Class List
Here are the classes, structs, unions and interfaces with brief descriptions:
[detail level 1234]
 CAbstractNeuralDynamicsThe configuration of a GeomAlgorithm requires that the neural dynamics is defined somewhere. The dynamics is used to define an OdeSystem
 CAbstractOdeSystemA geometric grid to represent population densities
 CBinEstimatorCalculates the coverage corresponding a given bin and a potential difference
 CBinCoverExpresses the coverage of a given bin, _index< as a fraction, _alpha
 CCNZLCacheA BinEstimator object is able to determine the begin and end cover of a given translated bin. When the synaptic efficacies have not changed, there is no need to recalculate the begin and end points of these bins, and these values are cached. These cached values, rather than the outcome of a BinEstimator are used by NumericalMasterEquation
 CCurrentCompensationParameterParameter for setting current compensation values for the neural models that use it
 CDiffusionParameterWhen to switch to a two Poisson input approximation, and what input jump to use then
 CGeomAlgorithmPopulation density algorithm based on Geometric binning: http://arxiv.org/abs/1309.1654
 CGeomInputConvertorInternally used by GeomLib, interprets input from white noise; calculates the current compensation contribution
 CGeomLibExceptionBase class for all exceptions thrown in GeomLib
 CGeomParameterParameter for the configuration of a GeomAlgorithm object. Users of SpikingOdeSystem should read the full description carefully
 CInitialDensityParameterParameter to specify a Gaussian density distribution in an AlgorithmGrid
 CLeakingOdeSystemSystem for neural dynamics of a strictly leaky nature
 CLifEstimatorDoes what a BinEstimator does, but is more efficient if the dynamics is leaky-integrate-and-fire. Calculates the coverage corresponding a given bin and a potential difference
 CBinCoverExpresses the coverage of a given bin, _index< as a fraction, _alpha
 CLifNeuralDynamicsLeaky-integrate-and-fire dynamics for LeakingOdeSystem
 CMasterParameterAn auxiliary struct to help communicate with GSL C code. This parameter is passed in as void* and recovered by a recast. For this reason there are naked pointers in this object. They do not own. In an earlier version of the code a cache was included, which may have led to undefined behaviour. This object should be kept as light weight as possible. In particular the inclusion of complex objects should be avoided
 CMuSigmaScalarProductEvaluates the scalar product of an input which arrives over double or MPILib::DelayedConnection
 CNeuronParameterParameters necessary for the configuration of a GeomAlgorithm or an OUAlgorithm
 CNumericalMasterEquationSolves the Poisson Master equation on the probability mass bins
 COdeDtParameterContains the parameters necessary to configure a concrete OdeSystem instance. See AbstractOdeSystem and derived classes. An AbstractOdeSystem is geometric grid: a grid defined by a system of ordinary differential equations. The grid needs dimensions: a minimum potential specified by _V_min, a maximum defined in the NeuronParameter as the threshold, and an initial density at the start of the simulation, as well as a time step. The time step implicitly defines the number of bins: if you want a finer grid, take a smaller time step. The time step directly determines the the number of bins between reversal potential and threshold. The number of negative bins follows is calculated similarly, but extrapolated to V_min rather than -V_threshold. For GeomAlgorithm, it is essential that all grids use the same time step, therefore OdeParameter, where you could specify the number of bins, and where the time step would be calculated will be deprecated
 COdeParameterContains the parameters necessary to configure a concrete OdeSystem instance. See AbstractOdeSystem and derived classes
 CQifOdeSystemA geometric grid based on Quadratic-Integrate-and Fire (QIF) dynamics
 CQifParameterThis parameter configures the QIFAlgorithm
 CResponseParameterResponse functions often feature in the work of Amit and Brunel (1997), and are useful for comparing population density results
 CSpikingOdeSystemIn this system of ordinary differential equations it is assumed that dynamics is always spiking
 CSpikingQifNeuralDynamicsThis class models the dynamics of of Quadratic Integrate and Fire (QIF) neurons
 CDelayAlgorithmThis algorithm is effectively a pipeline with a preselected delay
 CProbabilityQueueA queue to store probability density, effectively a pipeline
 CStampedProbabilityA time stamped measure of probability
 CGraphKeyServes to interpret the name of a graph assigned by any AbstractReportHandler, and serves as a key for searches on graphs in simulation files
 CReportA Report is sent by a MPINode when it is queried
 CReportValueReportValue objects cab be added to a Report when a particular quantity, as yet unknown at this stage, needs to be stored into the simulation data file
 CLogClass for logging reports. The usage of this log class is described on page The Log utilities provided by miind
 CMPIProxy_A class to handle all MPI related code. It also provides works if MPI is disabled
 CAlgorithmInterfaceThe interface for all algorithm classes
 CCanvasParameterAuxiliary class, stores the boundaries of the histograms shown in the running canvas
 CMPINetworkA representation of the network class. Probably the most central class that a client will use. MPINodes and their connections are created through its interface
 CMPINodeClass for nodes in an MPINetwork
 CRateAlgorithmAn Algorithm with constant rate
 CRateFunctorAn Algorithm that encapsulates a rate as a function of time
 CSimulationRunParameterParameter determining how a simulation is run. Specifiying begin and end time, log file names, etc
 CWilsonCowanAlgorithmThe background of this algorithm is described on page The Wilson-Cowan Algorithm. An example of a fully functional programming using this algorithm is also presented there. Here we present the documentation required by C++ clients of this algorithm