Changeset 89

Timestamp:

06/05/07 11:26:34 (1 year ago)

Author:

apdavison

Message:

Implemented AllToAllConnector and OneToOneConnector for nest, neuron and pcsim.

You can now pass either a Connector object or a string plus parameter dict to the Projection constructor, e.g.:

prj1 = Projection(p1, p2, 'allToAll', {'allow_self_connections':False})
prj2 = Projection(p1, p2, AllToAllConnector(allow_self_connections=False))

Files:

• branches/connector-class/common.py (modified) (3 diffs)
• branches/connector-class/nest.py (modified) (17 diffs)
• branches/connector-class/neuron.py (modified) (4 diffs)
• branches/connector-class/pcsim.py (modified) (2 diffs)
• branches/connector-class/test/nesttests.py (modified) (1 diff)
• branches/connector-class/test/neurontests.py (modified) (2 diffs)
• branches/connector-class/test/pcsimtests_population.py (modified) (3 diffs)

branches/connector-class/common.py

@@ +1 @@
+# encoding: utf-8
-"""
-Defines the PyNN classes and functions, and hence the FACETS API.
@@ -18 +19 @@
-
-# ==============================================================================
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-class ID(int):
@@ -649 +662 @@
-
-# ==============================================================================
+#   Connection method classes
+# ==============================================================================
+
+class Connector(object):
+    """Abstract base class for Connector classes."""
+    
+    def __init__(self):
+        _abstractMethod(self)
+    
+    def connect(self,projection):
+        """Connect all neurons in ``projection``"""
+        _abstractMethod(self)
+
+class AllToAllConnector(Connector):
+    """
+    Connects all cells in the presynaptic population to all cells in the
+    postsynaptic population.
+    """
+    
+    def __init__(self, allow_self_connections=True):
+        assert isinstance(allow_self_connections, bool)
+        self.allow_self_connections = allow_self_connections
+
+class OneToOneConnector(Connector):
+    """
+    Where the pre- and postsynaptic populations have the same size, connect
+    cell i in the presynaptic population to cell i in the postsynaptic
+    population for all i.
+    In fact, despite the name, this should probably be generalised to the
+    case where the pre and post populations have different dimensions, e.g.,
+    cell i in a 1D pre population of size n should connect to all cells
+    in row i of a 2D post population of size (n,m).
+    """
+    
+    def __init__(self):
+        pass
+    
+        
+# ==============================================================================
-#   Utility classes
-# ==============================================================================

