import gnu.trove.map.hash.TIntFloatHashMap; //导入依赖的package包/类
private void computeItemSim() {

		List<Integer> sortedItems = new ArrayList<Integer>();
		sortedItems.addAll(items);
		Collections.sort(sortedItems);
		int id1, id2;
		for (int i = 0; i < sortedItems.size() - 1; i++) {
			id1 = sortedItems.get(i);
			this.itemSim.put(id1, new TIntFloatHashMap());
			for (int j = i + 1; j < sortedItems.size(); j++) {
				id2 = sortedItems.get(j);
				float val = 0;
				if (map_item_intFeatures.containsKey(id1)
						& map_item_intFeatures.containsKey(id2))
					val = cmpJaccardSim(this.map_item_intFeatures.get(id1)
							.keySet(), this.map_item_intFeatures.get(id2)
							.keySet());

				if (val > MIN_SIM) {
					itemSim.get(id1).put(id2, val);
				}
			}

		}
	}
 

import gnu.trove.map.hash.TIntFloatHashMap; //导入依赖的package包/类
/**
 * Normalize a vector to unit length.
 * @param X
 * @return
 */
public static TIntFloatMap normalizeVector(TIntFloatMap X) {
    TIntFloatHashMap Y = new TIntFloatHashMap();
    double sumSquares = 0.0;
    for (double x : X.values()) {
        sumSquares += x * x;
    }
    if (sumSquares != 0.0) {
        double norm = Math.sqrt(sumSquares);
        for (int id : X.keys()) {
            Y.put(id, (float) (X.get(id) / norm));
        }
        return Y;
    }
    return X;
}
 

import gnu.trove.map.hash.TIntFloatHashMap; //导入依赖的package包/类
/**
 * Construct with the given parameters.
 * 
 * @param minRad
 *            minimum search radius
 * @param maxRad
 *            maximum search radius
 * @param radIncrement
 *            amount to increment search radius by between min and max.
 * @param nDegree
 *            number of degree increments
 */
public HoughCircles(int minRad, int maxRad, int radIncrement, int nDegree) {
	super();
	this.minRad = minRad;
	if (this.minRad <= 0)
		this.minRad = 1;
	this.maxRad = maxRad;
	this.radmap = new TIntObjectHashMap<TIntObjectHashMap<TIntFloatHashMap>>();
	this.radIncr = radIncrement;
	this.nRadius = (maxRad - minRad) / this.radIncr;
	this.nDegree = nDegree;
	this.cosanglemap = new float[nRadius][nDegree];
	this.sinanglemap = new float[nRadius][nDegree];
	for (int radIndex = 0; radIndex < this.nRadius; radIndex++) {
		for (int angIndex = 0; angIndex < nDegree; angIndex++) {
			final double ang = angIndex * (2 * PI / nDegree);
			final double rad = minRad + (radIndex * this.radIncr);
			this.cosanglemap[radIndex][angIndex] = (float) (rad * cos(ang));
			this.sinanglemap[radIndex][angIndex] = (float) (rad * sin(ang));
		}
	}
}
 

import gnu.trove.map.hash.TIntFloatHashMap; //导入依赖的package包/类
private float distanceEuclidean(int n, HashSparseVector sv, float baseDistance) {
    HashSparseVector center = classCenter.get(n);
    int count = classCount.get(n);
    float dist = baseDistance / (count * count);
    TIntFloatHashMap data = center.data;
    TIntFloatIterator it = sv.data.iterator();
    while (it.hasNext()) {
        it.advance();
        int key = it.key();
        if (!data.containsKey(key)) {
            dist += it.value() * it.value();
        }
        else {
            float temp = data.get(key) / count;
            dist -= temp * temp;
            dist += (it.value() - temp) * (it.value() - temp);
        }
    }
    return dist;
}
 

import gnu.trove.map.hash.TIntFloatHashMap; //导入依赖的package包/类
private void updateBaseDist(int classid, HashSparseVector vector) {
    float base = baseDistList.get(classid);
    TIntFloatHashMap center = classCenter.get(classid).data;
    TIntFloatIterator it =  vector.data.iterator();
    while (it.hasNext()) {
        it.advance();
        if (!center.containsKey(it.key())) {
            base += it.value() * it.value();
        }
        else {
            float temp = center.get(it.key());
            base -= temp * temp;
            base += (it.value() - temp) * (it.value() - temp);
        }
    }
    baseDistList.set(classid, base);
}
 

