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Releases: pybop-team/PyBOP

v24.9.1

18 Sep 07:48
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What's Changed

Patch release for yanked v24.9.0.

New Contributors

Full Changelog: https://github.com/pybop-team/PyBOP/blob/develop/CHANGELOG.md

v24.9.0

11 Sep 13:55
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What's Changed

New Contributors

Full Changelog: https://github.com/pybop-team/PyBOP/blob/develop/CHANGELOG.md

v24.6.1

31 Jul 12:29
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What's Changed

  • Release v24.6.1 by @BradyPlanden in #415
  • Increments supported PyBaMM version to >= v24.5

Full Changelog: https://github.com/pybop-team/PyBOP/blob/main/CHANGELOG.md#v2461---2024-07-31

v24.6

08 Jul 12:23
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Full Changelog: https://github.com/pybop-team/PyBOP/blob/main/CHANGELOG.md#v246---2024-07-08

What's Changed

New Contributors

v24.3.1

18 Jun 11:29
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Full Changelog: v24.3...v24.3.1

v24.3

25 Mar 20:03
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What's Changed

New Contributors

Full Changelog: https://github.com/pybop-team/PyBOP/blob/develop/CHANGELOG.md

v23.12

20 Dec 09:10
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Features

  • #141 - Adds documentation with Sphinx and PyData Sphinx Theme. Updates docstrings across package, relocates costs and dataset to top-level of package. Adds noxfile session and deployment workflow for docs.
  • #131 - Adds SciPyDifferentialEvolution optimiser, adds functionality for user-selectable maximum iteration limit to SciPyMinimize, NLoptOptimize, and BaseOptimiser classes.
  • #107 - Adds Equivalent Circuit Model (ECM) with examples, Import/Export parameter methods ParameterSet.import_parameter and ParameterSet.export_parameters, updates default FittingProblem.signal definition to "Voltage [V]", and testing infrastructure
  • #127 - Adds Windows and macOS runners to the test_on_push action
  • #114 - Adds standard plotting class pybop.StandardPlot() via plotly backend
  • #114 - Adds quick_plot(), plot_convergence(), and plot_cost2d() methods
  • #114 - Adds a SciPy minimize example and logging for non-Pints optimisers
  • #116 - Adds PSO, SNES, XNES, ADAM, and IPropMin optimisers to PintsOptimisers() class
  • #38 - Restructures the Problem classes ahead of adding a design optimisation example
  • #120 - Updates the parameterisation test settings including the number of iterations
  • #145 - Reformats Dataset to contain a dictionary and signal into a list of strings

Breaking Changes

  • #38 - Restructures the Problem classes into FittingProblem and DesignProblem. FittingProblem replaces previous Problem class
  • #145 - Reformats Dataset class to contain a dictionary and signal into a list of strings.

v23.12rc0

19 Dec 09:38
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v23.12rc0 Pre-release
Pre-release

CHANGELOG

  • #141 - Adds documentation with Sphinx and PyData Sphinx Theme. Updates docstrings across package, relocates costs and dataset to top-level of package. Adds noxfile session and deployment workflow for docs.
  • #131 - Adds SciPyDifferentialEvolution optimiser, adds functionality for user-selectable maximum iteration limit to SciPyMinimize, NLoptOptimize, and BaseOptimiser classes.
  • #107 - Adds Equivalent Circuit Model (ECM) with examples, Import/Export parameter methods ParameterSet.import_parameter and ParameterSet.export_parameters, updates default FittingProblem.signal definition to "Voltage [V]", and testing infrastructure
  • #127 - Adds Windows and macOS runners to the test_on_push action
  • #114 - Adds standard plotting class pybop.StandardPlot() via plotly backend
  • #114 - Adds quick_plot(), plot_convergence(), and plot_cost2d() methods
  • #114 - Adds a SciPy minimize example and logging for non-Pints optimisers
  • #116 - Adds PSO, SNES, XNES, ADAM, and IPropMin optimisers to PintsOptimisers() class
  • #38 - Restructures the Problem classes ahead of adding a design optimisation example
  • #120 - Updates the parameterisation test settings including the number of iterations
  • #145 - Reformats Dataset to contain a dictionary and signal into a list of strings

v23.11

20 Nov 15:55
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Initial release v23.11

  • Pints, NLOpt, and SciPy optimisers available
  • SumofSquareError and RootMeanSquareError cost functions available
  • Parameter and dataset classes available
  • Examples here