SiLeBAT/FSK-Lab

package metadata.swagger;

import static org.junit.Assert.assertEquals;
import static org.junit.Assert.assertNotNull;
import static org.junit.Assert.assertNull;

import java.io.InputStream;
import java.nio.file.Files;
import java.nio.file.Paths;

import org.apache.poi.ss.usermodel.Sheet;
import org.apache.poi.ss.usermodel.Workbook;
import org.apache.poi.ss.usermodel.WorkbookFactory;
import org.junit.Test;
import org.threeten.bp.LocalDate;

import de.bund.bfr.metadata.swagger.PredictiveModel;
import de.bund.bfr.metadata.swagger.PredictiveModelDataBackground;
import de.bund.bfr.metadata.swagger.PredictiveModelGeneralInformation;
import de.bund.bfr.metadata.swagger.PredictiveModelModelMath;
import de.bund.bfr.metadata.swagger.PredictiveModelScope;
import de.bund.bfr.metadata.swagger.PredictiveModelScopeProduct;

public class PredictiveModelSheetImporterTest {

    @SuppressWarnings("static-method")
    @Test
    public void test() throws Exception {
        Sheet sheet;
        try (InputStream stream = Files.newInputStream(Paths.get("files/annotation_v1.0.4.xlsx"));
                Workbook workbook = WorkbookFactory.create(stream)) {
            sheet = workbook.getSheet("Predictive Model");
        }

        PredictiveModel model = (PredictiveModel) new PredictiveModelSheetImporter().retrieveModel(sheet);
        test(model.getGeneralInformation());
        test(model.getScope());
        test(model.getDataBackground());
        test(model.getModelMath());
    }

    private static void test(PredictiveModelGeneralInformation information) throws Exception {
        assertEquals("Listeria Monocytogenes (DR of gQMRA)", information.getName());
        assertEquals("PUBLISHED SCIENTIFIC STUDIES", information.getSource());
        assertEquals("DR000001", information.getIdentifier());
        assertEquals(6, information.getAuthor().size());
        assertEquals(6, information.getCreator().size());
        assertEquals(LocalDate.of(2018, 3, 30), information.getCreationDate());
        assertNull(information.getModificationDate()); // Not set
        assertEquals("CC0 1.0", information.getRights());
        assertEquals("Open access", information.getAvailability());
        assertEquals("http://onlinelibrary.wiley.com/doi/10.2903/sp.efsa.2017.EN-1252/abstract", information.getUrl());
        assertEquals(".fskx", information.getFormat());
        assertEquals(3, information.getReference().size());
        assertEquals("English", information.getLanguage());
        assertEquals("FSK-Lab", information.getSoftware());
        assertEquals("R 3", information.getLanguageWrittenIn());
        assertNotNull(information.getModelCategory());
        assertEquals("Uncurated", information.getStatus());
        assertEquals("Objective", information.getObjective());
        assertEquals("Description", information.getDescription());
        
        TestUtils.testFirstCreator(information.getCreator().get(0));
        TestUtils.testFirstAuthor(information.getAuthor().get(0));
        TestUtils.testFirstReference(information.getReference().get(0));
    }

    private static void test(PredictiveModelScope scope) {
        assertEquals(10, scope.getProduct().size());
        assertEquals(1, scope.getHazard().size());
        assertNull(scope.getGeneralComment());
        assertNull(scope.getTemporalInformation());
        // TODO: spatial information: String*
        
        // product in PredictiveModelScope is different and needs to tested separately
        testFirstProduct(scope.getProduct().get(0));
        TestUtils.testFirstHazard(scope.getHazard().get(0));
    }

    private static void test(PredictiveModelDataBackground background) {
        assertNotNull(background.getStudy());
        assertEquals(3, background.getStudySample().size());
        assertEquals(3, background.getLaboratory().size());
        assertEquals(3, background.getAssay().size());

        TestUtils.testFirstAssay(background.getAssay().get(0));
    }

    private static void test(PredictiveModelModelMath math) {
        assertEquals(9, math.getParameter().size());
        assertEquals(1, math.getQualityMeasures().size());
        assertNull(math.getModelEquation());
        assertEquals("Maximum likelihood estimation (MLE)", math.getFittingProcedure());
        assertNull(math.getEvent());
        
        TestUtils.testFirstParameter(math.getParameter().get(0));
    }
    
    private static void testFirstProduct(PredictiveModelScopeProduct product) {
        assertEquals("Allspice", product.getName());
        assertEquals("description", product.getDescription());
        assertEquals("[]", product.getUnit());
        assertNull(product.getMethod());
        assertEquals("Aluminium foil - aluminium sheet", product.getPackaging().get(0));
        assertEquals("Canning", product.getTreatment().get(0));
        assertEquals("Afghanistan", product.getOriginCountry());
        assertEquals("A Coruña", product.getOriginArea());
        assertEquals("Adriatic", product.getFisheriesArea());
        assertEquals(LocalDate.of(2017, 11, 30), product.getProductionDate());
        assertEquals(LocalDate.of(2018,  11, 30), product.getExpiryDate());
    }
}