Fix issue with CovariateBlockState.merge_layers() when layers == True

src/graph_tool/community/covariate_blockmodel.py

@@ -101,14 +101,6 @@ class CovariateBlockState(BlockState):
         self.C = ec.fa.max() + 1
         self.layers = layers
 
-        if self.layers:
-            # we need to include the membership of the nodes in each layer
-            be = group_vector_property([self.ec, self.ec])
-            lstate = OverlapBlockState(self.g, b=be)
-            self.layer_entropy = lstate.entropy(dl=True, edges_dl=False) - lstate.entropy(dl=False)
-        else:
-            self.layer_entropy = 0
-
         if "max_BE" in kwargs:
             del kwargs["max_BE"]
         max_BE = 0
@@ -213,6 +205,8 @@ class CovariateBlockState(BlockState):
 
         self.overlap_stats = self.total_state.overlap_stats
 
+        self.__layer_entropy = None
+
         if _bm_test():
             assert self.mrs.fa.sum() == self.eweight.fa.sum(), "inconsistent mrs!"
 
@@ -439,6 +433,8 @@ class CovariateBlockState(BlockState):
         old_bmap = self.bmap.copy()
         self.bmap.del_c(l_src + 1)
         self.__bg = None
+        old_layer_entropy = self.__layer_entropy
+        self.__layer_entropy = None
 
         yield
 
@@ -452,6 +448,7 @@ class CovariateBlockState(BlockState):
                 self.base_ec.a[:] = old_base_ec.a
             self.C += 1
             self.bmap = old_bmap
+            self.__layer_entropy = old_layer_entropy
 
     def __getstate__(self):
         state = dict(g=self.g,
@@ -609,6 +606,19 @@ class CovariateBlockState(BlockState):
         else:
             return self.total_state.get_majority_blocks()
 
+    def __get_layer_entropy(self):
+        if self.__layer_entropy is None:
+            if self.layers:
+                # we need to include the membership of the nodes in each layer
+                g = self.base_g if self.overlap else self.g
+                ec = self.base_ec if self.overlap else self.ec
+                be = group_vector_property([ec, ec])
+                lstate = OverlapBlockState(g, b=be, deg_corr=False)
+                self.__layer_entropy = lstate.entropy(dl=True, edges_dl=False) - lstate.entropy(dl=False)
+            else:
+                self.__layer_entropy = 0
+        return self.__layer_entropy
+
     def entropy(self, complete=True, dl=False, partition_dl=True, edges_dl=True,
                 degree_dl=True, dense=False, multigraph=True, norm=False,
                 dl_ent=False, **kwargs):
@@ -684,7 +694,7 @@ class CovariateBlockState(BlockState):
                                 norm=False)
 
         if dl:
-            S += self.layer_entropy
+            S += self.__get_layer_entropy()
 
         if norm:
             S /= self.E