/*
* 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;
}
}