RF: Remove random_mod_old method and refs to module_merge method

Author: Katelyn Begany

brainx/modularity.py

@@ -516,7 +516,6 @@ def random_mod(self):
 
         if coin_flip > 0.5:
             #merge
-            #return self.module_merge(m1,m2)
             return self.compute_module_merge(m1,m2)
         else:
             #split
@@ -537,7 +536,7 @@ def random_mod(self):
             return self.compute_module_split(m1,n1,n2)
 
     def determine_node_split(self,m1):
-        """ Determine hwo to split notes within a module
+        """ Determine how to split nodes within a module
         """
 
         # list of nodes within that module
@@ -553,68 +552,6 @@ def determine_node_split(self,m1):
 
         return n1,n2
 
-
-    def random_mod_old(self):
-        """Makes a choice whether to merge or split modules in a partition
-
-        Returns:
-        -------
-        if splitting: m1, n1, n2
-          m1: the module to split
-          n1: the set of nodes to put in the first output module
-          n2: the set of nodes to put in the second output module
-
-        if merging: m1, m2
-          m1: module 1 to merge
-          m2: module 2 to merge
-        """
-
-        # number of modules in the partition
-        num_mods=len(self)
-
-
-        # Make a random choice bounded between 0 and 1, less than 0.5 means we will split the modules
-        # greater than 0.5 means we will merge the modules.
-
-        if num_mods >= self.num_nodes-1:
-            coin_flip = 1 #always merge if each node is in a separate module
-        elif num_mods <= 2:
-            coin_flip = 0 #always split if there's only one module
-        else:
-            coin_flip = random.random()
-
-        #randomly select two modules to operate on
-        rand_mods = np.random.permutation(range(num_mods))
-        m1 = rand_mods[0]
-        m2 = rand_mods[1]
-
-        if coin_flip > 0.5:
-            #merge
-            #return self.module_merge(m1,m2)
-            return self.module_merge(m1,m2)
-        else:
-            #split
-            # cannot have a module with less than 1 node
-            while len(self.index[m1]) <= 1:
-
-                #reselect the first  module
-                rand_mods = np.random.permutation(range(num_mods))
-                m1 = rand_mods[0]
-                #m1 = random.randint(0,num_mods)
-
-            # list of nodes within that module
-            list_nods = list(self.index[m1])
-
-            # randomly partition the list of nodes into 2
-            nod_split_ind = random.randint(1,len(list_nods)) #can't pick the first node as the division
-            n1 = set(list_nods[:nod_split_ind])
-            n2 = set(list_nods[nod_split_ind:])
-
-            #We may want to return output of merging/splitting directly, but
-            #for now we're returning inputs for those modules.
-
-            return self.module_split(m1,n1,n2)
-
     def random_node(self):
         """ Randomly reassign one node from one module to another
 
@@ -672,7 +609,7 @@ def check_integrity(self, partition):
 
         # Raise error if any partition contains NaN value(s)
         if [np.isnan(value) for sets in partition.values() for value in sets]:
-            raise ValueError("Partition contains NaN(s)")
+            raise ValueError("Partition contains NaN value(s)")
 
 #-----------------------------------------------------------------------------
 # Functions