Author: scooter
Date: 2011-08-18 20:51:44 -0700 (Thu, 18 Aug 2011)
New Revision: 26608
Added:
csplugins/trunk/ucsf/scooter/clusterMaker/src/clusterMaker/algorithms/attributeClusterers/FeatureVector/
csplugins/trunk/ucsf/scooter/clusterMaker/src/clusterMaker/algorithms/attributeClusterers/FeatureVector/FeatureVectorCluster.java
Removed:
csplugins/trunk/ucsf/scooter/clusterMaker/src/clusterMaker/algorithms/FeatureVector/
csplugins/trunk/ucsf/scooter/clusterMaker/src/clusterMaker/algorithms/attributeClusterers/FeatureVector/FeatureVectorCluster.java
Log:
Moved FeatureVector into attributeClusterers
Deleted:
csplugins/trunk/ucsf/scooter/clusterMaker/src/clusterMaker/algorithms/attributeClusterers/FeatureVector/FeatureVectorCluster.java
===================================================================
---
csplugins/trunk/ucsf/scooter/clusterMaker/src/clusterMaker/algorithms/FeatureVector/FeatureVectorCluster.java
2011-08-18 23:23:57 UTC (rev 26606)
+++
csplugins/trunk/ucsf/scooter/clusterMaker/src/clusterMaker/algorithms/attributeClusterers/FeatureVector/FeatureVectorCluster.java
2011-08-19 03:51:44 UTC (rev 26608)
@@ -1,415 +0,0 @@
-/* vim: set ts=2: */
-/**
- * Copyright (c) 2008 The Regents of the University of California.
- * All rights reserved.
- *
- * Redistribution and use in source and binary forms, with or without
- * modification, are permitted provided that the following conditions
- * are met:
- * 1. Redistributions of source code must retain the above copyright
- * notice, this list of conditions, and the following disclaimer.
- * 2. Redistributions in binary form must reproduce the above
- * copyright notice, this list of conditions, and the following
- * disclaimer in the documentation and/or other materials provided
- * with the distribution.
- * 3. Redistributions must acknowledge that this software was
- * originally developed by the UCSF Computer Graphics Laboratory
- * under support by the NIH National Center for Research Resources,
- * grant P41-RR01081.
- *
- * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDER "AS IS" AND ANY
- * EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
- * IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
- * PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE REGENTS BE LIABLE
- * FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
- * CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT
- * OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR
- * BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY,
- * WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE
- * OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE,
- * EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
- *
- */
-package clusterMaker.algorithms.FeatureVector;
-
-import java.awt.GridLayout;
-import java.util.ArrayList;
-import java.util.Arrays;
-import java.util.Comparator;
-import java.util.HashMap;
-import java.util.List;
-import java.util.Map;
-import javax.swing.JPanel;
-
-// Cytoscape imports
-import cytoscape.CyEdge;
-import cytoscape.CyNetwork;
-import cytoscape.CyNode;
-import cytoscape.Cytoscape;
-import cytoscape.data.CyAttributes;
-import cytoscape.data.Semantics;
-import cytoscape.layout.Tunable;
-import cytoscape.layout.TunableListener;
-import cytoscape.logger.CyLogger;
-import cytoscape.task.TaskMonitor;
-
-import clusterMaker.algorithms.AbstractClusterAlgorithm;
