/**
* Load the directed graph from the given file
*
* @param fileName the file to load the cart from
* @param featDefinition the feature definition
* @param dummy unused, just here for compatibility with the FeatureFileIndexer.
* @throws IOException , {@link MaryConfigurationException} if a problem occurs while loading
*/
public DirectedGraph load(InputStream inStream) throws IOException, MaryConfigurationException {
BufferedInputStream buffInStream = new BufferedInputStream(inStream);
assert buffInStream.markSupported();
buffInStream.mark(10000);
// open the CART-File and read the header
DataInput raf = new DataInputStream(buffInStream);
MaryHeader maryHeader = new MaryHeader(raf);
if (!maryHeader.hasCurrentVersion()) {
throw new IOException("Wrong version of database file");
}
if (maryHeader.getType() != MaryHeader.DIRECTED_GRAPH) {
if (maryHeader.getType() == MaryHeader.CARTS) {
buffInStream.reset();
return new MaryCARTReader().loadFromStream(buffInStream);
} else {
throw new IOException("Not a directed graph file");
}
}
// Read properties
short propDataLength = raf.readShort();
Properties props;
if (propDataLength == 0) {
props = null;
} else {
byte[] propsData = new byte[propDataLength];
raf.readFully(propsData);
ByteArrayInputStream bais = new ByteArrayInputStream(propsData);
props = new Properties();
props.load(bais);
bais.close();
}
// Read the feature definition
FeatureDefinition featureDefinition = new FeatureDefinition(raf);
// read the decision nodes
int numDecNodes = raf.readInt(); // number of decision nodes
// First we need to read all nodes into memory, then we can link them properly
// in terms of parent/child.
DecisionNode[] dns = new DecisionNode[numDecNodes];
int[][] childIndexes = new int[numDecNodes][];
for (int i = 0; i < numDecNodes; i++) {
// read one decision node
int featureNameIndex = raf.readInt();
int nodeTypeNr = raf.readInt();
DecisionNode.Type nodeType = DecisionNode.Type.values()[nodeTypeNr];
int numChildren = 2; // for binary nodes
switch (nodeType) {
case BinaryByteDecisionNode:
int criterion = raf.readInt();
dns[i] =
new DecisionNode.BinaryByteDecisionNode(
featureNameIndex, (byte) criterion, featureDefinition);
break;
case BinaryShortDecisionNode:
criterion = raf.readInt();
dns[i] =
new DecisionNode.BinaryShortDecisionNode(
featureNameIndex, (short) criterion, featureDefinition);
break;
case BinaryFloatDecisionNode:
float floatCriterion = raf.readFloat();
dns[i] =
new DecisionNode.BinaryFloatDecisionNode(
featureNameIndex, floatCriterion, featureDefinition);
break;
case ByteDecisionNode:
numChildren = raf.readInt();
if (featureDefinition.getNumberOfValues(featureNameIndex) != numChildren) {
throw new IOException(
"Inconsistent cart file: feature "
+ featureDefinition.getFeatureName(featureNameIndex)
+ " should have "
+ featureDefinition.getNumberOfValues(featureNameIndex)
+ " values, but decision node "
+ i
+ " has only "
+ numChildren
+ " child nodes");
}
dns[i] =
new DecisionNode.ByteDecisionNode(featureNameIndex, numChildren, featureDefinition);
break;
case ShortDecisionNode:
numChildren = raf.readInt();
if (featureDefinition.getNumberOfValues(featureNameIndex) != numChildren) {
throw new IOException(
"Inconsistent cart file: feature "
+ featureDefinition.getFeatureName(featureNameIndex)
+ " should have "
+ featureDefinition.getNumberOfValues(featureNameIndex)
+ " values, but decision node "
+ i
+ " has only "
+ numChildren
+ " child nodes");
}
dns[i] =
