neureka.backend.main.operations.functions

Class Log10

java.lang.Object

neureka.backend.api.template.operations.AbstractOperation

neureka.backend.main.operations.functions.Log10

All Implemented Interfaces:

Operation

public class Log10
extends AbstractOperation

Field Summary

Fields inherited from class neureka.backend.api.template.operations.AbstractOperation

_arity, _function, _isDifferentiable, _isIndexer, _isInline, _isOperator, _operator

Constructor Summary

Constructors

Constructor and Description
Log10()

Method Summary

Modifier and Type	Method and Description
double	calculate(double[] inputs, int j, int d, Function[] src) This method mainly ought to serve as a reference- and fallback- implementation for tensor backends and also as the backend for handling the calculation of scalar inputs passed to a given abstract syntax tree of Function instances...
Result	execute(Function caller, ExecutionCall<?> call)
java.lang.String	stringify(java.lang.String[] children)

Methods inherited from class neureka.backend.api.template.operations.AbstractOperation

asDerivative, getAlgorithm, getAlgorithmFor, getAllAlgorithms, getArity, getDefaultAlgorithm, getIdentifier, getOperator, isDifferentiable, isIndexer, isInline, isOperator, operationName, setAlgorithm, supports, supportsAlgorithm, toString

Methods inherited from class java.lang.Object

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

Methods inherited from interface neureka.backend.api.Operation

builder, setAlgorithm

Constructor Detail

Log10

public Log10()

Method Detail

execute

public Result execute(Function caller,
                      ExecutionCall<?> call)

stringify

public final java.lang.String stringify(java.lang.String[] children)

Description copied from class: AbstractOperation

Specified by:

stringify in interface Operation

Overrides:

stringify in class AbstractOperation

calculate

public final double calculate(double[] inputs,
                              int j,
                              int d,
                              Function[] src)

Description copied from interface: Operation

This method mainly ought to serve as a reference- and fallback- implementation for tensor backends and also as the backend for handling the calculation of scalar inputs passed to a given abstract syntax tree of Function instances...
( (almost) every Function instance contains an OperationType reference to which it passes scalar executions... )

This is also the reason why the last parameter of this method is a list of Function objects : The list stores the child nodes of the Function node that is currently being processed. Therefore, when implementing this method one should first call the child nodes in order to get the "real inputs" of this current node.

One might ask : Why does that not happen automatically? The answer is to that question lies in the other parameters of this method. Specifically the parameter "d" ! This argument determines if the derivative ought to be calculated and also which value is being targeted within the input array. Depending on this variable and also the nature of the operation, the execution calls to the child nodes of this node change considerably!

Parameters:

inputs - An array of scalar input variables.

j - The index variable for indexed execution on the input array. (-1 if no indexing should occur)

d - The index of the variable of which a derivative ought to be calculated.

src - The child nodes of the Function node to which this very OperationType belongs.

Returns:

The result of the calculation.