Author: scooter
Date: 2011-08-19 14:37:01 -0700 (Fri, 19 Aug 2011)
New Revision: 26610
Added:
csplugins/trunk/ucsf/scooter/clusterMaker/src/clusterMaker/algorithms/attributeClusterers/AbstractAttributeClusterer.java
Modified:
csplugins/trunk/ucsf/scooter/clusterMaker/src/clusterMaker/ClusterMaker.java
csplugins/trunk/ucsf/scooter/clusterMaker/src/clusterMaker/algorithms/attributeClusterers/AbstractAttributeClusterAlgorithm.java
csplugins/trunk/ucsf/scooter/clusterMaker/src/clusterMaker/algorithms/attributeClusterers/FeatureVector/FeatureVectorCluster.java
csplugins/trunk/ucsf/scooter/clusterMaker/src/clusterMaker/algorithms/attributeClusterers/hierarchical/EisenCluster.java
csplugins/trunk/ucsf/scooter/clusterMaker/src/clusterMaker/algorithms/attributeClusterers/hierarchical/HierarchicalCluster.java
csplugins/trunk/ucsf/scooter/clusterMaker/src/clusterMaker/algorithms/attributeClusterers/kmeans/KCluster.java
csplugins/trunk/ucsf/scooter/clusterMaker/src/clusterMaker/algorithms/attributeClusterers/kmeans/KMeansCluster.java
csplugins/trunk/ucsf/scooter/clusterMaker/src/clusterMaker/algorithms/attributeClusterers/kmedoid/KMCluster.java
csplugins/trunk/ucsf/scooter/clusterMaker/src/clusterMaker/algorithms/attributeClusterers/kmedoid/KMedoidCluster.java
Log:
More refactoring and cleanup
Modified:
csplugins/trunk/ucsf/scooter/clusterMaker/src/clusterMaker/ClusterMaker.java
===================================================================
---
csplugins/trunk/ucsf/scooter/clusterMaker/src/clusterMaker/ClusterMaker.java
2011-08-19 14:53:42 UTC (rev 26609)
+++
csplugins/trunk/ucsf/scooter/clusterMaker/src/clusterMaker/ClusterMaker.java
2011-08-19 21:37:01 UTC (rev 26610)
@@ -69,8 +69,8 @@
import
clusterMaker.algorithms.attributeClusterers.hierarchical.HierarchicalCluster;
import clusterMaker.algorithms.attributeClusterers.kmeans.KMeansCluster;
import clusterMaker.algorithms.attributeClusterers.kmedoid.KMedoidCluster;
+import
clusterMaker.algorithms.attributeClusterers.FeatureVector.FeatureVectorCluster;
-import clusterMaker.algorithms.FeatureVector.FeatureVectorCluster;
import clusterMaker.algorithms.networkClusterers.TransClust.TransClustCluster;
import clusterMaker.algorithms.networkClusterers.MCL.MCLCluster;
import clusterMaker.algorithms.networkClusterers.MCODE.MCODECluster;
@@ -81,6 +81,7 @@
// import clusterMaker.algorithms.Spectral.SpectralCluster;
// import clusterMaker.algorithms.CP.CPCluster;
import clusterMaker.algorithms.networkClusterers.AP.APCluster;
+
import clusterMaker.algorithms.clusterFilters.AbstractNetworkFilter;
import clusterMaker.algorithms.clusterFilters.HairCutFilter;
import clusterMaker.algorithms.clusterFilters.CuttingEdgeFilter;
Modified:
csplugins/trunk/ucsf/scooter/clusterMaker/src/clusterMaker/algorithms/attributeClusterers/AbstractAttributeClusterAlgorithm.java
===================================================================
---
csplugins/trunk/ucsf/scooter/clusterMaker/src/clusterMaker/algorithms/attributeClusterers/AbstractAttributeClusterAlgorithm.java
2011-08-19 14:53:42 UTC (rev 26609)
+++
csplugins/trunk/ucsf/scooter/clusterMaker/src/clusterMaker/algorithms/attributeClusterers/AbstractAttributeClusterAlgorithm.java
2011-08-19 21:37:01 UTC (rev 26610)
@@ -34,8 +34,10 @@
import java.util.ArrayList;
import java.util.Collections;
+import java.util.HashMap;
import java.util.List;
+import cytoscape.CyNode;
import cytoscape.Cytoscape;
import cytoscape.data.CyAttributes;
import cytoscape.groups.CyGroup;
@@ -174,7 +176,53 @@
}
}
- protected void createGroups() {
+ protected void createGroups(int nClusters, int[] clusters) {
+ if (matrix.isTransposed()) {
+ return;
+ }
+
+ if (monitor != null)
+ monitor.setStatus("Creating groups");
+
