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README updated
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@ -24,8 +24,8 @@ For all pull requests to the `develop` branch tests are executed for the most re
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```
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pytest -v
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```
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and `flake8` is executed with the command
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and the linter `flake8` is executed with the command
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```
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flake8 --ignore=E501,E722 --exclude=__init__.py pyerrors
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```
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Please make sure that all tests are passed for a new pull request.
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Please make sure that all tests are passed for a new pull requests.
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@ -22,21 +22,21 @@ pip install git+https://github.com/fjosw/pyerrors.git
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## Usage
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The basic objects of a pyerrors analysis are instances of the class `Obs`. They can be initialized with an array of Monte Carlo data (e.g. `samples1`) and a name for the given ensemble (e.g. `'ensemble1'`). The `gamma_method` can then be used to compute the statistical error, taking into account autocorrelations. The `print` method outputs a human readable result.
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```python
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import numpy as np
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import pyerrors as pe
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obs1 = pe.Obs([samples1], ['ensemble1'])
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obs1.gamma_method()
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obs1.print()
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```
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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
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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
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```python
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import numpy as np
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obs3 = 12.0 / obs1 ** 2 - np.exp(-1.0 / obs2)
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obs3.gamma_method()
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obs3.print()
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```
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More detailed examples can be found in the `/examples` folder:
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More detailed examples can be found in the `examples` folder:
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* [01_basic_example](examples/01_basic_example.ipynb)
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* [02_correlators](examples/02_correlators.ipynb)
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