Comments (9)
Ignore or, better, delete the .github/workflows/mirror_to_gitlavb.yml
file, i.e. this one.
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Ok, I'll do this into my development branch, so this will come in a next merge request
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I think I should rather restrict the execution to this repository. This way forks will simply ignore this workflow.. I’ll have a look at it asap.
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Look at the recent commit. I added this line which should stop the job from running on forks. Let me know if that does the trick.
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That's weird ... now it's the pytest before that fails : https://github.com/tlunet/pySDC/runs/5389320157?check_suite_focus=true
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That's a different issue... with the new quadrature, the error is much higher in the tests than they used to be. Since the tests take random values, sometimes the bounds are too strict, still. I have no idea what the new quadrature does this (need to set the bounds from ~1E-14
to ~1E-10
, it seems).
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Can't you just set a fixed random seed for the tests (at least, one that work). And btw, what do you mean by new quadrature ? Is it the optimized implementation I provided some time ago ?
from pysdc.
Yes, I could, but so far this was not necessary. And yes, this is the implementation you provided. I have no idea what's going on with the tests (all of those in the file are affected).
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I'll try to look into it. But in the meantime, the mirror test passed on my development branch, so I guess this issue can be closed 😉
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Related Issues (20)
- Rework default interface for Problem class
- Rework problem class implementations
- Exclude code from coverage HOT 12
- Reduce computation time for some tests HOT 4
- desc = _cusparse.createDnVec(x.size, x.data.ptr, cuda_dtype) HOT 10
- Suggestion for code formating HOT 1
- Improve Problem classes Documentation HOT 2
- Implement Multistep Methods for Comparison HOT 3
- Conda recent changes to use mamba solver per default HOT 1
- Timeout issues with mac runners HOT 3
- How to use pySDC with Fenics? HOT 1
- qDelta=PIC not giving the same result wether the sweeper is explicit or implicit HOT 2
- Parallel modifications of the `testequation0d` class due to GPU implementations HOT 3
- Spread initialization for non-autonomous problem HOT 10
- Generic implementation of a multicomponent Datatype class HOT 9
- Epsilon-embedding for differential equations - Efficient implementation HOT 3
- CodeQL fails for C/C++ code
- Couple with Gitlab-Repo HOT 1
- Issues with transfer operators HOT 3
- Can we delete the (old) dedalus branch ? HOT 2
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