/**
* Tries to evaluate the input that this instance was created with. Success of evaluation can be
* queried using {@link #errorOccurred()}. If an error occurred, the exception can be obtained
* using {@link #getLastError()}. If evaluation was successful, the result can be obtained using
* {@link #getRoot()}.
*
* @param rootNs The namespace to which ne declarations will be stored.
* @param workingNs The initial namespace to work with.
*/
public void evaluate(Namespace rootNs, Namespace workingNs) {
try {
final InputParser parser = new InputParser(this.input, this.encoding, this.reporter);
this.lastResult = parser.parse();
if (this.lastResult == null) {
return;
}
// set parent attributes for all nodes
final ASTVisitor parentSetter = new ParentSetter();
this.lastResult.visit(parentSetter);
final ProblemReporter reporter = this.reporter.subReporter(this.lastResult.getPosition());
// resolve types
TypeResolver.resolveAST(this.lastResult, workingNs, reporter);
if (!this.reporter.hasProblems()) {
final ASTVisitor executor = getExecutor(rootNs, workingNs, reporter);
this.lastResult.visit(executor);
}
} catch (UnsupportedEncodingException e) {
throw new RuntimeException("This should not have happened", e); // $NON-NLS-1$
} catch (ASTTraversalException e) {
e.printStackTrace();
this.lastError = e;
}
}
protected ParsedCommand parse(String[] input) {
if (isMissingArguments(input)) {
return createParsedCommandError(ERROR_MISSING_ARGS);
} else {
String inputArgs = input[INDEX_FOR_ARGS];
try {
String parsedTitle = getTitleWithDateKeywords(inputArgs);
Calendar[] parsedTimes = getStandardDatesTimes(inputArgs);
if (mustRemoveDateKeywordSection(parsedTimes, inputArgs)) {
parsedTitle = removeDateKeywordSection(parsedTitle);
}
String parsedDescription = getDescriptionFromString(inputArgs);
ArrayList<String> parsedTags = getTagsFromString(inputArgs);
ParsedCommand pc =
new ParsedCommand.ParsedCommandBuilder(MyParser.CommandType.ADD)
.title(parsedTitle)
.times(parsedTimes)
.description(parsedDescription)
.tags(parsedTags)
.build();
return pc;
} catch (InvalidArgumentsForParsedCommandException e) {
return InputParser.createParsedCommandError(e.getMessage());
}
}
}
public static void main(String[] args) throws IOException {
WeightedGraph wg = InputParser.parseAssignmentFile();
MaxSpaceGreedyClustering algo = new MaxSpaceGreedyClustering(wg);
int spacing = algo.findClusters(4);
System.out.println("Computed max spacing: " + spacing);
}
/**
* Creates a new <code>RequestCtx</code> by parsing XML from an input stream. Note that this a
* convenience method, and it will not do schema validation by default. You should be parsing the
* data yourself, and then providing the root node to the other <code>getInstance</code> method.
* If you use this convenience method, you probably want to turn on validation by setting the
* context schema file (see the programmer guide for more information on this).
