package com.slyk.sdp.algorithms.externalAlgorithms.fpTree;import java.util.ArrayList;
import java.util.List;/*** 描述：fpTree树节点* * @param <T>** @author <a href='mailto:xiaomingyang@shulianyikang.com'>xiaomingyang</a>* @created on 2019年5月23日，下午8:01:46*/
public class FpTreeNode<T> {/*** 当前节点频繁度*/private long count = 0;/*** 节点内容值*/private T nodeVal;/*** 父类节点*/private FpTreeNode<T> parent = null;/*** 当前节点子节点*/private List<FpTreeNode<T>> children = null;/*** helper*/private FpTreeHelper<T> helper = null;public FpTreeNode(long count, T nodeVal, FpTreeNode<T> parent, List<FpTreeNode<T>> children,FpTreeHelper<T> helper) {super();this.count = count;this.nodeVal = nodeVal;this.parent = parent;this.children = children;this.helper = helper;}/*** 描述：添加子节点** @param child* @return 被添加的子节点* @author <a href='mailto:xiaomingyang@shulianyikang.com'>xiaomingyang</a>* @created on 2019年5月23日，下午7:33:13*/public FpTreeNode<T> addChild(FpTreeNode<T> child) {if (this.getChildren() == null) {children = new ArrayList<FpTreeNode<T>>();}child.setParent(this);this.children.add(child);return child;}/*** 描述：向当前节点添加路径* <br/>* List结构数据前一项为后一项数据父节点，例：<br/>* a,b,c,d</br>* <table border="1px" cellspacing="0px">* <tr><th>节点</th><th>父节点</th></tr>* <tr><td>a</td><td>null</td></tr>* <tr><td>b</td><td>a</td></tr>* <tr><td>c</td><td>b</td></tr>* <tr><td>d</td><td>c</td></tr>* </table>* * @param path 树的一条路径，是某个事物下的数据记录列表* @param parentNode 路径第一个节点的父节点* @return * @author <a href='mailto:xiaomingyang@shulianyikang.com'>xiaomingyang</a>* @created on 2019年5月25日，下午9:42:41*/public void addPath(List<T> path, FpTreeNode<T> parentNode) {if (path == null || path.size() == 0) {return ;}T firstEl = path.get(0);if (parentNode != null && helper.nodeCompare(firstEl, parentNode.getNodeVal())) {parentNode.increaseCountOne();parentNode.addPath(path.subList(1, path.size()), parentNode);} else {FpTreeNode<T> fnode = new FpTreeNode<T>(1, firstEl, null, null, this.getHelper()); FpTreeNode<T> exsistChild = this.findChild(fnode.getNodeVal());if (exsistChild != null) {exsistChild.increaseCountOne();exsistChild.addPath(path.subList(1, path.size()), exsistChild);} else {FpTreeNode<T> node = this.addChild(fnode);node.addPath(path.subList(1, path.size()), node);}}}/*** 描述：计数器加一** @return 当前节点计数器* @author <a href='mailto:xiaomingyang@shulianyikang.com'>xiaomingyang</a>* @created on 2019年5月23日，下午7:36:21*/public long increaseCountOne() {return this.increaseCount(1);}/*** 描述：** @param increasement* @return 当前节点计数器* @author <a href='mailto:xiaomingyang@shulianyikang.com'>xiaomingyang</a>* @created on 2019年5月23日，下午7:37:16*/public long increaseCount(long increasement) {this.count += increasement;return this.count;}/*** 描述： 当前节点寻找指定子节点,有，则返回节点，无则返回null** @param childVal* @return* @author <a href='mailto:xiaomingyang@shulianyikang.com'>xiaomingyang</a>* @created on 2019年5月23日，下午7:41:42*/public FpTreeNode<T> findChild(T childVal) {if (children == null) {return null;}for (FpTreeNode<T> child : children) {if (helper.nodeCompare(child.getNodeVal(), childVal)) {return child;}}return null;}@Overridepublic String toString() {return super.toString() + "-node (val:" + this.getNodeVal() + ", count: " + this.getCount() + ")";}public long getCount() {return count;}public void setCount(long count) {this.count = count;}public T getNodeVal() {return nodeVal;}public void setNodeVal(T nodeVal) {this.nodeVal = nodeVal;}public FpTreeNode<T> getParent() {return parent;}public void setParent(FpTreeNode<T> parent) {this.parent = parent;}public List<FpTreeNode<T>> getChildren() {return children;}public void setChildren(List<FpTreeNode<T>> children) {this.children = children;}public FpTreeHelper<T> getHelper() {return helper;}public void setHelper(FpTreeHelper<T> helper) {this.helper = helper;}