import gnu.trove.map.hash.TIntFloatHashMap; //导入依赖的package包/类
private float getweight(int c1, int c2) {
	int max,min;
	if(c1<=c2){
		max = c2;
		min = c1;
	}else{
		max = c1;
		min = c2;
	}
	float w;
	TIntFloatHashMap map2 = wcc.get(min);
	if(map2==null){
		w = 0;
	}else
		w = map2.get(max);
	return w;
}
 

import gnu.trove.map.hash.TIntFloatHashMap; //导入依赖的package包/类
/**
 * 得到总能量值大于thres的元素对应的下标
 * 
 * @param data 稀疏向量
 * @param thres
 * @return 元素下标 int[][] 第一列表示大于阈值的元素 第二列表示小于阈值的元素
 */
public static int[][] getTop(TIntFloatHashMap data, float thres) {
	int[] idx = sort(data);
	int i;
	float total = 0;
	float[] cp = new float[idx.length];
	for (i = idx.length; i-- > 0;) {
		cp[i] = (float) Math.pow(data.get(idx[i]), 2);
		total += cp[i];
	}

	float ratio = 0;
	for (i = 0; i < idx.length; i++) {
		ratio += cp[i] / total;
		if (ratio > thres)
			break;
	}
	int[][] a = new int[2][];
	a[0] = Arrays.copyOfRange(idx, 0, i);
	a[1] = Arrays.copyOfRange(idx, i, idx.length);
	return a;
}
 

import gnu.trove.map.hash.TIntFloatHashMap; //导入依赖的package包/类
/**
 * 由大到小排序
 * @param tmap
 * @return 数组下标
 */
public static int[] sort(TIntFloatHashMap tmap) {
	HashMap<Integer, Float> map = new HashMap<Integer, Float>();

	TIntFloatIterator it = tmap.iterator();
	while (it.hasNext()) {
		it.advance();
		int id = it.key();
		float val = it.value();
		map.put(id, Math.abs(val));
	}
	it = null;

	List<Entry> list = sort(map);
	int[] idx = new int[list.size()];
	Iterator<Entry> it1 = list.iterator();
	int i=0;
	while (it1.hasNext()) {
		Entry entry = it1.next();
		idx[i++] = (Integer) entry.getKey();
	}
	return idx;
}
 

import gnu.trove.map.hash.TIntFloatHashMap; //导入依赖的package包/类
/**
 * Normalizes the probability values in a vector so that to sum to 1.0
 * @param vector
 * @return
 */
public static TIntFloatMap normalizeVector(TIntFloatMap vector)
{
	float total = 0;

               TFloatIterator iter = vector.valueCollection().iterator();
               while (iter.hasNext())
                      total += iter.next();
               
               TIntFloatMap normalized = new TIntFloatHashMap(vector.size());
	
               TIntFloatIterator iter2 = vector.iterator();
               while (iter2.hasNext())
               {
                       iter2.advance();
                       normalized.put(iter2.key(), iter2.value() / total);
               }		
	return normalized;
}
 

import gnu.trove.map.hash.TIntFloatHashMap; //导入依赖的package包/类
@Test
public void testGetSortedIndices() 
{
           TIntFloatMap m = new TIntFloatHashMap();
           m.put(0, 1f);
           m.put(1, 10f);
           m.put(2, 5f);
           m.put(3, 2f);

           int[] sorted = SemSigUtils.getSortedIndices(m);
           assertEquals(4, sorted.length);
           assertEquals(1, sorted[0]);
           assertEquals(2, sorted[1]);
           assertEquals(3, sorted[2]);
           assertEquals(0, sorted[3]);
       }
 

import gnu.trove.map.hash.TIntFloatHashMap; //导入依赖的package包/类
/**
 * 一次性统计概率，节约时间
 */
private void statisticProb() {
	System.out.println("统计概率");
	float totalword = alpahbet.size();
	TIntFloatIterator it = wordProb.iterator();
	while(it.hasNext()){
		it.advance();
		float v = it.value()/totalword;
		it.setValue(v);
		Cluster cluster = new Cluster(it.key(),v,alpahbet.lookupString(it.key()));
		clusters.put(it.key(), cluster);
	}

	TIntObjectIterator<TIntFloatHashMap> it1 = pcc.iterator();
	while(it1.hasNext()){
		it1.advance();
		TIntFloatHashMap map = it1.value();
		TIntFloatIterator it2 = map.iterator();
		while(it2.hasNext()){
			it2.advance();
			it2.setValue(it2.value()/totalword);
		}
	}

}
 

import gnu.trove.map.hash.TIntFloatHashMap; //导入依赖的package包/类
/**
 * 由大到小排序
 * @param map
 * @return 数组下标
 */
public static int[] sort(TIntFloatHashMap tmap) {
	HashMap<Integer, Float> map = new HashMap<Integer, Float>();