-import clusterMaker.algorithms.ClusterAlgorithm;
-import clusterMaker.algorithms.hierarchical.DistanceMetric;
-import clusterMaker.algorithms.hierarchical.EisenCluster;
-import clusterMaker.algorithms.hierarchical.Matrix;
-import clusterMaker.ui.ClusterViz;
-
-// clusterMaker imports
-
-public class FeatureVectorCluster extends AbstractClusterAlgorithm implements
TunableListener {
- /**
- * Linkage types
- */
- DistanceMetric[] distanceTypes = { DistanceMetric.EUCLIDEAN,
- DistanceMetric.CITYBLOCK,
- DistanceMetric.CORRELATION,
- DistanceMetric.ABS_CORRELATION,
-
DistanceMetric.UNCENTERED_CORRELATION,
-
DistanceMetric.ABS_UNCENTERED_CORRELATION,
- DistanceMetric.SPEARMANS_RANK,
- DistanceMetric.KENDALLS_TAU,
- DistanceMetric.VALUE_IS_CORRELATION
};
- String[] attributeArray = new String[1];
-
- DistanceMetric distanceMetric = DistanceMetric.EUCLIDEAN;
- boolean ignoreMissing = true;
- boolean selectedOnly = false;
- boolean zeroMissing = false;
- boolean createEdges = false;
- double edgeCutoff = 0.5;
- String dataAttributes = null;
- String edgeAttribute = null;
- TaskMonitor monitor = null;
- CyLogger logger = null;
- final static String interaction = "distance";
-
- public FeatureVectorCluster() {
- super();
- logger = CyLogger.getLogger(FeatureVectorCluster.class);
- initializeProperties();
- }
-
- public String getShortName() {return "featurevector";};
- public String getName() {return "Create Edges from Node Attributes";};
-
- public JPanel getSettingsPanel() {
- // Everytime we ask for the panel, we want to update our
attributes
- Tunable attributeTunable =
clusterProperties.get("attributeList");
- attributeArray = EisenCluster.getNodeAttributes();
- attributeTunable.setLowerBound((Object)attributeArray);
-
- return clusterProperties.getTunablePanel();
- }
-
- public ClusterViz getVisualizer() {
- return null;
- }
-
- public void initializeProperties() {
- super.initializeProperties();
-
- /**
- * Tuning values
- */
-
- // The distance metric to use
- clusterProperties.add(new Tunable("dMetric",
- "Distance Metric",
- Tunable.LIST, new Integer(0),
- (Object)distanceTypes,
(Object)null, 0));
-
- clusterProperties.add(new Tunable("attributeListGroup",
- "Source for array data",
- Tunable.GROUP, new
Integer(1)));
-
- // The attribute to use to get the weights
- attributeArray = EisenCluster.getNodeAttributes();
- clusterProperties.add(new Tunable("attributeList",
- "Array sources",
- Tunable.LIST, "",
- (Object)attributeArray,
(Object)null, Tunable.MULTISELECT));
-
- clusterProperties.add(new Tunable("parametersGroup",
- "Clustering Parameters",
- Tunable.GROUP, new
Integer(5)));
-
- // Whether or not to only cluster selected nodes/edges
- clusterProperties.add(new Tunable("selectedOnly",
- "Only use selected
nodes/edges for cluster",
- Tunable.BOOLEAN, new
Boolean(false)));
-
- // For expression data, we might want to exclude missing data
- clusterProperties.add(new Tunable("ignoreMissing",
- "Ignore nodes/edges with no
data",
- Tunable.BOOLEAN, new
Boolean(true)));
-
- // Whether to create a new network or add values to existing
network
- Tunable t = new Tunable("createEdges",
- "Create edges if they don't exist",
- Tunable.BOOLEAN, new Boolean(false));
- t.addTunableValueListener(this);
- clusterProperties.add(t);
-
- // If we're creating edges, do we have a cut-off value?
