./math/py-lmfit, Least-squares minimization with bounds and constraints

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Branch: CURRENT, Version: 0.9.12, Package name: py27-lmfit-0.9.12, Maintainer: prlw1

A library for least-squares minimization and data fitting in Python.
Built on top of scipy.optimize, lmfit provides a Parameter object
which can be set as fixed or free, can have upper and/or lower
bounds, or can be written in terms of algebraic constraints of
other Parameters. The user writes a function to be minimized as a
function of these Parameters, and the scipy.optimize methods are
used to find the optimal values for the Parameters. The
Levenberg-Marquardt (leastsq) is the default minimization algorithm,
and provides estimated standard errors and correlations between
varied Parameters. Other minimization methods, including Nelder-Mead's
downhill simplex, Powell's method, BFGS, Sequential Least Squares,
and others are also supported. Bounds and contraints can be placed
on Parameters for all of these methods.

In addition, methods for explicitly calculating confidence intervals
are provided for exploring minmization problems where the approximation
of estimating Parameter uncertainties from the covariance matrix
is questionable.


Required to run:
[devel/py-setuptools] [math/py-scipy] [math/py-numpy] [lang/python27] [lang/py-six] [math/py-asteval]

Required to build:
[pkgtools/cwrappers]

Master sites:

SHA1: 7c4a15975d9920c9cf12fd98aca7e7706daf18c9
RMD160: dc4bb6835e34fadd8786c1dd760f09df694dba6b
Filesize: 1532.712 KB

Version history: (Expand)


CVS history: (Expand)


   2019-06-15 09:21:21 by Adam Ciarcinski | Files touched by this commit (2) | Package updated
Log message:
py-lmfit: updated to 0.9.13

Version 0.9.13 Release Notes

New features:
Clearer warning message in fit reports when uncertainties should but cannot be \ 
estimated, including guesses of which Parameters to examine
SplitLorenztianModel and split_lorentzian function
HTML representations for Parameter, MinimizerResult, and Model so that they can \ 
be printed better with Jupyter
support parallelization for differential evolution

Bug fixes:
delay import of matplotlib (and so, the selection of its backend) as late as possible
fix for saving, loading, and reloading ModelResults
fix to leastsq to report the best-fit values, not the values tried last
fix synchronization of all parameter values on Model.guess()
improve deprecation warnings for outdated nan_policy keywords
fix for edge case in gformat()

Project managements:
using pre-commit framework to improve and enforce coding style
added code coverage report to github main page
updated docs, github templates, added several tests.
dropped support and testing for Python 3.4.
   2018-12-03 21:41:44 by Adam Ciarcinski | Files touched by this commit (2) | Package updated
Log message:
py-lmfit: updated to 0.9.12

Version 0.9.12 Release Notes

New features:
- SkewedVoigtModel was added as built-in model
- Parameter uncertainties and correlations are reported for least_squares
- Plotting of complex-valued models is now handled in ModelResult class
- A model's independent variable is allowed to be an object
- Added usersyms to Parameters() initialization to make it easier to add custom \ 
functions and symbols
- the numdifftools package can be used to calculate parameter uncertainties and \ 
correlations for all solvers that do not natively support this
- emcee can now be used as method keyword-argument to Minimizer.minimize and \ 
minimize function, which allows for using emcee in the Model class

(Bug)fixes:
- asteval errors are now flushed after raising
- max_time and evaluation time for ExpressionModel increased to 1 hour
- loading a saved ModelResult now restores all attributes
- development versions of scipy and emcee are now supported
- ModelResult.eval() do no longer overwrite the userkws dictionary
- running the test suite requires pytest only
- improved FWHM calculation for VoigtModel
   2018-07-13 08:22:35 by Adam Ciarcinski | Files touched by this commit (3) | Package updated
Log message:
py-lmfit: updated to 0.9.11

0.9.11:
make exception explicit

0.9.10:
add AMPGO and basin-hopping global optimization methods.
aborting a fit from the objective function now raises AbortFitException
fit statistics are more uniformly calculated.
the uncertainties package is now an external dependency, and an out-dated copy \ 
is no longer kept in lmfit.
more exceptions when import matplotlib are now tolerated.
many documentation fixes.
   2018-04-14 07:32:22 by Adam Ciarcinski | Files touched by this commit (3) | Package updated
Log message:
py-lmfit: updated to 0.9.9

Version 0.9.9:
Lmfit now uses the asteval (https://github.com/newville/asteval) package
instead of distributing its own copy. The minimum required asteval version
is 0.9.12, which is available on PyPi. If you see import errors related to
asteval, please make sure that you actually have the latest version installed.
   2018-02-27 07:40:07 by Adam Ciarcinski | Files touched by this commit (3) | Package updated
Log message:
py-lmfit: updated to 0.9.8

0.9.8:
update doc for 5 digit-precision fit statistics
increase default precision for chi-square, etc from 3 to 5
   2016-09-16 17:20:31 by Patrick Welche | Files touched by this commit (4)
Log message:
Add py-lmfit 0.9.5

A library for least-squares minimization and data fitting in Python,
based on scipy.optimize.