Upload of challenge version

These are the same files as discussed in https://www.synapse.org/#!Synapse:syn7349259/wiki/407357
bmds-lab · Aug 4, 2018 · a61486d · a61486d
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diff --git a/code/CogeneMatrix.jar b/code/CogeneMatrix.jar
diff --git a/code/CogeneMatrix.java b/code/CogeneMatrix.java
@@ -0,0 +1,219 @@
+import java.io.BufferedReader;
+import java.io.FileNotFoundException;
+import java.io.FileReader;
+import java.io.IOException;
+import java.io.PrintWriter;
+import java.util.Arrays;
+import java.util.HashMap;
+import java.util.Iterator;
+import java.util.Map;
+import java.util.Map.Entry;
+import java.util.Vector;
+
+/**
+ * 
+ */
+
+/**
+ * @author zuccong
+ *
+ */
+public class CogeneMatrix {
+
+
+	HashMap<Integer, HashMap<Integer,Double>> fusedCogeneMatrix = new HashMap<Integer, HashMap<Integer,Double>>();
+	HashMap<Integer,Double> networkweights = new HashMap<Integer,Double>();
+
+	/**
+	 * @return the networkweights
+	 */
+	public HashMap<Integer, Double> getNetworkweights() {
+		return networkweights;
+	}
+
+	/**
+	 * @param networkweights the networkweights to set
+	 */
+	public void setNetworkweights(HashMap<Integer, Double> networkweights) {
+		this.networkweights = networkweights;
+	}
+
+	public void readNetworkNumberVote(String filePath) throws FileNotFoundException, IOException {
+		try (BufferedReader br = new BufferedReader(new FileReader(filePath))) {
+			String line;
+			while ((line = br.readLine()) != null) {
+				String[] networkLine = line.split("\t", -1);
+				for(int i = 2; i<networkLine.length;i++) {
+					int nodeA = Integer.parseInt(networkLine[i]);
+					for(int j = 2; j<networkLine.length;j++) {
+						int nodeB = Integer.parseInt(networkLine[j]);
+						if(nodeA!=nodeB) {
+							HashMap<Integer,Double> tmp = new HashMap<Integer,Double>();
+							if(fusedCogeneMatrix.containsKey(nodeA)) {
+								tmp = fusedCogeneMatrix.get(nodeA);
+								double value =  1.0/6.0;
+								if(tmp.containsKey(nodeB))
+									value = value + tmp.get(nodeB);
+								tmp.put(nodeB, value);
+							}else {
+								double value =  1.0/6.0;
+								tmp.put(nodeB, value);
+							}
+							fusedCogeneMatrix.put(nodeA, tmp);
+						}
+					}
+
+				}
+
+			}
+		}
+
+	}
+
+
+	public void readNetworkWeightedVote(String filePath, int networkid) throws FileNotFoundException, IOException {
+		try (BufferedReader br = new BufferedReader(new FileReader(filePath))) {
+			String line;
+			while ((line = br.readLine()) != null) {
+				String[] networkLine = line.split("\t", -1);
+				for(int i = 2; i<networkLine.length;i++) {
+					int nodeA = Integer.parseInt(networkLine[i]);
+					for(int j = 2; j<networkLine.length;j++) {
+						int nodeB = Integer.parseInt(networkLine[j]);
+						if(nodeA!=nodeB) {
+							System.out.println(nodeA + " " + nodeB);
+							if(nodeA!=nodeB) {
+								HashMap<Integer,Double> tmp = new HashMap<Integer,Double>();
+								if(fusedCogeneMatrix.containsKey(nodeA)) {
+									tmp = fusedCogeneMatrix.get(nodeA);
+									double value =  networkWeight(networkid);
+									if(tmp.containsKey(nodeB))
+										value = value + tmp.get(nodeB);
+									tmp.put(nodeB, value);
+								}else {
+									double value =  networkWeight(networkid);
+									tmp.put(nodeB, value);
+								}
+								fusedCogeneMatrix.put(nodeA, tmp);
+							}
+						}
+					}
+
+				}
+
+			}
+		}
+
+	}
+
+
+	public void printCogeneMatrix() {
+		Iterator<Entry<Integer, HashMap<Integer, Double>>> it = fusedCogeneMatrix.entrySet().iterator();
+	    while (it.hasNext()) {
+	        Map.Entry pair = (Map.Entry)it.next();
