ca.nengo.math.impl
Class IndependentDimensionApproximator
java.lang.Object
ca.nengo.math.impl.IndependentDimensionApproximator
- All Implemented Interfaces:
- LinearApproximator, java.io.Serializable, java.lang.Cloneable
public class IndependentDimensionApproximator
- extends java.lang.Object
- implements LinearApproximator
A LinearApproximator for functions with no multidimensional nonlinearities. Each of the source functions
is assumed to be a function of one dimension. Consequently, only functions of one dimension can be decoded
directly. Linear functions of multiple dimensions can obtained later by combining weights of one-dimensional
functions.
- Author:
- Bryan Tripp
- See Also:
- Serialized Form
Methods inherited from class java.lang.Object |
equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
IndependentDimensionApproximator
public IndependentDimensionApproximator(float[] evaluationPoints,
float[][] values,
int[] dimensions,
int dimension,
Function costFunction,
float noise)
- Parameters:
evaluationPoints
- Points of evaluation of source functions, in the dimension along which they varyvalues
- Values of each source function at each pointdimensions
- The dimension along which each function variesdimension
- Dimension of the space from which source functions mapcostFunction
- As in WeightedCostApproximator, but in dimension along which functions varynoise
- Proportion of noise to add
getEvalPoints
public float[][] getEvalPoints()
- Specified by:
getEvalPoints
in interface LinearApproximator
- Returns:
- Points at which target functions are evaluated. Each row (or float[]) corresponds to
a single evaluation point. These points should usually be uniformly distributed, because
the sum of error at these points is treated as an integral over the domain of interest.
- See Also:
LinearApproximator.getEvalPoints()
getValues
public float[][] getValues()
- Specified by:
getValues
in interface LinearApproximator
- Returns:
- The values of component functions at the evaluation points. The first dimension
makes up the list of functions, and the second the values of these functions at each
evaluation point.
- See Also:
LinearApproximator.getValues()
findCoefficients
public float[] findCoefficients(Function target)
- Description copied from interface:
LinearApproximator
- Note: more information is needed than the arguments provide (for example
the functions that are to be combined to estimate the target). These other
data are object properties. This enables re-use of calculations based on these
data, for estimating multiple functions.
- Specified by:
findCoefficients
in interface LinearApproximator
- Parameters:
target
- Function to approximate
- Returns:
- coefficients on component functions which result in an approximation of the
target
- See Also:
LinearApproximator.findCoefficients(ca.nengo.math.Function)
clone
public LinearApproximator clone()
throws java.lang.CloneNotSupportedException
- Specified by:
clone
in interface LinearApproximator
- Overrides:
clone
in class java.lang.Object
- Throws:
java.lang.CloneNotSupportedException
main
public static void main(java.lang.String[] args)