OpenMDAO Logo

An open-source framework for efficient multidisciplinary optimization.

OpenMDAO 1.7.1

OpenMDAO v1.7.1 is now available!

Feel free to ask questions on our Stack Overflow tag if you experience any difficulties.

Here are the release notes for 1.7.1:
OpenMDAO Version 1.7.1 Alpha Release Notes
July 18, 2016

* Newton and NLGS solvers now also check for convergence by monitoring the unknown vectors for when it falls below a tolerance `utol`.
* The print_all_convergence function in Problem now has an argument level that lets you choose between:
0 — only display failures
1 — display iteration counts
2 — display residuals each iteration (this is the default)
* Added a SAND example from our users into our Examples section in our documentation.
* Implemented better error handling when user gives too many args to connect.
* Modified linear_system so that its derivatives are solved with an additional LU back-substitution solve_linear.

Bug fixes:
* Fixed bug in relevance checking related to pass_by_obj vars.
* Fixed doc problem where multiple requirements sections listed under Examples on docs main page.
* Fix for keyerror when you have an array scaler on a design variable or constraint and are using SLSQP
(so the return_type for jacobian is array) under full_model fd.
* Non-python files are no longer missing from our distribution.
* Fixed a bug where residual scaling/unscaling was applied to a finite-differenced Jacobian when it shouldn’t be.
* Fixed bug in Newton derivative calculation when containing system is set to ‘fd’ or ‘cs’.
* Fix for Newton when solving a system that has been set to ‘fd’ (or ‘cs’)

Comments are closed.

Fork me on GitHub