Overview
Request 812430 accepted
- Update to version 1.0.1
+ 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/*
Request History
glaubitz created request
- Update to version 1.0.1
+ 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/*
scarabeus_iv accepted request
ok lets get this in and I will skip the failing tests, they expose bugs in the scipy anyway.
Seems the tests fail on at least 32bit intel (rest didn't finish building yet).
Todd already reported that upstream half a year ago:
Maybe we should just disable i586 for the time being?
Unfortunately, arm64 fails as well.
If it is just this one test and it does not break rest functionality we can also just skip the test and consider it known fail on 32bit.
Don’t skip whole architecture, when skipping one test is enough, please. And if you file a but upstream (and make note in the SPEC file about it), there is absolutely no problem with skipping some tests.
@TheBlackCat, @alarrosa, @aplanas, @cyberiad, @dirkmueller, @mcepl, @mimi_vx, @pavlix, @posophe, @rjschwei, @scarabeus_iv, @sleep_walker, @tbechtold: review reminder