/**
* Copyright 2010 Neuroph Project http://neuroph.sourceforge.net
*
* 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.
*/
package org.neuroph.samples.timeseries;
import java.io.BufferedWriter;
import java.io.FileWriter;
import java.io.IOException;
/**
* Very simple basic class which wraps the data generation process for the Time-Series
* Prediction tutorial. Internally handles writing the data out to a system file. Also
* uses a buffer to simulate stepping along the time series data.
* See http://neuroph.sourceforge.net/TimeSeriesPredictionTutorial.html
*
* @author Laura Ellen Carter-Greaves
*/
public class GenerateSet {
private String filename;
private boolean simple;
private int sampleEvery;
private int memorySize;
/**
* Contructor for datase set generator which takes filename and data set settings as arguments
* @param filename
* @param simple
* @param sampleEvery
* @param memory
*/
public GenerateSet(String filename, boolean simple, int sampleEvery, int memory) {
super();
this.filename = filename;
this.simple = simple;
this.sampleEvery = sampleEvery;
this.memorySize = memory;
}
/**
* Does the data set generation
* @throws IOException
*/
public void doIt() throws IOException {
if(simple){
doItSimple();
}
else{
doItSupposition();
}
}
/**
* Generates simple sine wave data set
* @throws IOException
*/
private void doItSimple() throws IOException {
double buffer[]=new double[memorySize+1]; //the extra one is for the output value
int bufferSize=buffer.length;
int bufferFull=buffer.length;
GenerateSineWave gsw=new GenerateSineWave(1,1);
BufferedWriter out=new BufferedWriter(new FileWriter(filename));
for(int samples=0;samples<1000;samples++){
//run through next samples so we take samples EVERY 'sampleEvery' steps
for(int j=0;j<sampleEvery;j++){
gsw.getNextSample();
}
//shift buffer down by one
for(int i=1;i<bufferSize;i++){
buffer[i-1]=buffer[i];
}
//load latest into end of buffer
buffer[bufferSize-1]=gsw.getNextSample();
//check to see when buffer fills up
bufferFull--;
if(bufferFull<=0){ //if buffer full write out the buffer
for(int i=0;i<bufferSize;i++){
out.write(buffer[i]+"\t");
}
out.write("\n");
}
}
out.flush();
out.close();
}
/**
* Generates supposition sine wave data set
* @throws IOException
*/
private void doItSupposition() throws IOException{
BufferedWriter out=new BufferedWriter(new FileWriter(filename));
double buffer[]=new double[memorySize+1]; //the extra one is for the output value
int bufferSize=buffer.length;
int bufferFull=buffer.length;
GenerateSineWave gsw1=new GenerateSineWave(1,0.5);
GenerateSineWave gsw2=new GenerateSineWave(4,0.5);
for(int samples=0;samples<1000;samples++){
//run through next samples so we take samples EVERY
for(int j=0;j<sampleEvery;j++){
gsw1.getNextSample();
gsw2.getNextSample();
}
//shift buffer down by one
for(int i=1;i<bufferSize;i++){
buffer[i-1]=buffer[i];
}
//load latest into end of buffer
buffer[bufferSize-1]=gsw1.getNextSample()+gsw2.getNextSample();
//check to see when buffer fills up
bufferFull--;
if(bufferFull<=0){ //if buffer full write out the buffer
for(int i=0;i<bufferSize;i++){
out.write(buffer[i]+"\t");
}
out.write("\n");
}
}
out.flush();
out.close();
}
}