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Image pipeline issue with sky image size #925
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@cdeil |
@cdeil |
@registerrier @JouvinLea - This tutorial notebook is currently broken: The error is this:
See https://gist.github.com/cdeil/222ce8f3cc81223721173ce918b2b4e9#file-gistfile1-txt-L33 That tutorial is very similar to what we show here: The plan is that both the StackedImageObsMaker and the IACTImageEstimator will be replaced with new code #1277 and with the HESS test data release in a months we will have a better example dataset. I propose that we now simply remove the The alternative is that @leajouvin or @registerrier you update and fix that notebook now, if you think it's useful to keep. What do you think? |
@cdeil @registerrier |
I removed the image_pipe notebook : and also the old cube analysis notebooks: This is part of the effort to rewrite map-based analysis (both 2D and 3D) in Gammapy and to remove SkyImage / SkyCube and the old image and cube makers and Sherpa 3D fitting code. gammapy.maps is pretty well-developed, and development of new analysis code on top of it and even tutorial documentation has started: It's not very far along, but still, @registerrier and I discussed on Friday, and agreed that keeping tutorials for both old and new in parallel is confusing for users and hard to maintain for us and make progress on the new quickly, so we start by removing high-level tutorials for the old first to stop advertising it to users. We'll do the v0.8 release this week and after that we can remove some more things. @JouvinLea and @adonath - Thank you very much for all your work on Gammapy and developing SkyImage / SkyCube and the Sherpa-based analysis, and for agreeing to the plan to rewrite. We learned a lot from this, it was very valuable! |
@leajouvin - I changed the sky image tutorial notebook a little, the current version is here:
https://github.com/gammapy/gammapy-extra/blob/61765830218610d00a11fd413bf4a139bc506894/notebooks/image_pipe.ipynb
It works as before.
But if I change
nxpix=300, nypix=300
tonxpix=500, nypix=500
, then the background estimate fails completely (allNaN
I think, white output). There's also the weird trick to put a maximum FOV offset cut of 2.49, ideally evaluating for larger offsets would work by default (cc @joleroi) and fill zeros or extrapolate, not fail completely.@leajouvin - Can you reproduce this behaviour? Any idea what the issue is here? Probably having one pixel with offset > offset_max in the model leads to this behaviour? Is that it, or is there some other issue?
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