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docs: Changelog updated

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Fabian Joswig 2021-11-30 14:52:25 +00:00
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27
CHANGELOG.md
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@ -4,20 +4,33 @@ All notable changes to this project will be documented in this file.
## [2.0.0] - 2021-??-??
### Added
- `CObs` class added which can handle complex valued Markov chain Monte Carlo data and the corresponding error propagation
- Matrix to matrix operations like the matrix inverse now also work for complex matrices and matrices containing entries that are not `Obs` but `float` or `int`
- `Obs` objects now have methods `is_zero` and `is_zero_within_error`
- `CObs` class added which can handle complex valued Markov chain Monte Carlo data and the corresponding error propagation.
- Matrix to matrix operations like the matrix inverse now also work for complex matrices and matrices containing entries that are not `Obs` but `float` or `int`.
- The possibility to work with Monte Carlo histories which are evenly or unevenly spaced was added.
- The Corr class now has additional methods like `reverse`, `T_symmetry`, `correlate` and `reweight`.
- `linalg` module now has explicit functions `inv` and `cholesky`.
- `Obs` objects now have methods `is_zero` and `is_zero_within_error` as well as overloaded comparison operations.
- Functions to convert Obs data to or from jackknife was added.
- Alternative matrix multiplication routine `jack_matmul` was added to `linalg` module which makes use of the jackknife approximation and is much faster for large matrices.
- Additional input routines for npr data added to `input.hadrons`.
- Version number added.
### Changed
- Additional attributes can no longer be added to existing `Obs`. This makes it no longer possible to import `Obs` created with previous versions of pyerrors
- The default value for `Corr.prange` is now `None`
- The `input` module was restructured to contain one submodule per data source
- The internal bookkeeping system for ensembles/replica was changed. The separator for replica is now `|`.
- The fit functions were renamed to `least_squares` and `total_least_squares`.
- The fit functions can now deal with provided covariance matrices.
- The convention for the fit range in the Corr class has been changed.
- Obs.print was renamed to Obs.details and the output was improved.
- The default value for `Corr.prange` is now `None`.
- The `input` module was restructured to contain one submodule per data source.
- Performance of Obs.__init__ improved.
### Deprecated
- The function `plot_corrs` was deprecated as all its functionality is now contained within `Corr.show`
- The kwarg `bias_correction` in `derived_observable` was removed
- Obs no longer have an attribute `e_Q`
- Removed `fits.fit_exp`
- Removed jackknife module
## [1.1.0] - 2021-10-11
### Added
@ -77,7 +90,7 @@ All notable changes to this project will be documented in this file.
## [0.7.0] - 2020-03-10
### Added
- New fit funtions for fitting with and without x-errors added which use automatic differentiation and should be more reliable than the old ones.
- New fit functions for fitting with and without x-errors added which use automatic differentiation and should be more reliable than the old ones.
- Fitting with Bayesian priors added.
- New functions for visualization of fits which can be activated via the kwargs resplot and qqplot.
- chisquare/expected_chisquared which takes into account correlations in the data and non-linearities in the fit function can now be activated with the kwarg expected_chisquare.

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README.md
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@ -3,7 +3,7 @@
`pyerrors` is a python package for error computation and propagation of Markov chain Monte Carlo data.
- **Documentation:** https://fjosw.github.io/pyerrors/pyerrors.html
- **Examples**: https://github.com/fjosw/pyerrors/tree/develop/examples
- **Examples**: https://github.com/fjosw/pyerrors/tree/develop/examples (Do not work properly at the moment)
- **Contributing:** https://github.com/fjosw/pyerrors/blob/develop/CONTRIBUTING.md
- **Bug reports:** https://github.com/fjosw/pyerrors/issues