lattice/pyerrors
1
0
Fork 0
mirror of https://github.com/fjosw/pyerrors.git synced 2025-03-15 14:50:25 +01:00
Code Issues Projects Releases Packages Wiki Activity

Merge branch 'develop' into documentation

Browse source
This commit is contained in:
fjosw 2023-01-24 13:07:04 +00:00
commit 5eda97cce8
2 changed files with 3 additions and 3 deletions
Show stats Download patch file Download diff file Expand all files Collapse all files

4
examples/01_basic_example.ipynb
View file

@ -58,7 +58,7 @@
"cell_type": "markdown",
"metadata": {},
"source": [
"From this we can construct `Obs`, which are the basic object of `pyerrors`. For each sample we give to the obs, we also have to specify an ensemble/replica name. In this example we assume that both datasets originate from the same gauge field ensemble labeled 'ensemble1'."
"From this we can construct `Obs`, which are the basic object of `pyerrors`. For each sample we give to the obs, we also have to specify an ensemble/replica name. In this example we assume that both datasets originate from the same gauge field ensemble labeled 'ensemble1'. **For correct error propagation it is crucial that observations from the same Monte Carlo chain are initialized with the same name.**"
]
},
{
@ -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
View file

@ -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