cnnregressionmodeltest.java

化学图形处理软件

package org.openscience.cdk.test.qsar.model.R2;

import junit.framework.Test;
import junit.framework.TestSuite;
import org.openscience.cdk.exception.CDKException;
import org.openscience.cdk.qsar.model.QSARModelException;
import org.openscience.cdk.qsar.model.R2.CNNRegressionModel;
import org.openscience.cdk.qsar.model.R2.RModel;
import org.openscience.cdk.test.CDKTestCase;

/**
 * TestSuite that runs a test for the CNNRegressionModel
 *
 * @author Rajarshi Guha
 * @cdk.require r-project
 * @cdk.module test-qsar
 */

public class CNNRegressionModelTest extends CDKTestCase {

    public CNNRegressionModelTest() {
    }

    public static Test suite() {
        return new TestSuite(org.openscience.cdk.test.qsar.model.R2.CNNRegressionModelTest.class);
    }

    public void testCNNRegressionModel() throws CDKException, Exception, QSARModelException {

        double[][] x = getXData();
        double[] y = getYData();

        CNNRegressionModel cnnrm = new CNNRegressionModel(x, y, 3);
        assertNotNull(RModel.getRengine());
        assertEquals("cdkCNNModel0", cnnrm.getModelName());

        Double[] Wts = getWeights();
        cnnrm.setParameters("Wts", Wts);
        cnnrm.build();
        assertNotNull(cnnrm.getModelObject());

        double value = cnnrm.getValue();
        assertEquals(value, 8.076735, .000001);

        double[] wts = cnnrm.getWts();
        assertTrue(wts != null);
        assertEquals(-1.635880, wts[0], .000001);
        assertEquals(-6.227619, wts[1], .000001);
        assertEquals(-4.639471, wts[2], .000001);
        assertEquals(-4.060546, wts[3], .000001);

        double[][] fitted = cnnrm.getFittedValues();
        assertTrue(fitted != null);
        assertEquals(0.527783, fitted[0][0], .000001);
        assertEquals(0.527783, fitted[1][0], .000001);
        assertEquals(0.527783, fitted[2][0], .000001);
        assertEquals(0.203857, fitted[6][0], .000001);

        /* Test predictions */
        Double[][] newx = {
                {new Double(9.81536768251), new Double(3.82849269659), new Double(7.22212024421)},
                {new Double(0.197449829806), new Double(0.324130354642), new Double(2.8329420321)},
                {new Double(0.548460836141), new Double(7.28037586863), new Double(8.13728493983)},
                {new Double(1.76049278788), new Double(6.41731766803), new Double(5.53986167864)},
                {new Double(3.4541825491), new Double(9.78038580407), new Double(3.58954097059)}
        };

        cnnrm.setParameters("newdata", newx);
        cnnrm.setParameters("type", "raw"); // this is set by default so no real need
        cnnrm.predict();

        double[][] preds = cnnrm.getPredictions();
        assertTrue(preds != null);
        assertEquals(0.527783, preds[0][0], 0.000001);
        assertEquals(0.401678, preds[1][0], 0.000001);
        assertEquals(0.390702, preds[2][0], 0.000001);
        assertEquals(0.527783, preds[3][0], 0.000001);
        assertEquals(0.527783, preds[4][0], 0.000001);

        assertTrue(cnnrm.summary() != null);
    }

    public void testModelLoadSave() throws QSARModelException {
        double[][] x = getXData();
        double[] y = getYData();

        CNNRegressionModel cnnrm = new CNNRegressionModel(x, y, 3);
        assertNotNull(RModel.getRengine());
        assertEquals("cdkCNNModel1", cnnrm.getModelName());

        Double[] Wts = getWeights();
        cnnrm.setParameters("Wts", Wts);
        cnnrm.build();
        cnnrm.saveModel(cnnrm.getModelName(), "cnntest.Rda");

        CNNRegressionModel loadedModel = new CNNRegressionModel();
        loadedModel.loadModel("cnntest.Rda");

        System.out.println("loadedModel.getModelName() = " + loadedModel.getModelName());

//        assertEquals("cdkCNNModel0", loadedModel.getModelName());
        assertNotNull(loadedModel.getModelObject());

        double[] wts = cnnrm.getWts();
        assertTrue(wts != null);
        assertEquals(-1.635880, wts[0], .000001);
        assertEquals(-6.227619, wts[1], .000001);
        assertEquals(-4.639471, wts[2], .000001);
        assertEquals(-4.060546, wts[3], .000001);

        double[][] fitted = cnnrm.getFittedValues();
        assertTrue(fitted != null);
        assertEquals(0.527783, fitted[0][0], .000001);
        assertEquals(0.527783, fitted[1][0], .000001);
        assertEquals(0.527783, fitted[2][0], .000001);
        assertEquals(0.203857, fitted[6][0], .000001);

