Changeset 729 for trunk/src/connectors2.py

Timestamp:

03/12/10 01:26:31 (2 years ago)

Author:

pierre

Message:

Add a nice progress bar to all the new connectors in connectors2.py. Now, a verbose flag allows to display or not a progress bar indicating the percentage of connections established. Can be useful to know how long connections will take. Some minors ameliorations. Everything is now OK, some informal tests shows numbers of synapses are ok for all the connectors. The last point to test is to make sure distances are correct. Should be the case, but should be sure....

Files:

• trunk/src/connectors2.py (modified) (36 diffs)

trunk/src/connectors2.py

@@ -1 @@
-import numpy
-from pyNN import errors, common, core, random
+import numpy, logging, sys
+from pyNN import errors, common, core, random, utility
 from pyNN.space import Space
 from pyNN.random import RandomDistribution
@@ -7 +7 @@
                     sin, sinh, sqrt, tan, tanh, maximum, minimum
 
+logger = logging.getLogger("PyNN")
+
 class ConnectionAttributeGenerator(object):
     
@@ -13 +15 @@
         self.local_mask = local_mask
         self.safe       = safe
+        if self.safe:
+            self.get = self.get_safe    
         if isinstance(self.source, numpy.ndarray):
             self.source_iterator = iter(self.source)
     
-    def get(self, N, distance_matrix=None, sub_mask=None):
+    def check(self, data):
+        return data
+        
+    def extract(self, N, distance_matrix=None, sub_mask=None):
         if isinstance(self.source, basestring):
             assert distance_matrix is not None
@@ -39 +46 @@
             if sub_mask:
                 values = values[sub_mask]
-            return values
+            return values    
+
+    def get_safe(self, N, distance_matrix=None, sub_mask=None):
+        return self.check(self.extract(N, distance_matrix, sub_mask))
+    
+    def get(self, N, distance_matrix=None, sub_mask=None):
+        return self.extract(N, distance_matrix, sub_mask)
 
 
@@ -74 +87 @@
             logger.debug("Can't check weight, conductance status unknown.")
         return weight
-
-    def get(self, N, distance_matrix=None, sub_mask=None):
-      values = ConnectionAttributeGenerator.get(self, N, distance_matrix, sub_mask)      
-      if self.safe:
-          values = self.check(values)
-      return values
-
+        
+    
 
 class DelayGenerator(ConnectionAttributeGenerator):
@@ -88 +96 @@
         self.min_delay = common.get_min_delay()
         self.max_delay = common.get_max_delay()
-
+        
     def check(self, delay):
         all_negative = (delay<=self.max_delay).all()
@@ -94 +102 @@
         if not (all_negative and all_positive):
             raise errors.ConnectionError("delay (%s) is out of range [%s,%s]" % (delay, common.get_min_delay(), common.get_max_delay()))
-        return delay
-
-    def get(self, N, distance_matrix=None, sub_mask=None):
-        values = ConnectionAttributeGenerator.get(self, N, distance_matrix, sub_mask)
-        if self.safe:
-            values = self.check(values)
-        return values
-
+        return delay    
 
 class ProbaGenerator(ConnectionAttributeGenerator):
@@ -113 +114 @@
         self.space = space
         if mask is not None:
-            self.B = ((B.T)[mask]).T
+            self.B = B[:,mask]
         else:
             self.B = B
@@ -133 +134 @@
 class Connector(object):
     
-    def __init__(self, weights=0.0, delays=None, space=Space(), safe=True):
+    def __init__(self, weights=0.0, delays=None, space=Space(), safe=True, verbose=True):
         self.weights = weights
         self.space   = space
         self.safe    = safe
+        self.verbose = verbose
         min_delay    = common.get_min_delay()
         if delays is None:
@@ -143 +145 @@
             if core.is_listlike(delays):
                 assert min(delays) >= min_delay
-            else:
+            elif not (isinstance(delays, basestring) or isinstance(delays, RandomDistribution)):
                 assert delays >= min_delay
-            self.delays = delays
-    
+            self.delays = delays        
+        
     def connect(self, projection):
         pass
     
+    def progressbar(self, N):
+        self.prog = utility.ProgressBar(0, N, 20, mode='fixed')        
+    
+    def progression(self, count):
+        if self.verbose:
+            self.prog.update_amount(count)
+            print self.prog, "\r",
+            sys.stdout.flush()
+            
 
 
@@ -207 +218 @@
     """
     