branches/connector-class/nest.py

@@ -861 +861 @@
-        self._targets = []     # holds gids
-        self._sources = []     # holds gids
-connection_method = getattr(self,'_%s' % method)
-if target:
-    self.nconn = connection_method(methodParameters,synapse_type=target)
-else:
+self.synapse_type = target
+
+if isinstance(method, str):
+    connection_method = getattr(self,'_%s' % method)   
-            self.nconn = connection_method(methodParameters)
+        elif isinstance(method,common.Connector):
+            self.nconn = method.connect(self)
+
-        assert len(self._sources) == len(self._targets) == len(self._targetPorts), "Connection error. Source and target lists are of different lengths."
-        self.connection = Projection.ConnectionDict(self)
@@ -906 +909 @@
-    # --- Connection methods ---------------------------------------------------
-    
-,synapse_type=None
+
-        """
-        Connect all cells in the presynaptic population to all cells in the postsynaptic population.
@@ -914 +917 @@
-        if parameters and parameters.has_key('allow_self_connections'):
-            allow_self_connections = parameters['allow_self_connections']
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-        """
-        Where the pre- and postsynaptic populations have the same size, connect
@@ -937 +930 @@
-        in row i of a 2D post population of size (n,m).
-        """
-        self.synapse_type = synapse_type
-        if self.pre.dim == self.post.dim:
-            self._sources = numpy.reshape(self.pre.cell,(self.pre.cell.size,))
@@ -949 +941 @@
-            raise Exception("Method 'oneToOne' not yet implemented for the case where presynaptic and postsynaptic Populations have different sizes.")
-    
-,synapse_type=None
+
-        """
-        For each pair of pre-post cells, the connection probability is constant.
-        """
-        self.synapse_type = synapse_type
-        allow_self_connections = True
-        try:
@@ -976 +967 @@
-        return len(self._sources)
-    
-,synapse_type=None
+
-        """
-        For each pair of pre-post cells, the connection probability depends on distance.
@@ -982 +973 @@
-        for probability, involving 'd', e.g. "exp(-abs(d))", or "float(d<3)"
-        """
-        self.synapse_type = synapse_type
-        allow_self_connections = True
-        if type(parameters) == types.StringType:
@@ -1033 +1023 @@
-                        self._targetPorts.append(pynest.connect(pre_addr,post_addr))
-    
-,synapse_type=None
+
-        """Each presynaptic cell makes a fixed number of connections."""
-        self.synapse_type = synapse_type
-        allow_self_connections = True
-        if type(parameters) == types.IntType:
@@ -1077 +1066 @@
-                    self._targetPorts.append(pynest.connect(pre_addr,pynest.getAddress(post)))
-    
-,synapse_type=None
+
-        """Each postsynaptic cell receives a fixed number of connections."""
-        self.synapse_type = synapse_type
-        allow_self_connections = True
-        if type(parameters) == types.IntType:
@@ -1121 +1109 @@
-                    self._targetPorts.append(pynest.connect(pynest.getAddress(pre),post_addr))
-    
-,synapse_type=None
+
-        """
-        Load connections from a file.
-        """
-        self.synapse_type = synapse_type
-        if type(parameters) == types.FileType:
-            fileobj = parameters
@@ -1150 +1137 @@
-        f.close()
-        
-, synapse_type
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-,synapse_type=None
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+
-        """
-        Read connections from a list of tuples,
@@ -1159 +1146 @@
-        lists containing the neuron array coordinates.
-        """
-        self.synapse_type = synapse_type
-        for i in xrange(len(conn_list)):
-            src, tgt, weight, delay = conn_list[i][:]
@@ -1171 +1157 @@
-            self._targetPorts.append(pynest.connectWD(pre_addr,post_addr, 1000*weight, delay))
-
-,synapse_type=None
+
-        """
-        Source neuron is connected to a 2D targetd population with a spatial profile (Gauss).
@@ -1181 +1167 @@
-        sigma: sigma of the Gauss
-        """
-        self.synapse_type = synapse_type
-        def rcf_2D(parameters):
-            rng = parameters['rng']
@@ -1228 +1213 @@
-                rcf_2D(parameters)
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-        # debug get delays from outside
-        #delay_array = parameters['delays_array']
@@ -1245 +1229 @@
-        print 'leaving test_delay'
-        
-,synapse_type=None
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-        """
-        Source neuron is connected to a 3D targetd population with a spatial profile (Gauss).
@@ -1588 +1572 @@
-        # should be put here or in an external module.
-        raise Exception("Method not yet implemented")
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-# ==============================================================================
-#   Utility classes

