rest of the changes attempted

src/Taweret/core/base_mixer.py

@@ -230,12 +230,10 @@ def train(self):
         '''
         Run sampler to learn parameters. Method should also create class
         members that store the posterior and other diagnostic quantities
-        important for plotting
-        MAP values should also calculate and set as member variable of
-        class
+        important for plotting MAP values.
 
-        Return:
-        -------
+        Returns:
+        --------
         _posterior : np.ndarray
             the mcmc chain return from sampler
         '''

src/Taweret/utils/utils.py

@@ -25,7 +25,7 @@ def normed_mvn_loglike(y, cov):
     Evaluate the multivariate-normal log-likelihood for difference vector `y`
     and covariance matrix `cov`:
 
-        log_p = -1/2*[(y^T).(C^-1).y + log(det(C))] + const.
+    .. math:: log_p = -1/2*[(y^T).(C^-1).y + log(det(C))] + const.
 
     This likelihood IS NORMALIZED.
     The normalization const = -n/2*log(2*pi), where n is the dimensionality.