+ HashMap<String,List<CyNode>> groupMap = new
HashMap<String,List<CyNode>>();
+ attrList = new ArrayList<String>(matrix.nRows());
+ // Create the attribute list
+ for (int cluster = 0; cluster < nClusters; cluster++) {
+ List<CyNode> memberList = new ArrayList<CyNode>();
+ for (int i = 0; i < matrix.nRows(); i++) {
+ if (clusters[i] == cluster) {
+
attrList.add(matrix.getRowLabel(i)+"\t"+cluster);
+ if (debug)
+
logger.debug(matrix.getRowLabel(i)+"\t"+cluster);
+ memberList.add(matrix.getRowNode(i));
+ }
+ }
+ groupMap.put("Cluster_"+cluster, memberList);
+ }
+
+ List<String> groupNames = new ArrayList<String>();
+
+ if (createGroups) {
+ // Create our groups
+ CyGroup group = null;
+ for (String clusterName: groupMap.keySet()) {
+ List<CyNode> memberList =
groupMap.get(clusterName);
+ groupNames.add(clusterName);
+
+ if (debug)
+ logger.debug("Creating group:
"+clusterName);
+
+ // Create the group
+ group = CyGroupManager.createGroup(clusterName,
memberList, null);
+ if (group != null)
+ CyGroupManager.setGroupViewer(group,
"namedSelection", Cytoscape.getCurrentNetworkView(), false);
+ }
+ CyGroupManager.setGroupViewer(group, "namedSelection",
Cytoscape.getCurrentNetworkView(), true);
+ }
+
+ CyAttributes netAttr = Cytoscape.getNetworkAttributes();
+ String netID = Cytoscape.getCurrentNetwork().getIdentifier();
+ netAttr.setListAttribute(netID, ClusterMaker.GROUP_ATTRIBUTE,
groupNames);
}
public static boolean isAvailable(String type) {
@@ -198,31 +246,5 @@
return true;
}
-
- public static void getAttributesList(List<String>attributeList,
CyAttributes attributes,
- String prefix) {
- String[] names = attributes.getAttributeNames();
- for (int i = 0; i < names.length; i++) {
- if (attributes.getType(names[i]) ==
CyAttributes.TYPE_FLOATING ||
- attributes.getType(names[i]) ==
CyAttributes.TYPE_INTEGER) {
- attributeList.add(prefix+names[i]);
- }
- }
- }
- public static String[] getAllAttributes() {
- // Create the list by combining node and edge attributes into a
single list
- List<String> attributeList = new ArrayList<String>();
- getAttributesList(attributeList,
Cytoscape.getNodeAttributes(),"node.");
- getAttributesList(attributeList,
Cytoscape.getEdgeAttributes(),"edge.");
- Collections.sort(attributeList);
- return attributeList.toArray(new String[1]);
- }
-
- public static String[] getNodeAttributes() {
- List<String> attributeList = new ArrayList<String>();
- getAttributesList(attributeList,
Cytoscape.getNodeAttributes(),"node.");
- Collections.sort(attributeList);
- return attributeList.toArray(new String[1]);
- }
}
Added:
csplugins/trunk/ucsf/scooter/clusterMaker/src/clusterMaker/algorithms/attributeClusterers/AbstractAttributeClusterer.java
===================================================================
---
csplugins/trunk/ucsf/scooter/clusterMaker/src/clusterMaker/algorithms/attributeClusterers/AbstractAttributeClusterer.java
(rev 0)
+++
csplugins/trunk/ucsf/scooter/clusterMaker/src/clusterMaker/algorithms/attributeClusterers/AbstractAttributeClusterer.java
2011-08-19 21:37:01 UTC (rev 26610)
@@ -0,0 +1,104 @@
+/* vim: set ts=2: */
+/**
+ * Copyright (c) 20118 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;
+
+import java.util.ArrayList;
+import java.util.Collections;
+import java.util.List;
+
+import cytoscape.Cytoscape;
+import cytoscape.data.CyAttributes;
+import cytoscape.logger.CyLogger;
+import cytoscape.task.TaskMonitor;
+
+import clusterMaker.algorithms.AbstractClusterAlgorithm;
+
+/**
+ * This abstract class is the base class for all of the attribute clusterers
provided by
+ * clusterMaker. Fundamentally, an attribute clusterer is an algorithm which
functions to
+ * partition nodes or node attributes based on properties of the attributes.