- t = new Tunable("edgeCutoff", "Only create edges if nodes are
closer than this",
- Tunable.DOUBLE, new Double(0.5));
- t.setImmutable(true);
- clusterProperties.add(t);
-
- clusterProperties.add(new Tunable("advancedParametersGroup",
- "Advanced Parameters",
- Tunable.GROUP, new
Integer(3),
- new Boolean(true), null,
- Tunable.COLLAPSABLE));
-
- // Edge attribute to use for distances
- clusterProperties.add(new Tunable("edgeAttribute",
- "Edge attribute to use for
distance values",
- Tunable.STRING,
"FeatureDistance"));
-
- // How to handle missing data
- clusterProperties.add(new Tunable("zeroMissing",
- "Set missing data to zero
(not common)",
- Tunable.BOOLEAN, new
Boolean(false)));
-
- clusterProperties.initializeProperties();
- updateSettings(true);
- }
-
- public void updateSettings() {
- updateSettings(false);
- }
-
- public void tunableChanged(Tunable tunable) {
- if (tunable.getName().equals("createEdges")) {
- createEdges = ((Boolean)
tunable.getValue()).booleanValue();
- Tunable t = clusterProperties.get("edgeCutoff");
- if (createEdges)
- t.setImmutable(false);
- else
- t.setImmutable(true);
- }
- }
-
- public void updateSettings(boolean force) {
- clusterProperties.updateValues();
- super.updateSettings(force);
-
- Tunable t = clusterProperties.get("dMetric");
- if ((t != null) && (t.valueChanged() || force))
- distanceMetric = distanceTypes[((Integer)
t.getValue()).intValue()];
-
- t = clusterProperties.get("selectedOnly");
- if ((t != null) && (t.valueChanged() || force))
- selectedOnly = ((Boolean) t.getValue()).booleanValue();
-
- t = clusterProperties.get("attributeList");
- if ((t != null) && (t.valueChanged() || force)) {
- dataAttributes = (String) t.getValue();
- }
-
- t = clusterProperties.get("zeroMissing");
- if ((t != null) && (t.valueChanged() || force))
- zeroMissing = ((Boolean) t.getValue()).booleanValue();
-
- t = clusterProperties.get("edgeAttribute");
- if ((t != null) && (t.valueChanged() || force))
- edgeAttribute = (String) t.getValue();
-
- t = clusterProperties.get("createEdges");
- if ((t != null) && (t.valueChanged() || force))
- createEdges = ((Boolean) t.getValue()).booleanValue();
-
- t = clusterProperties.get("edgeCutoff");
- if ((t != null) && (t.valueChanged() || force))
- edgeCutoff = ((Double) t.getValue()).doubleValue();
-
- }
-
- public void doCluster(TaskMonitor monitor) {
- this.monitor = monitor;
- CyNetwork network = Cytoscape.getCurrentNetwork();
-
- // Sanity check all of our settings
- if (dataAttributes == null || dataAttributes.length() == 0) {
- if (monitor != null) {
- logger.warning("Must have an attribute list to
use for cluster weighting");
- monitor.setException(null, "Error: no attribute
list selected");
- } else
- logger.error("Must have an attribute list to
use for cluster weighting");
- return;
- }
-
- // Get our attributes we're going to use for the cluster
- String attributeArray[] = getAttributeArray(dataAttributes);
- // To make debugging easier, sort the attribute array
- Arrays.sort(attributeArray);
-
- if (monitor != null) {
- monitor.setPercentCompleted(0);
- monitor.setStatus("Initializaing");
- }
-
- // Create the matrix
- Matrix matrix = new Matrix(attributeArray, false,
ignoreMissing, selectedOnly);
-
- if (monitor != null) {
- monitor.setPercentCompleted(1);
- monitor.setStatus("Calculating edge distances");
- if (canceled) return;
- }
-
- // Create a weight vector of all ones (we don't use individual
weighting, yet)
- matrix.setUniformWeights();
-
- // Handle special cases
- if (zeroMissing)
- matrix.setMissingToZero();
-
- int nNodes = matrix.nRows();
-
- CyAttributes edgeAttributes = Cytoscape.getEdgeAttributes();
-
- // For each node, get the distance to all other nodes
- double maxdistance = 0.0;
- double mindistance = 0.0;
-
- double distanceMatrix[][] = new double[nNodes][nNodes];
- for (int i = 0; i < nNodes; i++) {
- for (int j = i+1; j < nNodes; j++) {
- double distance =
distanceMetric.getMetric(matrix, matrix, matrix.getWeights(), i, j);
- maxdistance = Math.max(maxdistance, distance);
- mindistance = Math.min(mindistance, distance);
- distanceMatrix[i][j] = distance;
- }
- if (monitor != null) {
- if (canceled) return;
- monitor.setPercentCompleted((int)(25 *
(double)i/(double)nNodes));
- }
- }
-
- if (monitor != null) {
- monitor.setStatus("Assigning values to edges");
- }
-
- int[] nodeArray = new int[2];
- Map<CyEdge, Double> edgeList = new HashMap<CyEdge, Double>();
- double scale = maxdistance - mindistance;
-
- /* Performance tuning -- what's taking all the time!