	TIntFloatIterator it = tmap.iterator();
	while (it.hasNext()) {
		it.advance();
		int id = it.key();
		float val = it.value();
		map.put(id, Math.abs(val));
	}
	it = null;

	List<Entry> list = sort(map);
	int[] idx = new int[list.size()];
	Iterator<Entry> it1 = list.iterator();
	int i=0;
	while (it1.hasNext()) {
		Entry entry = it1.next();
		idx[i++] = (Integer) entry.getKey();
	}
	return idx;
}
 

import gnu.trove.map.hash.TIntFloatHashMap; //导入依赖的package包/类
/**
 * Construct with the given parameters.
 *
 * @param minRad minimum search radius
 * @param maxRad maximum search radius
 */
public HoughCircles(int minRad, int maxRad, int radIncrement, int nDegree) {
	super();
	this.minRad = minRad;
	if(this.minRad <= 0) this.minRad = 1;
	this.maxRad = maxRad;
	this.radmap = new TIntObjectHashMap<TIntObjectHashMap<TIntFloatHashMap>>();
	this.radIncr = radIncrement;
	this.nRadius = (maxRad-minRad) / this.radIncr;
	this.nDegree = nDegree;
	this.cosanglemap = new float[nRadius][nDegree];
	this.sinanglemap = new float[nRadius][nDegree];
	for (int radIndex=0; radIndex<this.nRadius; radIndex++) {
		for (int angIndex=0; angIndex<nDegree; angIndex++) {
			double ang = angIndex * (2 * PI / nDegree);
			double rad = minRad + (radIndex * this.radIncr);
			this.cosanglemap [radIndex][angIndex] = (float) (rad*cos(ang));
			this.sinanglemap [radIndex][angIndex] = (float) (rad*sin(ang));
		}
	}
}
 

import gnu.trove.map.hash.TIntFloatHashMap; //导入依赖的package包/类
private void writeData(String filename) {
	try {
		BufferedWriter writer = new BufferedWriter(new FileWriter(filename));
		TIntFloatHashMap m;
		StringBuffer buf;
		for (int id : items) {

			buf = new StringBuffer();
			buf.append(id + "\t");
			m = map_item_intFeatures.get(id);
			int[] fIDs = m.keys();
			Arrays.sort(fIDs);
			for (int i = 0; i < fIDs.length; i++) {
				buf.append(fIDs[i] + ":" + m.get(fIDs[i]) + " ");
			}
			writer.append(buf);
			writer.newLine();

		}

		writer.flush();
		writer.close();

	} catch (IOException ex) {
		System.out.println(ex.getMessage());
	}
}
 

import gnu.trove.map.hash.TIntFloatHashMap; //导入依赖的package包/类
public UserModelRecommenderWorker(int u, BufferedWriter bw,
		TIntObjectHashMap<TIntFloatHashMap> map_item_intFeatures,
		Evaluator trainEval, Evaluator validEval, boolean silent, int topN,
		int num_features, List<Double> listC, List<Double> listEps,
		List<Integer> listSolverType, Map<Integer, Float> userTrainRatings,
		Map<Integer, Float> userValRatings, boolean implicit,
		int nValidNegEx, boolean addNegValidationEx, int timesRealFb, int minTrainEx,
		HashSet<Integer> items, float relUnknownItems, int topK, String metric) {

	this.topK = topK;
	this.metric = metric;
	this.u = u;
	this.bw = bw;
	this.map_item_intFeatures = map_item_intFeatures;
	this.trainEval = trainEval;
	this.validEval = validEval;
	this.silent = silent;
	this.topN = topN;
	this.num_features = num_features;
	this.listC = listC;
	this.listEps = listEps;
	this.listSolverType = listSolverType;
	this.userTrainRatings = userTrainRatings;
	this.userValRatings = userValRatings;
	this.implicit = implicit;
	this.relUnknownItems = relUnknownItems;
	this.nValidNegEx = nValidNegEx;
	this.timesRealFb = timesRealFb;
	this.minTrainEx = minTrainEx;
	this.items = items;
	this.addNegValidationEx = addNegValidationEx;
	originalTrainItems = new HashSet<Integer>();

