lmfit-py - 1.3.0 Latest Release

Published by newville 7 months ago

Version 1.3.0 Release Notes (April 4, 2024)

New features:

add 'min_rel_change' as optional variable in calculation of confidence intervals with
Model.conf_interval(). (PR #937).
Model.eval_uncertainty now takes an optional dscale parameter (default value of 0.01) to
set the step size for calculating derivatives (PR #933).
add calculation of predicted_interval to Model.eval_uncertainty (PR #933).

Bug fixes/enhancements:

restore best-fit parameter values for high accuracy values of constrained values (PR #907)
improvement to Model for the difference between Parameter, "independent variable", and
"option". With this change, keyword arguments to model functions with non-numerice
default values such as do_thing=True, or form='linear' has those arguments
become clearly identified as independent variables,and use the provided values as
default values. (PR #941)
better saving/loading saved states of Model now use dill, have several cleanups, and
are now versioned for future-proofing. Also, propagate funcdets for Parameters when
loading a Model. (PR #932, PR #934)
in the TNC method, maxfun is used instead of maxiter.
fix bug calculating r-squared for fits with weights (PR #921, PR #923)
fix bug in modelresult.eval_uncertainty() after load_modelresult() (PR #909)
use StringIO for pandas.read_json.
add test for MinimizerResult.uvars after successful fit (PR #913)
adding an example using basinhopping, can take other methods as command-line argument

Maintenance/Deprecations:

drop support for Python 3.7 that reached EOL on 2023-06-27 (PR #927)
fix tests for Python 3.12 and Python 3.13-dev
increase minimum numpy verstio to 1.23 and scipy to 1.8.
updates for compatibility with numpy 2.0
the dill package is now required. (#940)
build switchded to use pyproject.toml (#928)
fix broken links in Examples gallery
fix intersphinx mapping to scipy docs.

lmfit-py -

Published by newville over 1 year ago

Version 1.2.2 Release Notes (July 14, 2023)

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 datatype 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)

lmfit-py -

Published by newville over 1 year ago

Version 1.2.2 Release Notes (July 14, 2023)

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)

lmfit-py -

Published by newville over 1 year ago

Version 1.2.1 Release Notes (May 02, 2023)

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)

lmfit-py - 1.20

Published by newville over 1 year ago

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.

lmfit-py -

Published by newville over 1 year ago

Version 1.2.0rc1 Release Notes (April 03, 2023)

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.

lmfit-py -

Published by newville almost 2 years ago

Version 1.1.0 Release Notes (November 27, 2022)

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)

lmfit-py -

Published by newville almost 2 years ago

Version 1.0.4rc1

New features:

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

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)

Deprecations:

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

lmfit-py - 1.0.3

Published by newville about 3 years ago

Version 1.0.3 Release Notes (October 14, 2021)

Potentially breaking change:

argument x is now required for the guess method of Models (Issue #747; PR #748)

To get reasonable estimates for starting values one should always supply both x and y values; in some cases it would work
when only providing data (i.e., y-values). With the change above, x is now required in the guess method call, so scripts might
need to be updated to explicitly supply x.

Bug fixes/enhancements:

do not overwrite user-specified figure titles in Model.plot() functions and allow setting with title keyword argument (PR #711)
preserve Parameters subclass in deepcopy (@jenshnielsen; PR #719)
coerce data and indepdent_vars to NumPy array with dtype=float64 or dtype=complex128 where applicable (Issues #723 and #728)
fix collision between parameter names in built-in models and user-specified parameters (Issue #710 and PR #732)
correct error message in PolynomialModel (@kremeyer; PR #737)
improved handling of altered JSON data (Issue #739; PR #740, reported by Matthew Giammar)
map max_nfev to maxiter when using differential_evolution (PR #749, reported by Olivier B.)
correct use of noise versus experimental uncertainty in the documentation (PR #751, reported by Andrés Zelcer)
specify return type of eval method more precisely and allow for plotting of (Complex)ConstantModel by coercing their
float, int, or complex return value to a numpy.ndarray (Issue #684 and PR #754)
fix dho (Damped Harmonic Oscillator) lineshape (PR #755; @rayosborn)
reset Minimizer._abort to False before starting a new fit (Issue #756 and PR #757; @azelcer)
fix typo in guess_from_peak2d (@ivan-usovl; PR #758)

