Comments (13)
I am seeing the same thing for M3 chips and independently found analogous (or worse results). I did try set input E-modes to 0 but still recover crazy B-modes spectra regardless. In the attached plot an example of the result, where theory in the error bar is the usual Gaussian "fsky-approximated" error bar.
Note that problem also affects E-modes even if only B-modes are purified.
For reference, also compiling from source didn't fix the problem so it is probably not a conda package problem.
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Could you try installing the latest version currently on conda (v2)? I'm hoping that any issues with the new Mac chips are now gone.
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Sadly I'm seeing consistent results even with V2 (the variance is slightly worse)
![Screenshot 2024-06-08 at 15 15 29](https://private-user-images.githubusercontent.com/17526022/337880132-5b6b9339-1a10-44e8-85fe-072a0e20cf05.png?jwt=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.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.IO2tKZBAX3U3Ohpc_R1gOVvN4_sej6790YKMAuoEgEQ)
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OK, thanks a lot.
The fact that this still happens with the newer version narrows it down, I think. Most of the code is completely different, so this can only be coming from a couple of things. I'm trying to test this on my own without a mac, but in the meantime, can I check:
- Does this only happen with purification, and otherwise the code works as expected?
- If the answer above is yes, can you check if the two apodised masks (generated in linux or mac) are the same?
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@fjaviersanchez is not able to reproduce this with a fresh install from conda. His setup is:
-
M2 chip
-
healpy version: '1.16.6' , numpy version: '1.26.4', pymaster version: 2.0
@gfabbian can I check how this differs from yours?
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(also, just to check, you are indeed installing from conda, correct?)
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For more context, this is the recipe I followed to install the package:
conda create -n namaster2 namaster -c conda-forge
conda activate namaster2
conda install healpy -c conda-forge
I can play a bit with the numpy
and healpy
versions to see if those are responsible.
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@fjaviersanchez are you using conda with osx-arm64 platform or osx-64?
I have the same numpy/healpy as yours and see the issue even when creating a new environment :(. I also confirm issues show up in purification. Happy to rerun any test code you have. I can also send out a notebook if useful.
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Hmm, I just checked and this is my conda info:
platform : osx-arm64
I am using python 3.12. I haven't checked with 3.11 though, and I know that some people had issues with 3.11 with other packages. I can check!
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I believe the only thing different at this point is the chip as I also have python 3.12.
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Humm, but @jchamilton75 said he was using an M2 above...
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@jchamilton75 can you confirm if you see the problem with a fresh environment installation?
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After further offline iterations with @gfabbian (thanks so much for this @gfabbian ), it seems the issue was conflicting old versions of ducc0 installed via pip. When installing all packages consistently from conda the problem disappears (@gfabbian please correct me if what I just said is inaccurate).
I'll close this for now, but feel free to reopen if the issue reappears.
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