/* * Encog(tm) Core v3.4 - Java Version * http://www.heatonresearch.com/encog/ * https://github.com/encog/encog-java-core * Copyright 2008-2016 Heaton Research, Inc. * * 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. * * For more information on Heaton Research copyrights, licenses * and trademarks visit: * http://www.heatonresearch.com/copyright */ package org.encog.app.analyst.commands; import java.io.File; import org.encog.app.analyst.AnalystError; import org.encog.app.analyst.EncogAnalyst; import org.encog.app.analyst.csv.AnalystEvaluateRawCSV; import org.encog.app.analyst.script.prop.ScriptProperties; import org.encog.app.analyst.util.AnalystReportBridge; import org.encog.ml.MLMethod; import org.encog.ml.MLRegression; import org.encog.persist.EncogDirectoryPersistence; import org.encog.util.logging.EncogLogging; /** * This class is used to evaluate a machine learning method. Evaluation data is * provided and the ideal and actual responses from the machine learning method * are written to a file. * */ public class CmdEvaluateRaw extends Cmd { /** * The name of the command. */ public static final String COMMAND_NAME = "EVALUATE-RAW"; /** * Construct an evaluate raw command. * @param analyst The analyst object to use. */ public CmdEvaluateRaw(final EncogAnalyst analyst) { super(analyst); } /** * {@inheritDoc} */ @Override public boolean executeCommand(final String args) { // get filenames final String evalID = getProp().getPropertyString( ScriptProperties.ML_CONFIG_EVAL_FILE); final String resourceID = getProp().getPropertyString( ScriptProperties.ML_CONFIG_MACHINE_LEARNING_FILE); final String outputID = getProp().getPropertyString( ScriptProperties.ML_CONFIG_OUTPUT_FILE); EncogLogging.log(EncogLogging.LEVEL_DEBUG, "Beginning evaluate raw"); EncogLogging.log(EncogLogging.LEVEL_DEBUG, "evaluate file:" + evalID); EncogLogging.log(EncogLogging.LEVEL_DEBUG, "resource file:" + resourceID); final File evalFile = getScript().resolveFilename(evalID); final File resourceFile = getScript().resolveFilename(resourceID); final File outputFile = getAnalyst().getScript().resolveFilename( outputID); MLMethod m = (MLMethod) EncogDirectoryPersistence.loadObject(resourceFile); if( !(m instanceof MLRegression) ) { throw new AnalystError("The evaluate raw command can only be used with regression."); } final MLRegression method = (MLRegression)m; final boolean headers = getScript().expectInputHeaders(evalID); final AnalystEvaluateRawCSV eval = new AnalystEvaluateRawCSV(); eval.setScript(getScript()); getAnalyst().setCurrentQuantTask(eval); eval.setReport(new AnalystReportBridge(getAnalyst())); eval.analyze(getAnalyst(), evalFile, headers, getProp() .getPropertyCSVFormat( ScriptProperties.SETUP_CONFIG_CSV_FORMAT)); eval.process(outputFile, method); getAnalyst().setCurrentQuantTask(null); return eval.shouldStop(); } /** * {@inheritDoc} */ @Override public String getName() { return CmdEvaluateRaw.COMMAND_NAME; } }