/* * Encog(tm) Core v3.4 - Java Version * http://www.heatonresearch.com/encog/ * https://github.com/encog/encog-java-core * Copyright 2008-2016 Heaton Research, Inc. * * Licensed 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. * * For more information on Heaton Research copyrights, licenses * and trademarks visit: * http://www.heatonresearch.com/copyright */ package org.encog.util.normalize.input; import org.encog.util.normalize.NormalizationError; /** * Provides basic functionality, such as min/max and current value * for other input fields. */ public class BasicInputField implements InputField { /** * The maximum value encountered so far for this field. */ private double min = Double.POSITIVE_INFINITY; /** * The minimum value encountered so far for this field. */ private double max = Double.NEGATIVE_INFINITY; /** * The current value for this field, only used while normalizing. */ private double currentValue; /** * True if this field is used to actually generate the input for * the neural network. */ private boolean usedForNetworkInput = true; /** * Given the current value, apply to the min and max values. * @param d THe current value. */ public void applyMinMax(final double d) { this.min = Math.min(this.min, d); this.max = Math.max(this.max, d); } /** * @return The current value of the input field. This is only valid, * while the normalization is being performed. */ public double getCurrentValue() { return this.currentValue; } /** * @return The maximum value for all of the input data, this is calculated * during the first pass of normalization. */ public double getMax() { return this.max; } /** * @return The minimum value for all of the input data, this is calculated * during the first pass of normalization. */ public double getMin() { return this.min; } /** * @return True, if this field is used for network input. This is needed * so that the buildForNetworkInput method of the normalization class knows * how many input fields to expect. For instance, fields used only to * segregate data are not used for the actual network input and may * not be provided when the network is actually being queried. */ public boolean getUsedForNetworkInput() { return this.usedForNetworkInput; } /** * Not supported for this sort of class, may be implemented in subclasses. * Will throw an exception. * @param i The index. Not used. * @return The value at the specified index. */ public double getValue(final int i) { throw new NormalizationError("Can't call getValue on " + this.getClass().getSimpleName()); } /** * Set the current value of this field. This value is only valid while * the normalization is occurring. * @param currentValue The current value of this field. */ public void setCurrentValue(final double currentValue) { this.currentValue = currentValue; } /** * Set the current max value. * @param max The maximum value encountered on this field so far. */ public void setMax(final double max) { this.max = max; } /** * Set the current min value. * @param min The minimum value encountered on this field so far. */ public void setMin(final double min) { this.min = min; } /** * This is needed so that the buildForNetworkInput method of the * normalization class knows how many input fields to expect. For instance, * fields used only to segregate data are not used for the actual network * input and may not be provided when the network is actually being queried. * @param usedForNetworkInput True, if this field is used for network input. */ public void setUsedForNetworkInput(final boolean usedForNetworkInput) { this.usedForNetworkInput = usedForNetworkInput; } }