        /* Test predictions */
        Double[][] newx = {
                {new Double(9.81536768251), new Double(3.82849269659), new Double(7.22212024421)},
                {new Double(0.197449829806), new Double(0.324130354642), new Double(2.8329420321)},
                {new Double(0.548460836141), new Double(7.28037586863), new Double(8.13728493983)},
                {new Double(1.76049278788), new Double(6.41731766803), new Double(5.53986167864)},
                {new Double(3.4541825491), new Double(9.78038580407), new Double(3.58954097059)}
        };

        loadedModel.setParameters("newdata", newx);
        loadedModel.setParameters("type", "raw"); // this is set by default so no real need
        loadedModel.predict();

        double[][] preds = loadedModel.getPredictions();
        assertTrue(preds != null);
        assertEquals(0.527783, preds[0][0], 0.000001);
        assertEquals(0.401678, preds[1][0], 0.000001);
        assertEquals(0.390702, preds[2][0], 0.000001);
        assertEquals(0.527783, preds[3][0], 0.000001);
        assertEquals(0.527783, preds[4][0], 0.000001);


    }


    private Double[] getWeights() {
        return new Double[]{
                new Double(0.51404345), new Double(0.50840113), new Double(0.74685975), new Double(0.13561035),
                new Double(0.29352420), new Double(0.82764496), new Double(0.48282801), new Double(0.36164355),
                new Double(0.33401877), new Double(0.58141624), new Double(0.08336752), new Double(0.72385802),
                new Double(0.94860029), new Double(0.32215781), new Double(0.32806066), new Double(0.66709418)
        };
    }

    private double[] getYData() {
        return new double[]{0.548279405588, 0.749557798438, 0.704786225556, 0.064272559019, 0.959196778261, 0.443650457811, 0.139588310157, 0.697614953528, 0.894633307417, 0.288986449536, 0.968020911596, 0.00941763156173, 0.803870693657, 0.457124742168, 0.728543899161, 0.88083354383, 0.624089352674, 0.470379461181, 0.86877991158, 0.622721685808, 0.0250057478044, 0.2376603194, 0.112920370051, 0.608780223601, 0.62741359624, 0.39753977229, 0.396823887458, 0.0259021311271, 0.433022176171, 0.94665816668, 0.788805032857, 0.831096752197, 0.981239642073, 0.72411413954, 0.585272152663, 0.694317542691, 0.890624533901, 0.244048473797, 0.422902339036, 0.597269134374, 0.911340032927, 0.00186723050398, 0.439586593554, 0.714613974993, 0.815341829936, 0.726336948414, 0.742772100572, 0.597295528478, 0.305955366581, 0.155579392014, 0.000873693540479, 0.339225424495, 0.433434106377, 0.109738110471, 0.0193980726758, 0.258795872246, 0.322462583569, 0.326807898424, 0.079866937163, 0.741776416238, 0.597174006951, 0.289816194377, 0.691182117374, 0.113315930392, 0.302120795811, 0.616653275971, 0.833480904688, 0.881803762099, 0.734675438389, 0.269429129873, 0.977225860294, 0.327410536298, 0.319292292397, 0.876227987007, 0.832930007711, 0.941552570764, 0.0433177729231, 0.333665283905, 0.889264621262, 0.367930824862, 0.143633644589, 0.0106269520474, 0.623817520313, 0.237853599409, 0.301794094647, 0.912166461213, 0.663976930266, 0.918081800984, 0.909573924607, 0.976541368479, 0.340915467396, 0.617160565805, 0.0315242385532, 0.869413665191, 0.695610662213, 0.144537534715, 0.619567870639, 0.159550199731, 0.536333432502, 0.837898880743};
    }