+ */
+public abstract class AbstractAttributeClusterer extends
AbstractClusterAlgorithm {
+ // Common instance variables
+ protected String[] attributeArray = new String[1];
+ protected String dataAttributes = null;
+ protected DistanceMetric distanceMetric = DistanceMetric.EUCLIDEAN;
+ protected boolean clusterAttributes = false;
+ protected boolean createGroups = true;
+ protected boolean ignoreMissing = false;
+ protected boolean selectedOnly = false;
+ protected boolean adjustDiagonals = false;
+ protected boolean zeroMissing = false;
+ protected TaskMonitor monitor = null;
+ protected CyLogger logger = null;
+
+ protected void getAttributesList(List<String>attributeList,
CyAttributes attributes, String prefix) {
+ String[] names = attributes.getAttributeNames();
+ for (int i = 0; i < names.length; i++) {
+ if (attributes.getType(names[i]) ==
CyAttributes.TYPE_FLOATING ||
+ attributes.getType(names[i]) ==
CyAttributes.TYPE_INTEGER) {
+ attributeList.add(prefix+names[i]);
+ }
+ }
+ }
+
+ protected String[] getAllAttributes() {
+ // Create the list by combining node and edge attributes into a
single list
+ List<String> attributeList = new ArrayList<String>();
+ getAttributesList(attributeList,
Cytoscape.getNodeAttributes(),"node.");
+ getAttributesList(attributeList,
Cytoscape.getEdgeAttributes(),"edge.");
+ Collections.sort(attributeList);
+ return attributeList.toArray(new String[1]);
+ }
+
+ protected String[] getNodeAttributes() {
+ List<String> attributeList = new ArrayList<String>();
+ getAttributesList(attributeList,
Cytoscape.getNodeAttributes(),"node.");
+ Collections.sort(attributeList);
+ return attributeList.toArray(new String[1]);
+ }
+
+ protected 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;
+ }
+
+ public boolean isAvailable() {
+ return
AbstractAttributeClusterAlgorithm.isAvailable(getShortName());
+ }
+
+}
Modified:
csplugins/trunk/ucsf/scooter/clusterMaker/src/clusterMaker/algorithms/attributeClusterers/FeatureVector/FeatureVectorCluster.java
===================================================================
---
csplugins/trunk/ucsf/scooter/clusterMaker/src/clusterMaker/algorithms/attributeClusterers/FeatureVector/FeatureVectorCluster.java
2011-08-19 14:53:42 UTC (rev 26609)
+++
csplugins/trunk/ucsf/scooter/clusterMaker/src/clusterMaker/algorithms/attributeClusterers/FeatureVector/FeatureVectorCluster.java
2011-08-19 21:37:01 UTC (rev 26610)
@@ -55,26 +55,19 @@
import clusterMaker.algorithms.AbstractClusterAlgorithm;
import clusterMaker.algorithms.ClusterAlgorithm;
-import
clusterMaker.algorithms.attributeClusterers.AbstractAttributeClusterAlgorithm;
+import clusterMaker.algorithms.attributeClusterers.AbstractAttributeClusterer;
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];
+public class FeatureVectorCluster extends AbstractAttributeClusterer
implements TunableListener {
- 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() {
@@ -89,7 +82,7 @@
public JPanel getSettingsPanel() {
// Everytime we ask for the panel, we want to update our
attributes
Tunable attributeTunable =
clusterProperties.get("attributeList");
- attributeArray =
AbstractAttributeClusterAlgorithm.getNodeAttributes();
+ attributeArray = getNodeAttributes();
attributeTunable.setLowerBound((Object)attributeArray);