}

package com.slyk.sdp.algorithms.externalAlgorithms.fpTree;import java.util.ArrayList;
import java.util.Comparator;
import java.util.Iterator;
import java.util.LinkedHashMap;
import java.util.LinkedList;
import java.util.List;
import java.util.Map;
import java.util.Set;import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import org.springframework.util.Assert;import com.slyk.sdp.algorithms.externalAlgorithms.fpTree.util.ListSortUtils;/*** 描述：fptree项头表* * @param <K>** @author <a href='mailto:xiaomingyang@shulianyikang.com'>xiaomingyang</a>* @created on 2019年5月23日，下午8:05:14*/
@SuppressWarnings("hiding")
public class FpTreeHeader<K, Integer> extends LinkedHashMap <K, java.lang.Integer> {private static Logger logger = LoggerFactory.getLogger(FpTreeHeader.class);private static final long serialVersionUID = 1L;/*** 过滤、排序后的原始数据,用以做构建fptree输入数据*/private List<List<K>> inputData = new LinkedList<List<K>>();/*** helper*/private FpTreeHelper<K> helper;/*** 节点链,fptree构建后依据项头表建立的节点链列表*/private Map<K, List<FpTreeNode<K>>> treeNodeMap = new LinkedHashMap<K, List<FpTreeNode<K>>>();/*** 描述：添加helper** @param helper* @return* @author <a href='mailto:xiaomingyang@shulianyikang.com'>xiaomingyang</a>* @created on 2019年5月29日，上午10:54:18*/public FpTreeHeader<K, Integer> addHelper( FpTreeHelper<K> helper) {this.setHelper(helper);return this;}/*** 描述: 构建节点链列表** @param node* @author <a href='mailto:xiaomingyang@shulianyikang.com'>xiaomingyang</a>* Created On 2019年5月29日, 上午1:13:27*/protected void buildNodeEntryList(FpTreeNode<K> node) {if (node.getCount() != -1) {List<FpTreeNode<K>> nodeList = treeNodeMap.get(node.getNodeVal());if (nodeList == null) {nodeList = new ArrayList<FpTreeNode<K>>();nodeList.add(node);treeNodeMap.put(node.getNodeVal(), nodeList);} else {nodeList.add(node);}}if (node.getChildren() == null) {return ;}for (FpTreeNode<K> child : node.getChildren()) {buildNodeEntryList(child);}}/*** 描述：构建项头表** @param sourceData* @param absSupport* @return* @author <a href='mailto:xiaomingyang@shulianyikang.com'>xiaomingyang</a>* @created on 2019年5月23日，下午8:36:58*/@SuppressWarnings("unchecked")public FpTreeHeader<K, Integer> buildTable(List<List<K>> sourceData, int absSupport) {Assert.notNull(this.helper, "helper cannot be null, Set helper first!");logger.debug("构建项头表.");for (List<K> data : sourceData) {for (K k : data) {if (this.get(k) == null) {this.put(k, 1);} else {this.put(k, this.get(k) + 1);}}}// 过滤不满足项目Set<java.util.Map.Entry<K, java.lang.Integer>> set = this.entrySet();Iterator<java.util.Map.Entry<K, java.lang.Integer>> ite = set.iterator();while (ite.hasNext()) {java.util.Map.Entry<K, java.lang.Integer> entry = ite.next();if (entry.getValue() < absSupport) {ite.remove();}}// 项头表排序List<K> keylist = new ArrayList<K>(this.keySet());Map<K, Integer> thisRef = (Map<K, Integer>) new LinkedHashMap<String, Integer>();ListSortUtils.sort(keylist, this.getHelper().nodeEleCompare((FpTreeHeader<K, java.lang.Integer>) this));for (K k : keylist) {thisRef.put(k, (Integer) this.get(k));}this.clear();this.putAll((Map<? extends K, ? extends java.lang.Integer>) thisRef);// 对原始输入数据过滤并排序for (List<K> data : sourceData) {for (Iterator<K> itr = data.iterator(); itr.hasNext(); ) {K k = itr.next();if (!this.containsKey(k)) {itr.remove();}}FpTreeHeader<K, java.lang.Integer> _this = (FpTreeHeader<K, java.lang.Integer>) this;ListSortUtils.sort(data, new Comparator<K>() {@Overridepublic int compare(K o1, K o2) {int i = _this.get(o2) - _this.get(o1);if (i == 0) {Iterator<java.util.Map.Entry<K, java.lang.Integer>> itr = _this.entrySet().iterator();int index1 = 0;int index2 = 0;for (int a = 0,b = 0; itr.hasNext(); ) {a = a + 1;b = b + 1;java.util.Map.Entry<K, java.lang.Integer> entry = itr.next();if (helper.nodeCompare(entry.getKey(), o1)) {index1 = a;} else if (helper.nodeCompare(entry.getKey(), o2)) {index2 = b;}}i = index1 - index2;}return i;}});if (!data.isEmpty()) {inputData.add(data);}}sourceData = null;logger.debug("构建项头表完成.");return this;}public List<List<K>> getInputData() {return inputData;}public void setInputData(List<List<K>> inputData) {this.inputData = inputData;}public FpTreeHelper<K> getHelper() {return helper;}public void setHelper(FpTreeHelper<K> helper) {this.helper = helper;}public Map<K, List<FpTreeNode<K>>> getTreeNodeMap() {return treeNodeMap;}public void setTreeNodeMap(Map<K, List<FpTreeNode<K>>> treeNodeMap) {this.treeNodeMap = treeNodeMap;}
}

package com.slyk.sdp.algorithms.externalAlgorithms.fpTree;import java.io.ByteArrayInputStream;
import java.io.ByteArrayOutputStream;
import java.io.IOException;
import java.io.ObjectInputStream;
import java.io.ObjectOutputStream;
import java.util.ArrayList;
import java.util.Collections;
import java.util.Iterator;
import java.util.LinkedHashMap;
import java.util.List;
import java.util.ListIterator;
import java.util.Map;
import java.util.Set;import org.apache.commons.lang3.StringUtils;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import org.springframework.util.Assert;import com.slyk.sdp.algorithms.externalAlgorithms.fpTree.util.DoubleKeyMap;/*** FPtree* * 描述：@param <T>** @author <a href='mailto:xiaomingyang@shulianyikang.com'>xiaomingyang</a>* @created on 2019年6月3日，下午1:34:22*/
public class FpTree<T> {private static Logger logger = LoggerFactory.getLogger(FpTree.class);/*** 项头表*/private FpTreeHeader<T, Integer> fpTreeHeader;/*** helper*/private FpTreeHelper<T> helper;/*** root node*/private FpTreeNode<T> root;/*** 默认频繁度阈值*/protected static final int DEFAULT_ABS_SUPPORT = 0xf;private int absSupport = DEFAULT_ABS_SUPPORT;/*** 默认置信度*/private static final int DEFAULT_CONFIDENT = 3;/*** 置信度*/private int confident = DEFAULT_CONFIDENT;/*** 描述：挖掘树* <br/>代码参考自《机器学习实战》** @param outList* @param tree* @param basePat* @return* @throws ClassNotFoundException* @throws IOException* @author <a href='mailto:xiaomingyang@shulianyikang.com'>xiaomingyang</a>* @created on 2019年5月31日，下午5:50:45*/public List<List<T>> fpGrowth(List<List<T>> outList, FpTree<T> tree, List<T> prefix) throws ClassNotFoundException, IOException {logger.debug("开始conditionFpTree数据挖掘计算.");//// 挖掘频繁项集的步骤如下：// 1 从FP树提取条件模式基// 2 用条件模式基构造FP树// 3 重复1和2直到树只包含一个元素//