    private double[][] getXData() {
        return new double[][]{{5.33029143313, 8.13257437501, 2.66720308462},
                {3.29906147519, 5.06835102093, 6.47319431067},
                {5.69553153292, 5.88043843898, 9.73312992111},
                {5.29194559083, 6.78243188133, 3.2602449344},
                {6.18105762768, 3.36588488672, 3.94539328809},
                {1.32223357975, 8.78797039033, 7.77485740688},
                {0.391740629966, 5.08060997023, 8.28722389016},
                {4.27475126706, 8.52015977633, 7.21468545649},
                {7.14131409262, 8.67086866827, 7.64228671009},
                {8.55502719447, 5.25013245421, 5.73240025988},
                {5.31791067667, 7.99313789208, 1.64835209014},
                {9.03149835466, 1.94042287241, 9.28020345543},
                {0.925468187342, 4.97155215507, 7.69457858258},
                {9.16182426614, 4.74534182996, 6.58111071706},
                {1.15220637861, 1.78078924823, 2.24407287943},
                {9.24209878847, 7.87658524713, 2.38732162601},
                {8.50715035908, 9.16453417058, 0.618727514944},
                {5.84019865932, 5.20208546615, 6.61838858253},
                {3.76256505014, 0.329738943471, 0.874419640166},
                {9.96004184517, 9.14019090437, 4.90929645109},
                {4.44743194213, 3.95642974577, 7.62629150218},
                {1.24177865105, 1.48660423923, 1.20830798956},
                {8.35590316383, 1.14743031542, 6.29868134513},
                {6.12876561357, 4.63929392357, 5.87722199543},
                {8.11829752127, 0.13950274139, 2.54723293455},
                {4.40852772122, 5.07291389291, 0.100128243526},
                {2.58403059855, 1.78831569742, 5.19817475725},
                {8.04282601008, 3.76076347262, 1.43904088129},
                {3.43713025153, 4.35105074191, 0.0189145485124},
                {5.0236445539, 1.06317719489, 5.10306592945},
                {9.77434875025, 9.0666617274, 6.99448050277},
                {4.06797047248, 7.62659701718, 9.83152424086},
                {6.48920287132, 0.156594507329, 5.46872113685},
                {6.42883928789, 2.01940454563, 6.46523071259},
                {1.16293901493, 5.15391581673, 3.56182526491},
                {7.38000931385, 0.453325117578, 6.61031329357},
                {9.32963370626, 2.12590745134, 0.405388324151},
                {0.737255223472, 7.39059871721, 2.86079226118},
                {6.85301380605, 2.1615949728, 8.87574040247},
                {3.74156226774, 4.24620341057, 4.35371571862},
                {2.18208535888, 3.53972126321, 3.59052000965},
                {4.72006492073, 3.3574566235, 9.62444364758},
                {2.84331278854, 1.74554945195, 4.51285607572},
                {3.86999763691, 9.49323614413, 5.08797427552},
                {7.43099014174, 6.2755590307, 4.57542355747},
                {6.01320531795, 8.25706473123, 7.40439342966},
                {6.46384266575, 3.51112862363, 9.47435948698},
                {2.29011620065, 0.401145254435, 7.28671287627},
                {5.7219136188, 4.43209346253, 0.0622901932013},
                {4.30214056802, 1.68925570283, 7.89926376252},
                {0.64305256706, 8.22063584536, 4.33019352991},
                {6.44843380824, 9.10336359279, 6.8777037869},
                {2.45354486215, 5.34166315571, 8.04822795875},
                {9.13675572384, 8.19635101591, 6.85475060116},
                {8.0492824201, 7.55216736195, 3.73472402973},
                {4.40590062277, 5.27106603309, 2.59962025805},
                {0.313960278741, 0.11866096726, 4.07985095305},
                {0.462136466507, 0.415202739102, 1.03258083165},
                {6.74723654049, 7.7080622951, 7.22322407979},
                {1.97571555403, 3.18544339131, 5.56211977273},
                {3.14021838165, 0.81551917817, 3.95156287418},
                {4.05709817216, 2.98004731237, 5.8975379443},
                {4.25420450429, 7.78663760941, 5.98061090504},
                {6.2650372416, 7.96507652177, 6.43631309268},
                {0.248308143147, 5.07557198176, 7.06413762375},
                {2.83741089895, 0.652445391344, 3.32535947415},
                {5.98115064142, 9.88913498552, 9.3923706794},
                {3.45667026676, 1.37451287268, 2.35331272082},
                {7.83964781871, 2.22111016571, 9.10723793073},
                {0.509210152705, 7.97088780188, 6.17963669424},
                {5.50910552235, 6.92372624674, 8.43151367671},
                {9.94686419266, 5.16899669191, 1.77353096261},
                {1.46501561342, 4.39317416608, 4.66752677391},
                {7.34126711314, 1.50352255841, 7.42777093653},
                {6.80122177161, 2.48753341584, 4.30535748793},
                {3.43057685209, 9.11458889251, 8.1389601215},
                {7.82076320157, 4.99727977399, 8.31875065375},
                {8.62799832715, 5.67304190345, 1.40517550057},
                {2.20910090066, 5.45236965227, 0.190013284925},
                {8.27876352499, 3.23706166886, 6.23912802837},
                {8.69440791615, 0.729194277167, 3.45645694332},
                {8.30552885891, 2.53977734839, 0.498635632483},
                {6.35009207052, 5.87727519703, 4.92604761655},
                {2.21876644613, 3.85669457256, 9.44139826683},
                {5.49181700898, 1.69048597254, 2.29475976286},
                {3.79777411904, 0.437885574937, 8.10175192316},
                {8.11720195104, 8.84115458961, 6.25490466144},
                {4.58878775312, 5.51332276174, 3.85400216514},
                {6.01729101329, 9.69817519935, 7.63607038602},
                {4.14247512757, 9.633551519, 0.543555309265},
                {1.69925453337, 4.77655288911, 0.950497583032},
                {3.84897216241, 3.27769006984, 9.17922626403},
                {2.79348258306, 4.38230737375, 7.26219595942},
                {4.88988551153, 2.95206506434, 3.65797143803},
                {1.91134803528, 0.829719567085, 1.73891604909},
                {5.5514711696, 8.80684284298, 2.66911304157},
                {2.95100011358, 0.832983961872, 4.19266815334},
                {4.19942346415, 5.92478285192, 8.33053966924},
                {3.11127058351, 3.25340097022, 7.07258377268},
                {7.61105416732, 8.46642439572, 5.61730141222}};
    }

}