- long time = System.currentTimeMillis();
- long nodeFetchTime = 0L;
- long edgeFetchTime = 0L;
- long edgeCreateTime = 0L;
- long networkAddTime = 0L;
- long setAttributeTime = 0L;
- int newEdges = 0;
- */
-
- for (int i = 0; i < nNodes; i++) {
- for (int j = i+1; j < nNodes; j++) {
- // time = System.currentTimeMillis();
- double distance = distanceMatrix[i][j]/scale;
- CyNode source =
Cytoscape.getCyNode(matrix.getRowLabel(i));
- CyNode target =
Cytoscape.getCyNode(matrix.getRowLabel(j));
- nodeArray[0] = source.getRootGraphIndex();
- nodeArray[1] = target.getRootGraphIndex();
-
- // nodeFetchTime +=
System.currentTimeMillis()-time;
-
- if (createEdges == true && distance >
edgeCutoff)
- continue;
-
- // time = System.currentTimeMillis();
-
- CyEdge edge;
- int[] edgeArray =
network.getConnectingEdgeIndicesArray(nodeArray);
- // edgeFetchTime +=
System.currentTimeMillis()-time;
- // time = System.currentTimeMillis();
-
- if ((edgeArray == null || edgeArray.length ==
0) && createEdges == true) {
- edge = myCreateEdge(source, target,
edgeAttributes);
-
- // edgeCreateTime +=
System.currentTimeMillis()-time;
- // System.out.println("Creating edge
between "+source+" and "+target);
- if (edge != null) {
- // System.out.println("Adding
edge "+edge.getIdentifier()+" to network");
- // time =
System.currentTimeMillis();
- network.addEdge(edge);
- // networkAddTime +=
System.currentTimeMillis()-time;
- }
- } else if (edgeArray == null ||
edgeArray.length == 0) {
- continue;
- } else {
- edge =
(CyEdge)network.getEdge(edgeArray[0]);
- // edgeFetchTime +=
System.currentTimeMillis()-time;
- }
-
- if (edge == null) continue;
- // time = System.currentTimeMillis();
-
edgeAttributes.setAttribute(edge.getIdentifier(), edgeAttribute, distance);
- // setAttributeTime +=
System.currentTimeMillis()-time;
- }
- if (monitor != null) {
- if (canceled) return;
- monitor.setPercentCompleted((int)(25 + (75 *
(double)i/(double)nNodes)));
- }
- }
-
- /*
- System.out.println("Created "+newEdges+" edges");
- System.out.println("Edge creation time: "+edgeCreateTime+"ms");
- System.out.println("Network add time: "+networkAddTime+"ms");
- System.out.println("Edge fetch time: "+edgeFetchTime+"ms");
- System.out.println("Node fetch time: "+nodeFetchTime+"ms");
- System.out.println("Set attribute time:
"+setAttributeTime+"ms");
- */
-
- if (monitor != null)
- monitor.setStatus("Complete");
-
- // Tell any listeners that we're done
- pcs.firePropertyChange(ClusterAlgorithm.CLUSTER_COMPUTED, null,
this);
- }
-
- public boolean isAvailable() {
- // return EisenCluster.isAvailable(getShortName());
- return false;
- }
-
- /**
- * Cytoscape doesn't provide us with an easy way to create an edge
without searching
- * for it first. Since we've already searched for it, we are
absolutely certain
- * by this point that the edge doesn't exist, so we can save
significant time by
- * just going ahead and creating it.
- */
- private CyEdge myCreateEdge(CyNode source, CyNode target, CyAttributes
edgeAttributes) {
- int rootEdge = Cytoscape.getRootGraph().createEdge(source,
target);
- CyEdge edge = (CyEdge)
Cytoscape.getRootGraph().getEdge(rootEdge);
-
- // create the edge id
- String edge_name =
CyEdge.createIdentifier(source.getIdentifier(),
- interaction,
-
target.getIdentifier());
- edge.setIdentifier(edge_name);
-
- edgeAttributes.setAttribute(edge_name, Semantics.INTERACTION,
interaction);
- edgeAttributes.setAttribute(edge_name,
Semantics.CANONICAL_NAME, edge_name);
- return edge;
- }
-
- private String[] getAttributeArray(String dataAttributes) {
- String indices[] = dataAttributes.split(",");
- String selectedAttributes[] = new String[indices.length];
- for (int i = 0; i < indices.length; i++) {
- selectedAttributes[i] =
attributeArray[Integer.parseInt(indices[i])];
- }
- return selectedAttributes;
- }
-}
Copied:
csplugins/trunk/ucsf/scooter/clusterMaker/src/clusterMaker/algorithms/attributeClusterers/FeatureVector/FeatureVectorCluster.java
(from rev 26607,
csplugins/trunk/ucsf/scooter/clusterMaker/src/clusterMaker/algorithms/FeatureVector/FeatureVectorCluster.java)
===================================================================
---
csplugins/trunk/ucsf/scooter/clusterMaker/src/clusterMaker/algorithms/attributeClusterers/FeatureVector/FeatureVectorCluster.java
(rev 0)
+++
csplugins/trunk/ucsf/scooter/clusterMaker/src/clusterMaker/algorithms/attributeClusterers/FeatureVector/FeatureVectorCluster.java
2011-08-19 03:51:44 UTC (rev 26608)
@@ -0,0 +1,403 @@
+/* vim: set ts=2: */
+/**
+ * Copyright (c) 2008 The Regents of the University of California.