new DecisionNode.ShortDecisionNode(featureNameIndex, numChildren, featureDefinition);
}
dns[i].setUniqueDecisionNodeId(i + 1);
// now read the children, indexes only:
childIndexes[i] = new int[numChildren];
for (int k = 0; k < numChildren; k++) {
childIndexes[i][k] = raf.readInt();
}
}
// read the leaves
int numLeafNodes = raf.readInt(); // number of leaves, it does not include empty leaves
LeafNode[] lns = new LeafNode[numLeafNodes];
for (int j = 0; j < numLeafNodes; j++) {
// read one leaf node
int leafTypeNr = raf.readInt();
LeafNode.LeafType leafNodeType = LeafNode.LeafType.values()[leafTypeNr];
switch (leafNodeType) {
case IntArrayLeafNode:
int numData = raf.readInt();
int[] data = new int[numData];
for (int d = 0; d < numData; d++) {
data[d] = raf.readInt();
}
lns[j] = new LeafNode.IntArrayLeafNode(data);
break;
case FloatLeafNode:
float stddev = raf.readFloat();
float mean = raf.readFloat();
lns[j] = new LeafNode.FloatLeafNode(new float[] {stddev, mean});
break;
case IntAndFloatArrayLeafNode:
case StringAndFloatLeafNode:
int numPairs = raf.readInt();
int[] ints = new int[numPairs];
float[] floats = new float[numPairs];
for (int d = 0; d < numPairs; d++) {
ints[d] = raf.readInt();
floats[d] = raf.readFloat();
}
if (leafNodeType == LeafNode.LeafType.IntAndFloatArrayLeafNode)
lns[j] = new LeafNode.IntAndFloatArrayLeafNode(ints, floats);
else lns[j] = new LeafNode.StringAndFloatLeafNode(ints, floats);
break;
case FeatureVectorLeafNode:
throw new IllegalArgumentException(
"Reading feature vector leaf nodes is not yet implemented");
case PdfLeafNode:
throw new IllegalArgumentException("Reading pdf leaf nodes is not yet implemented");
}
lns[j].setUniqueLeafId(j + 1);
}
// Graph nodes
int numDirectedGraphNodes = raf.readInt();
DirectedGraphNode[] graphNodes = new DirectedGraphNode[numDirectedGraphNodes];
int[] dgnLeafIndices = new int[numDirectedGraphNodes];
int[] dgnDecIndices = new int[numDirectedGraphNodes];
for (int g = 0; g < numDirectedGraphNodes; g++) {
graphNodes[g] = new DirectedGraphNode(null, null);
graphNodes[g].setUniqueGraphNodeID(g + 1);
dgnLeafIndices[g] = raf.readInt();
dgnDecIndices[g] = raf.readInt();
}
// Now, link up the decision nodes with their daughters
for (int i = 0; i < numDecNodes; i++) {
// System.out.print(dns[i]+" "+dns[i].getFeatureName()+" ");
for (int k = 0; k < childIndexes[i].length; k++) {
Node child = childIndexToNode(childIndexes[i][k], dns, lns, graphNodes);
dns[i].addDaughter(child);
// System.out.print(" "+dns[i].getDaughter(k));
}
// System.out.println();
}
// And link up directed graph nodes
for (int g = 0; g < numDirectedGraphNodes; g++) {
Node leaf = childIndexToNode(dgnLeafIndices[g], dns, lns, graphNodes);
graphNodes[g].setLeafNode(leaf);
Node dec = childIndexToNode(dgnDecIndices[g], dns, lns, graphNodes);
if (dec != null && !dec.isDecisionNode())
throw new IllegalArgumentException("Only decision nodes allowed, read " + dec.getClass());
graphNodes[g].setDecisionNode((DecisionNode) dec);
// System.out.println("Graph node "+(g+1)+", leaf: "+Integer.toHexString(dgnLeafIndices[g])+",
// "+leaf+" -- dec: "+Integer.toHexString(dgnDecIndices[g])+", "+dec);
}
Node rootNode;
if (graphNodes.length > 0) {
rootNode = graphNodes[0];
} else if (dns.length > 0) {
rootNode = dns[0];
// CART behaviour, not sure if this is needed:
// Now count all data once, so that getNumberOfData()
// will return the correct figure.
((DecisionNode) rootNode).countData();
} else if (lns.length > 0) {
rootNode = lns[0]; // single-leaf tree...
