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CHANGELOG
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Changelog
---------
All notable changes to this project will be documented in this file.
The format is based on `Keep a changelog <https://keepachangelog.com/en/1.0.0/>`__.
[Unreleased]
++++++++++++
Added
* jackknife error support
* exponential tail
Fixed
* BDIO format has bug for python>=3.10
[1.5.3] - 19.02.2025
++++++++++++++++++++
Added
* added full support for complex observables
* added conj method to observable class
* temporary class `complex_observable` migrated to tests
* added p-value for non correlated fits
Fixed
* minor bugs
* added internal backend to matplotlib
[1.5.1] - 15.11.2024
++++++++++++++++++++
Added
* temporary support for complex observables via `complex_observable` class (binary operations `@`, `*`, unary operations `inv`, `eig`, `T`)
* extended output for peek function
Fixed
* fixed bug in chiexp for combined fits
* faster index search in transform.py for large observables
[1.5.0] - 10.10.2023
++++++++++++++++++++
Added
* added support for expected chi square
Fixed
* improved error estimation and plotting in presence of holes
* minor bugs fixed (I/O xml)
[1.4.1] - 18.01.2023
++++++++++++++++++++
Fixed
- fixed bug in transform (roll, sort..)
- improved behavior under roundoff errors
- fixed compatibility issues with numpy>=1.24.0
[1.4.0] - 20.08.2022
++++++++++++++++++++
Added
- finite volume 2to2 quantization condition
- write support for xml.gz format
- documentation updated
Fixed
- several minor bugs fixed
version 1.3.0, 06.02.2022:
- added utility functions (tensor_remove, import_string)
- minor bugs fixed
- added support xml and bdio format (dobs-tools, ALPHA Collab.)
- interface for synthetic autocorrelated data changed
- several bugs fixed
version 1.2.0, 21.07.2021:
- added support for binning of Monte Carlo data, and blocking for master-field data
- added support for linting of code
- performance improvements for slicing/indexing/extending observables
version 1.1.0, 08.05.2021:
- added support for root finder, basic interpolation, cumsum
- fixed documentation bugs
- minor improvements to mfit
- added support for variance and cov. matrix (data.py rewritten)
version 1.0.1, 10.11.2020:
- added IO with binary file format (default), based on bison
- performance improvements in create and derobs
- additional gradient class for optimization of element-wise operations
- minor bug fixes
version 1.0.0-alpha, 11.10.2020:
- IO with json file format supported
- pip install supported
- error of the error and 4th moment bias supported
- support for code coverage and automatic unit tests
- flexible fit modules (Levenberg-Marquardt minimizer)
- documentation and tutorials
- symbolic differentiation for fit functions
- support for eigenvalue/eigenvectors (including non-symmetric case)
- support for exp, log, cosh, arccosh, besselk
- fast C++ extensions for master-field case
- overloaded basic math operations (+,-,*,/)
- tensor operations: unary support (sum, trace), matmul via @ operand
- basic tensor manipulation (reshape, concatenate) and getitem
- FFT for autocorrelations
- support for external data with known covariances and systematic errors
- memory management system, utility functions
- random module for generation of autocorrelated data sets