def connect(self, source, targets, weights, delays):
"""
Connect a neuron to one or more other neurons with a static connection.
`source` -- the ID of the pre-synaptic cell.
`targets` -- a list/1D array of post-synaptic cell IDs, or a single ID.
`weight` -- a list/1D array of connection weights, or a single weight.
Must have the same length as `targets`.
`delays` -- a list/1D array of connection delays, or a single delay.
Must have the same length as `targets`.
"""
if not isinstance(source, (int, long)) or source < 0:
errmsg = "Invalid source ID: %s" % source
raise common.ConnectionError(errmsg)
if not common.is_listlike(targets):
targets = [targets]
if isinstance(weights, float):
weights = [weights]
if isinstance(delays, float):
delays = [delays]
assert len(targets) > 0
for target in targets:
if not isinstance(target, common.IDMixin):
raise common.ConnectionError("Invalid target ID: %s" % target)
assert len(targets) == len(weights) == len(delays), "%s %s %s" % (
len(targets), len(weights), len(delays))
if common.is_conductance(targets[0]):
weight_scale_factor = 1e-6 # Convert from µS to S
else:
weight_scale_factor = 1e-9 # Convert from nA to A
synapse_type = self.synapse_type or "excitatory"
if isinstance(synapse_type, basestring):
syn_target_id = ConnectionManager.synapse_target_ids[synapse_type]
syn_factory = pypcsim.SimpleScalingSpikingSynapse(
syn_target_id, weights[0], delays[0])
elif isinstance(synapse_type, pypcsim.SimObject):
syn_factory = synapse_type
else:
raise common.ConnectionError(
"synapse_type must be a string or a PCSIM synapse factory. Actual type is %s"
% type(synapse_type))
for target, weight, delay in zip(targets, weights, delays):
syn_factory.W = weight * weight_scale_factor
syn_factory.delay = delay * 0.001 # ms --> s
try:
c = net.connect(source, target, syn_factory)
except RuntimeError, e:
raise common.ConnectionError(e)
if target.local:
self.connections.append(
Connection(source, target, net.object(c),
1.0 / weight_scale_factor))
def connect(self, source, targets, weights, delays):
"""
Connect a neuron to one or more other neurons.
`source` -- the ID of the pre-synaptic cell.
`targets` -- a list/1D array of post-synaptic cell IDs, or a single ID.
`weight` -- a list/1D array of connection weights, or a single weight.
Must have the same length as `targets`.
`delays` -- a list/1D array of connection delays, or a single delay.
Must have the same length as `targets`.
"""
# are we sure the targets are all on the current node?
if common.is_listlike(source):
assert len(source) == 1
source = source[0]
if not common.is_listlike(targets):
targets = [targets]
assert len(targets) > 0
if self.synapse_type not in ('excitatory', 'inhibitory', None):
raise common.ConnectionError(
"synapse_type must be 'excitatory', 'inhibitory', or None (equivalent to 'excitatory')"
)
weights = weights * 1000.0 # weights should be in nA or uS, but iaf_neuron uses pA and iaf_cond_neuron uses nS.
# Using convention in this way is not ideal. We should
# be able to look up the units used by each model somewhere.
if self.synapse_type == 'inhibitory' and common.is_conductance(
targets[0]):
weights = -1 * weights # NEST wants negative values for inhibitory weights, even if these are conductances
if isinstance(weights, numpy.ndarray):
weights = weights.tolist()
elif isinstance(weights, float):
weights = [weights]
if isinstance(delays, numpy.ndarray):
delays = delays.tolist()
elif isinstance(delays, float):
delays = [delays]
try:
nest.DivergentConnect([source], targets, weights, delays,
self.synapse_model)
except nest.NESTError, e:
raise common.ConnectionError(
"%s. source=%s, targets=%s, weights=%s, delays=%s, synapse model='%s'"
% (e, source, targets, weights, delays, self.synapse_model))
def connect(self, source, targets, weights, delays):
"""
Connect a neuron to one or more other neurons with a static connection.
`source` -- the ID of the pre-synaptic cell.
`targets` -- a list/1D array of post-synaptic cell IDs, or a single ID.
`weight` -- a list/1D array of connection weights, or a single weight.
Must have the same length as `targets`.
`delays` -- a list/1D array of connection delays, or a single delay.
Must have the same length as `targets`.
"""
if not isinstance(source,
int) or source > state.gid_counter or source < 0:
errmsg = "Invalid source ID: %s (gid_counter=%d)" % (
source, state.gid_counter)
raise common.ConnectionError(errmsg)
if not common.is_listlike(targets):
targets = [targets]
if isinstance(weights, float):
weights = [weights]
if isinstance(delays, float):
delays = [delays]
assert len(targets) > 0
for target in targets:
if not isinstance(target, common.IDMixin):
raise common.ConnectionError("Invalid target ID: %s" % target)
assert len(targets) == len(weights) == len(delays), "%s %s %s" % (
len(targets), len(weights), len(delays))
for target, weight, delay in zip(targets, weights, delays):
if target.local:
if self.synapse_type is None:
self.synapse_type = weight >= 0 and 'excitatory' or 'inhibitory'
if self.synapse_model == 'Tsodyks-Markram' and 'TM' not in self.synapse_type:
self.synapse_type += '_TM'
synapse_object = getattr(target._cell, self.synapse_type)
nc = state.parallel_context.gid_connect(
int(source), synapse_object)
nc.weight[0] = weight
nc.delay = delay
# nc.threshold is supposed to be set by ParallelContext.threshold, called in _build_cell(), above, but this hasn't been tested
self.connections.append(Connection(source, target, nc))
def connect(self, source, targets, weights, delays):
"""
Connect a neuron to one or more other neurons with a static connection.
`source` -- the ID of the pre-synaptic cell.
`targets` -- a list/1D array of post-synaptic cell IDs, or a single ID.
`weight` -- a list/1D array of connection weights, or a single weight.
Must have the same length as `targets`.
`delays` -- a list/1D array of connection delays, or a single delay.
Must have the same length as `targets`.
"""
#print "connecting", source, "to", targets, "with weights", weights, "and delays", delays
if not common.is_listlike(targets):
targets = [targets]
if isinstance(weights, float):
weights = [weights]
if isinstance(delays, float):
delays = [delays]
assert len(targets) > 0
if not isinstance(source, common.IDMixin):
raise common.ConnectionError(
"source should be an ID object, actually %s" % type(source))
for target in targets:
if not isinstance(target, common.IDMixin):
raise common.ConnectionError("Invalid target ID: %s" % target)
assert len(targets) == len(weights) == len(delays), "%s %s %s" % (
len(targets), len(weights), len(delays))
if common.is_conductance(targets[0]):
units = uS
else:
units = nA
synapse_type = self.synapse_type or "excitatory"
synapse_obj = targets[0].cellclass.synapses[synapse_type]
try:
source_group = source.parent_group
except AttributeError, errmsg:
raise common.ConnectionError(
"%s. Maybe trying to connect from non-existing cell (ID=%s)." %
(errmsg, source))