} else {
rootNode = null;
}
// set the rootNode as the rootNode of cart
return new DirectedGraph(rootNode, featureDefinition, props);
}
private void printDirectedGraphNodes(DirectedGraph graph, DataOutput out, PrintWriter pw)
throws IOException {
for (DirectedGraphNode g : graph.getDirectedGraphNodes()) {
int id = g.getUniqueGraphNodeID();
if (id == 0) continue; // empty node, do not write
Node leaf = g.getLeafNode();
int leafID = 0;
int leafNodeType = 0;
if (leaf != null) {
if (leaf instanceof LeafNode) {
leafID = ((LeafNode) leaf).getUniqueLeafId();
leafNodeType = DirectedGraphReader.LEAFNODE;
} else if (leaf instanceof DirectedGraphNode) {
leafID = ((DirectedGraphNode) leaf).getUniqueGraphNodeID();
leafNodeType = DirectedGraphReader.DIRECTEDGRAPHNODE;
} else {
throw new IllegalArgumentException("Unexpected leaf type: " + leaf.getClass());
}
}
DecisionNode d = g.getDecisionNode();
int decID = d != null ? d.getUniqueDecisionNodeId() : 0;
if (out != null) {
int outLeafId = leafID == 0 ? 0 : leafID | (leafNodeType << 30);
out.writeInt(outLeafId);
int outDecId = decID == 0 ? 0 : decID | (DirectedGraphReader.DECISIONNODE << 30);
out.writeInt(outDecId);
}
if (pw != null) {
pw.print("DGN" + id);
if (leafID == 0) {
pw.print(" 0");
} else if (leaf.isLeafNode()) {
pw.print(" id" + leafID);
} else {
assert leaf.isDirectedGraphNode();
pw.print(" DGN" + leafID);
}
if (decID == 0) pw.print(" 0");
else pw.print(" -" + decID);
pw.println();
}
}
}
private void printDecisionNodes(DirectedGraph graph, DataOutput out, PrintWriter pw)
throws IOException {
for (DecisionNode decNode : graph.getDecisionNodes()) {
int id = decNode.getUniqueDecisionNodeId();
String nodeDefinition = decNode.getNodeDefinition();
int featureIndex = decNode.getFeatureIndex();
DecisionNode.Type nodeType = decNode.getDecisionNodeType();
if (out != null) {
// dump in binary form to output
out.writeInt(featureIndex);
out.writeInt(nodeType.ordinal());
// Now, questionValue, which depends on nodeType
switch (nodeType) {
case BinaryByteDecisionNode:
out.writeInt(((BinaryByteDecisionNode) decNode).getCriterionValueAsByte());
assert decNode.getNumberOfDaugthers() == 2;
break;
case BinaryShortDecisionNode:
out.writeInt(((BinaryShortDecisionNode) decNode).getCriterionValueAsShort());
assert decNode.getNumberOfDaugthers() == 2;
break;
case BinaryFloatDecisionNode:
out.writeFloat(((BinaryFloatDecisionNode) decNode).getCriterionValueAsFloat());
assert decNode.getNumberOfDaugthers() == 2;
break;
case ByteDecisionNode:
case ShortDecisionNode:
out.writeInt(decNode.getNumberOfDaugthers());
}
// The child nodes
for (int i = 0, n = decNode.getNumberOfDaugthers(); i < n; i++) {
Node daughter = decNode.getDaughter(i);
if (daughter == null) {
out.writeInt(0);
} else if (daughter.isDecisionNode()) {
int daughterID = ((DecisionNode) daughter).getUniqueDecisionNodeId();
// Mark as decision node:
daughterID |= DirectedGraphReader.DECISIONNODE << 30;
out.writeInt(daughterID);
} else if (daughter.isLeafNode()) {
int daughterID = ((LeafNode) daughter).getUniqueLeafId();
// Mark as leaf node:
if (daughterID != 0) daughterID |= DirectedGraphReader.LEAFNODE << 30;
out.writeInt(daughterID);
} else if (daughter.isDirectedGraphNode()) {
int daughterID = ((DirectedGraphNode) daughter).getUniqueGraphNodeID();
