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Fabian Joswig 2021-10-19 10:39:12 +01:00
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@ -22,21 +22,21 @@ pip install git+https://github.com/fjosw/pyerrors.git
## Usage
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.
```python
import numpy as np
import pyerrors as pe
obs1 = pe.Obs([samples1], ['ensemble1'])
obs1.gamma_method()
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
import numpy as np
obs3 = 12.0 / obs1 ** 2 - np.exp(-1.0 / obs2)
obs3.gamma_method()
obs3.print()
```
More detailed examples can be found in the `/examples` folder:
More detailed examples can be found in the `examples` folder:
* [01_basic_example](examples/01_basic_example.ipynb)
* [02_correlators](examples/02_correlators.ipynb)