        DoubleKeyMap<T, List<T>, Integer> cpbs = tree.buildPrefixPath();// 从项头表逆序访问ListIterator<Map.Entry<T, Integer>> li =new ArrayList<Map.Entry<T, Integer>>(this.fpTreeHeader.entrySet()).listIterator(this.fpTreeHeader.size()); for ( ;li.hasPrevious(); ) {Map.Entry<T, Integer> entry = li.previous(); T fpHeaderItem = entry.getKey();List<T> newBasePat = new ArrayList<T>(prefix);newBasePat.add(fpHeaderItem);this.getHelper().resultHandler(newBasePat, confident, entry.getValue());logger.debug("发现频繁项集：" + newBasePat.toString());Set<List<T>> set = cpbs.get(fpHeaderItem).keySet();Iterator<List<T>> setItr = set.iterator();Map<String, List<T>> cpbInputData = new LinkedHashMap<String, List<T>>();for ( ; setItr.hasNext(); ) {List<T> cpb = setItr.next();Integer count = cpbs.get(fpHeaderItem, cpb);for (int repeat = 0; repeat < count; repeat++) {if (!cpb.isEmpty()) {cpbInputData.put(cpb.toString() + "-" + repeat, cpb);}}}FpTree<T> cpbTree = new FpTree<T>();cpbTree.setHelper(this.getHelper());cpbTree = cpbTree.init(this.getAbsSupport(), this.getConfident(), cpbInputData);if (!cpbTree.getFpTreeHeader().keySet().isEmpty()) {cpbTree.fpGrowth(outList, cpbTree, newBasePat);}cpbTree = null;cpbInputData = null;}logger.debug("完成conditionFpTree数据挖掘计算.");return outList;}/*** 描述：初始、构建fptree，为数据挖掘做准备* <br/>* <strong>* 输入sourceMap数据结构：</br>* KEY&emsp;&emsp;            LIST</br>* T0&emsp;&emsp;             1,2,3,4</br>* T1&emsp;&emsp;             1</br>* T2&emsp;&emsp;             3,4</br>* T3&emsp;&emsp;             2,3</br>* </strong>* * @param absSupport* @param sourceMap* @return* @author <a href='mailto:xiaomingyang@shulianyikang.com'>xiaomingyang</a>* @created on 2019年5月29日，上午11:53:11*/public FpTree<T> init(Integer absSupport, Integer confident, Map<String, List<T>> sourceMap) {logger.debug("开始fptree构建.");this.absSupport = absSupport == null ? this.getAbsSupport() : absSupport;this.confident = confident == null ? this.getConfident() : confident;List<List<T>> sourceData = new ArrayList<List<T>>();Set<String> keys = sourceMap.keySet();for (String key : keys) {List<T> inList = sourceMap.get(key);sourceData.add(inList);}this.fpTreeHeader = new FpTreeHeader<T, Integer>().addHelper(helper).buildTable(sourceData, absSupport);sourceData = null;root = buildTree();//        logger.info("构建构建节点链.");this.fpTreeHeader.buildNodeEntryList(root);
//        logger.info("构建构建节点链完成.");logger.debug("完成fptree构建..");return this;} /*** 描述：构建条件模式基** @return* @author <a href='mailto:xiaomingyang@shulianyikang.com'>xiaomingyang</a>* @created on 2019年5月29日，下午2:37:47*/public DoubleKeyMap<T, List<T>, Integer> buildPrefixPath() {Assert.notNull(this.fpTreeHeader, "fpTreeHeader cannot be null, Set helper first!");logger.debug("构建条件模式基");DoubleKeyMap<T, List<T>, Integer> cpb = new DoubleKeyMap<T, List<T>, Integer>();// 从项头表逆序寻找条件模式集ListIterator<Map.Entry<T, Integer>> li =new ArrayList<Map.Entry<T, Integer>>(this.fpTreeHeader.entrySet()).listIterator(this.fpTreeHeader.size()); for ( ;li.hasPrevious(); ) {Map.Entry<T, Integer> entry = li.previous(); T fpHeaderItem = entry.getKey();List<FpTreeNode<T>> nodeList = this.getFpTreeHeader().getTreeNodeMap().get(fpHeaderItem);for (FpTreeNode<T> node : nodeList) {cpb = findPrefixPath(node, cpb);}}logger.debug("完成构建条件模式基");return cpb;}/*** 描述：寻找条件模式基** @param node 节点链中的节点* @return* @author <a href='mailto:xiaomingyang@shulianyikang.com'>xiaomingyang</a>* @created on 2019年5月27日，上午1:05:45*/private