WIP: optimisation algo.

src/model.py

@@ -353,10 +353,10 @@ class Conditions:
             if(child.tag == "condition"):
                 self.__conditions.append(Condition(child))
 
-    def get_condition(self, i):
+    def get_one(self, i):
         return self.__conditions[i]
 
-    def get_conditions_array(self):
+    def get_all(self):
         return self.__conditions
 
 
@@ -397,10 +397,10 @@ class Transitions:
             if(child.tag == "transition"):
                 self.__transitions.append(Transition(child))
 
-    def get_transition(self, i):
+    def get_one(self, i):
         return self.__transitions[i]
 
-    def get_transitions_array(self):
+    def get_all(self):
         return self.__transitions
 
 ## Model

src/rules_tree.py

@@ -6,24 +6,6 @@ import model
 #       1) node_id <> pas de doublons
 #       2) tout node doit avoir un node_parent_id
 
-conditions_set = set()
-conditions_list = []
-transitions_set = set()
-
-for i in range(0, len(model.testmodel.get_conditions().get_conditions_array())):
-    condition = model.testmodel.get_conditions().get_condition(i)
-    conditions_set.add((condition.get_node_self_id(),
-                        condition.get_node_parent_id(),
-                        condition.get_coord("x"),  # TODO  y,z,...
-                        condition.get_site(),
-                        condition.get_weight()))
-
-
-for i in range(0,
-               len(model.testmodel.get_transitions().get_transitions_array())):
-    transition = model.testmodel.get_transitions().get_transition(i)
-    transitions_set.add((transition.get_id(), transition.get_parent()))
-
 
 class CondTreeNode(NodeMixin):
     def __init__(self, id, x, site, weight, parent_node_id):
@@ -36,8 +18,8 @@ class CondTreeNode(NodeMixin):
         self.weight = weight
 
     def add_parent_node(self, parent_node):
+        print('orphan node ', self.id, ' is adopted by node ', parent_node.id)
         self.parent = parent_node
-        # print('orphan node ', self.id, ' is adopted by node ', parent_node.id)
 
 
 class TransTreeNode(NodeMixin):
@@ -52,28 +34,43 @@ class TransTreeNode(NodeMixin):
         self.parent = parent_node
 
 
-for i in conditions_set:  # sorted(conditions_set, key=i.id):
+conditions_set = set()
-    condition = CondTreeNode(i[0], i[2], i[3], i[4], i[1])   # TODO y,z,...
+transitions_set = set()
-    conditions_list.append(condition)
-
 root = 0
 
-for i in conditions_list:
+for i in range(0, len(model.testmodel.get_conditions().get_all())):
-    if (i.parent is None):
+    condition = model.testmodel.get_conditions().get_one(i)
-        for j in conditions_list:
+    conditions_set.add(CondTreeNode(
-            if (i.parent_node_id == j.id):
+                       condition.get_node_self_id(),
+                       condition.get_node_parent_id(),
+                       condition.get_coord("x"),
+                       condition.get_site(),
+                       condition.get_weight()))
+
+for i in range(0, len(model.testmodel.get_transitions().get_all())):
+    transition = model.testmodel.get_transitions().get_one(i)
+    transitions_set.add(TransTreeNode(
+                        transition.get_id(),
+                        transition.get_parent()))
+
+#                      0          1          2          3      4
+#        <condition site="1" weight="0" node_id="3" parent="2" x="2"/>
+
+for i in conditions_set:
+    if (i.parent_node_id == 0):
+        root = i
+
+for i in conditions_set:
+    for j in conditions_set:
+        if ((i != j) & (i.parent_node_id == j.id)):
             i.add_parent_node(j)
-            else:
-                root = j
 
 for condition_node in LevelOrderIter(root):
     if condition_node.is_leaf:
-        for i in transitions_set:
+        for transition_node in transitions_set:
-            transition_node = TransTreeNode(i[1], i[0])
+            if (str(condition_node.id) == transition_node.parent):
-            if (str(condition_node.id) == i[1]):
                 transition_node.add_parent_leaf_node(condition_node)
 
-
 for pre, fill, node in RenderTree(root):
     treestr = u"%s%s" % (pre, node.id)
     if (type(node) == CondTreeNode):
@@ -84,4 +81,5 @@ for pre, fill, node in RenderTree(root):
         else:
             print(']   >  ', node.children[0].id, end='\n')
 
+print('\nNext step: single rule extraction from tree.  😃️')
 # print([node.id for node in LevelOrderIter(root) if node.is_leaf])