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fjosw 2022-05-31 10:52:36 +00:00
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.gitignore vendored
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@ -6,6 +6,9 @@ __pycache__
.cache .cache
examples/B1k2_pcac_plateau.p examples/B1k2_pcac_plateau.p
examples/Untitled.* examples/Untitled.*
examples/pcac_plateau_test_ensemble.json.gz
core.* core.*
*.swp *.swp
htmlcov htmlcov
build
pyerrors.egg-info

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CHANGELOG.md
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@ -2,6 +2,26 @@
All notable changes to this project will be documented in this file. All notable changes to this project will be documented in this file.
## [2.1.0] - 2022-05-31
### Added
- `obs.covariance` now has the option to smooth small eigenvalues of the matrix with the method described in hep-lat/9412087.
- `Corr.prune` was added which can reduce the size of a correlator matrix before solving the GEVP.
- `Corr.show` has two additional optional arguments. `hide_sigma` to hide data points with large errors and `references` to display reference values as horizontal lines.
- I/O routines for ALPHA dobs format added.
- `input.hadrons` functionality extended.
### Changed
- The standard behavior of the `Corr.GEVP` method has changed. It now returns all eigenvectors of the system instead of only the specified ones as default. The standard way of sorting the eigenvectors was changed to `Eigenvalue`. The argument `sorted_list` was deprecated in favor of `sort`.
- Before performing a correlated fit the routine first runs an uncorrelated one to obtain a better guess for the initial parameters.
### Fixed
- `obs.covariance` now also gives correct estimators if data defined on non-identical configurations is passed to the function.
- Rounding errors in estimating derivatives of fit parameters with respect to input data from the inverse hessian reduced. This should only make a difference when the magnitude of the errors of different fit parameters vary vastly.
- Bug in json.gz format fixed which did not properly store the replica mean values. Format version bumped to 1.1.
- The GEVP matrix is now symmetrized before solving the system for all sorting options not only the one with fixed `ts`.
- Automatic range estimation improved in `fits.residual_plot`.
- Bugs in `input.bdio` fixed.
## [2.0.0] - 2022-03-31 ## [2.0.0] - 2022-03-31
### Added ### Added
- The possibility to work with Monte Carlo histories which are evenly or unevenly spaced was added. - The possibility to work with Monte Carlo histories which are evenly or unevenly spaced was added.

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pyerrors/fits.py
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@ -95,7 +95,8 @@ def least_squares(x, y, func, priors=None, silent=False, **kwargs):
If true all output to the console is omitted (default False). If true all output to the console is omitted (default False).
initial_guess : list initial_guess : list
can provide an initial guess for the input parameters. Relevant for can provide an initial guess for the input parameters. Relevant for
non-linear fits with many parameters. non-linear fits with many parameters. In case of correlated fits the guess is used to perform
an uncorrelated fit which then serves as guess for the correlated fit.
method : str, optional method : str, optional
can be used to choose an alternative method for the minimization of chisquare. can be used to choose an alternative method for the minimization of chisquare.
The possible methods are the ones which can be used for scipy.optimize.minimize and The possible methods are the ones which can be used for scipy.optimize.minimize and