public Map<String, Map<GM_Position, Double>> readMatResultsFile(final String pStrFilter) {
MatFileReader lMatFileReader = null;
final MatFileFilter lMatFilter = new MatFileFilter();
Map<String, Map<GM_Position, Double>> lRes = null;
try {
if (pStrFilter != null) {
lMatFilter.addArrayName(STR_XP_NAME);
lMatFilter.addArrayName(STR_YP_NAME);
lMatFilter.addArrayName(pStrFilter);
}
if (m_strResultsFile == null) {
lMatFileReader = new MatFileReader(FileUtils.toFile(m_resultsFile.getURL()), lMatFilter);
} else {
lMatFileReader = new MatFileReader(m_strResultsFile, lMatFilter);
}
} catch (final Exception e) {
// throw new MatlabIOException( "Cannot open or read SWAN result matlab file." );
}
if (lMatFileReader != null) {
try {
final GM_Position lShiftPosition =
SWANDataConverterHelper.readCoordinateShiftValues(m_resultsFile);
m_doubleShiftX = lShiftPosition.getX();
m_doubleShiftY = lShiftPosition.getY();
final Map<String, MLArray> lMapData = lMatFileReader.getContent();
// printDebugParsedSWANRawData( lMatFileReader, null );
lRes = getValuesFormatedNameDatePosition(lMapData);
// printDebugResultData( lRes, null );
} catch (final Exception e) {
e.printStackTrace();
}
}
return lRes;
}
// debug only: raw text output of results
private static void printDebugParsedSWANRawData(final MatFileReader mfr, final String outputPath)
throws IOException, MatlabIOException {
String outputPathTmp = "d:/temp/MatReaderOut-"; // $NON-NLS-1$
if (outputPath != null && !"".equals(outputPath)) // $NON-NLS-1$
{
outputPathTmp = outputPath;
}
final Map<String, MLArray> lMapData = mfr.getContent();
final FileWriter fstream = new FileWriter(outputPathTmp + (new Date()).getTime());
final BufferedWriter out = new BufferedWriter(fstream);
final Set<String> lSetKeys = lMapData.keySet();
for (final String lStrKey : lSetKeys) {
final MLArray lValues = lMapData.get(lStrKey);
out.write(lValues.contentToString());
}
out.close();
}
@BeforeClass
public static void loadData() throws Exception {
MatFileReader reader = new MatFileReader("machine-learning-ex3/ex3/ex3data1.mat");
Map<String, MLArray> content = reader.getContent();
Assert.assertNotNull(content);
X = factory.createMatrix(((MLDouble) content.get("X")).getArray());
y = factory.createMatrix(((MLDouble) content.get("y")).getArray());
System.out.println("X: " + X.numRows() + "*" + X.numColumns());
System.out.println("y: " + y.numRows() + "*" + y.numColumns());
assertEquals(X.numRows(), y.numRows());
assertEquals(1, y.numColumns());
double[][] images = new double[100][];
int[] randIndexes = new ArrayUtil().randperm(X.numRows());
for (int i = 0; i < images.length; i++) images[i] = X.getRow(randIndexes[i]).asArray();
String[] labels = new String[images.length];
for (int i = 0; i < labels.length; i++)
labels[i] = String.valueOf((int) y.get(randIndexes[i], 0));
JPanel panel = displayUtil.createImageGrid(images, 20, 20, 2, labels);
displayUtil.saveImage(panel, "./target/Ex3TrainingSample.png");
}