+ * All rights reserved.
+ *
+ * Redistribution and use in source and binary forms, with or without
+ * modification, are permitted provided that the following conditions
+ * are met:
+ * 1. Redistributions of source code must retain the above copyright
+ * notice, this list of conditions, and the following disclaimer.
+ * 2. Redistributions in binary form must reproduce the above
+ * copyright notice, this list of conditions, and the following
+ * disclaimer in the documentation and/or other materials provided
+ * with the distribution.
+ * 3. Redistributions must acknowledge that this software was
+ * originally developed by the UCSF Computer Graphics Laboratory
+ * under support by the NIH National Center for Research Resources,
+ * grant P41-RR01081.
+ *
+ * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDER "AS IS" AND ANY
+ * EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
+ * IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
+ * PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE REGENTS BE LIABLE
+ * FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
+ * CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT
+ * OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR
+ * BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY,
+ * WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE
+ * OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE,
+ * EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+ *
+ */
+package clusterMaker.algorithms.attributeClusterers.FeatureVector;
+
+import java.awt.GridLayout;
+import java.util.ArrayList;
+import java.util.Arrays;
+import java.util.Comparator;
+import java.util.HashMap;
+import java.util.List;
+import java.util.Map;
+import javax.swing.JPanel;
+
+// Cytoscape imports
+import cytoscape.CyEdge;
+import cytoscape.CyNetwork;
+import cytoscape.CyNode;
+import cytoscape.Cytoscape;
+import cytoscape.data.CyAttributes;
+import cytoscape.data.Semantics;
+import cytoscape.layout.Tunable;
+import cytoscape.layout.TunableListener;
+import cytoscape.logger.CyLogger;
+import cytoscape.task.TaskMonitor;
+
+import clusterMaker.algorithms.AbstractClusterAlgorithm;
+import clusterMaker.algorithms.ClusterAlgorithm;
+import
clusterMaker.algorithms.attributeClusterers.AbstractAttributeClusterAlgorithm;
+import clusterMaker.algorithms.attributeClusterers.DistanceMetric;
+import clusterMaker.algorithms.attributeClusterers.Matrix;
+import clusterMaker.ui.ClusterViz;
+
+// clusterMaker imports
+
+public class FeatureVectorCluster extends AbstractClusterAlgorithm implements
TunableListener {
+ String[] attributeArray = new String[1];
+
+ DistanceMetric distanceMetric = DistanceMetric.EUCLIDEAN;
+ boolean ignoreMissing = true;
+ boolean selectedOnly = false;
+ boolean zeroMissing = false;
+ boolean createEdges = false;
+ double edgeCutoff = 0.5;
+ String dataAttributes = null;
+ String edgeAttribute = null;
+ TaskMonitor monitor = null;
+ CyLogger logger = null;
+ final static String interaction = "distance";
+
+ public FeatureVectorCluster() {
+ super();
+ logger = CyLogger.getLogger(FeatureVectorCluster.class);
+ initializeProperties();
+ }
+
+ public String getShortName() {return "featurevector";};
+ public String getName() {return "Create Edges from Node Attributes";};
