Merge branch 'develop' into release

compiler/pom.xml

@@ -19,7 +19,7 @@ Copyright (C) 2024 gregory higgins (C) 2024 gregory higgins
     <parent>
         <groupId>com.fluxtion</groupId>
         <artifactId>root-parent-pom</artifactId>
-        <version>9.1.17-SNAPSHOT</version>
+        <version>9.1.18-SNAPSHOT</version>
         <relativePath>../parent-root/pom.xml</relativePath>
     </parent>
 

compiler/src/test/java/com/fluxtion/runtime/ml/RegressionTest.java

@@ -0,0 +1,103 @@
+package com.fluxtion.runtime.ml;
+
+import com.fluxtion.compiler.builder.dataflow.DataFlow;
+import com.fluxtion.compiler.generation.util.CompiledAndInterpretedSepTest;
+import com.fluxtion.compiler.generation.util.MultipleSepTargetInProcessTest;
+import com.fluxtion.runtime.annotations.ExportService;
+import com.fluxtion.runtime.annotations.OnEventHandler;
+import com.fluxtion.runtime.annotations.OnTrigger;
+import com.fluxtion.runtime.dataflow.FlowSupplier;
+import lombok.Data;
+import lombok.EqualsAndHashCode;
+import lombok.Value;
+import org.junit.Assert;
+import org.junit.Test;
+
+import java.util.Arrays;
+
+public class RegressionTest extends MultipleSepTargetInProcessTest {
+    public RegressionTest(CompiledAndInterpretedSepTest.SepTestConfig testConfig) {
+        super(testConfig);
+    }
+
+    @Test
+    public void simpleTest() {
+        sep(c -> c.addNode(new PredictiveLinearRegressionModel(new AreaFeature()), "predictiveModel"));
+
+        //initial prediction is NaN
+        PredictiveModel predictiveModel = getField("predictiveModel");
+        Assert.assertTrue(Double.isNaN(predictiveModel.predictedValue()));
+
+        //set calibration prediction is 0
+        sep.getExportedService(CalibrationProcessor.class).setCalibration(
+                Arrays.asList(
+                        Calibration.builder()
+                                .featureClass(AreaFeature.class)
+                                .weight(2).co_efficient(1.5)
+                                .featureVersion(0)
+                                .build()));
+        Assert.assertEquals(0, predictiveModel.predictedValue(), 0.000_1);
+
+        //send record to generate a prediction
+        onEvent(new HouseDetails(12, 3));
+        Assert.assertEquals(36, predictiveModel.predictedValue(), 0.000_1);
+    }
+
+    @Test
+    public void subscribeTest() {
+        writeSourceFile = true;
+        sep(c -> {
+            FlowSupplier<HouseDetails> processedDouseDetails = DataFlow.subscribe(HouseDetails.class).flowSupplier();
+            c.addNode(new PredictiveLinearRegressionModel(new AreaFeatureSubscribed(processedDouseDetails)), "predictiveModel");
+        });
+
+        //initial prediction is NaN
+        PredictiveModel predictiveModel = getField("predictiveModel");
+        Assert.assertTrue(Double.isNaN(predictiveModel.predictedValue()));
+
+        //set calibration prediction is 0
+        sep.getExportedService(CalibrationProcessor.class).setCalibration(
+                Arrays.asList(
+                        Calibration.builder()
+                                .featureClass(AreaFeatureSubscribed.class)
+                                .weight(2)
+                                .co_efficient(1.5)
+                                .featureVersion(0)
+                                .build()));
+        Assert.assertEquals(0, predictiveModel.predictedValue(), 0.000_1);
+
+        //send record to generate a prediction
+        onEvent(new HouseDetails(12, 3));
+        Assert.assertEquals(36, predictiveModel.predictedValue(), 0.000_1);
+    }
+
+
+    public static class AreaFeature extends AbstractFeature implements @ExportService CalibrationProcessor {
+
+        @OnEventHandler
+        public boolean processRecord(HouseDetails houseDetails) {
+            value = houseDetails.area * co_efficient * weight;
+            return true;
+        }
+    }
+
+    @Data
+    @EqualsAndHashCode(callSuper = true)
+    public static class AreaFeatureSubscribed extends AbstractFeature implements @ExportService CalibrationProcessor {
+
+        private final FlowSupplier<HouseDetails> houseDetailSupplier;
+
+        @OnTrigger
+        public boolean processRecord() {
+            value = houseDetailSupplier.get().area * co_efficient * weight;
+            return true;
+        }
+
+    }
+
+    @Value
+    public static class HouseDetails {
+        double area;
+        double distance;
+    }
+}

