1 files changed, 117 insertions, 0 deletions
diff --git a/src/main/java/org/apache/commons/math3/ml/neuralnet/sofm/LearningFactorFunctionFactory.java b/src/main/java/org/apache/commons/math3/ml/neuralnet/sofm/LearningFactorFunctionFactory.java
new file mode 100644
index 0000000..9165e82
--- /dev/null
+++ b/src/main/java/org/apache/commons/math3/ml/neuralnet/sofm/LearningFactorFunctionFactory.java
@@ -0,0 +1,117 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements.  See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License.  You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.commons.math3.ml.neuralnet.sofm;
+
+import org.apache.commons.math3.ml.neuralnet.sofm.util.ExponentialDecayFunction;
+import org.apache.commons.math3.ml.neuralnet.sofm.util.QuasiSigmoidDecayFunction;
+import org.apache.commons.math3.exception.OutOfRangeException;
+
+/**
+ * Factory for creating instances of {@link LearningFactorFunction}.
+ *
+ * @since 3.3
+ */
+public class LearningFactorFunctionFactory {
+    /** Class contains only static methods. */
+    private LearningFactorFunctionFactory() {}
+
+    /**
+     * Creates an exponential decay {@link LearningFactorFunction function}.
+     * It will compute <code>a e<sup>-x / b</sup></code>,
+     * where {@code x} is the (integer) independent variable and
+     * <ul>
+     *  <li><code>a = initValue</code>
+     *  <li><code>b = -numCall / ln(valueAtNumCall / initValue)</code>
+     * </ul>
+     *
+     * @param initValue Initial value, i.e.
+     * {@link LearningFactorFunction#value(long) value(0)}.
+     * @param valueAtNumCall Value of the function at {@code numCall}.
+     * @param numCall Argument for which the function returns
+     * {@code valueAtNumCall}.
+     * @return the learning factor function.
+     * @throws org.apache.commons.math3.exception.OutOfRangeException
+     * if {@code initValue <= 0} or {@code initValue > 1}.
+     * @throws org.apache.commons.math3.exception.NotStrictlyPositiveException
+     * if {@code valueAtNumCall <= 0}.
+     * @throws org.apache.commons.math3.exception.NumberIsTooLargeException
+     * if {@code valueAtNumCall >= initValue}.
+     * @throws org.apache.commons.math3.exception.NotStrictlyPositiveException
+     * if {@code numCall <= 0}.
+     */
+    public static LearningFactorFunction exponentialDecay(final double initValue,
+                                                          final double valueAtNumCall,
+                                                          final long numCall) {
+        if (initValue <= 0 ||
+            initValue > 1) {
+            throw new OutOfRangeException(initValue, 0, 1);
+        }
+
+        return new LearningFactorFunction() {
+            /** DecayFunction. */
+            private final ExponentialDecayFunction decay
+                = new ExponentialDecayFunction(initValue, valueAtNumCall, numCall);
+
+            /** {@inheritDoc} */
+            public double value(long n) {
+                return decay.value(n);
+            }
+        };
+    }
+
+    /**
+     * Creates an sigmoid-like {@code LearningFactorFunction function}.
+     * The function {@code f} will have the following properties:
+     * <ul>
+     *  <li>{@code f(0) = initValue}</li>
+     *  <li>{@code numCall} is the inflexion point</li>
+     *  <li>{@code slope = f'(numCall)}</li>
+     * </ul>
+     *
+     * @param initValue Initial value, i.e.
+     * {@link LearningFactorFunction#value(long) value(0)}.
+     * @param slope Value of the function derivative at {@code numCall}.
+     * @param numCall Inflexion point.
+     * @return the learning factor function.
+     * @throws org.apache.commons.math3.exception.OutOfRangeException
+     * if {@code initValue <= 0} or {@code initValue > 1}.
+     * @throws org.apache.commons.math3.exception.NumberIsTooLargeException
+     * if {@code slope >= 0}.
+     * @throws org.apache.commons.math3.exception.NotStrictlyPositiveException
+     * if {@code numCall <= 0}.
+     */
+    public static LearningFactorFunction quasiSigmoidDecay(final double initValue,
+                                                           final double slope,
+                                                           final long numCall) {
+        if (initValue <= 0 ||
+            initValue > 1) {
+            throw new OutOfRangeException(initValue, 0, 1);
+        }
+
+        return new LearningFactorFunction() {
+            /** DecayFunction. */
+            private final QuasiSigmoidDecayFunction decay
+                = new QuasiSigmoidDecayFunction(initValue, slope, numCall);
+
+            /** {@inheritDoc} */
+            public double value(long n) {
+                return decay.value(n);
+            }
+        };
+    }
+}