-
Notifications
You must be signed in to change notification settings - Fork 47
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
Support ipopt with gradient approximation #1310
Conversation
Codecov ReportAttention: Patch coverage is
❗ Your organization needs to install the Codecov GitHub app to enable full functionality. Additional details and impacted files@@ Coverage Diff @@
## develop #1310 +/- ##
============================================
- Coverage 83.14% 53.31% -29.83%
============================================
Files 153 153
Lines 12451 12459 +8
============================================
- Hits 10352 6643 -3709
- Misses 2099 5816 +3717 ☔ View full report in Codecov by Sentry. |
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.
Thanks, as discussed would probably good to have a small test for this.
just added a test. Not sure what the failing julia test has to do with it. |
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.
Looks good, thanks :)
Ipopt supports approximation of Jacobian/Gradients. With this PR pyPESTO will support it, too (fixes #1284).