transientDynamics

Class NetworkLeakyIntegratorWithIntrinsicPlasticityStepHandler

java.lang.Object

transientDynamics.NetworkLeakyIntegratorWithIntrinsicPlasticityStepHandler

All Implemented Interfaces:

org.apache.commons.math3.ode.sampling.StepHandler

public class NetworkLeakyIntegratorWithIntrinsicPlasticityStepHandler
extends java.lang.Object
implements org.apache.commons.math3.ode.sampling.StepHandler

Constructor Summary

Constructors

Constructor and Description
NetworkLeakyIntegratorWithIntrinsicPlasticityStepHandler(java.util.Collection<java.util.List<java.lang.Double>> patterns, java.io.File dataDirectory)

Method Summary

Methods

Modifier and Type	Method and Description
void	everyStep(double t, double[] state)
void	handleStep(org.apache.commons.math3.ode.sampling.StepInterpolator interpolator, boolean isLast) Handle the last accepted step
void	init(double t0, double[] state, double t) Initialize step handler at the start of an ODE integration.
void	printNeuronState(double t, double[] state, java.io.PrintStream out)
void	printPatternActivity(double t, double[] state, java.io.PrintStream out)
void	printPatternOverlap(double t, double[] state, java.io.PrintStream out) Print the overlap of the given state with all the patterns successively.

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

NetworkLeakyIntegratorWithIntrinsicPlasticityStepHandler

public NetworkLeakyIntegratorWithIntrinsicPlasticityStepHandler(java.util.Collection<java.util.List<java.lang.Double>> patterns,
                                                        java.io.File dataDirectory)
                                                         throws java.io.FileNotFoundException

Throws:

java.io.FileNotFoundException

Method Detail

handleStep

public void handleStep(org.apache.commons.math3.ode.sampling.StepInterpolator interpolator,
              boolean isLast)

Description copied from interface: org.apache.commons.math3.ode.sampling.StepHandler

Handle the last accepted step

Specified by:

handleStep in interface org.apache.commons.math3.ode.sampling.StepHandler

Parameters:

interpolator - interpolator for the last accepted step. For efficiency purposes, the various integrators reuse the same object on each call, so if the instance wants to keep it across all calls (for example to provide at the end of the integration a continuous model valid throughout the integration range, as the ContinuousOutputModel class does), it should build a local copy using the clone method of the interpolator and store this copy. Keeping only a reference to the interpolator and reusing it will result in unpredictable behavior (potentially crashing the application).

isLast - true if the step is the last one

init

public void init(double t0,
        double[] state,
        double t)

Description copied from interface: org.apache.commons.math3.ode.sampling.StepHandler

Initialize step handler at the start of an ODE integration.

This method is called once at the start of the integration. It may be used by the step handler to initialize some internal data if needed.

Specified by:

init in interface org.apache.commons.math3.ode.sampling.StepHandler

Parameters:

t0 - start value of the independent time variable

state - array containing the start value of the state vector

t - target time for the integration

everyStep

public void everyStep(double t,
             double[] state)

printNeuronState

public void printNeuronState(double t,
                    double[] state,
                    java.io.PrintStream out)

printPatternActivity

public void printPatternActivity(double t,
                        double[] state,
                        java.io.PrintStream out)

printPatternOverlap

public void printPatternOverlap(double t,
                       double[] state,
                       java.io.PrintStream out)

Print the overlap of the given state with all the patterns successively. The overlap is the cosine of the angle between the state vector and the pattern vector.

Parameters:

t - time $t$

state - network state

out - stream to print to