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Merge branch 'develop' of github.com:fjosw/pyerrors into develop

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README.md
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[![flake8](https://github.com/fjosw/pyerrors/actions/workflows/flake8.yml/badge.svg)](https://github.com/fjosw/pyerrors/actions/workflows/flake8.yml) [![CI](https://github.com/fjosw/pyerrors/actions/workflows/CI.yml/badge.svg)](https://github.com/fjosw/pyerrors/actions/workflows/CI.yml) [![](https://img.shields.io/badge/python-3.6+-blue.svg)](https://www.python.org/downloads/) [![flake8](https://github.com/fjosw/pyerrors/actions/workflows/flake8.yml/badge.svg)](https://github.com/fjosw/pyerrors/actions/workflows/flake8.yml) [![Build/Test](https://github.com/fjosw/pyerrors/actions/workflows/CI.yml/badge.svg)](https://github.com/fjosw/pyerrors/actions/workflows/CI.yml) [![](https://img.shields.io/badge/python-3.6+-blue.svg)](https://www.python.org/downloads/)
# pyerrors # pyerrors
`pyerrors` is a python package for error computation and propagation of Markov chain Monte Carlo data. `pyerrors` is a python package for error computation and propagation of Markov chain Monte Carlo data.
It is based on the **gamma method** [arXiv:hep-lat/0306017](https://arxiv.org/abs/hep-lat/0306017). Some of its features are: It is based on the **gamma method** [arXiv:hep-lat/0306017](https://arxiv.org/abs/hep-lat/0306017). Some of its features are:
@ -16,7 +16,11 @@ There exist similar implementations of gamma method error analysis suites in
## Installation ## Installation
To install the most recent release of `pyerrors` run To install the most recent release of `pyerrors` run
```bash ```bash
pip install git+https://github.com/fjosw/pyerrors.git pip install git+https://github.com/fjosw/pyerrors.git@master
```
to install the current `develop` version run
```bash
pip install git+https://github.com/fjosw/pyerrors.git@develop
``` ```
## Usage ## Usage
@ -31,6 +35,7 @@ obs1.print()
Often one is interested in secondary observables which can be arbitrary functions of primary observables. `pyerrors` overloads most basic math operations and `numpy` functions such that the user can work with `Obs` objects as if they were floats Often one is interested in secondary observables which can be arbitrary functions of primary observables. `pyerrors` overloads most basic math operations and `numpy` functions such that the user can work with `Obs` objects as if they were floats
```python ```python
import numpy as np import numpy as np
obs3 = 12.0 / obs1 ** 2 - np.exp(-1.0 / obs2) obs3 = 12.0 / obs1 ** 2 - np.exp(-1.0 / obs2)
obs3.gamma_method() obs3.gamma_method()
obs3.print() obs3.print()
@ -44,6 +49,5 @@ More detailed examples can be found in the `examples` folder:
* [04_fit_example](examples/04_fit_example.ipynb) * [04_fit_example](examples/04_fit_example.ipynb)
* [05_matrix_operations](examples/05_matrix_operations.ipynb) * [05_matrix_operations](examples/05_matrix_operations.ipynb)
## License ## License
[MIT](https://choosealicense.com/licenses/mit/) [MIT](https://choosealicense.com/licenses/mit/)

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setup.py
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from setuptools import setup, find_packages from setuptools import setup, find_packages
setup(name='pyerrors', setup(name='pyerrors',
version='1.1.0', version='2.0.0',
description='Error analysis for lattice QCD', description='Error analysis for lattice QCD',
author='Fabian Joswig', author='Fabian Joswig',
author_email='fabian.joswig@ed.ac.uk', author_email='fabian.joswig@ed.ac.uk',

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tests/test_linalg.py
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@ -94,15 +94,11 @@ def test_matrix_functions():
for (i, j), entry in np.ndenumerate(check): for (i, j), entry in np.ndenumerate(check):
diff = entry - sym[i, j] diff = entry - sym[i, j]
diff.gamma_method() assert diff.is_zero()
assert math.isclose(diff.value, 0.0, abs_tol=1e-9), 'value ' + str(i) + ',' + str(j)
assert math.isclose(diff.dvalue, 0.0, abs_tol=1e-9), 'dvalue ' + str(i) + ',' + str(j)
# Check eigh # Check eigh
e, v = pe.linalg.eigh(sym) e, v = pe.linalg.eigh(sym)
for i in range(dim): for i in range(dim):
tmp = sym @ v[:, i] - v[:, i] * e[i] tmp = sym @ v[:, i] - v[:, i] * e[i]
for j in range(dim): for j in range(dim):
tmp[j].gamma_method() assert tmp[j].is_zero()
assert math.isclose(tmp[j].value, 0.0, abs_tol=1e-9), 'value ' + str(i) + ',' + str(j)
assert math.isclose(tmp[j].dvalue, 0.0, abs_tol=1e-9), 'dvalue ' + str(i) + ',' + str(j)

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tests/test_pyerrors.py
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@ -245,4 +245,4 @@ def test_cobs():
assert np.allclose(0.0, diff.real.deltas['t']) assert np.allclose(0.0, diff.real.deltas['t'])
assert np.allclose(0.0, diff.imag.deltas['t']) assert np.allclose(0.0, diff.imag.deltas['t'])
div = my_cobs / other assert (my_cobs / other * other - my_cobs).is_zero()