Various:

update asteval dependency to >= 0.9.22 to avoid DeprecationWarnings from NumPy v1.20.0 (PR #707)
remove incorrectly spelled DonaichModel and donaich lineshape, deprecated in version 1.0.1 (PR #707)
remove occurrences of OrderedDict throughout the code; dict is order-preserving since Python 3.6 (PR #713)
update the contributing instructions (PR #718; @martin-majlis)
(again) defer import of matplotlib to when it is needed (@zobristnicholas; PR #721)
fix description of name argument in Parameters.add (@kristianmeyerr; PR #725)
update dependencies, make sure a functional development environment is installed on Windows (Issue #712)
use setuptools_scm for version info instead of versioneer (PR #729)
transition to using f-strings (PR #730)
mark test_manypeaks_speed.py as flaky to avoid intermittent test failures (repeat up to 5 times; PR #745)
update scipy dependency to >= 1.14.0 (PR #751)
improvement to output of examples in sphinx-gallery and use higher resolution figures (PR #753)
remove deprecated functions lmfit.printfuncs.report_errors and asteval argument in Parameters class (PR #759)

lmfit-py -

Published by newville over 3 years ago

Version 1.0.2 officially supports Python 3.9 and has dropped support for Python 3.5. The minimum version
of the following dependencies were updated: asteval>=0.9.21, numpy>=1.18, and scipy>=1.3.

New features:

added two-dimensional Gaussian lineshape and model (PR #642; @mpmdean)
all built-in models are now registered in lmfit.models.lmfit_models; new Model class attribute valid_forms (PR #663; @rayosborn)
added a SineModel (PR #676; @lneuhaus)
add the run_mcmc_kwargs argument to Minimizer.emcee to pass to the emcee.EnsembleSampler.run_mcmc function (PR #694; @rbnvrw)

Bug fixes:

ModelResult.eval_uncertainty should use provided Parameters (PR #646)
center in lognormal model can be negative (Issue #644, PR #645; @YoshieraHuang)
restore best-fit values after calculation of covariance matrix (Issue #655, PR #657)
add helper-function not_zero to prevent ZeroDivisionError in lineshapes and use in exponential lineshape (Issue #631, PR #664; @s-weigand)
save last_internal_values and use to restore internal values if fit is aborted (PR #667)
dumping a fit using the lbfgsb method now works, convert bytes to string if needed (Issue #677, PR #678; @leonfoks)
fix use of callable Jacobian for scalar methods (PR #681; @mstimberg)
preserve float/int types when encoding for JSON (PR #696; @jedzill4)
better support for saving/loading of ExpressionModels and assure that init_params and init_fit are set when loading a ModelResult (PR #706)

Various:

update minimum dependencies (PRs #688, #693)
improvements in coding style, docstrings, CI, and test coverage (PRs #647, #649, #650, #653, #654; #685, #668, #689)
fix typo in Oscillator (PR #658; @flothesof)
add example using SymPy (PR #662)
allow better custom pool for emcee() (Issue #666, PR #667)
update NIST Strd reference functions and tests (PR #670)
make building of documentation cross-platform (PR #673; @s-weigand)
relax module name check in test_check_ast_errors for Python 3.9 (Issue #674, PR #675; @mwhudson)
fix/update layout of documentation, now uses the sphinx13 theme (PR #687)
fixed DeprecationWarnings reported by NumPy v1.2.0 (PR #699)
increase value of tiny and check for it in bounded parameters to avoid "parameter not moving from initial value" (Issue #700, PR #701)
add max_nfev to basinhopping and brute (now supported everywhere in lmfit) and set to more uniform default values (PR #701)
use Azure Pipelines for CI, drop Travis (PRs #696 and #702)

lmfit-py -

Published by newville over 4 years ago

Version 1.0.1 Release Notes

Version 1.0.1 is the last release that supports Python 3.5. All newer version will
require 3.6+ so that we can use formatting-strings and rely on dictionaries being ordered.

New features:

added thermal distribution model and lineshape (PR #620; @mpmdean)
introduced a new argument max_nfev to uniformly specify the maximum number of function evalutions (PR #610)
Please note: all other arguments (e.g., maxfev, maxiter, ...) will no longer be passed to the underlying
solver. A warning will be emitted stating that one should use max_nfev.
the attribute call_kws was added to the MinimizerResult class and contains the keyword arguments that are
supplied to the solver in SciPy.

Bug fixes:

fixes to the load and __setstate__ methods of the Parameter class
fixed failure of ModelResult.dump() due to missing attributes (Issue #611, PR #623; @mpmdean)
guess_from_peak function now also works correctly with decreasing x-values or when using
pandas (PRs #627 and #629; @mpmdean)
the Parameter.set() method now correctly first updates the boundaries and then the value (Issue #636, PR #637; @arunpersaud)

Various:

fixed typo for the use of expressions in the documentation (Issue #610; @jkrogager)
removal of PY2-compatibility and unused code and improved test coverage (PRs #619, #631, and #633)
removed deprecated isParameter function and automatic conversion of an uncertainties object (PR #626)
inaccurate FWHM calculations were removed from built-in models, others labeled as estimates (Issue #616 and PR #630)
corrected spelling mistake for the Doniach lineshape and model (Issue #634; @rayosborn)
removed unsupported/untested code for IPython notebooks in lmfit/ui/*

lmfit-py -

Published by newville almost 5 years ago

Version 1.0.0 supports Python 3.5, 3.6, 3.7, and 3.8

New features:

no new features are introduced in 1.0.0.

