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Commits on Aug 14, 2024

• M-LOOP 3.3.5

  

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Commits on Feb 25, 2024

• Fix Nelder-Mead init_simplex_corner creation

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• Fix some controller.py log message typos

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Commits on Feb 7, 2024

• Fixed documentation error.

  

  spielman

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• Updated logging_config.txt

  

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• Added doc string.

  

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• Update logger to enable more informative log messages if desired.

  

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• Documentation improvement

  

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Commits on Feb 1, 2024

• Convert last_out_params to a queue.

  

  spielman

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• Fixed trivial error in the RandomLearner

  

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Commits on Nov 17, 2023

• Bump M-LOOP version to 3.3.4

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• Zero-index run numbers

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Commits on Nov 16, 2023

• Record best_in_extras in controller archive

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Commits on Sep 8, 2023

• Fix GaussianProcessVisualizer parameter scaling

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Commits on May 12, 2023

• Bump M-LOOP version to 3.3.3

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Commits on Mar 16, 2023

• Bump version numbers for 3.3.2 release

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Commits on Feb 10, 2023

• Replace deprecated np.float

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• Remove *args from ParameterScaler.__init__()

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Commits on Aug 12, 2022

• Bump version to 3.3.1

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Commits on Jul 5, 2022

• Removed a comma in Controller._update_controller_with_learner_attributes() which was accidentally left in during a copy/paste.

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Commits on Jun 30, 2022

• Clip values outside, but close to, boundaries.

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Commits on Jun 14, 2022

• Added a max_duration halting option to Controller.

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• Bumped version number to 3.3.0.

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Commits on Jun 13, 2022

• Simplified the color generation for cost vs run plots.

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• Added support to ControllerVisualizer.plot_cost_vs_run() for plotting results from third party controllers.

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• Controllers now always save an out_type value during each iteration.

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• As a further saftey check, Controller._put_params_and_out_dict() now checks that parameter values are within the allowed boundaries before sending them to the interface to be tested experimentally.

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• Learner.put_params_and_get_cost() will now raise a RuntimeError if its suggested parameter values are outside of the allowed boundaries.

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• Added warning log messages whenever the RandomVisualizer or NelderMeadVisualizer create_visualization() methods are called, as they don't currently actually generate any plots.

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• show_all_default_visualizations() now works for random and Nelder-Mead learners.

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Commits on Apr 28, 2022

• M-LOOP now uses its own numpy random number generator rather than the default one.

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Commits on Apr 26, 2022

• Corrected the scaling of the trust region limits used to mark the trust region in predicted cross section plots.

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• Corrected some cost scaling for the neural nets in learners.py and visualizations.py.

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Commits on Apr 4, 2022

• The "Showing visualizations..." log message is now only logged if show_plots is True in visualizaiton functions which accept that argument.

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Commits on Mar 23, 2022

• Removed the NeuralNetLearner.nn_training_file_dir attribute.

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