-    def __init__(self, allow_self_connections=True, weights=0.0, delays=None, space=Space(), safe=True):
+    def __init__(self, allow_self_connections=True, weights=0.0, delays=None, space=Space(), safe=True, verbose=True):
         """
         Create a new connector.
@@ -223 +234 @@
                    dependent weights or delays
         """
-        Connector.__init__(self, weights, delays, space, safe)
+        Connector.__init__(self, weights, delays, space, safe, verbose)
         assert isinstance(allow_self_connections, bool)
         self.allow_self_connections = allow_self_connections
@@ -229 +240 @@
     def connect(self, projection):
         connector = ProbabilisticConnector(projection, self.weights, self.delays, self.allow_self_connections, self.space, safe=self.safe)        
+        self.progressbar(len(projection.pre))
         for count, src in enumerate(projection.pre.all()):
             connector._probabilistic_connect(src, 1)
-
-
+            self.progression(count)
+            
     
 
@@ -240 +252 @@
     """
     
-    def __init__(self, p_connect, allow_self_connections=True, weights=0.0, delays=None, space=Space(), safe=True):
+    def __init__(self, p_connect, allow_self_connections=True, weights=0.0, delays=None, space=Space(), 
+                       safe=True, verbose=True):
         """
         Create a new connector.
@@ -258 +271 @@
                    dependent weights or delays
         """
-        Connector.__init__(self, weights, delays, space, safe)
+        Connector.__init__(self, weights, delays, space, safe, verbose)
         assert isinstance(allow_self_connections, bool)
         self.allow_self_connections = allow_self_connections
@@ -267 +280 @@
         #assert projection.rng.parallel_safe
         connector = ProbabilisticConnector(projection, self.weights, self.delays, self.allow_self_connections, self.space, safe=self.safe)
-        for src in projection.pre.all():
+        self.progressbar(len(projection.pre))
+        for count, src in enumerate(projection.pre.all()):
             connector._probabilistic_connect(src, self.p_connect)
-
+            self.progression(count)
+            
 
 class DistanceDependentProbabilityConnector(ProbabilisticConnector):
@@ -277 +292 @@
     
     def __init__(self, d_expression, allow_self_connections=True,
-                 weights=0.0, delays=None, space=Space(), safe=True):
+                 weights=0.0, delays=None, space=Space(), safe=True, verbose=True):
         """
         Create a new connector.
@@ -290 +305 @@
                      to the global minimum delay.
         """
-        Connector.__init__(self, weights, delays, space, safe)
+        Connector.__init__(self, weights, delays, space, safe, verbose)
         assert isinstance(d_expression, str)
         try:
@@ -305 +320 @@
         connector       = ProbabilisticConnector(projection, self.weights, self.delays, self.allow_self_connections, self.space, safe=self.safe)
         proba_generator = ProbaGenerator(self.d_expression, connector.local)
-
-        for src in projection.pre.all():     
+        self.progressbar(len(projection.pre))
+        for count, src in enumerate(projection.pre.all()):     
             connector.distance_matrix.set_source(src.position)
             proba  = proba_generator.get(connector.N, connector.distance_matrix)
@@ -312 +327 @@
                 proba = proba.astype(float)
             connector._probabilistic_connect(src, proba)
-
+            self.progression(count)
+    
 
 class FromListConnector(Connector):
@@ -319 +335 @@
     """
     
-    def __init__(self, conn_list):
+    def __init__(self, conn_list, safe=True, verbose=True):
         """
         Create a new connector.
@@ -331 +347 @@
         """
         # needs extending for dynamic synapses.
-        Connector.__init__(self, 0., common.get_min_delay())
+        Connector.__init__(self, 0., common.get_min_delay(), safe=safe, verbose=verbose)
         self.conn_list = conn_list        
         
@@ -337 +353 @@
         """Connect-up a Projection."""
         # slow: should maybe sort by pre
-        for i in xrange(len(self.conn_list)):
+        self.progressbar(len(self.conn_list))
+        for count, i in enumerate(xrange(len(self.conn_list))):
             src, tgt, weight, delay = self.conn_list[i][:]
             src = projection.pre[tuple(src)]           
             tgt = projection.post[tuple(tgt)]
             projection.connection_manager.connect(src, [tgt], weight, delay)
-
+            self.progression(count)
+            
 
 class FromFileConnector(FromListConnector):
@@ -349 +367 @@
     """
     
-    def __init__(self, filename, distributed=False):
+    def __init__(self, filename, distributed=False, safe=True, verbose=True):
         """
         Create a new connector.
@@ -360 +378 @@
                          distributed simulations.
         """
-        Connector.__init__(self, 0., common.get_min_delay())
+        Connector.__init__(self, 0., common.get_min_delay(), safe=safe, verbose=verbose)
         self.filename = filename
         self.distributed = distributed
@@ -397 +415 @@
     """
     
