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An open-source framework for efficient multidisciplinary optimization.

OpenMDAO 1.5.0 Released!

OpenMDAO v1.5.0 is now available!
And remember, we are now pip-installable, as we are now indexed on pypi:

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

Here are the release notes for 1.5.0:

OpenMDAO Version 1.5.0 Alpha Release Notes
* Proper MPI/PETSC installation/testing/usage now documented in User Guide.
* User can run a DOE in parallel.
* Removed pyoptsparse output from our test output to declutter things.
* User can run a model in parallel using pass_by_obj data transfer under MPI.
* Pyoptdriver now supports saving its history file.
* User can call cleanup method on problem that closes all recorders.
* Converted Brent driver from OpenMDAO Classic to OpenMDAO 1.x
* Case recorder will (optionally) save gradient information from driver cases that requested a gradient in that run.
* OpenMDAO now makes suggestions to user how to improve efficiency when the layout of systems in the model is not optimal.
* OpenMDAO now uses feature of pyOptSparse that allows a single Jacobian element to be sparse.

* User now gets an error if they pass `promotes` keyword arg into any System.
* Dealt with the duplicate executions of explicit comps when using a solver.
* Fixed bug in accessing prob.unknowns and prob.resids.
* Fixed bug where pyOptSparse/SLSQP failed with Pointer.
* Fixed a bug in pass_by_obj_check_derivatives.
* Fixed MPI hangs that were related to use of Python 3.
* Fixed a bug in ExecComp expressions that didn’t allow the use of ‘:’ notation.
* Added missing documentation of ‘.keys()’ in recorder documentation.
* Fixed a bug in the pass_by_obj params.
* Fixed a problem in recent CADRE runs.

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