Fix formula in docstring

Author: padix-key

src/springcraft/anm.py

@@ -326,32 +326,16 @@ def bfactor(self, mode_subset=None, tem=None,
         )
 
     def dcc(self, mode_subset=None, norm=True, tem=None, tem_factors=K_B):
-        """
+        r"""
         Computes the normalized *dynamic cross-correlation* between 
-        nodes of the ANM. The DCC for a nodepair :math:`ij` is computed as:
-
-        .. math:: 
-
-        DCC_{ij} = \frac{3 k_B T}{\gamme} \sum_k^L \left[ \frac{\vec{u}_k \cdot \vec{u}_k^T}{\lambda_k} \right]_{ij}
-
-        with :math:`\lambda` and :math:`\vec{u}` as 
-        Eigenvalues and Eigenvectors corresponding to mode :math:`k` of 
-        the modeset :math:`L`.
-
-        DCCs can be normalized to MSFs exhibited by two compared nodes
-        following:
-
-        .. math::
-
-        nDCC_{ij} = \frac{DCC_{ij}}{[\DCC_{ii} DCC_{jj}]^{1/2}}
+        nodes of the ANM.
 
         The DCC is a measure for the correlation in fluctuations
         exhibited by a given pair of nodes. If normalized, pairs with 
         correlated fluctuations (same phase and period), 
         anticorrelated fluctuations (opposite phase, same period)
         and non-correlated fluctuations are assigned (normalized) 
         DCC values of 1, -1 and 0 respectively.
-        
         For results consistent with MSFs, temperature-weighted
         absolute values can be computed (only relevant if results
         are not normalized).
@@ -374,12 +358,31 @@ def dcc(self, mode_subset=None, norm=True, tem=None, tem_factors=K_B):
             If tem is None, no temperature scaling is conducted. 
         tem_factors : int, float, optional
             Factors included in temperature weighting 
-            (with K_B as preset).
+            (with :math:`k_B` as preset).
 
         Returns
         -------
         dcc : ndarray, shape=(n, n), dtype=float
             DCC values for ENM nodes.
+        
+        Notes
+        -----
+        The DCC for a nodepair :math:`ij` is computed as:
+
+        .. math:: 
+
+            DCC_{ij} = \frac{3 k_B T}{\gamma} \sum_k^L \left[ \frac{\vec{u}_k \cdot \vec{u}_k^T}{\lambda_k} \right]_{ij}
+
+        with :math:`\lambda` and :math:`\vec{u}` as 
+        Eigenvalues and Eigenvectors corresponding to mode :math:`k` of 
+        the modeset :math:`L`.
+
+        DCCs can be normalized to MSFs exhibited by two compared nodes
+        following:
+
+        .. math::
+
+            nDCC_{ij} = \frac{DCC_{ij}}{[DCC_{ii} DCC_{jj}]^{1/2}}
         """
         return nma.dcc(
             self, mode_subset, norm, tem, tem_factors

src/springcraft/gnm.py

@@ -245,32 +245,16 @@ def bfactor(self, mode_subset=None, tem=None,
         )
 
     def dcc(self, mode_subset=None, norm=True, tem=None, tem_factors=K_B):
-        """
+        r"""
         Computes the normalized *dynamic cross-correlation* between 
-        nodes of the GNM. The DCC for a nodepair :math:`ij` is computed as:
-
-        .. math:: 
-
-        DCC_{ij} = \frac{3 k_B T}{\gamme} \sum_k^L \left[ \frac{\vec{u}_k \cdot \vec{u}_k^T}{\lambda_k} \right]_{ij}
-
-        with :math:`\lambda`. and :math:`\vec{u}`. as 
-        Eigenvalues and Eigenvectors corresponding to mode :math:`k`. of 
-        the modeset :math:`L`.
-
-        DCCs can be normalized to MSFs exhibited by two compared nodes
-        following:
-
-        .. math::
-
-        nDCC_{ij} = \frac{DCC_{ij}}{[\DCC_{ii} DCC_{jj}]^{1/2}}
+        nodes of the GNM.
 
