@Test
public void testCalc() {

	List <Vector> data = new ArrayList <>();
	Row[] testArray =
		new Row[]{
			Row.of(new Object[]{0, "0:1 1:2 2:6 3:0 4:2 5:3 6:1 7:1 8:0 9:0 10:3"}),
			Row.of(new Object[]{1, "0:1 1:3 2:0 3:1 4:3 5:0 6:0 7:2 8:0 9:0 10:1"}),
			Row.of(new Object[]{2, "0:1 1:4 2:1 3:0 4:0 5:4 6:9 7:0 8:1 9:2 10:0"}),
			Row.of(new Object[]{3, "0:2 1:1 2:0 3:3 4:0 5:0 6:5 7:0 8:2 9:3 10:9"}),
			Row.of(new Object[]{4, "0:3 1:1 2:1 3:9 4:3 5:0 6:2 7:0 8:0 9:1 10:3"}),
			Row.of(new Object[]{5, "0:4 1:2 2:0 3:3 4:4 5:5 6:1 7:1 8:1 9:4 10:0"}),
			Row.of(new Object[]{6, "0:2 1:1 2:0 3:3 4:0 5:0 6:5 7:0 8:2 9:2 10:9"}),
			Row.of(new Object[]{7, "0:1 1:1 2:1 3:9 4:2 5:1 6:2 7:0 8:0 9:1 10:3"}),
			Row.of(new Object[]{8, "0:4 1:4 2:0 3:3 4:4 5:2 6:1 7:3 8:0 9:0 10:0"}),
			Row.of(new Object[]{9, "0:2 1:8 2:2 3:0 4:3 5:0 6:2 7:0 8:2 9:7 10:2"}),
			Row.of(new Object[]{10, "0:1 1:1 2:1 3:9 4:0 5:2 6:2 7:0 8:0 9:3 10:3"}),
			Row.of(new Object[]{11, "0:4 1:1 2:0 3:0 4:4 5:5 6:1 7:3 8:0 9:1 10:0"})
		};
	for (int i = 0; i < testArray.length; i++) {
		data.add(VectorUtil.parseSparse((String) testArray[i].getField(1)));
	}
	int row = 11;
	int col = 5;
	double[] temp = new double[] {0.8936825549031158,
		0.9650683744577933,
		1.1760851442955271,
		0.889011463028263,
		1.0355502890838704,
		1.1720254142865503,
		0.8496512959061578,
		1.1564109073902848,
		0.8528198328651976,
		1.072261907065107,
		1.0112487630821958,
		1.0288027427394206,
		1.1256918577237478,
		1.0641131417250107,
		0.9830788207753957,
		0.9519235842178695,
		1.0531103642783968,
		1.0846663792488604,
		0.9317316401779444,
		0.9816247167440154,
		0.953061129524052,
		0.8836097897537777,
		0.8539728772760822,
		1.109432137460693,
		0.9801693423689286,
		0.9385725168762017,
		1.009886079821316,
		0.9741390218380398,
		0.8734624459614093,
		0.8548583255850564,
		0.8934120594879987,
		1.0200469492393616,
		0.9461610896051537,
		1.1912819895664948,
		0.9650275833536232,
		0.9312815665885328,
		0.984681817963758,
		1.1412711858668625,
		1.1159082714127344,
		1.0219124026668207,
		1.1052645047308647,
		1.1380919062139254,
		0.9684793634316371,
		1.023922805813918,
		1.0777999541431174,
		0.8730213177341947,
		1.0353598060502658,
		1.047104264664753,
		1.1284793487722498,
		0.8898021261569816,
		1.1634869627283706,
		0.817874601150865,
		1.0424867867765728,
		1.167773175905418,
		0.915224402643435};
	DenseMatrix lambda = new DenseMatrix(row, col, temp, false).transpose();
	DenseMatrix alpha = new DenseMatrix(5, 1, new double[] {0.2, 0.3, 0.4, 0.5, 0.6});
	DenseMatrix gammad = new DenseMatrix(5, 1, new double[] {0.7, 0.8, 0.9, 1.0, 1.1});
	int numTopic = 5;
	int vocabularySize = 11;
	double beta = 0.2;
	int taskNum = 1;
	double loglikelihood = OnlineLogLikelihood.logLikelihood(data, lambda, alpha, gammad,
		numTopic, vocabularySize, beta, taskNum);
	Assert.assertEquals(-833.0890905595685, loglikelihood, 10e-4);
	System.out.println("loglikelihood: " + loglikelihood);
}