start to clean up GMRF

src/dr/app/beast/development_parsers.properties

@@ -75,8 +75,9 @@ dr.evomodelxml.branchratemodel.TimeVaryingBranchRateModelParser
 
 # GMRF
 dr.evomodel.coalescent.GMRFDensityComponent
+dr.inferencexml.distribution.RandomFieldParser
+dr.inferencexml.distribution.RandomFieldGradientParser
 dr.inferencexml.distribution.GaussianMarkovRandomFieldParser
-dr.inferencexml.distribution.GaussianMarkovRandomFieldParser2
 
 # GAUSSIAN PROCESS
 dr.evomodelxml.coalescent.GPSkytrackAnalysisParser

src/dr/evomodel/antigenic/NewAntigenicLikelihood.java

@@ -364,17 +364,17 @@ public int compare(Measurement lhs, Measurement rhs) {
     public void updateParametersOnDevice() {
         if (!precisionKnown) {
             transferPrecision();
-//            precisionKnown = true;
+            precisionKnown = true;
         }
 
         if (!locationsKnown) {
             transferLocations();
-//            locationsKnown = true;
+            locationsKnown = true;
         }
 
         if (!observationsKnown) {
             transferObservations();
-//            observationsKnown = true;
+            observationsKnown = true;
         }
     }
 

src/dr/inference/distribution/GaussianMarkovRandomFieldModel.java → src/dr/inference/distribution/OldGaussianMarkovRandomFieldModel.java

@@ -27,7 +27,7 @@
 
 import dr.inference.model.*;
 import dr.inferencexml.distribution.MultivariateNormalDistributionModelParser;
-import dr.math.distributions.GaussianMarkovRandomField;
+import dr.math.distributions.OldGaussianMarkovRandomField;
 import dr.math.distributions.GaussianProcessRandomGenerator;
 
 
@@ -38,12 +38,12 @@
  * Pratyusa Datta
  */
 
-public class GaussianMarkovRandomFieldModel extends AbstractModel implements
+public class OldGaussianMarkovRandomFieldModel extends AbstractModel implements
         ParametricMultivariateDistributionModel, GaussianProcessRandomGenerator, GradientProvider, HessianProvider {
 
-    public GaussianMarkovRandomFieldModel(int dim,
-                                                 Parameter incrementPrecisionParameter,
-                                                 Parameter startParameter) {
+    public OldGaussianMarkovRandomFieldModel(int dim,
+                                             Parameter incrementPrecisionParameter,
+                                             Parameter startParameter) {
         super(MultivariateNormalDistributionModelParser.NORMAL_DISTRIBUTION_MODEL);
 
         this.dim = dim;
@@ -146,8 +146,8 @@ public Variable<Double> getLocationVariable() {
     // Private instance variables and functions
     // **************************************************************
 
-    private GaussianMarkovRandomField createNewDistribution() {
-        return new GaussianMarkovRandomField(getDimension(),
+    private OldGaussianMarkovRandomField createNewDistribution() {
+        return new OldGaussianMarkovRandomField(getDimension(),
                 incrementPrecision.getParameterValue(0), start.getParameterValue(0));
     }
 
@@ -156,8 +156,8 @@ private GaussianMarkovRandomField createNewDistribution() {
     private final Parameter incrementPrecision;
     private final Parameter start;
 
-    private GaussianMarkovRandomField distribution;
-    private GaussianMarkovRandomField storedDistribution;
+    private OldGaussianMarkovRandomField distribution;
+    private OldGaussianMarkovRandomField storedDistribution;
 
     private boolean distributionKnown;
     private boolean storedDistributionKnown;

src/dr/inference/distribution/RandomField.java

@@ -0,0 +1,118 @@
+/*
+ * RandomField.java
+ *
+ * Copyright (c) 2002-2023 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.inference.distribution;
+
+import dr.inference.model.*;
+import dr.math.distributions.RandomFieldDistribution;
+
+/**
+ * @author Marc Suchard
+ * @author Pratyusa Datta
+ * @author Filippo Monti
+ * @author Xiang Ji
+ */
+
+public class RandomField extends AbstractModelLikelihood {
+
+    private final Parameter field;
+    private final RandomFieldDistribution distribution;
+
+    private boolean likelihoodKnown;
+    private double logLikelihood;
+
+    private boolean savedLikelihoodKnown;
+    private double savedLogLikelihood;
+
+    public RandomField(String name,
+                       Parameter field,
+                       RandomFieldDistribution distribution) {
+        super(name);
+
+        this.field = field;
+        this.distribution = distribution;
+
+        addVariable(field);
+        addModel(distribution);
+
+        likelihoodKnown = false;
+    }
+
+    public Parameter getField() { return field; }
+
+    public RandomFieldDistribution getDistribution() { return distribution; }
+
+    @Override
+    protected void handleModelChangedEvent(Model model, Object object, int index) {
+        if (model == distribution) {
+            throw new RuntimeException("Not yet implemented");
+        } else {
+            throw new IllegalArgumentException("Unknown model");
+        }
+    }
+
+    @Override
+    protected void handleVariableChangedEvent(Variable variable, int index, Parameter.ChangeType type) {
+        if (variable == field) {
+            likelihoodKnown = false;
+        } else {
+            throw new IllegalArgumentException("Unknown variable");
+        }
+    }
+
+    @Override
+    protected void storeState() {
+        savedLikelihoodKnown = likelihoodKnown;
+        savedLogLikelihood = logLikelihood;
+    }
+
+    @Override
+    protected void restoreState() {
+        likelihoodKnown = savedLikelihoodKnown;
+        logLikelihood = savedLogLikelihood;
+    }
+
+    @Override
+    protected void acceptState() { }
+
+    @Override
+    public Model getModel() { return this; }
+
+    @Override
+    public double getLogLikelihood() {
+
+        if (!likelihoodKnown) {
+            logLikelihood = 0;
+            likelihoodKnown = true;
+        }
+
+        return logLikelihood;
+    }
+
+    @Override
+    public void makeDirty() {
+        likelihoodKnown = false;
+    }
+}