+	        int nodeA = (int) pair.getKey();
+	        HashMap<Integer, Double> tmp = (HashMap<Integer, Double>) pair.getValue();
+	        Iterator ittmp = tmp.entrySet().iterator();
+	        while (ittmp.hasNext()) {
+	        	Map.Entry pairtmp = (Map.Entry)ittmp.next();
+	        	//System.out.println(nodeA + " " + (int)pairtmp.getKey() + " = " + (double)pairtmp.getValue());
+	        }
+	    }
+	}
+
+	public void printCogeneMatrixOnFile(PrintWriter out) {
+		Iterator<Entry<Integer, HashMap<Integer, Double>>> it = fusedCogeneMatrix.entrySet().iterator();
+	    while (it.hasNext()) {
+	        Map.Entry pair = (Map.Entry)it.next();
+	        int nodeA = (int) pair.getKey();
+	        HashMap<Integer, Double> tmp = (HashMap<Integer, Double>) pair.getValue();
+	        Iterator ittmp = tmp.entrySet().iterator();
+	        while (ittmp.hasNext()) {
+	        	Map.Entry pairtmp = (Map.Entry)ittmp.next();
+	        	out.println(nodeA + "\t" + (int)pairtmp.getKey() + "\t" + (double)pairtmp.getValue());
+	        }
+	    }
+    	out.flush();
+	}
+
+	public double networkWeight(int networkid) {
+		switch (networkid) {
+		case 1:  return networkweights.get(1);
+		case 2:  return networkweights.get(2);
+		case 3:  return networkweights.get(3);
+		case 4:  return networkweights.get(4);
+		case 5:  return networkweights.get(5);
+		case 6:  return networkweights.get(6);
+		default: return networkweights.get(1);
+		}
+	}
+
+
+
+	/**
+	 * @param args
+	 * @throws IOException 
+	 * @throws FileNotFoundException 
+	 */
+	public static void main(String[] args) throws FileNotFoundException, IOException {
+		CogeneMatrix cm1 = new CogeneMatrix();
+		System.out.println("Reading network");
+
+		Vector<String> networkFiles = new Vector<String>();
+		for(int i = 0; i < args.length; i++) {
+			networkFiles.add(args[i]);
+            System.out.println(args[i]);
+        }
+		for(String file : networkFiles) {
+			cm1.readNetworkNumberVote(file);
+		}
+
+		/*cm1.readNetworkNumberVote("/Users/zuccong/Dropbox/DMI_challenge/results/sc2_round4/run3/1_ppi_anonym_aligned_v2.txt");
+		cm1.readNetworkNumberVote("/Users/zuccong/Dropbox/DMI_challenge/results/sc2_round4/run3/2_ppi_anonym_aligned_v2.txt");
+		cm1.readNetworkNumberVote("/Users/zuccong/Dropbox/DMI_challenge/results/sc2_round4/run3/3_signal_anonym_aligned_undirected_v3_normalised.txt");
+		cm1.readNetworkNumberVote("/Users/zuccong/Dropbox/DMI_challenge/results/sc2_round4/run3/4_coexpr_anonym_aligned_v2.txt");
+		cm1.readNetworkNumberVote("/Users/zuccong/Dropbox/DMI_challenge/results/sc2_round4/run3/5_cancer_anonym_aligned_v2.txt");
+		cm1.readNetworkNumberVote("/Users/zuccong/Dropbox/DMI_challenge/results/sc2_round4/run3/6_homology_anonym_aligned_v2_normalised.txt");
+		*/
+		System.out.println("Network read");
+		//cm1.printCogeneMatrix();
+		PrintWriter out1 = new PrintWriter("../data/subchallenge2/communities_graph_uniform_voting.txt");
+
+		cm1.printCogeneMatrixOnFile(out1);
+		out1.close();
+
+		CogeneMatrix cm2 = new CogeneMatrix();
+
+		System.out.println("Reading network");
+		cm2.networkweights.put(1, 13.0/52.0);
+		cm2.networkweights.put(2, 9.0/52.0);
+		cm2.networkweights.put(3, 7.0/52.0);
+		cm2.networkweights.put(4, 9.0/52.0);
+		cm2.networkweights.put(5, 5.0/52.0);
+		cm2.networkweights.put(6, 9.0/52.0);
+
+		int i =1;
+		for(String file : networkFiles) {
+			cm2.readNetworkWeightedVote(file, i);
+			i++;
+		}
+
+		/*
+		cm2.readNetworkWeightedVote("/Users/zuccong/Dropbox/DMI_challenge/results/sc2_round4/run3/1_ppi_anonym_aligned_v2.txt", 1);
+		cm2.readNetworkWeightedVote("/Users/zuccong/Dropbox/DMI_challenge/results/sc2_round4/run3/2_ppi_anonym_aligned_v2.txt", 2);
