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docs: gm alias added to basic example, hyperlink fixed in documentation.

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Fabian Joswig 2023-01-24 13:06:14 +00:00
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2
examples/01_basic_example.ipynb
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@ -233,7 +233,7 @@
],
"source": [
"c_obs3 = np.sin(c_obs1 / c_obs2 - 1)\n",
"c_obs3.gamma_method()\n",
"c_obs3.gm() # gm is a short alias for gamma_method\n",
"c_obs3.details()"
]
},

2
pyerrors/__init__.py
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@ -41,7 +41,7 @@ print(my_new_obs) # Print the result to stdout
`pyerrors` introduces a new datatype, `Obs`, which simplifies error propagation and estimation for auto- and cross-correlated data.
An `Obs` object can be initialized with two arguments, the first is a list containing the samples for an observable from a Monte Carlo chain.
The samples can either be provided as python list or as numpy array.
The second argument is a list containing the names of the respective Monte Carlo chains as strings. These strings uniquely identify a Monte Carlo chain/ensemble. **It is crucial for the correct error propagation that observations from the same Monte Carlo history are labeled with the same name. See [Multiple ensembles/replica](#Multiple-ensembles/replica) for details.**
The second argument is a list containing the names of the respective Monte Carlo chains as strings. These strings uniquely identify a Monte Carlo chain/ensemble. **It is crucial for the correct error propagation that observations from the same Monte Carlo history are labeled with the same name. See [Multiple ensembles/replica](#Multiple-ensemblesreplica) for details.**
```python
import pyerrors as pe