Changeset 405

Timestamp:

06/28/08 09:39:13 (5 months ago)

Author:

pierre

Message:

Confusion in the FixNumberPre? and FixNumberPost? connectors in nest2 as noted by pyNN users here. Others minors stuff not really interesting

Files:

• trunk/src/common.py (modified) (2 diffs)
• trunk/src/nest1/connectors.py (modified) (1 diff)
• trunk/src/nest2/__init__.py (modified) (3 diffs)
• trunk/src/nest2/connectors.py (modified) (4 diffs)
• trunk/src/recording.py (modified) (1 diff)

trunk/src/common.py

@@ -215 +215 @@
-    if not periodic_boundaries == None:
-        d = numpy.minimum(abs(d),periodic_boundaries-abs(d))
-        #d = numpy.array(map(min, ((x_i, y_i) for (x_i, y_i) in zip(abs(d), periodic_boundaries-abs(d)))))
-    if mask is not None:
-        d = d[mask]
@@ -246 +245 @@
-            diff2 = diff2.flatten()
-            diff2 = numpy.minimum(diff2, periodic_boundaries[i]-diff2)
-            #diff2 = numpy.array(map(min, ((x_i, y_i) for (x_i, y_i) in zip(diff2, periodic_boundaries[i]-diff2))))
-            diff2 = diff2.reshape(dims)
-        diff2 **= 2

trunk/src/nest1/connectors.py

@@ -113 +113 @@
-        for post in postsynaptic_neurons:
-            distances = common.distances(projection.pre, post, self.mask, self.scale_factor, self.offset, periodic_boundaries)
+            # We evaluate the probabilities of connections for those distances
-            func = eval("lambda d: %s" %self.d_expression)
-            distances[:,0] = func(distances[:,0])
-            rarr = rng.uniform(0, 1, len(distances[:,0]),)
+            # We get the list of cells that will established a connection
-            idx = numpy.where((distances[:,0] >= 1) | ((0 < distances[:,0]) & (distances[:,0] < 1) & (rarr < distances[:,0])))[0]
-            source_list = presynaptic_neurons[idx].tolist()
-
+
+
-                try:
-                    source_list.remove(post)
-                except Exception:
-                    pass
-            #for pre in presynaptic_neurons:
-                #if self.allow_self_connections or pre != post: 
-                    ## calculate the distance between the two cells :
-                    #p = distances[idx_pre,0]
-                    #if p >= 1 or (0 < p < 1 and rarr[j] < p):
-                        #source_list.append(pre)
-                #j += 1
-                #idx_pre += 1
-            N = len(source_list)
-            weights = self.getWeights(N)

trunk/src/nest2/__init__.py

@@ -144 +144 @@
-            nest_filename = _merge_files(self._device, gather)
-            data = recording.readArray(nest_filename, sepchar=None)
-
+#
-            if data.size > 0:
-                # the following returns indices, not IDs. I'm not sure this is what we want.
@@ -164 +164 @@
-                user_filename += '.%d' % rank()
-            if gather == False or rank() == 0: # if we gather, only do this on the master node
-
-
+
-        else:
-            system_line = 'cat %s >> %s' % (nest_filename, user_filename)
@@ -767 +766 @@
-        else:
-            rng = rng or numpy.random
-
-
+
-
-        self.recorders[variable].record(tmp_list)

trunk/src/nest2/connectors.py

@@ -131 +131 @@
-            rng = numpy.random
-        for pre in presynaptic_neurons:
+            # We compute the distances from the post cell to all the others
-            distances = common.distances(pre, projection.post, self.mask,
-                                         self.scale_factor, self.offset,
-                                         periodic_boundaries)
+            # We evaluate the probabilities of connections for those distances
-            func = eval("lambda d: %s" %self.d_expression)
-            distances[0] = func(distances[0])
+            # We get the list of cells that will established a connection
-            rarr = rng.uniform(0, 1, len(distances[0,:]),)
-            idx = numpy.where((distances[0,:] >= 1) | ((0 < distances[0,:]) & (distances[0,:] < 1) & (rarr < distances[0,:])))[0]
-            target_list = postsynaptic_neurons[idx].tolist()
-
+
+
-                try:
-                    target_list.remove(pre)
-                except Exception:
-                    pass
-            #for post in postsynaptic_neurons:
-            #    if self.allow_self_connections or pre != post: 
-                    # calculate the distance between the two cells :
-            #        p = distances[0,idx_post]
-            #        if p >= 1 or (0 < p < 1 and rarr[j] < p):
-            #            target_list.append(post)
-            #    j += 1
-            #    idx_post += 1
-            N = len(target_list)
-            weights = self.getWeights(N)
@@ -163 +159 @@
-
-
-reConnector(common.FixedNumberPre
+ostConnector(common.FixedNumberPost
-    
-    def connect(self, projection):
@@ -185 +181 @@
-            weights = _convertWeight(weights, projection.synapse_type).tolist()
-            delays = self.getDelays(N).tolist()
-
+
-            nest.DivergentConnectWD([pre], target_list.tolist(), weights, delays)
-
-            projection._sources += [pre]*N
-            conn_dict = nest.GetConnections([pre], projection._plasticity_model)[0]
@@ -209 +204 @@
-    return n
-
-ostConnector(common.FixedNumberPost
+reConnector(common.FixedNumberPre
-    
-    def connect(self, projection):

trunk/src/recording.py

@@ -68 +68 @@
-    # Writing spiketimes, cell_id-min(cell_id)                    
-    # open file
-
+
+
+
+
+
+
+
-        data = readArray(sim_filename, sepchar=None)
-