return clusterProperties.getTunablePanel();
@@ -117,7 +110,7 @@
Tunable.GROUP, new
Integer(1)));
// The attribute to use to get the weights
- attributeArray =
AbstractAttributeClusterAlgorithm.getNodeAttributes();
+ attributeArray = getNodeAttributes();
clusterProperties.add(new Tunable("attributeList",
"Array sources",
Tunable.LIST, "",
@@ -367,7 +360,6 @@
}
public boolean isAvailable() {
- // return EisenCluster.isAvailable(getShortName());
return false;
}
@@ -391,13 +383,4 @@
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;
- }
}
Modified:
csplugins/trunk/ucsf/scooter/clusterMaker/src/clusterMaker/algorithms/attributeClusterers/hierarchical/EisenCluster.java
===================================================================
---
csplugins/trunk/ucsf/scooter/clusterMaker/src/clusterMaker/algorithms/attributeClusterers/hierarchical/EisenCluster.java
2011-08-19 14:53:42 UTC (rev 26609)
+++
csplugins/trunk/ucsf/scooter/clusterMaker/src/clusterMaker/algorithms/attributeClusterers/hierarchical/EisenCluster.java
2011-08-19 21:37:01 UTC (rev 26610)
@@ -527,33 +527,6 @@
return nodeList;
}
- public static void getAttributesList(List<String>attributeList,
CyAttributes attributes,
- String prefix) {
- String[] names = attributes.getAttributeNames();
- for (int i = 0; i < names.length; i++) {
- if (attributes.getType(names[i]) ==
CyAttributes.TYPE_FLOATING ||
- attributes.getType(names[i]) ==
CyAttributes.TYPE_INTEGER) {
- attributeList.add(prefix+names[i]);
- }
- }
- }
-
- public static String[] getAllAttributes() {
- // Create the list by combining node and edge attributes into a
single list
- List<String> attributeList = new ArrayList<String>();
- getAttributesList(attributeList,
Cytoscape.getNodeAttributes(),"node.");
- getAttributesList(attributeList,
Cytoscape.getEdgeAttributes(),"edge.");
- Collections.sort(attributeList);
- return attributeList.toArray(new String[1]);
- }
-
- public static String[] getNodeAttributes() {
- List<String> attributeList = new ArrayList<String>();
- getAttributesList(attributeList,
Cytoscape.getNodeAttributes(),"node.");
- Collections.sort(attributeList);
- return attributeList.toArray(new String[1]);
- }
-
/**
* This function searches the distance matrix to find the pair with the
shortest
* distance between them. The indices of the pair are returned in ip
and jp; the
Modified:
csplugins/trunk/ucsf/scooter/clusterMaker/src/clusterMaker/algorithms/attributeClusterers/hierarchical/HierarchicalCluster.java
===================================================================
---
csplugins/trunk/ucsf/scooter/clusterMaker/src/clusterMaker/algorithms/attributeClusterers/hierarchical/HierarchicalCluster.java
2011-08-19 14:53:42 UTC (rev 26609)
+++
csplugins/trunk/ucsf/scooter/clusterMaker/src/clusterMaker/algorithms/attributeClusterers/hierarchical/HierarchicalCluster.java
2011-08-19 21:37:01 UTC (rev 26610)
@@ -47,7 +47,7 @@
import cytoscape.task.TaskMonitor;
import clusterMaker.algorithms.ClusterAlgorithm;
-import clusterMaker.algorithms.AbstractClusterAlgorithm;
+import clusterMaker.algorithms.attributeClusterers.AbstractAttributeClusterer;
import clusterMaker.algorithms.attributeClusterers.DistanceMetric;
import clusterMaker.algorithms.attributeClusterers.Matrix;