}
 

import gnu.trove.map.hash.TIntFloatHashMap; //导入依赖的package包/类
public UserProfileSimilarityRecommenderWorker(int u,
		HashSet<Integer> items, BufferedWriter bw,
		TIntObjectHashMap<TIntFloatHashMap> map_item_intFeatures, int topN,
		Map<Integer, Float> userTrainRatings, boolean implicit,
		Float evalRatingThresh) {

	this.u = u;
	this.items = items;
	this.bw = bw;
	this.map_item_intFeatures = map_item_intFeatures;
	this.topN = topN;
	this.userTrainRatings = userTrainRatings;
	this.implicit = implicit;
	this.evalRatingThresh = evalRatingThresh;
}
 

import gnu.trove.map.hash.TIntFloatHashMap; //导入依赖的package包/类
private float cmpCosineSim(TIntFloatHashMap v1, TIntFloatHashMap v2) {

		TIntHashSet inters = new TIntHashSet();
		inters.addAll(v1.keySet());
		inters.retainAll(v2.keySet());

		if (inters.size() == 0)
			return 0;
		else {
			int i = 0;
			TIntIterator it = inters.iterator();
			float num = 0;
			float norm_v1 = 0;
			float norm_v2 = 0;
			while (it.hasNext()) {
				i = it.next();
				num += v1.get(i) * v2.get(i);
			}
			for (int k1 : v1.keys())
				norm_v1 += (v1.get(k1) * v1.get(k1));
			for (int k2 : v2.keys())
				norm_v2 += (v2.get(k2) * v2.get(k2));
			return num / (float) (Math.sqrt(norm_v1) * Math.sqrt(norm_v2));

		}

	}
 

import gnu.trove.map.hash.TIntFloatHashMap; //导入依赖的package包/类
private void loadItemFeatureData(String file_name) {

		BufferedReader br;
		try {
			br = new BufferedReader(new FileReader(file_name));
			String line = null;
			int count = 0;
			while ((line = br.readLine()) != null) {
				try {
					String[] vals = line.split("\t");
					int id = Integer.parseInt(vals[0]);

					if (items.contains(id)) {

						map_item_intFeatures.put(id, new TIntFloatHashMap());

						String[] values = vals[1].trim().split(" ");
						for (int i = 0; i < values.length; i++) {
							String[] pair = values[i].split(":");
							int fId = Integer.parseInt(pair[0]);
							float fVal = Float.parseFloat(pair[1]);
							map_item_intFeatures.get(id).put(fId, fVal);
						}
						count++;
					}
				} catch (Exception ex) {
					// System.out.println(ex.getMessage());
					// System.out.println(line);
				}
			}
			logger.info("item metadata loaded for evaluation - " + count
					+ " items");
			br.close();
		} catch (IOException e) {
			e.printStackTrace();
		}

	}
 

import gnu.trove.map.hash.TIntFloatHashMap; //导入依赖的package包/类
public static TIntObjectHashMap<TIntFloatHashMap> loadInputUsersRatings(String file) {
	TIntObjectHashMap<TIntFloatHashMap> user_rating =new TIntObjectHashMap<TIntFloatHashMap>();
	try {
		BufferedReader br = new BufferedReader(new FileReader(file));
		String line = null;
		float rate;
		int user_id, item_id;

		while ((line = br.readLine()) != null) {
			String[] vals = line.split("\t");
			
			if(vals.length==2)
				rate=1;
			else
				rate = Float.parseFloat(vals[2]);
			
			user_id = Integer.parseInt(vals[0]);
			item_id = Integer.parseInt(vals[1]);

			user_rating.putIfAbsent(user_id, new TIntFloatHashMap());
			user_rating.get(user_id).put(item_id, rate);

		}

		br.close();
	} catch (Exception e) {
		e.printStackTrace();
	}
	return user_rating;
}
 

import gnu.trove.map.hash.TIntFloatHashMap; //导入依赖的package包/类
/**
 * Constuctor
 */
public UserPathExtractorWorker(int user_id, TIntFloatHashMap trainRatings,
                               TIntFloatHashMap validationRatings, ArrayList<String> items_id,
                               BufferedWriter train_file, BufferedWriter validation_file,
                               BufferedWriter test_file, boolean normalize,
                               THashMap<String, String> items_path_index, String path_file,
                               TObjectIntHashMap<String> path_index, THashMap<String, String> paths,
                               int user_items_sampling, float ratesThreshold,
                               TIntObjectHashMap<TIntHashSet> items_link) {

    this.user_id = user_id;
    this.items_id = items_id;
    this.trainRatings = trainRatings;
    this.validationRatings = validationRatings;
    this.train_file = train_file;
    this.validation_file = validation_file;
    this.test_file = test_file;
    this.normalize = normalize;
    this.items_path_index = items_path_index;
    this.path_index = path_index;
    this.paths = paths;
    this.path_file = path_file;
    this.user_items_sampling = user_items_sampling;
    this.ratesThreshold = ratesThreshold;
    this.items_link = items_link;

}