Skip to content

MNT clarification on check_pca_float_dtype_preservation's new tol level. #15819

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.

Sign up for GitHub

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

Merged
merged 1 commit into from
Dec 10, 2019
Merged

MNT clarification on check_pca_float_dtype_preservation's new tol level. #15819

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
3 changes: 3 additions & 0 deletions sklearn/decomposition/tests/test_pca.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -532,6 +532,9 @@ def check_pca_float_dtype_preservation(svd_solver):
assert pca_64.transform(X_64).dtype == np.float64
assert pca_32.transform(X_32).dtype == np.float32

# the rtol is set such that the test passes on all platforms tested on
# conda-forge: PR#15775
Copy link
Member

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

It takes me some time to figure out that this PR is in scikit-learn :)

Copy link
Member

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

Yeah, but then conda-forge doesn't have 5 digit PRs, I think it's fine )

# see: https://github.com/conda-forge/scikit-learn-feedstock/pull/113
assert_allclose(pca_64.components_, pca_32.components_, rtol=2e-4)


Expand Down