parent-root/pom.xml

@@ -21,7 +21,7 @@
     <modelVersion>4.0.0</modelVersion>
     <groupId>com.fluxtion</groupId>
     <artifactId>root-parent-pom</artifactId>
-    <version>9.1.17-SNAPSHOT</version>
+    <version>9.1.18-SNAPSHOT</version>
     <packaging>pom</packaging>
     <name>fluxtion :: poms :: parent root</name>
 

pom.xml

@@ -19,7 +19,7 @@ along with this program.  If not, see
     <modelVersion>4.0.0</modelVersion>
     <groupId>com.fluxtion</groupId>
     <artifactId>fluxtion.master</artifactId>
-    <version>9.1.17-SNAPSHOT</version>
+    <version>9.1.18-SNAPSHOT</version>
     <packaging>pom</packaging>
     <name>fluxtion</name>
 

runtime/pom.xml

@@ -20,7 +20,7 @@ Copyright (C) 2024 gregory higgins (C) 2024 gregory higgins
     <parent>
         <groupId>com.fluxtion</groupId>
         <artifactId>root-parent-pom</artifactId>
-        <version>9.1.17-SNAPSHOT</version>
+        <version>9.1.18-SNAPSHOT</version>
         <relativePath>../parent-root/pom.xml</relativePath>
     </parent>
 

runtime/src/main/java/com/fluxtion/runtime/annotations/feature/Experimental.java

@@ -0,0 +1,11 @@
+package com.fluxtion.runtime.annotations.feature;
+
+/**
+ * Marks a class or method as a experimental feature. Mirrors the use of jdk experimental features:
+ * <p/>
+ * Experimental features represent early versions of (mostly) VM-level features, which can be risky, incomplete, or even
+ * unstable. In most cases, they need to be enabled using dedicated flags. For the purpose of comparison, if an
+ * experimental feature is considered 25% “done”, then a preview feature should be at least 95% “done”
+ */
+public @interface Experimental {
+}

runtime/src/main/java/com/fluxtion/runtime/annotations/feature/Preview.java

@@ -0,0 +1,11 @@
+package com.fluxtion.runtime.annotations.feature;
+
+/**
+ * Marks a class or method as a preview feature. Mirrors the use of jdk preview features:
+ * <p/>
+ * A preview feature is a new feature of the Java language, Java Virtual Machine, or Java SE API that is fully specified,
+ * fully implemented, and yet impermanent. It is available in a JDK feature release to provoke developer feedback based
+ * on real world use; this may lead to it becoming permanent in a future Java SE Platform.
+ */
+public @interface Preview {
+}

runtime/src/main/java/com/fluxtion/runtime/ml/AbstractFeature.java

@@ -0,0 +1,40 @@
+package com.fluxtion.runtime.ml;
+
+import com.fluxtion.runtime.annotations.Initialise;
+import com.fluxtion.runtime.annotations.feature.Experimental;
+
+import java.util.List;
+
+@Experimental
+public abstract class AbstractFeature implements Feature, CalibrationProcessor {
+
+    protected double co_efficient;
+    protected double weight;
+    protected double value;
+
+    @Initialise
+    public void init() {
+        co_efficient = 0;
+        weight = 0;
+        value = 0;
+    }
+
+    @Override
+    public boolean setCalibration(List<Calibration> calibrations) {
+        for (int i = 0, calibrationsSize = calibrations.size(); i < calibrationsSize; i++) {
+            Calibration calibration = calibrations.get(i);
+            if (calibration.getFeatureIdentifier().equals(identifier())) {
+                co_efficient = calibration.getCo_efficient();
+                weight = calibration.getWeight();
+                return true;
+            }
+        }
+        return false;
+    }
+
+    @Override
+    public double value() {
+        return value;
+    }
+
+}

