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/*
* 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;
import org.apache.commons.math3.distribution.RealDistribution;
import org.apache.commons.math3.distribution.UniformRealDistribution;
import org.apache.commons.math3.analysis.UnivariateFunction;
import org.apache.commons.math3.analysis.function.Constant;
import org.apache.commons.math3.random.RandomGenerator;
/**
* Creates functions that will select the initial values of a neuron's
* features.
*
* @since 3.3
*/
public class FeatureInitializerFactory {
/** Class contains only static methods. */
private FeatureInitializerFactory() {}
/**
* Uniform sampling of the given range.
*
* @param min Lower bound of the range.
* @param max Upper bound of the range.
* @param rng Random number generator used to draw samples from a
* uniform distribution.
* @return an initializer such that the features will be initialized with
* values within the given range.
* @throws org.apache.commons.math3.exception.NumberIsTooLargeException
* if {@code min >= max}.
*/
public static FeatureInitializer uniform(final RandomGenerator rng,
final double min,
final double max) {
return randomize(new UniformRealDistribution(rng, min, max),
function(new Constant(0), 0, 0));
}
/**
* Uniform sampling of the given range.
*
* @param min Lower bound of the range.
* @param max Upper bound of the range.
* @return an initializer such that the features will be initialized with
* values within the given range.
* @throws org.apache.commons.math3.exception.NumberIsTooLargeException
* if {@code min >= max}.
*/
public static FeatureInitializer uniform(final double min,
final double max) {
return randomize(new UniformRealDistribution(min, max),
function(new Constant(0), 0, 0));
}
/**
* Creates an initializer from a univariate function {@code f(x)}.
* The argument {@code x} is set to {@code init} at the first call
* and will be incremented at each call.
*
* @param f Function.
* @param init Initial value.
* @param inc Increment
* @return the initializer.
*/
public static FeatureInitializer function(final UnivariateFunction f,
final double init,
final double inc) {
return new FeatureInitializer() {
/** Argument. */
private double arg = init;
/** {@inheritDoc} */
public double value() {
final double result = f.value(arg);
arg += inc;
return result;
}
};
}
/**
* Adds some amount of random data to the given initializer.
*
* @param random Random variable distribution.
* @param orig Original initializer.
* @return an initializer whose {@link FeatureInitializer#value() value}
* method will return {@code orig.value() + random.sample()}.
*/
public static FeatureInitializer randomize(final RealDistribution random,
final FeatureInitializer orig) {
return new FeatureInitializer() {
/** {@inheritDoc} */
public double value() {
return orig.value() + random.sample();
}
};
}
}
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