-
-
Notifications
You must be signed in to change notification settings - Fork 26k
[MRG] Replace all the deprecated random_integers by randint. #6712
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
Conversation
@@ -627,7 +627,7 @@ def lasso_stability_path(X, y, scaling=0.5, random_state=None, | |||
paths = Parallel(n_jobs=n_jobs, verbose=verbose)( | |||
delayed(_lasso_stability_path)( | |||
X, y, mask=rng.rand(n_samples) < sample_fraction, | |||
weights=1. - scaling * rng.random_integers(0, 1, | |||
weights=1. - scaling * rng.randint(0, 1, | |||
size=(n_features,)), |
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.
Indentation
Please check indentation, and where possible avoid line wrapping. |
26921cd
to
d2a8abd
Compare
Sorry for that, it's corrected now. |
LGTM, +1 once CI is all-green. |
d2a8abd
to
fc5e305
Compare
@@ -23,7 +23,11 @@ def compute_bench(samples_range, features_range): | |||
print('Iteration %03d of %03d' % (it, max_it)) | |||
print('==============================') | |||
print() | |||
data = nr.random_integers(-50, 50, (n_samples, n_features)) | |||
<<<<<<< HEAD |
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.
There are some merge conflicts you missed...
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.
ooops
+1 from me too! |
+1 after cleaning the conflict |
fc5e305
to
91c4279
Compare
Sorry for the forgotten HEAD. |
91c4279
to
af42686
Compare
The function random_integers was recently deprecated in numpy resulting a lot of warnings during the test. This PR is done to correct that.