Lmfit

Latest version: v1.2.2

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1.2.2

=================================================

New features:

- add ``ModelResult.uvars`` output to a ``ModelResult`` after a successful fit
that contains ``ufloats`` from the ``uncertainties`` package which can be
used for downstream calculations that propagate the uncertainties (and
correlations) of the variable Parameters. (PR 888)

- Outputs of residual functions, including ``Model._residual``, are more
explicitly coerced to 1d-arrays of dataype Float64. This decreases the
expectation for the user-supplied code to return ndarrays, and increases the
tolerance for more "array-like" objects or ndarrays that are not Float64 or
1-dimensional. (PR 899)

- ``Model.fit`` now takes a ``coerce_farray`` option, defaulting to ``True`` to
control whether to input data and independent variables that are "array-like"
are coerced to ndarrays of datatype Float64 or Complex128. If set to
``False`` then independent data that "array-like" (``pandas.Series``, int32
arrays, etc) will be sent to the model function unaltered. The user may then
use other features of these objects, but may also need to explicitly coerce
the datatype of the result the change described above about coercing the
result causes problems. (Discussion 873; PR 899)

Bug fixes/enhancements:

- fixed bug in ``Model.make_params()`` for non-composite models that use a
prefix (Discussion 892; Issue 893; PR 895)

- fixed bug with aborted fits for several methods having incorrect or invalid
fit statistics. (Discussion 894; Issue 896; PR 897)

- ``Model.eval_uncertainty`` now correctly calculates complex (real/imaginary pairs)
uncertainties for Models that generate complex results. (Issue 900; PR 901)

- ``Model.eval`` now returns and array-like value. This adds to the coercion
features above and fixes a bug for composite models that return lists (Issue 875; PR 901)

- the HTML representation for a ``ModelResult`` or ``MinimizerResult`` are
improved, and create fewer entries in the Table of Contents for Jupyter lab.
(Issue 884; PR 883; PR 902)

1.2.2rc1

1.2.1

=================================================

Bug fixes/enhancements:

- fixed bug in ``Model.make_params()`` for initial parameter values that were
not recognized as floats such as ``np.Int64``. (Issue 871; PR 872)

- explicitly set ``maxfun`` for ``l-bfgs-b`` method when setting
``maxiter``. (Issue 864; Discussion 865; PR 866)

1.2.0

New features:

- add ``create_params`` function (PR 844)
- add ``chi2_out`` and ``nsigma`` options to ``conf_interval2d()``
- add ``ModelResult.summary()`` to return many resulting fit statistics and attributes into a JSON-able dict.
- add ``correl_table()`` function to ``lmfit.printfuncs`` and ``correl_mode`` option to ``fit_report()`` and
``ModelResult.fit_report()`` to optionally display a RST-formatted table of a correlation matrix.

Bug fixes/enhancements:

- fix bug when setting ``param.vary=True`` for a constrained parameter (Issue 859; PR 860)
- fix bug in reported uncertainties for constrained parameters by better propating uncertainties (Issue 855; PR 856)
- Coercing of user input data and independent data for ``Model`` to float64 ndarrays is somewhat less aggressive and
will not increase the precision of numpy ndarrays (see :ref:`model_data_coercion_section` for details). The resulting
calculation from a model or objective function is more aggressively coerced to float64. (Issue 850; PR 853)
- the default value of ``epsfcn`` is increased to 1.e-10 to allow for handling of data with precision less than float64
(Issue 850; PR 853)
- fix ``conf_interval2d`` to use "increase chi-square by sigma**2*reduced chi-square" to give the ``sigma``-level
probabilities (Issue 848; PR 852)
- fix reading of older ``ModelResult`` (Issue 845; included in PR 844)
- fix deepcopy of ``Parameters`` and user data (mguhyo; PR 837)
- improve ``Model.make_params`` and ``create_params`` to take optional dict of Parameter attributes (PR 844)
- fix reporting of ``nfev`` from ``least_squares`` to better reflect actual number of function calls (Issue 842; PR 844)
- fix bug in ``Model.eval`` when mixing parameters and keyword arguments (PR 844, 839)
- re-adds ``residual`` to saved ``Model`` result (PR 844, 830)
- ``ConstantModel`` and ``ComplexConstantModel`` will return an ndarray of the same shape as the independent variable
``x`` (JeppeKlitgaard, Issue 840; PR 841)
- update tests for latest versions of NumPy and SciPy.
- many fixes of doc typos and updates of dependencies, pre-commit hooks, and CI.