-    def __init__(self, n, allow_self_connections=True, weights=0.0, delays=None, space=Space(), safe=True):
+    def __init__(self, n, allow_self_connections=True, weights=0.0, delays=None, space=Space(), safe=True, verbose=True):
         """
         Create a new connector.
@@ -415 +433 @@
                      to the global minimum delay.
         """
-        Connector.__init__(self, weights, delays, space, safe)
+        Connector.__init__(self, weights, delays, space, safe, verbose)
         assert isinstance(allow_self_connections, bool)
         self.allow_self_connections = allow_self_connections
@@ -433 +451 @@
         weights_generator = WeightGenerator(self.weights, local, projection, self.safe)
         delays_generator  = DelayGenerator(self.delays, local, self.safe)
-        distance_matrix   = DistanceMatrix(projection.post.positions, self.space, numpy.arange(len(projection.post)))
+        distance_matrix   = DistanceMatrix(projection.post.positions, self.space)
         candidates        = projection.post.all_cells.flatten()            
+        self.progressbar(len(projection.pre))        
         
         if isinstance(projection.rng, random.NativeRNG):
             raise Exception("Use of NativeRNG not implemented.")        
         
-        for src in projection.pre.all():
+        for count, src in enumerate(projection.pre.all()):
             # pick n neurons at random
             if hasattr(self, 'rand_distr'):
@@ -463 +482 @@
             if len(targets) > 0:
                 projection.connection_manager.connect(src, targets.tolist(), weights, delays)
-                    
+            
+            self.progression(count)
+            
 
 class FixedNumberPreConnector(Connector):
@@ -477 +498 @@
     """
     
-    def __init__(self, n, allow_self_connections=True, weights=0.0, delays=None, space=Space(), safe=True):
+    def __init__(self, n, allow_self_connections=True, weights=0.0, delays=None, space=Space(), safe=True, verbose=True):
         """
         Create a new connector.
@@ -510 +531 @@
     def connect(self, projection):
         """Connect-up a Projection."""
-        local             = numpy.arange(len(projection.post))        
+        local             = projection.pre._mask_local.flatten()
         weights_generator = WeightGenerator(self.weights, local, projection, self.safe)
         delays_generator  = DelayGenerator(self.delays, local, self.safe)
         distance_matrix   = DistanceMatrix(projection.pre.positions, self.space)
         candidates        = projection.pre.all_cells.flatten()                        
+        self.progressbar(len(projection.pre))                
         
         if isinstance(projection.rng, random.NativeRNG):
             raise Exception("Warning: use of NativeRNG not implemented.")
             
-        for tgt in projection.post.local_cells.flat:
+        for count, tgt in enumerate(projection.post.local_cells.flat):
             # pick n neurons at random
             if hasattr(self, 'rand_distr'):
@@ -543 +565 @@
             for src, w, d in zip(sources, weights, delays):
                 projection.connection_manager.connect(src, [tgt], w, d)
-                    
+            
+            self.progression(count)
+            
 
 class OneToOneConnector(Connector):
@@ -557 +581 @@
     
     
-    def __init__(self, weights=0.0, delays=None, space=Space()):
+    def __init__(self, weights=0.0, delays=None, space=Space(), safe=True, verbose=True):
         """
         Create a new connector.
@@ -567 +591 @@
                      to the global minimum delay.
         """
-        Connector.__init__(self, weights, delays, space)
+        Connector.__init__(self, weights, delays, space, verbose)
+        self.space = space
+        self.safe  = safe
     
     def connect(self, projection):
@@ -574 +600 @@
             N                 = projection.post.size
             local             = projection.post._mask_local.flatten()
-            weights_generator = WeightGenerator(self.weights, local, projection)
-            delays_generator  = DelayGenerator(self.delays, local)                
+            weights_generator = WeightGenerator(self.weights, local, projection, self.safe)
+            delays_generator  = DelayGenerator(self.delays, local, self.safe)                
             weights           = weights_generator.get(N)
             delays            = delays_generator.get(N)
+            self.progressbar(len(projection.post.local_cells))                        
+            count             = 0
             
             for tgt, w, d in zip(projection.post.local_cells, weights, delays):
@@ -584 +612 @@
                 # the float is in case the values are of type numpy.float64, which NEST chokes on
                 projection.connection_manager.connect(src, [tgt], float(w), float(d))
+                self.progression(count)
+                count += 1
         else:
             raise errors.InvalidDimensionsError("OneToOneConnector does not support presynaptic and postsynaptic Populations of different sizes.")