pypcsim.ConnectionDecisionPredicate:
Help on ConnectionDecisionPredicate [class]:
Binary predicate to decide on a connection between an object from a source population and an object in the destination population
pypcsim.PlainConnectionDecisionPredicate:
Help on PlainConnectionDecisionPredicate [class]: Predicate which
works for populations of class SimObjectPopulation and classes
derived from it
pypcsim.FamilyIdConnectionDecisionPredicate:
Help on FamilyIdConnectionDecisionPredicate [class]: Predicate
which works for populations of class SpatialFamilyPopulation and
classes derived from it
pypcsim.SpatialConnectionDecisionPredicate:
Help on SpatialConnectionDecisionPredicate [class]: Predicate which
works for populations of class SpatialSimObjectPopulation and
classes derived from it
pypcsim.EuclidianDistanceConnectionPredicate:
Help on EuclidianDistanceConnectionPredicate [class]: Predicate for
generating connections which a connection probability which depends
on the spatial distance between SimObject's
pypcsim.LateralEuclidianDistanceConnectionPredicate:
Help on LateralEuclidianDistanceConnectionPredicate [class]:
Predicate for generating connections which a connection probability
which depends on the lateral distance between SimObjects
pypcsim.SphereConnectionPredicate:
Help on SphereConnectionPredicate [class]: Predicate for
connections within a sphere with given radius
pypcsim.PyConnectionDecisionPredicate:
Help on PyConnectionDecisionPredicate [class]: Interface for
ConnectionDecisionPredicate which allows to implement
ConnectionDecisionPredicate's directly in python
pypcsim.ConnectionIterator:
Help on ConnectionIterator [class]: Interface for iterating over
connections to be made between populations of sim objects
pypcsim.DegreeDistributionConnections:
Help on DegreeDistributionConnections [class]:
This ConnectionIterator generates connections such the either the in or out degree of a SimObject in the population follows a given probability distribution.
pypcsim.EuclideanDistanceRandomConnections:
Help on EuclideanDistanceRandomConnections [class]: Implementation
of a ConnectionIterator which generates connections which a
connection probability which depends on the spatial distance
between SimObject's.
pypcsim.PredicateBasedConnections:
Help on PredicateBasedConnections [class]: Implementation of a
ConnectionIterator which connects each pair for which the given
connection decisions predicate is true.
pypcsim.RandomConnections:
Help on RandomConnections [class]: Fast implementation of pure
random connections with a given connection probability
pypcsim.ConnectionsProjection:
Help on ConnectionsProjection [class]: Class for making connections
between populations of SimObjects
pypcsim.AnalogPointNeuron:
Help on AnalogPointNeuron [class]:
This class implements a neuron which just adds up all its inputs (synapses and analog messages) in a linear fashion
pypcsim.LinearNeuron:
Help on LinearNeuron [class]:
This class implements a neuron which just adds up all its inputs (synapses and analog messages) in a linear fashion
pypcsim.CbExIzhiNeuron:
Help on CbExIzhiNeuron [class]:
A conductance based 'extended' Izhikevich neuron
Based on Chapter 8 of Izhikevich 2007 - Dynamical Systems in Neuroscience
pypcsim.CbIzhiNeuron:
Help on CbIzhiNeuron [class]:
A conductance based Izhikevich neuron.
pypcsim.CbLifNeuron:
Help on CbLifNeuron [class]:
A leaky-integrate-and-fire (I&F) neuron.
pypcsim.HHNeuron:
Help on HHNeuron [class]: Conductance based spiking neuron using
Traubs modified HH model with an additional M channel and OU Noise
pypcsim.HHNeuronTraubMiles91:
Help on HHNeuronTraubMiles91 [class]:
Conductance based spiking neuron using Traubs modified HH model.
pypcsim.ExIzhiNeuron:
Help on ExIzhiNeuron [class]:
A current based 'extended' Izhikevich neuron
Based on Chapter 8 of Izhikevich 2007 - Dynamical Systems in Neuroscience
pypcsim.IzhiNeuron:
Help on IzhiNeuron [class]:
A current based Izhikevich neuron.
pypcsim.LifNeuron:
Help on LifNeuron [class]:
A leaky-integrate-and-fire (I&F) neuron.
pypcsim.Point3DSet:
Help on Point3DSet [class]:
Arbitray set of points in 3 dimensions (double precision)
pypcsim.CuboidIntegerGrid3D:
Help on CuboidIntegerGrid3D [class]: Set of 3D points which have
integer coordinates and are within some cuboid subspace
pypcsim.Point3DSetSpliter:
Help on Point3DSetSpliter [class]:
Class which specifies a spliting algorithm to split one Point3DSet set of points into several disjunct subsets.
pypcsim.RatioBasedSpliter:
Help on RatioBasedSpliter [class]:
Splits a Point3DSet into several subsets based on a probability distribution.
pypcsim.TriangleDistribution:
Help on TriangleDistribution [class]:
Triangle distribution
The returned floating-point values x satisfy a <= x <= c;
x has a triangle distribution, where b is the most probable value for x.
pypcsim.DistributedNetwork:
Help on DistributedNetwork [class]:
Network holding the common functionalities for distributed simulations.
pypcsim.DistributedMultiThreadNetwork:
Help on DistributedMultiThreadNetwork [class]:
Network which encapsulates a distributed multi-threaded simulation.