import clusterMaker.ui.ClusterViz;
@@ -55,7 +55,7 @@
// clusterMaker imports
-public class HierarchicalCluster extends AbstractClusterAlgorithm {
+public class HierarchicalCluster extends AbstractAttributeClusterer {
/**
* Linkage types
*/
@@ -64,19 +64,8 @@
ClusterMethod.MAXIMUM_LINKAGE,
ClusterMethod.CENTROID_LINKAGE };
- String[] attributeArray = new String[1];
ClusterMethod clusterMethod = ClusterMethod.AVERAGE_LINKAGE;
- DistanceMetric distanceMetric = DistanceMetric.EUCLIDEAN;
- boolean clusterAttributes = false;
- boolean createGroups = true;
- boolean ignoreMissing = false;
- boolean selectedOnly = false;
- boolean adjustDiagonals = false;
- boolean zeroMissing = false;
- String dataAttributes = null;
- TaskMonitor monitor = null;
- CyLogger logger = null;
TreeView treeView = null;
public HierarchicalCluster() {
@@ -91,7 +80,7 @@
public JPanel getSettingsPanel() {
// Everytime we ask for the panel, we want to update our
attributes
Tunable attributeTunable =
clusterProperties.get("attributeList");
- attributeArray = EisenCluster.getAllAttributes();
+ attributeArray = getAllAttributes();
attributeTunable.setLowerBound((Object)attributeArray);
return clusterProperties.getTunablePanel();
@@ -128,7 +117,7 @@
Tunable.GROUP, new
Integer(1)));
// The attribute to use to get the weights
- attributeArray = EisenCluster.getAllAttributes();
+ attributeArray = getAllAttributes();
clusterProperties.add(new Tunable("attributeList",
"Array sources",
Tunable.LIST, "",
@@ -280,10 +269,6 @@
pcs.firePropertyChange(ClusterAlgorithm.CLUSTER_COMPUTED, null,
this);
}
- public boolean isAvailable() {
- return EisenCluster.isAvailable(getShortName());
- }
-
private void setParameters(EisenCluster algorithm) {
algorithm.setCreateGroups(createGroups);
algorithm.setIgnoreMissing(ignoreMissing);
@@ -292,12 +277,4 @@
algorithm.setZeroMissing(zeroMissing);
}
- 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;
- }
}
Modified:
csplugins/trunk/ucsf/scooter/clusterMaker/src/clusterMaker/algorithms/attributeClusterers/kmeans/KCluster.java
===================================================================
---
csplugins/trunk/ucsf/scooter/clusterMaker/src/clusterMaker/algorithms/attributeClusterers/kmeans/KCluster.java
2011-08-19 14:53:42 UTC (rev 26609)
+++
csplugins/trunk/ucsf/scooter/clusterMaker/src/clusterMaker/algorithms/attributeClusterers/kmeans/KCluster.java
2011-08-19 21:37:01 UTC (rev 26610)
@@ -96,26 +96,10 @@
// Cluster
int ifound = kmeans(nClusters, nIterations, matrix, metric,
clusters);
- groupMap = new HashMap<String,List<CyNode>>();
- attrList = new ArrayList<String>(matrix.nRows());
- // Create the attribute list
- for (int cluster = 0; cluster < nClusters; cluster++) {
- List<CyNode> memberList = new ArrayList<CyNode>();
- for (int i = 0; i < matrix.nRows(); i++) {
- if (clusters[i] == cluster) {
-
attrList.add(matrix.getRowLabel(i)+"\t"+cluster);
- if (debug)
-
logger.debug(matrix.getRowLabel(i)+"\t"+cluster);
- memberList.add(matrix.getRowNode(i));
- }
- }
- groupMap.put("Cluster_"+cluster, memberList);
- }
- rowOrder = matrix.indexSort(clusters, clusters.length);
-
if (!interimRun) {
if (!matrix.isTransposed())
- createGroups();
+ createGroups(nClusters, clusters);
+ rowOrder = matrix.indexSort(clusters, clusters.length);