+		cm2.readNetworkWeightedVote("/Users/zuccong/Dropbox/DMI_challenge/results/sc2_round4/run3/3_signal_anonym_aligned_undirected_v3_normalised.txt", 3);
+		cm2.readNetworkWeightedVote("/Users/zuccong/Dropbox/DMI_challenge/results/sc2_round4/run3/4_coexpr_anonym_aligned_v2.txt", 4);
+		cm2.readNetworkWeightedVote("/Users/zuccong/Dropbox/DMI_challenge/results/sc2_round4/run3/5_cancer_anonym_aligned_v2.txt", 5);
+		cm2.readNetworkWeightedVote("/Users/zuccong/Dropbox/DMI_challenge/results/sc2_round4/run3/6_homology_anonym_aligned_v2_normalised.txt", 6);
+		*/
+		System.out.println("Network read");
+		//cm2.printCogeneMatrix();
+		PrintWriter out2 = new PrintWriter("../data/subchallenge2/communities_graph_weighted_voting.txt");
+
+		cm2.printCogeneMatrixOnFile(out2);
+		out2.close();
+
+
+	}
+
+}
diff --git a/code/SC1_pipeline.sh b/code/SC1_pipeline.sh
@@ -0,0 +1,80 @@
+
+
+#######################
+# Assumed structure   #
+#  and required files #
+#######################
+
+# Two folders, "data" and "code"
+
+# The "data" folder contains two folders, "subchallenge1" and "subchallenge2", which contain the input networks
+
+# The "code" folder contains our code, as well as a folder "louvain" which contains the executable files "convert", "matrix", "louvain" and "hierarchy", which are all compiled from the file "louvain-generic.tar.gz" downloaded from http://sourceforge.net/projects/louvain/
+
+# File pageRank.c needs to be compiled to an executable called "pageRank" (in the "code" folder)
+
+# The following commands assume that "code" is the working directory
+
+
+######################
+# Pre-processing for #
+#  networks 3 and 6  #
+######################
+
+# Note: this needs to run only once
+
+python convertToUndirected.py
+python normaliseWeights.py 3_signal_anonym_undirected_v3
+python normaliseWeights.py 6_homology_anonym_v2
+
+
+########################
+# Calculating PageRank #
+#  on all six networks #
+########################
+
+# Note: this needs to run only once
+
+# Usage: ./pageRank <nb_nodes> <nb_edges> <input_file> <output_file> <directed|undirected>
+
+# Network 1
+
+ ./pageRank 17397 2232405 ../data/subchallenge1/1_ppi_anonym_v2.txt ./PR_1_ppi_anonym_v2.txt undirected
+
+# Network 2
+
+./pageRank 12420 397309 ../data/subchallenge1/2_ppi_anonym_v2.txt ./PR_2_ppi_anonym_v2.txt undirected
+
+# Network 3
+
+./pageRank 5254 21826 ../data/subchallenge1/3_signal_anonym_undirected_v3_normalised.txt ./PR_3_signal_anonym_undirected_v3_normalised.txt undirected
+
+# Network 4
+
+ ./pageRank 12588 1000000 ../data/subchallenge1/4_coexpr_anonym_v2.txt ./PR_4_coexpr_anonym_v2.txt undirected
+
+# Network 5
+
+./pageRank 14679 1000000 ../data/subchallenge1/5_cancer_anonym_v2.txt ./PR_5_cancer_anonym_v2.txt undirected
+
+# Network 6
+
+./pageRank 10475 4223606 ../data/subchallenge1/6_homology_anonym_v2_normalised.txt ./PR_6_homology_anonym_v2_normalised.txt undirected
+
+
+########################
+# Running our method   #
+#  on the six networks #
+########################
+
+# Usage: python enhancedRecursiveLouvain_recPR_sc1.py <network> <threshold for recursion>
+
+python enhancedRecursiveLouvain_recPR_sc1.py 1_ppi_anonym_v2 80 
+python enhancedRecursiveLouvain_recPR_sc1.py 2_ppi_anonym_v2 80 
+python enhancedRecursiveLouvain_recPR_sc1.py 3_signal_anonym_undirected_v3_normalised 80 
+python enhancedRecursiveLouvain_recPR_sc1.py 4_coexpr_anonym_v2 95 
+python enhancedRecursiveLouvain_recPR_sc1.py 5_cancer_anonym_v2 90 
+python enhancedRecursiveLouvain_recPR_sc1.py 6_homology_anonym_v2_normalised 80
+
+python finaliseEnhancedLouvain_sc1.py 
+