/*
 * SvmTest.java
 * Copyright (c) 2017
 * Authors: Ionut Damian, Michael Dietz, Frank Gaibler, Daniel Langerenken, Simon Flutura,
 * Vitalijs Krumins, Antonio Grieco
 * *****************************************************
 * This file is part of the Social Signal Interpretation for Java (SSJ) framework
 * developed at the Lab for Human Centered Multimedia of the University of Augsburg.
 *
 * SSJ has been inspired by the SSI (http://openssi.net) framework. SSJ is not a
 * one-to-one port of SSI to Java, it is an approximation. Nor does SSJ pretend
 * to offer SSI's comprehensive functionality and performance (this is java after all).
 * Nevertheless, SSJ borrows a lot of programming patterns from SSI.
 *
 * This library is free software; you can redistribute it and/or modify it under the
 * terms of the GNU General Public License as published by the Free Software
 * Foundation; either version 3 of the License, or any later version.
 *
 * This library is distributed in the hope that it will be useful, but WITHOUT
 * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
 * FOR A PARTICULAR PURPOSE.
 * See the GNU General Public License for more details.
 *
 * You should have received a copy of the GNU General Public License along
 * with this library; if not, see <http://www.gnu.org/licenses/>.
 */

package hcm.ssj;

import androidx.test.filters.SmallTest;
import androidx.test.runner.AndroidJUnit4;

import junit.framework.Assert;

import org.junit.Test;
import org.junit.runner.RunWith;

import java.io.File;

import hcm.ssj.androidSensor.AndroidSensor;
import hcm.ssj.androidSensor.AndroidSensorChannel;
import hcm.ssj.androidSensor.SensorType;
import hcm.ssj.body.AccelerationFeatures;
import hcm.ssj.core.Pipeline;
import hcm.ssj.core.Provider;
import hcm.ssj.file.FileWriter;
import hcm.ssj.ml.ClassifierT;
import hcm.ssj.ml.SVM;
import hcm.ssj.test.Logger;

import static androidx.test.InstrumentationRegistry.getContext;


@RunWith(AndroidJUnit4.class)
@SmallTest
public class SvmTest
{
	@Test
	public void testSVM() throws Exception
	{
		// Resources
		File dir = getContext().getFilesDir();
		String modelName = "search_model.trainer";
		TestHelper.copyAssetToFile(modelName, new File(dir, modelName));
		TestHelper.copyAssetToFile(modelName + ".SVM.model", new File(dir, modelName + ".SVM.model"));
		TestHelper.copyAssetToFile(modelName + ".SVM.option", new File(dir, modelName + ".SVM.option"));
		String outputFileName = getClass().getSimpleName() + ".test";
		File outputFile = new File(dir, outputFileName);

		// Setup
		Pipeline frame = Pipeline.getInstance();
		frame.options.bufferSize.set(10.0f);

		// Sensor
		AndroidSensor accSensor = new AndroidSensor();
		AndroidSensor gyrSensor = new AndroidSensor();

		// Channel
		AndroidSensorChannel accChannel = new AndroidSensorChannel();
		accChannel.options.sensorType.set(SensorType.LINEAR_ACCELERATION);
		accChannel.options.sampleRate.set(40);
		frame.addSensor(accSensor, accChannel);

		AndroidSensorChannel gyrChannel = new AndroidSensorChannel();
		gyrChannel.options.sensorType.set(SensorType.GYROSCOPE);
		gyrChannel.options.sampleRate.set(40);
		frame.addSensor(gyrSensor, gyrChannel);

		// Transformer
		AccelerationFeatures accFeatures = new AccelerationFeatures();
		frame.addTransformer(accFeatures, accChannel, 2, 2);

		AccelerationFeatures gyrFeatures = new AccelerationFeatures();
		frame.addTransformer(gyrFeatures, gyrChannel, 2, 2);

		// SVM
		SVM svm = new SVM();
		svm.options.file.setValue(dir.getAbsolutePath() + File.separator + modelName);
		frame.addModel(svm);

		ClassifierT classifier = new ClassifierT();
		classifier.setModel(svm);
		frame.addTransformer(classifier, new Provider[]{accFeatures, gyrFeatures}, 2, 0);

		// Consumer
		Logger log = new Logger();
		frame.addConsumer(log, classifier, 2, 0);

		FileWriter svmWriter = new FileWriter();
		svmWriter.options.filePath.setValue(dir.getAbsolutePath());
		svmWriter.options.fileName.set(outputFileName);
		frame.addConsumer(svmWriter, classifier, 2, 0);

		// Start framework
		frame.start();

		// Wait duration
		try
		{
			Thread.sleep(TestHelper.DUR_TEST_NORMAL);
		}
		catch (Exception e)
		{
			e.printStackTrace();
		}

		// Stop framework
		frame.stop();
		frame.clear();

		// Get data file
		File data = new File(dir, outputFileName + "~");

		// Verify
		Assert.assertTrue(outputFile.length() > 100);
		Assert.assertTrue(data.length() > 100);

		if (outputFile.exists()) outputFile.delete();
		if (data.exists()) data.delete();
	}
}