+
+ public JPanel getSettingsPanel() {
+ // Everytime we ask for the panel, we want to update our
attributes
+ Tunable attributeTunable =
clusterProperties.get("attributeList");
+ attributeArray =
AbstractAttributeClusterAlgorithm.getNodeAttributes();
+ attributeTunable.setLowerBound((Object)attributeArray);
+
+ return clusterProperties.getTunablePanel();
+ }
+
+ public ClusterViz getVisualizer() {
+ return null;
+ }
+
+ public void initializeProperties() {
+ super.initializeProperties();
+
+ /**
+ * Tuning values
+ */
+
+ // The distance metric to use
+ clusterProperties.add(new Tunable("dMetric",
+ "Distance Metric",
+ Tunable.LIST, new Integer(0),
+ (Object)Matrix.distanceTypes,
(Object)null, 0));
+
+ clusterProperties.add(new Tunable("attributeListGroup",
+ "Source for array data",
+ Tunable.GROUP, new
Integer(1)));
+
+ // The attribute to use to get the weights
+ attributeArray =
AbstractAttributeClusterAlgorithm.getNodeAttributes();
+ clusterProperties.add(new Tunable("attributeList",
+ "Array sources",
+ Tunable.LIST, "",
+ (Object)attributeArray,
(Object)null, Tunable.MULTISELECT));
+
+ clusterProperties.add(new Tunable("parametersGroup",
+ "Clustering Parameters",
+ Tunable.GROUP, new
Integer(5)));
+
+ // Whether or not to only cluster selected nodes/edges
+ clusterProperties.add(new Tunable("selectedOnly",
+ "Only use selected
nodes/edges for cluster",
+ Tunable.BOOLEAN, new
Boolean(false)));
+
+ // For expression data, we might want to exclude missing data
+ clusterProperties.add(new Tunable("ignoreMissing",
+ "Ignore nodes/edges with no
data",
+ Tunable.BOOLEAN, new
Boolean(true)));
+
+ // Whether to create a new network or add values to existing
network
+ Tunable t = new Tunable("createEdges",
+ "Create edges if they don't exist",
+ Tunable.BOOLEAN, new Boolean(false));
+ t.addTunableValueListener(this);
+ clusterProperties.add(t);
+
+ // If we're creating edges, do we have a cut-off value?
+ t = new Tunable("edgeCutoff", "Only create edges if nodes are
closer than this",
+ Tunable.DOUBLE, new Double(0.5));
+ t.setImmutable(true);
+ clusterProperties.add(t);
+
+ clusterProperties.add(new Tunable("advancedParametersGroup",
+ "Advanced Parameters",
+ Tunable.GROUP, new
Integer(3),
+ new Boolean(true), null,
+ Tunable.COLLAPSABLE));
+
+ // Edge attribute to use for distances
+ clusterProperties.add(new Tunable("edgeAttribute",
+ "Edge attribute to use for
distance values",
+ Tunable.STRING,
"FeatureDistance"));
+
+ // How to handle missing data
+ clusterProperties.add(new Tunable("zeroMissing",
+ "Set missing data to zero
(not common)",
+ Tunable.BOOLEAN, new
Boolean(false)));
+
+ clusterProperties.initializeProperties();
+ updateSettings(true);
+ }
+
+ public void updateSettings() {
+ updateSettings(false);
+ }
+
+ public void tunableChanged(Tunable tunable) {
+ if (tunable.getName().equals("createEdges")) {
+ createEdges = ((Boolean)
tunable.getValue()).booleanValue();
+ Tunable t = clusterProperties.get("edgeCutoff");
+ if (createEdges)
+ t.setImmutable(false);
+ else
+ t.setImmutable(true);
+ }
+ }
+
+ public void updateSettings(boolean force) {
+ clusterProperties.updateValues();
+ super.updateSettings(force);
+
+ Tunable t = clusterProperties.get("dMetric");
