Changeset 433

Timestamp:

08/05/08 13:59:20 (2 months ago)

Author:

pierre

Message:

Work on nest2.py, still to improve the building time of a large network. The _targets_ports are removed, and we use the FindConnections?() method of nest to retrieve the connections after they have been build. It seems to work. unit tests have also been updated, just to take into account the fact that now, we use a particular synapse_context for each projection, and that connections are retrieved within those contexts. Minor others stuffs, like adding the Result directory to the test directory, changing the simple_STDP.py test file to deal with the new way of handling synaptic_contexts.

Files:

• trunk/src/nest1/connectors.py (modified) (2 diffs)
• trunk/src/nest2/__init__.py (modified) (14 diffs)
• trunk/src/nest2/connectors.py (modified) (11 diffs)
• trunk/test/Results (added)
• trunk/test/VAbenchmarks.py (modified) (1 diff)
• trunk/test/simple_STDP.py (modified) (2 diffs)
• trunk/test/unittests/nest2tests.py (modified) (9 diffs)

trunk/src/nest1/connectors.py

@@ -21 +21 @@
-        all_positive = (weight>=0).all()
-        assert all_negative or all_positive, "Weights must be either all positive or all negative"
-
-
-
+
+
-    elif is_number(weight):
-        if synapse_type == 'inhibitory' and weight > 0:
@@ -73 +72 @@
-        presynaptic_neurons  = numpy.reshape(projection.pre.cell,(projection.pre.cell.size,))
-        npre = projection.pre.size
+        if projection.rng:
+            if isinstance(projection.rng, NativeRNG):
+                print "Warning: use of NativeRNG not implemented. Using NumpyRNG"
+                rng = numpy.random
+            else:
+                rng = projection.rng
+        else:
+            rng = numpy.random
-        for post in postsynaptic_neurons:
-
-
-
-
+
-            source_list = numpy.compress(numpy.less(rarr, self.p_connect), presynaptic_neurons).tolist()
-            # if self connections are not allowed, check whether pre and post are the same

trunk/src/nest2/__init__.py

@@ -125 +125 @@
-        if file is False:
-            device_parameters.update(to_file=False, to_memory=True)
+        # line needed for old version of nest 2.0
+        # device_parameters.pop('to_memory')
-        nest.SetStatus(self._device, device_parameters)
-
@@ -574 +576 @@
-        if isinstance(cellclass, type):
-            self.celltype = cellclass(cellparams)
+            self.cellparams = self.celltype.parameters
-            if not parent:
-                self.cell = nest.Create(self.celltype.nest_name, self.size)
@@ -579 +582 @@
-                #A SubPopulation has been created, those fields will be filled later
-                self.cell = []
-            self.cellparams = self.celltype.parameters
-        elif isinstance(cellclass, str):
-            if not parent:
@@ -911 +913 @@
-            nest.sps(self.recorders['spikes']._device[0])
-            nest.sr("%d GetAddress %d append" %(self.recorders['spikes']._device[0], node))
+            #nest.sr("GetStatus /events get")
-            nest.sr("GetStatus /n_events get")
-            n_spikes += nest.spp()
@@ -985 +988 @@
-
-        def __init__(self, parent):
-
+
+
+
+
+
+
+
-
-        def __getitem__(self, id):
-            """Returns a (source address, target port number) tuple."""
-
-
+
+
+
+
+
+
+
+
+
+
+
+
+
-
-    def __init__(self, presynaptic_population, postsynaptic_population,
@@ -1042 +1062 @@
-        # Set synaptic plasticity parameters
-        original_synapse_context = nest.GetSynapseContext()
-
-
-
+
+
+
+
+
+
+
+
+
-
-        if hasattr(self, '_short_term_plasticity_parameters') and self._short_term_plasticity_parameters:
-_plasticity_model
+plasticity_name
-            synapse_defaults.pop('num_connections') # otherwise NEST tells you to check your spelling!
-            if 'num_connectors' in synapse_defaults:
-                synapse_defaults.pop('num_connectors')
-            synapse_defaults.update(self._short_term_plasticity_parameters)
-
-
+
-
-        if hasattr(self, '_stdp_parameters') and self._stdp_parameters:
@@ -1068 +1093 @@
-                raise Exception("Postsynaptic cell model does not support STDP.")
-
-_plasticity_model
+plasticity_name
-            if 'num_connectors' in synapse_defaults:
-                synapse_defaults.pop('num_connectors') # otherwise NEST tells you to check your spelling!
-            synapse_defaults.pop('num_connections') # otherwise NEST tells you to check your spelling!
-            synapse_defaults.update(self._stdp_parameters)
-_plasticity_model
+plasticity_name
-
-        # Create connections
@@ -1097 +1122 @@
-    def connections(self):
-        """for conn in prj.connections()..."""
+        self.connection.reset()
-        for i in xrange(len(self)):
-            yield self.connection[i]
@@ -1230 +1256 @@
-            if optimized:
-                for src in self.pre.cell.flat:
-_plasticity_model
+plasticity_name
-            else:
-                for src, port in self.connections():
-_plasticity_model
+plasticity_name
-        elif isinstance(value, (list, numpy.ndarray)):
-            # this is probably not the most efficient way - should sort by src and then use SetConnections?
@@ -1239 +1265 @@
-            for (src,port),v in zip(self.connections(), value):
-                try:
-_plasticity_model
+plasticity_name
-                except common.RoundingWarning:
-                    logging.warning("Rounding occurred when setting %s to %s" % (name, v))
@@ -1296 +1322 @@
-                                                                    self._method)
-        print "\tsource\ttarget\tport"
-
-
+
+
+
+
-        print "Connection data for the presynaptic population (%s)" % self.pre.label
-        for src in self.pre.cell.flat:
-_plasticity_model
+plasticity_name
-
-    def _get_connection_values(self, format, parameter_name, gather):
@@ -1307 +1335 @@
-            values = []
-            for src, port in self.connections():
-_plasticity_model
+plasticity_name
-        elif format == 'array':
-            values = numpy.zeros((self.pre.size, self.post.size))
-            for src, port in self.connections():
-_plasticity_model
+plasticity_name
-                                         parameter_name, 'target')
-                # note that we assume that Population ids are consecutive, which is the case, but we should
@@ -1350 +1378 @@
-        weights = []; delays = []
-        for src, port in self.connections():
-_plasticity_model
+plasticity_name
-                                            'weight', 'delay')
-            # Note unit change from pA to nA or nS to uS, depending on synapse type
@@ -1394 +1422 @@
-        """
-        description = common.Projection.describe(self, template)
-
-
+
+
+
+
+
-        for i in xrange(len(self._targets)):
-            idx  = numpy.where(numpy.array(dict['targets']) == self._targets[i])[0]