*
* @param input a stream providing the XML data
* @return a new <code>RequestCtx</code>
* @throws ParsingException if there is an error parsing the input
*/
public static RequestCtx getInstance(InputStream input) throws ParsingException {
return getInstance(InputParser.parseInput(input, "Request"));
}
public static void main(String[] args) throws IOException, Exception {
// break into cases for each data set
// for congressional, partition into training and test sets
int whichDataSet = -1;
Scanner in = new Scanner(System.in);
String whichMonk = "";
boolean IG = false;
int tempIG = -1;
// check input parameters
try {
if (args.length > 3) throw new NumberFormatException();
tempIG = Integer.parseInt(args[0]);
whichDataSet = Integer.parseInt(args[1]);
// System.out.println(tempIG + " " + whichDataSet);
if (args.length < 2 || whichDataSet < 0 || whichDataSet > 2 || tempIG < 0 || tempIG > 1) {
throw new NumberFormatException();
}
// System.out.println(tempIG + " " + whichDataSet);
if (args.length < 3 && whichDataSet == 1) {
throw new NumberFormatException();
}
// System.out.println(tempIG + "* " + whichDataSet);
if (args.length == 3) {
int whichMonkInt = Integer.parseInt(args[2]);
if (whichMonkInt == 1) whichMonk = "monks-1";
else if (whichMonkInt == 2) whichMonk = "monks-2";
else if (whichMonkInt == 3) whichMonk = "monks-3";
else throw new NumberFormatException();
}
if (tempIG == 0) IG = false;
else IG = true;
} catch (NumberFormatException e) {
System.out.println(
"ERROR: \n\nUsage: ./run_traditional <IG or GR> <whichDataSet> <whichMonkDataSet> \n"
+ "IG or GR: (0) for information gain, (1) for gain ratio"
+ "\nwhichDataSet can be: (0=Congressional, 1=MONK, 2=Mushroom)"
+ "\nwhichMonkDataSet is only relevant if Monk chosen can be: (1 2 or 3)");
System.exit(1);
}
// cases for each data set
switch (whichDataSet) {
case 0:
{
fileName = "house-votes-84.data";
System.out.println("\n\nRunning data set: " + fileName);
parser = new CongressionalInputParser();
outputClasses = parser.initializeOutputClasses();
masterAttributes = parser.initializeMasterAttributesAndValues();
attributes = parser.getAttributesSet();
examples = parser.readExamples(fileName);
partitionIntoTestAndTraining(examples);
traditionalDecisionTreeBuilder =
new GreedyInformationGainDecisionTree(
trainingExamples, masterAttributes, attributes, outputClasses, IG);
System.out.println("\n\nnumber of congressional Examples: " + examples.size());
break;
}
case 1:
{
String fileName1 = whichMonk + ".train";
String fileName2 = whichMonk + ".test";
System.out.println("\n\nRunning data set: " + fileName1);
parser = new MonkInputParser();
outputClasses = parser.initializeOutputClasses();
masterAttributes = parser.initializeMasterAttributesAndValues();
attributes = parser.getAttributesSet();
trainingExamples = parser.readExamples(fileName1);
testExamples = parser.readExamples(fileName2);
traditionalDecisionTreeBuilder =
new GreedyInformationGainDecisionTree(
trainingExamples, masterAttributes, attributes, outputClasses, IG);
System.out.println(
"\n\nnumber of monk " + whichMonk + " Examples: " + trainingExamples.size());
break;
}
case 2:
{
String fileName1 = "agaricus-lepiota.data";
System.out.println("\n\nRunning data set: " + fileName1);
parser = new MushroomInputParser();
outputClasses = parser.initializeOutputClasses();
masterAttributes = parser.initializeMasterAttributesAndValues();
attributes = parser.getAttributesSet();
examples = parser.readExamples(fileName1);
// testExamples = parser.readExamples(fileName2);
partitionIntoTestAndTraining(examples);
traditionalDecisionTreeBuilder =
new GreedyInformationGainDecisionTree(
trainingExamples, masterAttributes, attributes, outputClasses, IG);
System.out.println("\n\nnumber of mushroom Examples: " + examples.size());
break;
}
}
// System.out.println(trainingExamples.get(1).getAttributeList());
finalDecisionTree =
traditionalDecisionTreeBuilder.makeDecisionTree(trainingExamples, attributes, null);
// System.out.println(finalDecisionTree.toString());
System.out.println("\nTesting the tree on the TRAINING examples...");
tester = new DecisionTreeTester(trainingExamples, masterAttributes, attributes, outputClasses);
tester.test(finalDecisionTree);
String out = tester.printPerformanceMetrics();
System.out.println(out);
System.out.println("\nTesting the tree on the " + testExamples.size() + " TEST examples...");
tester = new DecisionTreeTester(testExamples, masterAttributes, attributes, outputClasses);
tester.test(finalDecisionTree);
out = tester.printPerformanceMetrics();
System.out.println(out);
System.out.println("Successful completion of program");
}