pypcsim.DistributedSingleThreadNetwork:
Help on DistributedSingleThreadNetwork [class]:
Network which encapsulates a distributed single-threaded simulation.
pypcsim.MultiThreadNetwork:
Help on MultiThreadNetwork [class]:
Network which encapsulates a multi-threaded simulation in one process on a multi-processor machine.
pypcsim.SingleThreadNetwork:
Help on SingleThreadNetwork [class]: Network which can only be run
by one thread
pypcsim.SimObjectFactory:
Help on SimObjectFactory [class]: This class provides the interface
for creating SimObject instances
pypcsim.SimObject:
Help on SimObject [class]: Base class for all objects to simulate.
pypcsim.AnalogLevelBasedInputNeuron:
Help on AnalogLevelBasedInputNeuron [class]:
Input neuron where the analog input signal is composed of muliple constant levels with different durations.
pypcsim.AnalogPointNeuron:
Help on AnalogPointNeuron [class]:
This class implements a neuron which just adds up all its inputs (synapses and analog messages) in a linear fashion
pypcsim.LinearNeuron:
Help on LinearNeuron [class]:
This class implements a neuron which just adds up all its inputs (synapses and analog messages) in a linear fashion
pypcsim.CbIzhiNeuron:
Help on CbIzhiNeuron [class]:
A conductance based Izhikevich neuron.
pypcsim.ExIzhiNeuronBase:
Help on ExIzhiNeuronBase [class]:
An extended Izhikevich neuron
Based on Chapter 8 of Izhikevich 2007 - Dynamical Systems in Neuroscience
pypcsim.CbExIzhiNeuron:
Help on CbExIzhiNeuron [class]:
A conductance based 'extended' Izhikevich neuron
Based on Chapter 8 of Izhikevich 2007 - Dynamical Systems in Neuroscience
pypcsim.ExIzhiNeuron:
Help on ExIzhiNeuron [class]:
A current based 'extended' Izhikevich neuron
Based on Chapter 8 of Izhikevich 2007 - Dynamical Systems in Neuroscience
pypcsim.IzhiNeuron:
Help on IzhiNeuron [class]:
A current based Izhikevich neuron.
pypcsim.LifNeuronBase:
Help on LifNeuronBase [class]:
A leaky-integrate-and-fire (I&F) neuron.
pypcsim.CbLifNeuron:
Help on CbLifNeuron [class]:
A leaky-integrate-and-fire (I&F) neuron.
pypcsim.SimObjectVariationFactory:
Help on SimObjectVariationFactory [class]: Randomized generation of
SimObjects Allows for specification of random distribution objects
associated with each field of the SimObject class that is produced
by the factory.
pypcsim.SpatialSimObjectPopulation:
Help on SpatialSimObjectPopulation [class]: Population of
SimObject's with associated locations in 3D space
pypcsim.CuboidGridObjectPopulation:
Help on CuboidGridObjectPopulation [class]:
SpatialSimObjectPopulation class with SimObject's on an integer
grid in 3D
pypcsim.SpatialFamilyPopulation:
Help on SpatialFamilyPopulation [class]:
This class associates a family ID and a location in 3D space with each simulation object in the population
pypcsim.SpatialFamilyIDGenerator:
Help on SpatialFamilyIDGenerator [class]:
Base class for generating several different families of objects (created by different factories) into one population.
pypcsim.RatioBasedFamilies:
Help on RatioBasedFamilies [class]:
Generator which does a random assignment of locations to family IDs.
pypcsim.SpikeEvent:
Help on SpikeEvent [struct]: Information about the spike time
pypcsim.CbIzhiNeuron:
Help on CbIzhiNeuron [class]:
A conductance based Izhikevich neuron.
pypcsim.ExIzhiNeuronBase:
Help on ExIzhiNeuronBase [class]:
An extended Izhikevich neuron
Based on Chapter 8 of Izhikevich 2007 - Dynamical Systems in Neuroscience
pypcsim.CbExIzhiNeuron:
Help on CbExIzhiNeuron [class]:
A conductance based 'extended' Izhikevich neuron
Based on Chapter 8 of Izhikevich 2007 - Dynamical Systems in Neuroscience
pypcsim.ExIzhiNeuron:
Help on ExIzhiNeuron [class]:
A current based 'extended' Izhikevich neuron
Based on Chapter 8 of Izhikevich 2007 - Dynamical Systems in Neuroscience
pypcsim.IzhiNeuron:
Help on IzhiNeuron [class]:
A current based Izhikevich neuron.
pypcsim.LifNeuronBase:
Help on LifNeuronBase [class]:
A leaky-integrate-and-fire (I&F) neuron.
pypcsim.CbLifNeuron:
Help on CbLifNeuron [class]:
A leaky-integrate-and-fire (I&F) neuron.
pypcsim.WiringMethod:
Help on WiringMethod [class]: Interface for connecting populations
of SimObject's
pypcsim.DistributedSyncWiringMethod:
Help on DistributedSyncWiringMethod [class]: Implementation of a
WiringMethod which allows fast wiring of populations which span
multiple MPI nodes
pypcsim.OneToOneWiringMethod:
Help on OneToOneWiringMethod [class]: Simple implementation of
WiringMethod which build a one-to-one connection between
corresponding SimObject's in the SimObjectPopulation's
pypcsim.SimpleAllToAllWiringMethod:
Help on SimpleAllToAllWiringMethod [class]: Standard implementation
of wiring up two populations of SimObject's.