runtime/src/main/java/com/fluxtion/runtime/ml/Calibration.java

@@ -0,0 +1,20 @@
+package com.fluxtion.runtime.ml;
+
+import com.fluxtion.runtime.annotations.feature.Experimental;
+import lombok.Builder;
+import lombok.Data;
+
+@Data
+@Builder
+@Experimental
+public class Calibration {
+    private String featureIdentifier;
+    private Class<? extends Feature> featureClass;
+    private int featureVersion;
+    private double co_efficient;
+    private double weight;
+
+    public String getFeatureIdentifier() {
+        return featureIdentifier == null ? featureClass.getSimpleName() : featureIdentifier;
+    }
+}

runtime/src/main/java/com/fluxtion/runtime/ml/CalibrationProcessor.java

@@ -0,0 +1,8 @@
+package com.fluxtion.runtime.ml;
+
+import java.util.List;
+
+public interface CalibrationProcessor {
+
+    boolean setCalibration(List<Calibration> calibration);
+}

runtime/src/main/java/com/fluxtion/runtime/ml/Feature.java

@@ -0,0 +1,25 @@
+package com.fluxtion.runtime.ml;
+
+import com.fluxtion.runtime.annotations.ExportService;
+import com.fluxtion.runtime.annotations.feature.Experimental;
+import com.fluxtion.runtime.node.NamedNode;
+
+@Experimental
+public interface Feature extends NamedNode, @ExportService CalibrationProcessor {
+
+    default String identifier() {
+        return getClass().getSimpleName();
+    }
+
+    default int version() {
+        return 0;
+    }
+
+    @Override
+    default String getName() {
+        return identifier() + "_" + version();
+    }
+
+    double value();
+
+}

runtime/src/main/java/com/fluxtion/runtime/ml/MutableDouble.java

@@ -0,0 +1,20 @@
+package com.fluxtion.runtime.ml;
+
+import com.fluxtion.runtime.annotations.feature.Experimental;
+
+@Experimental
+public class MutableDouble {
+    double value;
+
+    public MutableDouble(double value) {
+        this.value = value;
+    }
+
+    public MutableDouble() {
+        this(Double.NaN);
+    }
+
+    void reset() {
+        value = Double.NaN;
+    }
+}

runtime/src/main/java/com/fluxtion/runtime/ml/PredictiveLinearRegressionModel.java

@@ -0,0 +1,59 @@
+package com.fluxtion.runtime.ml;
+
+import com.fluxtion.runtime.annotations.*;
+import com.fluxtion.runtime.annotations.feature.Experimental;
+
+import java.util.IdentityHashMap;
+import java.util.List;
+import java.util.Map;
+
+@Experimental
+public class PredictiveLinearRegressionModel implements PredictiveModel, @ExportService CalibrationProcessor {
+
+    private transient final Map<Feature, MutableDouble> valueMap;
+    private final Feature[] features;
+    private double prediction = Double.NaN;
+
+    public PredictiveLinearRegressionModel(Feature... features) {
+        this.features = features;
+        this.valueMap = new IdentityHashMap<>(features.length);
+        for (Feature feature : features) {
+            valueMap.put(feature, new MutableDouble(0));
+        }
+    }
+
+    @Initialise
+    public void init() {
+        prediction = Double.NaN;
+    }
+
+    @Override
+    @NoPropagateFunction
+    public boolean setCalibration(List<Calibration> calibrations) {
+        double previousValue = prediction;
+        prediction = 0;
+        for (Feature feature : features) {
+            prediction += feature.value();
+        }
+        return previousValue != prediction | Double.isNaN(previousValue) != Double.isNaN(prediction);
+    }
+
+    @OnParentUpdate
+    public void featureUpdated(Feature featureUpdated) {
+        MutableDouble previousValue = valueMap.get(featureUpdated);
+        double newValue = featureUpdated.value();
+        prediction += newValue - previousValue.value;
+        previousValue.value = newValue;
+    }
+
+    @OnTrigger
+    public boolean calculateInference() {
+        return true;
+    }
+
+
+    @Override
+    public double predictedValue() {
+        return prediction;
+    }
+}

runtime/src/main/java/com/fluxtion/runtime/ml/PredictiveModel.java

@@ -0,0 +1,9 @@
+package com.fluxtion.runtime.ml;
+
+import com.fluxtion.runtime.annotations.feature.Experimental;
+
+@Experimental
+public interface PredictiveModel {
+
+    double predictedValue();
+}