Skip to content

Latest commit

 

History

History
70 lines (50 loc) · 3.87 KB

CHANGELOG.md

File metadata and controls

70 lines (50 loc) · 3.87 KB

Change Log

All notable changes to this project will be documented in this file.

The format is based on Keep a Changelog and this project adheres to Semantic Versioning.

[0.7.2] - 2024-08-16

Fixed

  • Added additional logic in galibrate.run_gao_julia for checking if the OS is Linux and turning off Julia pre-compilation for PyJulia; ; fix for Issue #14

[0.7.1] - 2024-07-23

Fixed

  • Updated the logic for setting the optimizer backend via the run_gao variable; fix for Issue #12

[0.7.0] - 2023-04-27 to 2024-07-23

Added

  • New benchmarks module that defines functions often used to test and benchmark single-objective optimization applications.
  • New examples for each of the functions defined in the benchmarks functions.
  • 3-point line example.
  • PySB double-enzymatic model example.
  • Functions to resume/continue GAO runs for additional generations: GAO.resume and underlying functions run_gao_py.continue_gao, run_gao_numba.continue_gao, and run_gao_cython.continue_gao.
  • run_gao_julia which ports key functions to Julia via PyJulia as another alternative to Numba or Cython acceleration.
  • Notebook 01_profile-performance in a new notebooks directory.
  • Notebook 02_benchmark-parametric-scaling-performance the new notebooks directory.
  • tests directory.
  • Test code for the galibrate.benchmarks and galibrate.sampled_parameters.
  • Test code for galibrate.gao and the galibrate.gao.GAO class, as well as different integrations using the Python, Cython, Numba, and Julia backend versions: test_gao, test_gao_py, test_gao_numba, test_gao_cython, and test_gao_julia.
  • Test code for the GaoIt class in the pysb submodule galibrate.pysb.galibrate_it: test code in test_pysb
  • Test code for the galibrate.run_gao_numba, galibrate.run_gao_julia, and galibrate.run_gao_cython modules: test code in test_rungaonumba, test_rungaojulia, and test_rungaocython, respectively.
  • New functions in galibrate.gao that load specific backend version: _set_run_gao_numba, etc.

Changed

  • The setup.py uses setuptools now instead of distutils. The new setup includes the Cython .pyx and Julia .jl files as data files in the package.
  • Renamed the galibrate.pysb_utils to galibrate.pysb.
  • Formatted code using the Black format.

Fixed

  • Corrected instances of self.parm in the GaoIt class to self.parms; fix for Issue #8
  • Added an __init__.py under pysb_utils that imports the GaoIt and GAlibrateIt classes; fix for Issue #7
  • Error in the GaoIt.mask function which called self.names instead of correct fucntion call self.names().
  • Error in the GaoIt.add_all_nonkinetic_params with misspelled pysb_model.paramters - correct: pysb_model.parameters
  • Switched instances of np.int to np.int64 or np.int_ (Cython module) for the following NumPy deprecation warning: DeprecationWarning: np.int is a deprecated alias for the builtin int.

[0.6.0] - 2020-06-21

Added

  • core GA now returns an array with fitness value of the fittest individual from each generation which can be accessed from the GAO property GAO.best_fitness_per_generation.

Fixed

  • Bug fix in core GA for sorting the population before selection and mating.

[0.5.0] - 2020-06-20

Added

  • Optional progress bar to monitor passage of generations during GAO run that is only displayed if tqdm is installed.
  • Optional multiprocessing based parallelism when evaluating the fitness function over the population during a GAO run.

[Unreleased] - yyyy-mm-dd

N/A

Added

Changed

Fixed