Releases: lmfit/lmfit-py
0.9.7rc1
0.9.6
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 themethod='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 thebrute
method, anduser_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.
0.9.6rc1
0.9.5
0.9.4 release
Merge pull request #353 from lmfit/prep094rc2 Prep094rc2
0.9.4rc1: Merge pull request #343 from lmfit/prep0.9.4
Prepare 0.9.4
release 0.9.3
more doc tweaks