* Move Algo_MonteCarlo code-wise for consistency with the combo box

1 files changed, 29 insertions, 29 deletions

diff --git a/tsp.py b/tsp.py
index 6bdc1e3..5c9b2cb 100755
--- a/tsp.py
+++ b/tsp.py
@@ -301,6 +301,35 @@ class Algo_2opt (Algo):
     def do_2opt (self, path):
         return self.random_reverse (path)
 
+class Algo_MonteCarlo (Algo_2opt):
+    '''2opt-based algorithm with Monte-Carlo perturbations'''
+
+    unsuccessful_loops      = 0
+    MAX_UNSUCCESSFUL_LOOPS  = 1000
+
+    def run (self, path = None):
+        '''Algorithm main loop'''
+        if not path:
+            path = self.context.nearest_neighbours_best ()
+        current = path
+        while True:
+            yield path
+            path = self.do_2opt (current)
+            if path.length < current.length:
+                current = path
+                self.unsuccessful_loops = 0
+            else:
+                '''If we did not find a better result, increment this'''
+                self.unsuccessful_loops += 1
+            '''After MAX_UNSUCCESSFUL_LOOPS, perturbate the current path'''
+            if self.unsuccessful_loops > self.MAX_UNSUCCESSFUL_LOOPS:
+                path = current = self.perturbate (current)
+                self.unsuccessful_loops = 0
+
+    def perturbate (self, path):
+        '''Perturbate a path by exchanging two points'''
+        return self.random_swap (path)
+
 class Algo_Annealing (Algo_2opt):
     '''Simulated annealing algorithm'''
 
@@ -344,35 +373,6 @@ based on the current number of iterations (or so)'''
         '''Temperature law: t = t0 - accepted_updates * 0.001 (min'd to 0.1)'''
         return max (self.t0 - self.updates * 0.001, 0.1)
 
-class Algo_MonteCarlo (Algo_2opt):
-    '''2opt-based algorithm with Monte-Carlo perturbations'''
-
-    unsuccessful_loops      = 0
-    MAX_UNSUCCESSFUL_LOOPS  = 1000
-
-    def run (self, path = None):
-        '''Algorithm main loop'''
-        if not path:
-            path = self.context.nearest_neighbours_best ()
-        current = path
-        while True:
-            yield path
-            path = self.do_2opt (current)
-            if path.length < current.length:
-                current = path
-                self.unsuccessful_loops = 0
-            else:
-                '''If we did not find a better result, increment this'''
-                self.unsuccessful_loops += 1
-            '''After MAX_UNSUCCESSFUL_LOOPS, perturbate the current path'''
-            if self.unsuccessful_loops > self.MAX_UNSUCCESSFUL_LOOPS:
-                path = current = self.perturbate (current)
-                self.unsuccessful_loops = 0
-
-    def perturbate (self, path):
-        '''Perturbate a path by exchanging two points'''
-        return self.random_swap (path)
-
 class AlgoThread (threading.Thread):
     '''Threading running a given algorithm'''