trunk/src/nest2/connectors.py

@@ -12 +12 @@
-from pyNN.random import RandomDistribution, NativeRNG
-from math import *
+from random import sample
-from numpy import arccos, arcsin, arctan, arctan2, ceil, cos, cosh, e, exp, \
-                  fabs, floor, fmod, hypot, ldexp, log, log10, modf, pi, power, \
@@ -22 +23 @@
-        all_positive = (weight>=0).all()
-        assert all_negative or all_positive, "Weights must be either all positive or all negative"
-
-
-
+
+
-    elif is_number(weight):
-        if synapse_type == 'inhibitory' and weight > 0:
@@ -46 +46 @@
-
-    def connect(self, projection):
-
+_local
-        target_list = postsynaptic_neurons.tolist()
-        for pre in projection.pre.cell.flat:
@@ -60 +60 @@
-            projection._targets += target_list
-            projection._sources += [pre]*N
-
+#
-            nest.DivergentConnectWD([pre], target_list, weights, delays)
-        return len(projection._targets)
@@ -71 +71 @@
-            projection._targets = projection.post.cell.flatten()
-            N = len(projection._sources)
-
+#
-            weights = self.getWeights(N)
-            weights = _convertWeight(weights, projection.synapse_type).tolist()
@@ -83 +83 @@
-    
-    def connect(self, projection):
-.flatten()
+_local
-        npost = len(postsynaptic_neurons)
-
-
-
-
-
+
+
+
+
+
+
+
+
+
+
-            target_list = numpy.compress(numpy.less(rarr, self.p_connect), postsynaptic_neurons).tolist()
+            #N           = rng.binomial(npost,self.p_connect,1)[0]
+            #target_list = sample(postsynaptic_neurons, N)
-            # if self connections are not allowed, check whether pre and post are the same
-            if not self.allow_self_connections and pre in target_list:
@@ -97 +104 @@
-            weights = self.getWeights(N)
-            weights = _convertWeight(weights, projection.synapse_type).tolist()
-
+ 
-            projection._targets += target_list
-            projection._sources += [pre]*N
-
+#
-            nest.DivergentConnectWD([pre], target_list, weights, delays)
-        return len(projection._sources)
@@ -157 +164 @@
-            projection._targets += target_list
-            projection._sources += [pre]*N 
-
+#
-            nest.DivergentConnectWD([pre], target_list, weights, delays)
-        return len(projection._sources)
@@ -191 +198 @@
-                total_targets = len(all_targets)
-                projection._targets += all_targets[-N:]
-
+#
-        return len(projection._sources)
-
@@ -235 +242 @@
-        end_ports = _n_connections(projection.pre, projection._plasticity_model)
-        for pre, start_port, end_port in zip(presynaptic_neurons, start_ports, end_ports):
-
+#
-            projection._sources += [pre]*(end_port-start_port)
-            conn_dict = nest.GetConnections([pre], projection._plasticity_model)[0]
@@ -253 +260 @@
-        projection._sources.append(src)
-        projection._targets.append(tgt)
-
+#
-        weights.append(_convertWeight(weight, projection.synapse_type))
-        delays.append(delay)