1.2.0rc1

=================================================

New features:

- add ``create_params`` function (PR 844)
- add ``chi2_out`` and ``nsigma`` options to ``conf_interval2d()``
- add ``ModelResult.summary()`` to return many resulting fit statistics and attributes into a JSON-able dict.
- add ``correl_table()`` function to ``lmfit.printfuncs`` and ``correl_mode`` option to ``fit_report()`` and
``ModelResult.fit_report()`` to optionally display a RST-formatted table of a correlation matrix.

Bug fixes/enhancements:

- fix bug in reported uncertainties for constrained parameters by better propating uncertainties (Issue 855; PR 856)
- Coercing of user input data and independent data for ``Model`` to float64 ndarrays is somewhat less aggressive and
will not increase the precision of numpy ndarrays (see :ref:`model_data_coercion_section` for details). The resulting
calculation from a model or objective function is more aggressively coerced to float64. (Issue 850; PR 853)
- the default value of ``epsfcn`` is increased to 1.e-10 to allow for handling of data with precision less than float64
(Issue 850; PR 853)
- fix ``conf_interval2d`` to use "increase chi-square by sigma**2*reduced chi-square" to give the ``sigma``-level
probabilities (Issue 848; PR 852)
- fix reading of older ``ModelResult`` (Issue 845; included in PR 844)
- fix deepcopy of ``Parameters`` and user data (mguhyo; PR 837)
- improve ``Model.make_params`` and ``create_params`` to take optional dict of Parameter attributes (PR 844)
- fix reporting of ``nfev`` from ``least_squares`` to better reflect actual number of function calls (Issue 842; PR 844)
- fix bug in ``Model.eval`` when mixing parameters and keyword arguments (PR 844, 839)
- re-adds ``residual`` to saved ``Model`` result (PR 844, 830)
- ``ConstantModel`` and ``ComplexConstantModel`` will return an ndarray of the same shape as the independent variable
``x`` (JeppeKlitgaard, Issue 840; PR 841)
- update tests for latest versions of NumPy and SciPy.
- many fixes of doc typos and updates of dependencies, pre-commit hooks, and CI.

1.1.0

=================================================

Supported Python Versions: 3.7, 3.8, 3.9, 3.10, 3.11
Minimal requirements: numpy>=1.19, scipy>=1.6, uncertainties>=3.1.4, asteval>=0.9.28

New features:

- add ``Pearson4Model`` (lellid; PR 800)
- add ``SplineModel`` (PR 804)
- add R^2 ``rsquared`` statistic to fit outputs and reports for Model fits (Issue 803; PR 810)
- add calculation of ``dely`` for model components of composite models (Issue 761; PR 826)

Bug fixes/enhancements:

- make sure variable ``spercent`` is always defined in ``params_html_table`` functions (reported by MySlientWind; Issue 768, PR 770)
- always initialize the variables ``success`` and ``covar`` the ``MinimizerResult`` (reported by Marc W. Pound; PR 771)
- build package following PEP517/PEP518; use ``pyproject.toml`` and ``setup.cfg``; leave ``setup.py`` for now (PR 777)
- components used to create a ``CompositeModel`` can now have different independent variables (Julian-Hochhaus; Discussion 787; PR 788)
- fixed function definition for ``StepModel(form='linear')``, was not consistent with the other ones (matpompili; PR 794)
- fixed height factor for ``Gaussian2dModel``, was not correct (matpompili; PR 795)
- for covariances with negative diagonal elements, we set the covariance to ``None`` (PR 813)
- fixed linear mode for ``RectangleModel`` (arunpersaud; Issue 815; PR 816)
- report correct initial values for parameters with bounds (Issue 820; PR 821)
- allow recalculation of confidence intervals (jagerber48; PR 798)
- include 'residual' in JSON output of ModelResult.dumps (mac01021; PR 830)
- supports and is tested against Python 3.11; updated minimum required version of SciPy, NumPy, and asteval (PR 832)

Deprecations:

- remove support for Python 3.6 which reached EOL on 2021-12-23 (PR 790)

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