// Update the network attributes
updateAttributes("kmeans");
}
Modified:
csplugins/trunk/ucsf/scooter/clusterMaker/src/clusterMaker/algorithms/attributeClusterers/kmeans/KMeansCluster.java
===================================================================
---
csplugins/trunk/ucsf/scooter/clusterMaker/src/clusterMaker/algorithms/attributeClusterers/kmeans/KMeansCluster.java
2011-08-19 14:53:42 UTC (rev 26609)
+++
csplugins/trunk/ucsf/scooter/clusterMaker/src/clusterMaker/algorithms/attributeClusterers/kmeans/KMeansCluster.java
2011-08-19 21:37:01 UTC (rev 26610)
@@ -47,8 +47,7 @@
import cytoscape.task.TaskMonitor;
import clusterMaker.algorithms.ClusterAlgorithm;
-import clusterMaker.algorithms.AbstractClusterAlgorithm;
-import
clusterMaker.algorithms.attributeClusterers.AbstractAttributeClusterAlgorithm;
+import clusterMaker.algorithms.attributeClusterers.AbstractAttributeClusterer;
import clusterMaker.algorithms.attributeClusterers.DistanceMetric;
import clusterMaker.algorithms.attributeClusterers.Matrix;
import clusterMaker.ui.ClusterViz;
@@ -56,19 +55,9 @@
// clusterMaker imports
-public class KMeansCluster extends AbstractClusterAlgorithm {
- String[] attributeArray = new String[1];
-
+public class KMeansCluster extends AbstractAttributeClusterer {
int kNumber = 0;
int rNumber = 0;
- DistanceMetric distanceMetric = DistanceMetric.EUCLIDEAN;
- boolean clusterAttributes = false;
- boolean createGroups = true;
- boolean ignoreMissing = false;
- boolean selectedOnly = false;
- String dataAttributes = null;
- TaskMonitor monitor = null;
- CyLogger logger = null;
KnnView knnView = null;
public KMeansCluster() {
@@ -83,7 +72,7 @@
public JPanel getSettingsPanel() {
// Everytime we ask for the panel, we want to update our
attributes
Tunable attributeTunable =
clusterProperties.get("attributeList");
- attributeArray =
AbstractAttributeClusterAlgorithm.getAllAttributes();
+ attributeArray = getAllAttributes();
attributeTunable.setLowerBound((Object)attributeArray);
// We also want to update the number our "guestimate" for k
@@ -140,7 +129,7 @@
Tunable.GROUP, new
Integer(1)));
// The attribute to use to get the weights
- attributeArray =
AbstractAttributeClusterAlgorithm.getAllAttributes();
+ attributeArray = getAllAttributes();
clusterProperties.add(new Tunable("attributeList",
"Array sources",
Tunable.LIST, "",
@@ -256,16 +245,4 @@
pcs.firePropertyChange(ClusterAlgorithm.CLUSTER_COMPUTED, null,
this);
}
- public boolean isAvailable() {
- return
AbstractAttributeClusterAlgorithm.isAvailable(getShortName());
- }
-
- 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;
- }
}
Modified:
csplugins/trunk/ucsf/scooter/clusterMaker/src/clusterMaker/algorithms/attributeClusterers/kmedoid/KMCluster.java
===================================================================
---
csplugins/trunk/ucsf/scooter/clusterMaker/src/clusterMaker/algorithms/attributeClusterers/kmedoid/KMCluster.java
2011-08-19 14:53:42 UTC (rev 26609)
+++
csplugins/trunk/ucsf/scooter/clusterMaker/src/clusterMaker/algorithms/attributeClusterers/kmedoid/KMCluster.java
2011-08-19 21:37:01 UTC (rev 26610)
@@ -97,26 +97,9 @@
// Cluster
int ifound = kmedoid(nClusters, nIterations, matrix, metric,
clusters);
-
- groupMap = new HashMap<String,List<CyNode>>();