trunk/test/VAbenchmarks.py

@@ -140 +140 @@
-rng = NumpyRNG(seed=rngseed, parallel_safe=False, rank=node_id, num_processes=np)
-uniformDistr = RandomDistribution('uniform', [v_reset,v_thresh], rng=rng)
-if simulator == "brian":
-    uniformDistr = RandomDistribution('uniform', [v_reset*0.001,v_thresh*0.001], rng=rng)
-exc_cells.randomInit(uniformDistr)
-inh_cells.randomInit(uniformDistr)

trunk/test/simple_STDP.py

@@ -36 +36 @@
-
-if simulator == "nest2":
-'stdp_synapse_hom'
+prj.plasticity_name
-    print nest.GetStatus([p2[0]])
-
@@ -47 +47 @@
-    while t < 50:
-        t = run(1.0)
-'stdp_synapse_hom'
+prj.plasticity_name
-        print "%4.1f   %6.4f   %7.3f   %6.4f" % (t, prj.getWeights()[0], syn_dict['Kplus'], syn_dict['weight'])
-#run(1000.0)

trunk/test/unittests/nest2tests.py

@@ -11 +11 @@
-import os
-
-
-'static_synapse'
+, plasticity_name
+plasticity_name
-    if isinstance(conn_dict, dict):
-        return conn_dict['weight']
@@ -18 +18 @@
-        raise Exception("Either the source id (%s) or the port number (%s) or both is invalid." % (src, port))
-
-
-'static_synapse'
+, plasticity_name
+plasticity_name
-    if isinstance(conn_dict, dict):
-        return conn_dict['delay']
@@ -445 +445 @@
-                        ###print "--------", prj.label, srcP.label, tgtP.label, src, tgt
-                        ###print nest.nest.GetConnections([src],'static_synapse') ###
-
+, prj.plasticity_name
-                    assert weights == [0.0]*len(prj._sources)
-    
@@ -483 +483 @@
-                    for src, tgt in prj.connections():
-                        #print nest.nest.GetConnections([src],[tgt])
-
+, prj.plasticity_name
-                    assert weights == [0.]*len(prj._sources)
-                    
@@ -497 +497 @@
-        # are equal.
-        for src,tgt in prj1.connections():
-
-
+, prj1.plasticity_name
+, prj1.plasticity_name
-        for src,tgt in prj2.connections():
-
-
+, prj2.plasticity_name
+, prj2.plasticity_name
-        assert (w1 == w2) and (d1 == d2)
-
@@ -527 +527 @@
-            prj.setWeights(1.234)
-            for src, tgt in prj.connections():
-
+, prj.plasticity_name
-
-    #def testSetAndGetID(self):
@@ -540 +540 @@
-            weights_out = []
-            for src,tgt in prj.connections():
-
+, prj.plasticity_name
-            self.assert_(arrays_almost_equal(weights_in, weights_out, 1e-8), "%s != %s" % (weights_in, weights_out))
-            
@@ -549 +549 @@
-        w1 = []; w2 = [];
-        for src,tgt in prj1.connections():
-
+, prj1.plasticity_name
-        prj1.randomizeWeights(self.distrib_Numpy)        
-        for src, tgt in prj1.connections():
-
+, prj1.plasticity_name
-        self.assertNotEqual(w1,w2)
-        
@@ -561 +561 @@
-        d1 = []; d2 = [];
-        for src,tgt in prj1.connections():
-
+, prj1.plasticity_name
-        prj1.randomizeDelays(self.distrib_Numpy)        
-        for src, tgt in prj1.connections():
-
+, prj1.plasticity_name
-        self.assertNotEqual(d1,d2)
-