Package org.encog.app.analyst.csv

Source Code of org.encog.app.analyst.csv.TimeSeriesUtil

/*
* Encog(tm) Core v3.3 - Java Version
* http://www.heatonresearch.com/encog/
* https://github.com/encog/encog-java-core
* Copyright 2008-2014 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.app.analyst.csv;

import java.util.ArrayList;
import java.util.HashMap;
import java.util.List;
import java.util.Map;

import org.encog.app.analyst.AnalystError;
import org.encog.app.analyst.EncogAnalyst;
import org.encog.app.analyst.script.normalize.AnalystField;
import org.encog.util.EngineArray;

/**
* A utility used to breat data into time-series lead and lag.
*/
public class TimeSeriesUtil {

  /**
   * The lag depth.
   */
  private final int lagDepth;
 
  /**
   * The lead depth.
   */
  private final int leadDepth;
 
  /**
   * The total depth.
   */
  private final int totalDepth;
 
  /**
   * The analyst to use.
   */
  private final EncogAnalyst analyst;
 
  /**
   * The input size.
   */
  private final int inputSize;
 
  /**
   * The output size.
   */
  private final int outputSize;
 
  /**
   * The buffer to hold the time-series data.
   */
  private final List<double[]> buffer = new ArrayList<double[]>();
 
  /**
   * The heading map.
   */
  private final Map<String, Integer> headingMap
    = new HashMap<String, Integer>();

  /**
   * Construct the time-series utility.
   * @param theAnalyst The analyst to use.
   * @param headings The column headings.
   */
  public TimeSeriesUtil(final EncogAnalyst theAnalyst, boolean includeOutput,
      final List<String> headings) {
    this.analyst = theAnalyst;
    this.lagDepth = analyst.getLagDepth();
    this.leadDepth = analyst.getLeadDepth();
    this.totalDepth = this.lagDepth + this.leadDepth + 1;
    this.inputSize = includeOutput ? analyst.determineTotalColumns() : analyst.determineTotalInputFieldCount();
    this.outputSize = analyst.determineInputCount()
        + analyst.determineOutputCount();

    int headingIndex = 0;
    for (final String column : headings) {
      this.headingMap.put(column, headingIndex++);
    }
  }

  /**
   * @return the analyst
   */
  public EncogAnalyst getAnalyst() {
    return this.analyst;
  }

  /**
   * @return the buffer
   */
  public List<double[]> getBuffer() {
    return this.buffer;
  }

  /**
   * @return the headingMap
   */
  public Map<String, Integer> getHeadingMap() {
    return this.headingMap;
  }

  /**
   * @return the inputSize
   */
  public int getInputSize() {
    return this.inputSize;
  }

  /**
   * @return the lagDepth
   */
  public int getLagDepth() {
    return this.lagDepth;
  }

  /**
   * @return the leadDepth
   */
  public int getLeadDepth() {
    return this.leadDepth;
  }

  /**
   * @return the outputSize
   */
  public int getOutputSize() {
    return this.outputSize;
  }

  /**
   * @return the totalDepth
   */
  public int getTotalDepth() {
    return this.totalDepth;
  }

  /**
   * Process a row.
   * @param input The input.
   * @return The output.
   */
  public double[] process(final double[] input) {
    if (input.length != this.inputSize) {
      throw new AnalystError("Invalid input size: " + input.length
          + ", should be " + this.inputSize);
    }

    this.buffer.add(0, EngineArray.arrayCopy(input));

    // are we ready yet?
    if (this.buffer.size() < this.totalDepth) {
      return null;
    }

    // create output
    final double[] output = new double[this.outputSize];

    int outputIndex = 0;
    for (final AnalystField field : this.analyst.getScript().getNormalize()
        .getNormalizedFields()) {
      if (!field.isIgnored()) {
        if (!this.headingMap.containsKey(field.getName())) {
          throw new AnalystError("Undefined field: "
              + field.getName());
        }
        final int headingIndex = this.headingMap.get(field.getName());
        final int timeslice = translateTimeSlice(field.getTimeSlice());
        final double[] row = this.buffer.get(timeslice);
        final double d = row[headingIndex];
        output[outputIndex++] = d;
      }
    }

    // keep the buffer at a good size
    while (this.buffer.size() > this.totalDepth) {
      this.buffer.remove(this.buffer.size() - 1);
    }

    return output;
  }

  /**
   * Translate a timeslice from a pos/neg number to a displacement
   * into the buffer.
   * @param index The index.
   * @return The translated displacement.
   */
  private int translateTimeSlice(final int index) {
    return Math.abs(index - this.leadDepth);
  }

}
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