+ if ((t != null) && (t.valueChanged() || force))
+ distanceMetric = Matrix.distanceTypes[((Integer)
t.getValue()).intValue()];
+
+ t = clusterProperties.get("selectedOnly");
+ if ((t != null) && (t.valueChanged() || force))
+ selectedOnly = ((Boolean) t.getValue()).booleanValue();
+
+ t = clusterProperties.get("attributeList");
+ if ((t != null) && (t.valueChanged() || force)) {
+ dataAttributes = (String) t.getValue();
+ }
+
+ t = clusterProperties.get("zeroMissing");
+ if ((t != null) && (t.valueChanged() || force))
+ zeroMissing = ((Boolean) t.getValue()).booleanValue();
+
+ t = clusterProperties.get("edgeAttribute");
+ if ((t != null) && (t.valueChanged() || force))
+ edgeAttribute = (String) t.getValue();
+
+ t = clusterProperties.get("createEdges");
+ if ((t != null) && (t.valueChanged() || force))
+ createEdges = ((Boolean) t.getValue()).booleanValue();
+
+ t = clusterProperties.get("edgeCutoff");
+ if ((t != null) && (t.valueChanged() || force))
+ edgeCutoff = ((Double) t.getValue()).doubleValue();
+
+ }
+
+ public void doCluster(TaskMonitor monitor) {
+ this.monitor = monitor;
+ CyNetwork network = Cytoscape.getCurrentNetwork();
+
+ // Sanity check all of our settings
+ if (dataAttributes == null || dataAttributes.length() == 0) {
+ if (monitor != null) {
+ logger.warning("Must have an attribute list to
use for cluster weighting");
+ monitor.setException(null, "Error: no attribute
list selected");
+ } else
+ logger.error("Must have an attribute list to
use for cluster weighting");
+ return;
+ }
+
+ // Get our attributes we're going to use for the cluster
+ String attributeArray[] = getAttributeArray(dataAttributes);
+ // To make debugging easier, sort the attribute array
+ Arrays.sort(attributeArray);
+
+ if (monitor != null) {
+ monitor.setPercentCompleted(0);
+ monitor.setStatus("Initializaing");
+ }
+
+ // Create the matrix
+ Matrix matrix = new Matrix(attributeArray, false,
ignoreMissing, selectedOnly);
+
+ if (monitor != null) {
+ monitor.setPercentCompleted(1);
+ monitor.setStatus("Calculating edge distances");
+ if (canceled) return;
+ }
+
+ // Create a weight vector of all ones (we don't use individual
weighting, yet)
+ matrix.setUniformWeights();
+
+ // Handle special cases
+ if (zeroMissing)
+ matrix.setMissingToZero();
+
+ int nNodes = matrix.nRows();
+
+ CyAttributes edgeAttributes = Cytoscape.getEdgeAttributes();
+
+ // For each node, get the distance to all other nodes
+ double maxdistance = 0.0;
+ double mindistance = 0.0;
+
+ double distanceMatrix[][] = new double[nNodes][nNodes];
+ for (int i = 0; i < nNodes; i++) {
+ for (int j = i+1; j < nNodes; j++) {
+ double distance =
distanceMetric.getMetric(matrix, matrix, matrix.getWeights(), i, j);
+ maxdistance = Math.max(maxdistance, distance);
+ mindistance = Math.min(mindistance, distance);
+ distanceMatrix[i][j] = distance;
+ }
+ if (monitor != null) {
+ if (canceled) return;
+ monitor.setPercentCompleted((int)(25 *
(double)i/(double)nNodes));
+ }
+ }
+
+ if (monitor != null) {
+ monitor.setStatus("Assigning values to edges");
+ }
+
+ int[] nodeArray = new int[2];
+ Map<CyEdge, Double> edgeList = new HashMap<CyEdge, Double>();
+ double scale = maxdistance - mindistance;
+
+ /* Performance tuning -- what's taking all the time!
