1/e2 it could be nice to have an idea of the variance to see if the measured residuals are significant or not. If not, then we should increase the number of galaxies (or increase the SNR). To give you an idea in the unit test used to check metacal in the ngmix repo they use 1000 galaxies with SNR=80000.
- I am still confuse by the discrepancy between R11/R22. I would be curious to see what ngmix gives you on the same sample.
- In
Averaging the response comparison over many galaxiesyou should fix the plot, we cannot see what is going on. Also, I am very surprise by the value you have (-350), this should not happen given your dataset. - The end of your code failed
- In
Some general comments:
- It is hard to check all the changes, there is a lot of files
- Some of the files are more tan a month old
- Some clean up would be nice :)
- Globally I think it is pretty nice and we are getting closer, it is very nice to see!
EiffL
andrevitorelli
I am trying to generate a more realistic set of galaxy stamps to test autometacal. These methods will be available inside the datasets subpackage and eventually integrated into tensorflow-datasets api within autometacal.
I have created a notebook at notebooks/Datasets.ipynb to explore different ways to do so.
Currently, I have implementations of:
Both 2. and 3. have problems for sure, which is why I'm seeking some guidance from @aguinot also. I'm trying to improve 2. getting code from galaxy2galaxy now.
PS: I have also tried to do bulge+disk models (with some reasonable assumptions) by modifying 1., and tested them as I was doing before - the results were comparable to 1.