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bias correction removed

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Fabian Joswig 2021-10-18 14:25:41 +01:00
parent f627a52bba
commit 09b2525d29
2 changed files with 9 additions and 16 deletions
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15
CHANGELOG.md
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@ -9,24 +9,25 @@ All notable changes to this project will be documented in this file.
- `Obs` objects now have methods `is_zero` and `is_zero_within_error`
### 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`
- 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
### Deprecated
- The function `plot_corrs` was deprecated as all its functionality is now contained within `Corr.show`
- Obs no longer have an attribute e_Q
- The kwarg `bias_correction` in `derived_observable` was removed
- Obs no longer have an attribute `e_Q`
## [1.1.0] - 2021-10-11
### 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
- `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
## [1.0.1] - 2020-11-03
### Fixed
- Bug in pyerrors.covariance fixed that appeared when working with several
- Bug in `pyerrors.covariance` fixed that appeared when working with several
replica of different length.
## [1.0.0] - 2020-10-13

10
pyerrors/pyerrors.py
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@ -726,9 +726,6 @@ def derived_observable(func, data, **kwargs):
man_grad -- manually supply a list or an array which contains the jacobian
of func. Use cautiously, supplying the wrong derivative will
not be intercepted.
bias_correction -- if True, the bias correction specified in
hep-lat/0306017 eq. (19) is performed, not recommended.
(Only applicable for more than 1 replicum)
Notes
-----
@ -831,12 +828,7 @@ def derived_observable(func, data, **kwargs):
new_samples.append(new_deltas[name] + new_r_values[name][i_val])
final_result[i_val] = Obs(new_samples, new_names)
# Bias correction
if replicas > 1 and kwargs.get('bias_correction'):
final_result[i_val].value = (replicas * new_val - final_result[i_val].value) / (replicas - 1)
else:
final_result[i_val].value = new_val
final_result[i_val].value = new_val
if multi == 0:
final_result = final_result.item()