- attrList = new ArrayList<String>(matrix.nRows());
- // Create the attribute list
- for (int cluster = 0; cluster < nClusters; cluster++) {
- List<CyNode> memberList = new ArrayList<CyNode>();
- for (int i = 0; i < matrix.nRows(); i++) {
- if (clusters[i] == cluster) {
-
attrList.add(matrix.getRowLabel(i)+"\t"+cluster);
- if (debug)
-
logger.debug(matrix.getRowLabel(i)+"\t"+cluster);
- memberList.add(matrix.getRowNode(i));
- }
- }
- groupMap.put("Cluster_"+cluster, memberList);
- }
-
if (!interimRun) {
if (!matrix.isTransposed())
- createGroups();
+ createGroups(nClusters, clusters);
rowOrder = matrix.indexSort(clusters, clusters.length);
updateAttributes("kmedoid");
}
Modified:
csplugins/trunk/ucsf/scooter/clusterMaker/src/clusterMaker/algorithms/attributeClusterers/kmedoid/KMedoidCluster.java
===================================================================
---
csplugins/trunk/ucsf/scooter/clusterMaker/src/clusterMaker/algorithms/attributeClusterers/kmedoid/KMedoidCluster.java
2011-08-19 14:53:42 UTC (rev 26609)
+++
csplugins/trunk/ucsf/scooter/clusterMaker/src/clusterMaker/algorithms/attributeClusterers/kmedoid/KMedoidCluster.java
2011-08-19 21:37:01 UTC (rev 26610)
@@ -48,7 +48,7 @@
import clusterMaker.algorithms.ClusterAlgorithm;
import clusterMaker.algorithms.AbstractClusterAlgorithm;
-import
clusterMaker.algorithms.attributeClusterers.AbstractAttributeClusterAlgorithm;
+import clusterMaker.algorithms.attributeClusterers.AbstractAttributeClusterer;
import clusterMaker.algorithms.attributeClusterers.DistanceMetric;
import clusterMaker.algorithms.attributeClusterers.Matrix;
import clusterMaker.ui.ClusterViz;
@@ -56,19 +56,9 @@
// clusterMaker imports
-public class KMedoidCluster extends AbstractClusterAlgorithm {
- String[] attributeArray = new String[1];
-
+public class KMedoidCluster extends AbstractAttributeClusterer {
int kNumber = 0;
int rNumber = 0;
- DistanceMetric distanceMetric = DistanceMetric.EUCLIDEAN;
- boolean clusterAttributes = false;
- boolean createGroups = true;
- boolean ignoreMissing = false;
- boolean selectedOnly = false;
- String dataAttributes = null;
- TaskMonitor monitor = null;
- CyLogger logger = null;
KnnView knnView = null;
public KMedoidCluster() {
@@ -83,7 +73,7 @@
public JPanel getSettingsPanel() {
// Everytime we ask for the panel, we want to update our
attributes
Tunable attributeTunable =
clusterProperties.get("attributeList");
- attributeArray =
AbstractAttributeClusterAlgorithm.getAllAttributes();
+ attributeArray = getAllAttributes();
attributeTunable.setLowerBound((Object)attributeArray);
// We also want to update the number our "guestimate" for k
@@ -140,7 +130,7 @@
Tunable.GROUP, new
Integer(1)));
// The attribute to use to get the weights
- attributeArray =
AbstractAttributeClusterAlgorithm.getAllAttributes();
+ attributeArray = getAllAttributes();
clusterProperties.add(new Tunable("attributeList",
"Array sources",
Tunable.LIST, "",
@@ -256,16 +246,4 @@
pcs.firePropertyChange(ClusterAlgorithm.CLUSTER_COMPUTED, null,
this);
}
- public boolean isAvailable() {
- return
AbstractAttributeClusterAlgorithm.isAvailable(getShortName());
- }
-
- 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;
- }
}
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