         The DCC is a measure for the correlation in fluctuations
         exhibited by a given pair of nodes. If normalized, pairs with 
         correlated fluctuations (same phase and period), 
         anticorrelated fluctuations (opposite phase, same period)
         and non-correlated fluctuations are assigned (normalized) 
         DCC values of 1, -1 and 0 respectively.
-        
         For results consistent with MSFs, temperature-weighted
         absolute values can be computed (only relevant if results
         are not normalized).
@@ -293,12 +277,31 @@ def dcc(self, mode_subset=None, norm=True, tem=None, tem_factors=K_B):
             If tem is None, no temperature scaling is conducted. 
         tem_factors : int, float, optional
             Factors included in temperature weighting 
-            (with K_B as preset).
+            (with :math:`k_B` as preset).
 
         Returns
         -------
         dcc : ndarray, shape=(n, n), dtype=float
             DCC values for ENM nodes.
+        
+        Notes
+        -----
+        The DCC for a nodepair :math:`ij` is computed as:
+
+        .. math:: 
+
+            DCC_{ij} = \frac{3 k_B T}{\gamma} \sum_k^L \left[ \frac{\vec{u}_k \cdot \vec{u}_k^T}{\lambda_k} \right]_{ij}
+
+        with :math:`\lambda` and :math:`\vec{u}` as 
+        Eigenvalues and Eigenvectors corresponding to mode :math:`k` of 
+        the modeset :math:`L`.
+
+        DCCs can be normalized to MSFs exhibited by two compared nodes
+        following:
+
+        .. math::
+
+            nDCC_{ij} = \frac{DCC_{ij}}{[DCC_{ii} DCC_{jj}]^{1/2}}
         """
         return nma.dcc(
             self, mode_subset, norm, tem, tem_factors

src/springcraft/nma.py

@@ -229,7 +229,7 @@ def bfactor(enm, mode_subset=None, tem=None,
     return b_factors
 
 def dcc(enm, mode_subset=None, norm=True, tem=None, tem_factors=K_B):
-    """
+    r"""
     Computes the normalized *dynamic cross-correlation* between 
     nodes of the GNM/ANM.
 
@@ -254,7 +254,7 @@ def dcc(enm, mode_subset=None, norm=True, tem=None, tem_factors=K_B):
         If tem is None, no temperature scaling is conducted. 
     tem_factors : int, float, optional
         Factors included in temperature weighting 
-        (with K_B as preset).
+        (with :math:`k_B` as preset).
 
     Returns
     -------
@@ -268,7 +268,7 @@ def dcc(enm, mode_subset=None, norm=True, tem=None, tem_factors=K_B):
 
     .. math:: 
 
-        DCC_{ij} = \frac{3 k_B T}{\gamme} \sum_k^L \left[ \frac{\vec{u}_k \cdot \vec{u}_k^T}{\lambda_k} \right]_{ij}
+        DCC_{ij} = \frac{3 k_B T}{\gamma} \sum_k^L \left[ \frac{\vec{u}_k \cdot \vec{u}_k^T}{\lambda_k} \right]_{ij}
 
     with :math:`\lambda` and :math:`\vec{u}` as 
     Eigenvalues and Eigenvectors corresponding to mode :math:`k` of 
@@ -279,7 +279,7 @@ def dcc(enm, mode_subset=None, norm=True, tem=None, tem_factors=K_B):
 
     .. math::
 
-        nDCC_{ij} = \frac{DCC_{ij}}{[\DCC_{ii} DCC_{jj}]^{1/2}}
+        nDCC_{ij} = \frac{DCC_{ij}}{[DCC_{ii} DCC_{jj}]^{1/2}}
     """
     from .gnm import GNM
     from .anm import ANM