+ long time = System.currentTimeMillis();
+ long nodeFetchTime = 0L;
+ long edgeFetchTime = 0L;
+ long edgeCreateTime = 0L;
+ long networkAddTime = 0L;
+ long setAttributeTime = 0L;
+ int newEdges = 0;
+ */
+
+ for (int i = 0; i < nNodes; i++) {
+ for (int j = i+1; j < nNodes; j++) {
+ // time = System.currentTimeMillis();
+ double distance = distanceMatrix[i][j]/scale;
+ CyNode source =
Cytoscape.getCyNode(matrix.getRowLabel(i));
+ CyNode target =
Cytoscape.getCyNode(matrix.getRowLabel(j));
+ nodeArray[0] = source.getRootGraphIndex();
+ nodeArray[1] = target.getRootGraphIndex();
+
+ // nodeFetchTime +=
System.currentTimeMillis()-time;
+
+ if (createEdges == true && distance >
edgeCutoff)
+ continue;
+
+ // time = System.currentTimeMillis();
+
+ CyEdge edge;
+ int[] edgeArray =
network.getConnectingEdgeIndicesArray(nodeArray);
+ // edgeFetchTime +=
System.currentTimeMillis()-time;
+ // time = System.currentTimeMillis();
+
+ if ((edgeArray == null || edgeArray.length ==
0) && createEdges == true) {
+ edge = myCreateEdge(source, target,
edgeAttributes);
+
+ // edgeCreateTime +=
System.currentTimeMillis()-time;
+ // System.out.println("Creating edge
between "+source+" and "+target);
+ if (edge != null) {
+ // System.out.println("Adding
edge "+edge.getIdentifier()+" to network");
+ // time =
System.currentTimeMillis();
+ network.addEdge(edge);
+ // networkAddTime +=
System.currentTimeMillis()-time;
+ }
+ } else if (edgeArray == null ||
edgeArray.length == 0) {
+ continue;
+ } else {
+ edge =
(CyEdge)network.getEdge(edgeArray[0]);
+ // edgeFetchTime +=
System.currentTimeMillis()-time;
+ }
+
+ if (edge == null) continue;
+ // time = System.currentTimeMillis();
+
edgeAttributes.setAttribute(edge.getIdentifier(), edgeAttribute, distance);
+ // setAttributeTime +=
System.currentTimeMillis()-time;
+ }
+ if (monitor != null) {
+ if (canceled) return;
+ monitor.setPercentCompleted((int)(25 + (75 *
(double)i/(double)nNodes)));
+ }
+ }
+
+ /*
+ System.out.println("Created "+newEdges+" edges");
+ System.out.println("Edge creation time: "+edgeCreateTime+"ms");
+ System.out.println("Network add time: "+networkAddTime+"ms");
+ System.out.println("Edge fetch time: "+edgeFetchTime+"ms");
+ System.out.println("Node fetch time: "+nodeFetchTime+"ms");
+ System.out.println("Set attribute time:
"+setAttributeTime+"ms");
+ */
+
+ if (monitor != null)
+ monitor.setStatus("Complete");
+
+ // Tell any listeners that we're done
+ pcs.firePropertyChange(ClusterAlgorithm.CLUSTER_COMPUTED, null,
this);
+ }
+
+ public boolean isAvailable() {
+ // return EisenCluster.isAvailable(getShortName());
+ return false;
+ }
+
+ /**
+ * Cytoscape doesn't provide us with an easy way to create an edge
without searching
+ * for it first. Since we've already searched for it, we are
absolutely certain
+ * by this point that the edge doesn't exist, so we can save
significant time by
+ * just going ahead and creating it.
+ */
+ private CyEdge myCreateEdge(CyNode source, CyNode target, CyAttributes
edgeAttributes) {
+ int rootEdge = Cytoscape.getRootGraph().createEdge(source,
target);
+ CyEdge edge = (CyEdge)
Cytoscape.getRootGraph().getEdge(rootEdge);
+
+ // create the edge id
+ String edge_name =
CyEdge.createIdentifier(source.getIdentifier(),
+ interaction,
+
target.getIdentifier());
+ edge.setIdentifier(edge_name);
+
+ edgeAttributes.setAttribute(edge_name, Semantics.INTERACTION,
interaction);
+ edgeAttributes.setAttribute(edge_name,
Semantics.CANONICAL_NAME, edge_name);
+ return edge;
+ }
+
+ private String[] getAttributeArray(String dataAttributes) {
+ String indices[] = dataAttributes.split(",");
+ String selectedAttributes[] = new String[indices.length];
+ for (int i = 0; i < indices.length; i++) {
+ selectedAttributes[i] =
attributeArray[Integer.parseInt(indices[i])];
+ }
+ return selectedAttributes;
+ }
+}
--
You received this message because you are subscribed to the Google Groups
"cytoscape-cvs" group.
To post to this group, send email to [email protected].
To unsubscribe from this group, send email to
[email protected].
For more options, visit this group at
http://groups.google.com/group/cytoscape-cvs?hl=en.
