Fix segmentation fault #62
Merged
Conversation
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
astrofrog
commented
Jan 27, 2023
|
I think the segfault was actually my fault, now just seeing some regular failures - one is due to numpy/numpy#23110 |
This occurred when e.g. tx < xmax but tx was close enough to xmax that ix was as if tx == xmax.
astrofrog
force-pushed
the
fix-segfault
branch
from
ebe9264
to
49c20f6
Compare
astrofrog
force-pushed
the
fix-segfault
branch
from
49c20f6
to
a1b7d31
Compare
…ted values as these trip many corner cases in Numpy itself and we can never aim for 100% agreement on all these corner cases.
astrofrog
force-pushed
the
fix-segfault
branch
from
f784d7b
to
7cef589
Compare
astrofrog
force-pushed
the
fix-segfault
branch
from
f1e4ff7
to
6d5a4ca
Compare
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
@olebole - I think this fixes the segmentation faults in our code that occurred in #60 but I'm now running into segmentation faults in Numpy itself during the computation of the reference values. That will take a bit longer to investigate. These are basically popping up because of new test cases Hypothesis is doing, but I need to figure out what is triggering the segfaults on the Numpy side.