docs: latex in docstring of covariance fixed

.github/workflows/flake8.yml

@@ -21,6 +21,6 @@ jobs:
       - name: flake8 Lint
         uses: py-actions/flake8@v1
         with:
-          ignore: "E501,W605"
+          ignore: "E501"
           exclude: "__init__.py, input/__init__.py"
           path: "pyerrors"

CONTRIBUTING.md

@@ -30,6 +30,6 @@ pytest --cov=pyerrors --cov-report html
 ```
 The linter `flake8` is executed with the command
 ```
-flake8 --ignore=E501,W605 --exclude=__init__.py pyerrors
+flake8 --ignore=E501 --exclude=__init__.py pyerrors
 ```
 Please make sure that all tests are passed for a new pull requests.

pyerrors/obs.py

@@ -1333,7 +1333,7 @@ def correlate(obs_a, obs_b):
 
 
 def covariance(obs, visualize=False, correlation=False, **kwargs):
-    """Calculates the covariance matrix of a set of observables.
+    r'''Calculates the covariance matrix of a set of observables.
 
     The gamma method has to be applied first to all observables.
 
@@ -1349,11 +1349,9 @@ def covariance(obs, visualize=False, correlation=False, **kwargs):
     Notes
     -----
     The covariance is estimated by calculating the correlation matrix assuming no autocorrelation and then rescaling the correlation matrix by the full errors including the previous gamma method estimate for the autocorrelation of the observables. For observables defined on a single ensemble this is equivalent to assuming that the integrated autocorrelation time of an off-diagonal element is equal to the geometric mean of the integrated autocorrelation times of the corresponding diagonal elements.
-    $$
-    \tau_{\mathrm{int}, ij}=\sqrt{\tau_{\mathrm{int}, i}\times \tau_{\mathrm{int}, j}}
-    $$
+    $$\tau_{\mathrm{int}, ij}=\sqrt{\tau_{\mathrm{int}, i}\times \tau_{\mathrm{int}, j}}$$
     This construction ensures that the estimated covariance matrix is positive semi-definite (up to numerical rounding errors).
-    """
+    '''
 
     length = len(obs)
     cov = np.zeros((length, length))