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.
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.
Changes to 0.9.7 not immediately obvious
Version 0.9.6 Release Notes
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
Minimizer.brute() or using the method='brute' option to
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.