branches/connector-class/neuron.py

@@ -1155 +1155 @@
-        hoc_commands = ['objref %s' % self.hoc_label,
-                        '%s = new List()' % self.hoc_label]
-        connection_method = getattr(self,'_%s' % method)
-        self.synapse_type = target
-        self._syn_objref = _translate_synapse_type(self.synapse_type)
-        
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-            hoc_commands += connection_method(methodParameters)
+        elif isinstance(method,common.Connector):
+            hoc_commands += method.connect(self)
-        hoc_execute(hoc_commands, "--- Projection[%s].__init__() ---" %self.label)
-        
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-        if parameters and parameters.has_key('allow_self_connections'):
-            allow_self_connections = parameters['allow_self_connections']
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-    def _oneToOne(self,parameters=None):
@@ -1237 +1233 @@
-        cell i in a 1D pre population of size n should connect to all cells
-        in row i of a 2D post population of size (n,m).
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-    def _fixedProbability(self,parameters):
@@ -1758 +1748 @@
-
-# ==============================================================================
+#   Connection method classes
+# ==============================================================================
+
+class HocConnector(object):
+    
+    def singleConnect(self,projection,src,tgt):
+        """
+        Write hoc commands to connect a single pair of neurons.
+        """
+        cmdlist = ['nc = pc.gid_connect(%d,%s.object(%d).%s)' % (src,
+                                                                 projection.post.hoc_label,
+                                                                 projection.post.gidlist.index(tgt),
+                                                                 projection._syn_objref),
+                'tmp = %s.append(nc)' % projection.hoc_label]
+        projection.connections.append((src,tgt))
+        return cmdlist
+
+class AllToAllConnector(common.AllToAllConnector, HocConnector):    
+    
+    def connect(self, projection):
+        hoc_commands = []
+        for tgt in projection.post.gidlist:
+            for src in projection.pre.fullgidlist:
+                if self.allow_self_connections or projection.pre != projection.post or tgt != src:
+                    hoc_commands += self.singleConnect(projection,src,tgt)
+        return hoc_commands
+
+class OneToOneConnector(common.OneToOneConnector, HocConnector):
+    
+    def connect(self, projection):
+        if projection.pre.dim == projection.post.dim:
+            hoc_commands = []
+            for tgt in projection.post.gidlist:
+                src = tgt - projection.post.gid_start + projection.pre.gid_start
+                hoc_commands += self.singleConnect(projection,src,tgt)
+        else:
+            raise Exception("Method '%s' not yet implemented for the case where presynaptic and postsynaptic Populations have different sizes." % sys._getframe().f_code.co_name)
+        return hoc_commands
+    
+# ==============================================================================
-#   Utility classes
-# ==============================================================================

branches/connector-class/pcsim.py

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-        
-        # Determine connection decider
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-        if not target:
-            self.syn_factory = SimpleScalingSpikingSynapse(1, 1, pcsim_globals.minDelay/1000)
@@ -1265 +1268 @@
-
-# ==============================================================================
+#   Connection method classes
+# ==============================================================================
+
+class AllToAllConnector(common.AllToAllConnector):    
+    
+    def connect(self, projection):
+        # what about allow_self_connections?
+        decider = RandomConnections(1)
+        wiring_method = DistributedSyncWiringMethod(pcsim_globals.net)
+        return decider, wiring_method
+
+class OneToOneConnector(common.OneToOneConnector):
+    
+    def connect(self, projection):
+        if projection.pre.dim == projection.post.dim:
+            decider = RandomConnections(1)
+            wiring_method = OneToOneWiringMethod(pcsim_globals.net)
+            return decider, wiring_method
+        else:
+            raise Exception("Connection method not yet implemented for the case where presynaptic and postsynaptic Populations have different sizes.")
+    
+
+
+# ==============================================================================
-#   Utility classes
-# ==============================================================================

branches/connector-class/test/nesttests.py

@@ -410 +410 @@
-            for tgtP in [self.target6, self.target33]:
-                prj1 = nest.Projection(srcP, tgtP, "allToAll")
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-    def testdistantDependentProbability(self):
-        """For all connections created with "distanceDependentProbability" it should be possible to obtain the weight using pyneuron.getWeight()"""

branches/connector-class/test/neurontests.py

@@ -462 +462 @@
-            for tgtP in [self.target6, self.target33]:
-                prj1 = neuron.Projection(srcP, tgtP, 'allToAll')
+                prj2 = neuron.Projection(srcP, tgtP, neuron.AllToAllConnector())
-                prj1.setWeights(1.234)
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-    def testFixedProbability(self):
-        """For all connections created with "fixedProbability" it should be possible to obtain the weight using pyneuron.getWeight()"""
@@ -481 +484 @@
-        """For all connections created with "OneToOne" it should be possible to obtain the weight using pyneuron.getWeight()"""
-        prj1 = neuron.Projection(self.source33, self.target33, 'oneToOne')
+        prj2 = neuron.Projection(self.source33, self.target33, neuron.OneToOneConnector())
-        assert len(prj1.connections) == self.source33.size
+        assert len(prj2.connections) == self.source33.size
-     
-    def testdistantDependentProbability(self):

branches/connector-class/test/pcsimtests_population.py

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-class PopulationSetTest(unittest.TestCase):
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-# ==============================================================================
-class PopulationCallTest(unittest.TestCase): # to write later
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-class PopulationRecordTest(unittest.TestCase): # to write later
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-class PopulationOtherTest(unittest.TestCase): # to write later
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-class ProjectionInitTest(unittest.TestCase):
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