// Mark as directed graph node:
if (daughterID != 0) daughterID |= DirectedGraphReader.DIRECTEDGRAPHNODE << 30;
out.writeInt(daughterID);
}
}
}
if (pw != null) {
// dump to print writer
StringBuilder strNode = new StringBuilder("-" + id + " " + nodeDefinition);
for (int i = 0, n = decNode.getNumberOfDaugthers(); i < n; i++) {
strNode.append(" ");
Node daughter = decNode.getDaughter(i);
if (daughter == null) {
strNode.append("0");
} else if (daughter.isDecisionNode()) {
int daughterID = ((DecisionNode) daughter).getUniqueDecisionNodeId();
strNode.append("-").append(daughterID);
out.writeInt(daughterID);
} else if (daughter.isLeafNode()) {
int daughterID = ((LeafNode) daughter).getUniqueLeafId();
if (daughterID == 0) strNode.append("0");
else strNode.append("id").append(daughterID);
} else if (daughter.isDirectedGraphNode()) {
int daughterID = ((DirectedGraphNode) daughter).getUniqueGraphNodeID();
if (daughterID == 0) strNode.append("0");
else strNode.append("DGN").append(daughterID);
}
}
pw.println(strNode.toString());
}
}
}
@Override
public boolean compute() throws IOException, MaryConfigurationException {
logger.info("Duration tree trainer started.");
FeatureFileReader featureFile = FeatureFileReader.getFeatureFileReader(getProp(FEATUREFILE));
UnitFileReader unitFile = new UnitFileReader(getProp(UNITFILE));
FeatureVector[] allFeatureVectors = featureFile.getFeatureVectors();
int maxData = Integer.parseInt(getProp(MAXDATA));
if (maxData == 0) maxData = allFeatureVectors.length;
FeatureVector[] featureVectors = new FeatureVector[Math.min(maxData, allFeatureVectors.length)];
System.arraycopy(allFeatureVectors, 0, featureVectors, 0, featureVectors.length);
logger.debug(
"Total of "
+ allFeatureVectors.length
+ " feature vectors -- will use "
+ featureVectors.length);
AgglomerativeClusterer clusterer =
new AgglomerativeClusterer(
featureVectors,
featureFile.getFeatureDefinition(),
null,
new DurationDistanceMeasure(unitFile),
Float.parseFloat(getProp(PROPORTIONTESTDATA)));
DirectedGraphWriter writer = new DirectedGraphWriter();
DirectedGraph graph;
int iteration = 0;
do {
graph = clusterer.cluster();
iteration++;
if (graph != null) {
writer.saveGraph(graph, getProp(DURTREE) + ".level" + iteration);
}
} while (clusterer.canClusterMore());
if (graph == null) {
return false;
}
// Now replace each leaf with a FloatLeafNode containing mean and stddev
for (LeafNode leaf : graph.getLeafNodes()) {
FeatureVectorLeafNode fvLeaf = (FeatureVectorLeafNode) leaf;
FeatureVector[] fvs = fvLeaf.getFeatureVectors();
double[] dur = new double[fvs.length];
for (int i = 0; i < fvs.length; i++) {
dur[i] =
unitFile.getUnit(fvs[i].getUnitIndex()).duration / (float) unitFile.getSampleRate();
}
double mean = MathUtils.mean(dur);
double stddev = MathUtils.standardDeviation(dur, mean);
FloatLeafNode floatLeaf = new FloatLeafNode(new float[] {(float) stddev, (float) mean});
Node mother = fvLeaf.getMother();
assert mother != null;
if (mother.isDecisionNode()) {
((DecisionNode) mother).replaceDaughter(floatLeaf, fvLeaf.getNodeIndex());
} else {
assert mother.isDirectedGraphNode();
assert ((DirectedGraphNode) mother).getLeafNode() == fvLeaf;
((DirectedGraphNode) mother).setLeafNode(floatLeaf);
}
}
writer.saveGraph(graph, getProp(DURTREE));
return true;
}