add parser, still need to check numbers

src/dr/app/beast/development_parsers.properties

@@ -167,7 +167,8 @@ dr.inferencexml.hmc.LFMFactorPotentialDerivativeParser
 dr.inferencexml.hmc.LFMLoadingsPotentialDerivativeParser
 dr.inferencexml.distribution.RowDimensionMultinomialPriorParser
 dr.inferencexml.distribution.IndependentNormalDistributionModelParser
-
+dr.inferencexml.distribution.GMRFDistributionLikelihoodParser
+
 # CONSTRAINTS
 dr.inference.model.EqualityConstraintModel
 dr.inference.model.EqualityConstrainedParameter

src/dr/inferencexml/distribution/GMRFDistributionLikelihoodParser.java

@@ -0,0 +1,103 @@
+/*
+ * GMRFDistributionLikelihoodParser.java
+ *
+ * Copyright (c) 2002-2015 Alexei Drummond, Andrew Rambaut and Marc Suchard
+ *
+ * This file is part of BEAST.
+ * See the NOTICE file distributed with this work for additional
+ * information regarding copyright ownership and licensing.
+ *
+ * BEAST is free software; you can redistribute it and/or modify
+ * it under the terms of the GNU Lesser General Public License as
+ * published by the Free Software Foundation; either version 2
+ * of the License, or (at your option) any later version.
+ *
+ *  BEAST is distributed in the hope that it will be useful,
+ *  but WITHOUT ANY WARRANTY; without even the implied warranty of
+ *  MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+ *  GNU Lesser General Public License for more details.
+ *
+ * You should have received a copy of the GNU Lesser General Public
+ * License along with BEAST; if not, write to the
+ * Free Software Foundation, Inc., 51 Franklin St, Fifth Floor,
+ * Boston, MA  02110-1301  USA
+ */
+
+package dr.inferencexml.distribution;
+
+import dr.evomodelxml.coalescent.GMRFSkyrideLikelihoodParser;
+import dr.evomodelxml.coalescent.smooth.SmoothSkygridLikelihoodParser;
+import dr.inference.model.Parameter;
+import dr.math.distributions.GMRFDistributionLikelihood;
+import dr.xml.*;
+
+/**
+ * @author Marc Suchard
+ * @author Xiang Ji
+ */
+public class GMRFDistributionLikelihoodParser  extends AbstractXMLObjectParser {
+
+    private static final String POPULATION_PARAMETER = GMRFSkyrideLikelihoodParser.POPULATION_PARAMETER;
+    private static final String PRECISION_PARAMETER = GMRFSkyrideLikelihoodParser.PRECISION_PARAMETER;
+
+    private static final String SINGLE_BETA = GMRFSkyrideLikelihoodParser.SINGLE_BETA;
+    private static final String TIME_AWARE_SMOOTHING = GMRFSkyrideLikelihoodParser.TIME_AWARE_SMOOTHING;
+
+    private static final String LAMBDA_PARAMETER = GMRFSkyrideLikelihoodParser.LAMBDA_PARAMETER;
+
+
+    public final String NAME = "gmrfDistributionLikelihood";
+
+    @Override
+    public Object parseXMLObject(XMLObject xo) throws XMLParseException {
+
+        XMLObject cxo = xo.getChild(POPULATION_PARAMETER);
+        Parameter popParameter = (Parameter) cxo.getChild(Parameter.class);
+
+        cxo = xo.getChild(PRECISION_PARAMETER);
+        Parameter precParameter = (Parameter) cxo.getChild(Parameter.class);
+
+        Parameter lambda;
+        if (xo.getChild(LAMBDA_PARAMETER) != null) {
+            cxo = xo.getChild(LAMBDA_PARAMETER);
+            lambda = (Parameter) cxo.getChild(Parameter.class);
+        } else {
+            lambda = new Parameter.Default(LAMBDA_PARAMETER, 1.0);
+        }
+
+        Parameter gridPoints = SmoothSkygridLikelihoodParser.getGridPoints(xo);
+        return new GMRFDistributionLikelihood(NAME, precParameter, lambda, gridPoints, popParameter);
+    }
+
+    @Override
+    public XMLSyntaxRule[] getSyntaxRules() {
+        return rules;
+    }
+    private final XMLSyntaxRule[] rules = {
+            new ElementRule(POPULATION_PARAMETER, new XMLSyntaxRule[]{
+                    new ElementRule(Parameter.class)
+            }),
+            new ElementRule(PRECISION_PARAMETER, new XMLSyntaxRule[]{
+                    new ElementRule(Parameter.class)
+            }),
+            new ElementRule(SINGLE_BETA, new XMLSyntaxRule[] {
+                    new ElementRule(Parameter.class),
+            }, true),
+            AttributeRule.newBooleanRule(TIME_AWARE_SMOOTHING, true),
+    };
+
+    @Override
+    public String getParserDescription() {
+        return null;
+    }
+
+    @Override
+    public Class getReturnType() {
+        return GMRFDistributionLikelihood.class;
+    }
+
+    @Override
+    public String getParserName() {
+        return NAME;
+    }
+}

src/dr/math/distributions/GMRFDistributionLikelihood.java

@@ -30,14 +30,15 @@
 import dr.inference.model.Model;
 import dr.inference.model.Parameter;
 import dr.inference.model.Variable;
+import dr.xml.Reportable;
 import no.uib.cipr.matrix.DenseVector;
 import no.uib.cipr.matrix.SymmTridiagMatrix;
 
 /**
  * @author Xiang Ji
  * @author Marc A. Suchard
  */
-public class GMRFDistributionLikelihood extends AbstractModelLikelihood implements MultivariateDistribution {
+public class GMRFDistributionLikelihood extends AbstractModelLikelihood implements MultivariateDistribution, Reportable {
 
     private Parameter precisionParameter;
 
@@ -63,6 +64,7 @@ public GMRFDistributionLikelihood(String name,
         this.gridParameter = gridParameter;
         this.fieldLength = popSizeParameter.getDimension();
         this.popSizeParameter = popSizeParameter;
+        setupGMRFWeights();
         addVariable(precisionParameter);
         addVariable(lambdaParameter);
         addVariable(gridParameter);
@@ -143,12 +145,12 @@ private DenseVector getMeanAdjustedGamma(double[] x) {
 
     @Override
     public double[][] getScaleMatrix() {
-        return new double[0][];
+        throw new RuntimeException("Not yet implemented");
     }
 
     @Override
     public double[] getMean() {
-        return new double[0];
+        throw new RuntimeException("Not yet implemented");
     }
 
     @Override
@@ -188,11 +190,16 @@ public Model getModel() {
 
     @Override
     public double getLogLikelihood() {
-        return 0;
+        return logPdf(popSizeParameter.getParameterValues());
     }
 
     @Override
     public void makeDirty() {
 
     }
+
+    @Override
+    public String getReport() {
+        return "gmrfDistributionLikelihood(" + getLogLikelihood() + ")";
+    }
 }