Pyerrors

Added
- The possibility to work with Monte Carlo histories which are evenly or unevenly spaced was added.
- `cov_Obs` added as a possibility to propagate the error of non Monte Carlo data together with Monte Carlo data.
- `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`.
- Support for a new `json.gz` file format was added.
- The Corr class now has additional methods like `reverse`, `T_symmetry`, `correlate` and `reweight`.
- `Corr.m_eff` can now cope with periodic and anti-periodic correlation functions.
- Forward, backward and improved variants of the first and second derivative were added to the `Corr` class.
- `GEVP` functionality of the `Corr` class was reworked and improved.
- The `linalg` module now has explicit functions `inv`, `cholesky` and `det`.
- `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 routines `einsum` and `jack_matmul` were added to `linalg` module which make use of the jackknife approximation and are much faster for large matrices.
- Additional input routines for npr data added to `input.hadrons`.
- The `sfcf` and `openQCD` input modules can now handle all recent file type versions.
- `extract_t0` can now visualize the extraction on the fly.
- Module added which provides the Dirac gamma matrices in the Grid convention.
- Version number added.

Changed
- 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 output of the fit functions is now a dedicated results class which keeps track of all relevant information.
- The fit functions can now deal with provided covariance matrices.
- `covariance` can now operate on a list or array of `Obs` and returns a matrix. The covariance estimate by pyerrors is now always positive semi-definite (within machine precision. Various warnings and exceptions were added for cases in which estimated covariances are close to singular.
- The convention for the fit range in the Corr class has been changed.
- Various method of the `Corr` class were renamed.
- `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.

Removed
- The function `plot_corrs` was deprecated as all its functionality is now contained within `Corr.show`.
- `fits.covariance_matrix` was removed as it is now redundant with the functionality of `covariance`.
- The kwarg `bias_correction` in `derived_observable` was removed.
- Obs no longer have an attribute `e_Q`.
- Removed `fits.fit_exp`.
- Removed jackknife module.

Added
- `Corr` class added
- `roots` module added which can find the roots of a function that depends on Monte Carlo data via pyerrors `Obs`
- `input/hadrons` module added which can read hdf5 files written by [Hadrons](https://github.com/aportelli/Hadrons)
- `read_rwms` can now read reweighting factors in the format used by openQCD-2.0.

Fixed
- Bug in `pyerrors.covariance` fixed that appeared when working with several
replica of different length.

Added
- Compatibility with the BDIO Native format outlined [here](https://ific.uv.es/~alramos/docs/ADerrors/tutorial/). Read and write function added to input.bdio
- new function `input.bdio.read_dSdm` which can read the bdio output of the
program `dSdm` by Tomasz Korzec
- Expected chisquare implemented for fits with xerrors
- New implementation of the covariance of two observables which employs the
arithmetic mean of the integrated autocorrelation times of the two
observables. This new procedure has proven to be less biased in simulated
data and is also much faster to compute as the computation time is of O(N)
whereas the evaluation of the full correlation function is of O(Nlog(N)).
- Added function `gen_correlated_data` to `misc` which generates a set of
observables with given covariance and autocorrelation.

Fixed
- Bias correction hep-lat/0306017 eq. (49) is no longer applied to the
exponential tail in the critical slowing down analysis, but only to the part
which is directly estimated from rho. This can lead to slightly smaller
errors when using the critical slowing down analysis. The values for the
integrated autocorrelation time tauint now include this bias correction (up
to now the bias correction was applied after estimating tauint). The errors
resulting from the automatic windowing procedure are unchanged.

Fixed
- Bug in `fits.standard_fit` fixed which occurred when attempting a fit with zero
degrees of freedom.

Added
- `merge_obs` function added which allows to merge Obs which describe different replica of the same observable and have been read in separately. Use with care as there is no safeguard implemented which prevent you from merging unrelated Obs.
- `standard fit` and `odr_fit` can now treat fits with several x-values via tuples.
- Fit functions have a new kwarg `dict_output` which allows to change the
output to a dictionary containing additional information.
- `S_dict` and `tau_exp_dict` added to Obs in which global values for individual ensembles can be stored.
- new function `read_pbp` added which reads dS/dm_q from pbp.dat files.
- new function `extract_t0` added which can extract the value of t0 from .ms.dat files of openQCD v 1.2

Changed
- When creating an Obs object defined for multiple replica/ensembles, the given names are now sorted alphabetically before assigning the internal dictionaries. This makes sure that `my_Obs` has the same dictionaries as `my_Obs * 1` (`derived_observable` always sorted the names). WARNING: `Obs` created with previous versions of pyerrors may not be completely identical to new ones (The internal dictionaries may have different ordering). However, this should not affect the inner workings of the error analysis.

Fixed
- Bug in `covariance` fixed which appeared when different ensemble contents were used.