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Published March 26, 2017 | Version 0.9.6
Software Open

lmfit/lmfit-py: 0.9.6

  • 1. University of Chicago
  • 2. UCLA
  • 3. Freie Universität Berlin
  • 4. Brookhaven National Lab
  • 5. Stanford University
  • 6. University of Copenhagen
  • 7. Brookhaven National Laboratory
  • 8. MPI for Nuclear Physics
  • 9. Los Alamos National Lab
  • 10. Uchicago
  • 11. Technical University of Denmark, University of Ulm
  • 12. @JRCSTU
  • 13. Well Typed LLP

Description

Partial release notes for lmfit 0.9.6:

  • Support for SciPy 0.14 has been dropped: SciPy 0.15 is now required. This is especially important for lmfit maintenance, as it means we can now rely on SciPy having code for differential evolution and do not need to keep a local copy.

  • A brute force method was added, which can be used either with :meth:Minimizer.brute or using the method='brute' option to :meth:Minimizer.minimize. This method requires finite bounds on all varying parameters, or that parameters have a finite brute_step attribute set to specify the step size.

  • Custom cost functions can now be used for the scalar minimizers using the reduce_fcn option.

  • Many improvements to documentation and docstrings in the code were made. As part of that effort, all API documentation in this main Sphinx documentation now derives from the docstrings.

  • Uncertainties in the resulting best-fit for a model can now be calculated from the uncertainties in the model parameters.

  • Parameters have two new attributes: brute_step, to specify the step size when using the brute method, and user_data, which is unused but can be used to hold additional information the user may desire. This will be preserved on copy and pickling.

  • Several bug fixes and cleanups.

  • Versioneer was updated to 0.18.

  • Tests can now be run either with nose or pytest.

Files

lmfit/lmfit-py-0.9.6.zip

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