Improvements:

support for Python 2 and use of the six package are removed. (PR #612)

Various:

documentation updates to clarify the use of emcee. (PR #614)

lmfit-py -

Published by newville almost 5 years ago

Version 0.9.15 is the last release that supports Python 2.7; it now also fully suports Python 3.8.

New features, improvements, and bug fixes:

move application of parameter bounds to setter instead of getter (PR #587)
add support for non-array Jacobian types in least_squares (Issue #588, @ezwelty in PR #589)
add more information (i.e., acor and acceptance_fraction) about emcee fit (@j-zimmermann in PR #593)
"name" is now a required positional argument for Parameter class, update the magic methods (PR #595)
fix nvars count and bound handling in confidence interval calculations (Issue #597, PR #598)
support Python 3.8; requires asteval >= 0.9.16 (PR #599)
only support emcee version 3 (i.e., no PTSampler anymore) (PR #600)
fix and refactor prob_func in confidence interval calculations (PR #604)
fix adding Parameters with custom user-defined symbols (Issue #607, PR #608; thanks to @gbouvignies for the report)

Various:

bump requirements to LTS version of SciPy/ NumPy and code clean-up (PR #591)
documentation updates (PR #596, and others)
improve test coverage and Travis CI updates (PR #595, and others)
update pre-commit hooks and configuration in setup.cfg

To-be deprecated:

function Parameter.isParameter and conversion from uncertainties.core.Variable to value in _getval (PR #595)

lmfit-py -

Published by newville almost 5 years ago

version 0.9.15rc1

Version 0.9.15 is the last release that supports Python 2.7; it now also fully supports Python 3.8.

New features, improvements, and bug fixes:

move application of parameter bounds to setter instead of getter (PR #587)
add support for non-array Jacobian types in least_squares (Issue #588, @ezwelty in PR #589)
add more information (i.e., acor and acceptance_fraction) about emcee fit (@j-zimmermann in PR #593)
"name" is now a required positional argument for Parameter class, update the magic methods (PR #595)
fix nvars count and bound handling in confidence interval calculations (Issue #597, PR #598)
support Python 3.8; requires asteval >= 0.9.16 (PR #599)
only support emcee version 3 (i.e., no PTSampler anymore) (PR #600)
fix and refactor prob_bunc in confidence interval calculations (PR #604)
fix adding Parameters with custom user-defined symbols (Issue #607, PR #608; thanks to @gbouvignies for the report)

Various:

bump requirements to LTS version of SciPy/ NumPy and code clean-up (PR #591)
documentation updates (PR #596, and others)
improve test coverage and Travis CI updates (PR #595, and others)
update pre-commit hooks and configuration in setup.cfg

To-be deprecated:

function Parameter.isParameter and conversion from uncertainties.core.Variable to value in _getval (PR #595)

lmfit-py -

Published by newville about 5 years ago

New features:

the global optimizers shgo and dual_annealing (new in SciPy v1.2) are now supported (Issue #527; PRs #545 and #556)
eval method added to the Parameter class (PR #550 by @zobristnicholas)
avoid ZeroDivisionError in printfuncs.params_html_table (PR #552 by @aaristov and PR #559)
add parallelization to brute method (PR #564, requires SciPy v1.3)

Bug fixes:

consider only varying parameters when reporting potential issues with calculating errorbars (PR #549) and compare
value to both min and max (PR #571)
guard against division by zero in lineshape functions and FWHM and height expression calculations (PR #545)
fix issues with restoring a saved Model (Issue #553; PR #554)
always set result.method for emcee algorithm (PR #558)
more careful adding of parameters to handle out-of-order constraint expressions (Issue #560; PR #561)
make sure all parameters in Model.guess() use prefixes (PRs #567 and #569)
use inspect.signature for PY3 to support wrapped functions (Issue #570; PR #576)
fix result.nfev``` for brute`` method when using parallelization (Issue #578; PR #579)

Various:

remove "missing" in the Model class (replaced by nan_policy) and "drop" as option to nan_policy
(replaced by omit) deprecated since 0.9 (PR #565).
deprecate 'report_errors' in printfuncs.py (PR #571)
updates to the documentation to use jupyter-sphinx to include examples/output (PRs #573 and #575)
include a Gallery with examples in the documentation using sphinx-gallery (PR #574 and #583)
improve test-coverage (PRs #571, #572 and #585)
add/clarify warning messages when NaN values are detected (PR #586)
several updates to docstrings (Issue #584; PR #583, and others)
update pre-commit hooks and several docstrings