Java tutorial
/* * Copyright 2016 * Ubiquitous Knowledge Processing (UKP) Lab * Technische Universitt Darmstadt * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. */ package de.tudarmstadt.ukp.dkpro.core.api.datasets; import java.io.File; import java.util.Arrays; import org.apache.commons.lang.ArrayUtils; import org.apache.commons.logging.Log; import org.apache.commons.logging.LogFactory; import de.tudarmstadt.ukp.dkpro.core.api.datasets.internal.SplitImpl; public interface Dataset { String getName(); String getLanguage(); String getEncoding(); File[] getDataFiles(); File[] getLicenseFiles(); Split getDefaultSplit(); default Split getSplit(double aTrainRatio) { return getSplit(aTrainRatio, 1.0 - aTrainRatio); } default Split getSplit(double aTrainRatio, double aTestRatio) { Log LOG = LogFactory.getLog(getClass()); File[] all = getDataFiles(); Arrays.sort(all, (File a, File b) -> { return a.getName().compareTo(b.getName()); }); LOG.info("Found " + all.length + " files"); int trainPivot = (int) Math.round(all.length * aTrainRatio); int testPivot = (int) Math.round(all.length * aTestRatio) + trainPivot; File[] train = (File[]) ArrayUtils.subarray(all, 0, trainPivot); File[] test = (File[]) ArrayUtils.subarray(all, trainPivot, testPivot); LOG.debug("Assigned " + train.length + " files to training set"); LOG.debug("Assigned " + test.length + " files to test set"); if (testPivot != all.length) { LOG.info("Files missing from split: [" + (all.length - testPivot) + "]"); } return new SplitImpl(train, test, null); } }