-
Notifications
You must be signed in to change notification settings - Fork 155
New issue
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
chore(test): lower p_value_limit to decrease test failure probability #1787
Merged
Merged
Changes from all commits
Commits
File filter
Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
There are no files selected for viewing
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
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
Oops, something went wrong.
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Outdated suggestions cannot be applied.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.
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
how much does this slow the test down ?
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
Not at all, the number of samples has not changed
It's just more permissive
This new value is a bit arbitrary, like the previous one was
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
I see, what sort of impact does this have on the "tolerance" ?
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
I don't see how this is better than the test_random_from_distribution_custom_mod test function that verifies the actual p-value
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
Decreasing the
p_value_limit
means there are less false positives (test fails where it shouldn't) but more false negatives.False positives rate is the
p_value_limit
which is well known.False negative rates depend on the real distribution (if it's not uniform). It's hard to quantify since we don't know what this distribution is.
For a fixed
p_value_limit
, increasing the number of samples reduces the false negative rates (of all other distributions) but again it's hard to quantify.So it's hard to know by how much the number of samples needs to be increased to compensate for the decrease of the
p_value_limit
impact on the false negative rates.Compared to combining n sub-tests (while keeping the same total number of samples), we can detect correlated deviations in sample-sets of sub-tests which individually appear plausible (even when combined as if they were independent) but when analyzed together are much less plausible, which means the detection is finer.