/** * Copyright (C) 2013 - present by OpenGamma Inc. and the OpenGamma group of companies * * Please see distribution for license. */ package com.opengamma.financial.analytics.covariance; import java.util.Collections; import java.util.Map; import java.util.Set; import com.opengamma.engine.ComputationTarget; import com.opengamma.engine.function.AbstractFunction; import com.opengamma.engine.function.FunctionCompilationContext; import com.opengamma.engine.function.FunctionExecutionContext; import com.opengamma.engine.function.FunctionInputs; import com.opengamma.engine.target.ComputationTargetType; import com.opengamma.engine.value.ComputedValue; import com.opengamma.engine.value.ValueProperties; import com.opengamma.engine.value.ValuePropertyNames; import com.opengamma.engine.value.ValueRequirement; import com.opengamma.engine.value.ValueRequirementNames; import com.opengamma.engine.value.ValueSpecification; import com.opengamma.financial.analytics.DoubleLabelledMatrix2D; /** * Converts a covariance matrix to a correlation matrix. */ public class CorrelationMatrixFunction extends AbstractFunction.NonCompiledInvoker { // CompiledFunctionDefinition @Override public ComputationTargetType getTargetType() { return SampledCovarianceMatrixFunction.TYPE; } @Override public Set<ValueSpecification> getResults(final FunctionCompilationContext context, final ComputationTarget target) { return Collections.singleton(new ValueSpecification(ValueRequirementNames.CORRELATION_MATRIX, target.toSpecification(), ValueProperties.all())); } @Override public Set<ValueRequirement> getRequirements(final FunctionCompilationContext context, final ComputationTarget target, final ValueRequirement desiredValue) { return Collections.singleton(new ValueRequirement(ValueRequirementNames.COVARIANCE_MATRIX, target.toSpecification(), desiredValue.getConstraints().withoutAny(ValuePropertyNames.FUNCTION))); } @Override public Set<ValueSpecification> getResults(final FunctionCompilationContext context, final ComputationTarget target, final Map<ValueSpecification, ValueRequirement> inputs) { final ValueSpecification input = inputs.keySet().iterator().next(); return Collections.singleton(new ValueSpecification(ValueRequirementNames.CORRELATION_MATRIX, target.toSpecification(), input.getProperties().copy().withoutAny(ValuePropertyNames.FUNCTION) .with(ValuePropertyNames.FUNCTION, getUniqueId()).get())); } // FunctionInvoker @Override public Set<ComputedValue> execute(final FunctionExecutionContext context, final FunctionInputs inputs, final ComputationTarget target, final Set<ValueRequirement> desiredValues) { final ValueRequirement desiredValue = desiredValues.iterator().next(); final DoubleLabelledMatrix2D input = (DoubleLabelledMatrix2D) inputs.getValue(ValueRequirementNames.COVARIANCE_MATRIX); final DoubleLabelledMatrix2D output = new DoubleLabelledMatrix2D(input.getXKeys(), input.getXLabels(), input.getYKeys(), input.getYLabels(), input.getValues()); // TODO: This is a really dumb way to do this. There should be something in OG-Analytics or OG-Maths that will do this faster. This is a crude mechanism to // transform the covariance matrix to something that is more easily displayed final double[][] values = output.getValues(); final double[] stddev = new double[values.length]; for (int i = 0; i < values.length; i++) { stddev[i] = Math.sqrt(values[i][i]); } for (int i = 0; i < values.length; i++) { final double[] v = values[i]; final double a = stddev[i]; for (int j = 0; j < v.length; j++) { v[j] /= a * stddev[j]; } } return Collections.singleton(new ComputedValue(new ValueSpecification(ValueRequirementNames.CORRELATION_MATRIX, target.toSpecification(), desiredValue.getConstraints()), output)); } }