DoubleKeyMap<T, List<T>, Integer> findPrefixPath(FpTreeNode<T> node, DoubleKeyMap<T, List<T>, Integer> cpb) {Assert.notNull(this.fpTreeHeader, "fpTreeHeader cannot be null, Set helper first!");List<T> prefixPath = new ArrayList<T>();FpTreeNode<T> up = node.getParent();while (up.getParent() != null) {prefixPath.add(up.getNodeVal());up = up.getParent();}Collections.reverse(prefixPath);cpb.put(node.getNodeVal(), prefixPath, (int) node.getCount());return cpb;}/*** 描述：构建fptree** @return* @author <a href='mailto:xiaomingyang@shulianyikang.com'>xiaomingyang</a>* @created on 2019年5月24日，上午11:45:34*/private FpTreeNode<T> buildTree() {Assert.notNull(this.helper, "helpser cannot be null, Set helper first!");Assert.notNull(this.fpTreeHeader, "fpTreeHeader cannot be null, Set helper first!");FpTreeNode<T> rootNode = new FpTreeNode<T>(-1, null, null, null, helper);int index = 0;for (List<T> path : this.fpTreeHeader.getInputData()) {rootNode.addPath(path, rootNode);index += 1;logger.debug("fptree完成进度:" + index + "/" + this.fpTreeHeader.getInputData().size());}return rootNode;}/*** 描述: 打印树,以便直观观察** @param node* @param ins* @author <a href='mailto:xiaomingyang@shulianyikang.com'>xiaomingyang</a>* Created On 2019年5月29日, 上午12:27:43*/public void display(FpTreeNode<T> node, int ins) {if (node.getParent() == null) {logger.info("打印树形结构如下：");}System.out.print(StringUtils.repeat("  ", ins) + node.getNodeVal() + "  " + node.getCount() + "\n");if (node.getChildren() == null) {return ;}ins = ins + 1;for (FpTreeNode<T> subNode : node.getChildren()) {display(subNode, ins);}}/*** 描述：deepCopy** @param src* @return* @throws IOException* @throws ClassNotFoundException* @author <a href='mailto:xiaomingyang@shulianyikang.com'>xiaomingyang</a>* @created on 2019年5月30日，下午5:28:26*/@SuppressWarnings("unchecked")public static <T> List<T> deepCopy(List<T> src) throws IOException, ClassNotFoundException {  ByteArrayOutputStream byteOut = new ByteArrayOutputStream();  ObjectOutputStream out = new ObjectOutputStream(byteOut);  out.writeObject(src); ByteArrayInputStream byteIn = new ByteArrayInputStream(byteOut.toByteArray());  ObjectInputStream in = new ObjectInputStream(byteIn);  List<T> dest = (List<T>) in.readObject();  return dest;  }  public FpTreeHeader<T, Integer> getFpTreeHeader() {return fpTreeHeader;}public void setFpTreeHeader(FpTreeHeader<T, Integer> fpTreeHeader) {this.fpTreeHeader = fpTreeHeader;}public FpTreeHelper<T> getHelper() {return helper;}public void setHelper(FpTreeHelper<T> helper) {this.helper = helper;}public FpTreeNode<T> getRoot() {return root;}public void setRoot(FpTreeNode<T> root) {this.root = root;}public int getAbsSupport() {return absSupport;}public void setAbsSupport(int absSupport) {this.absSupport = absSupport;}public int getConfident() {return confident;}public void setConfident(int confident) {this.confident = confident;}
}

package com.slyk.sdp.algorithms.externalAlgorithms.fpTree;import java.util.Comparator;
import java.util.List;/*** 描述：fptree helper class* * @param <T>** @author <a href='mailto:xiaomingyang@shulianyikang.com'>xiaomingyang</a>* @created on 2019年5月23日，下午7:49:46*/
public interface FpTreeHelper<T> {/*** 描述：比较目标节点和源节点是否相等，等返回true,否则false** @param target* @param source* @return* @author <a href='mailto:xiaomingyang@shulianyikang.com'>xiaomingyang</a>* @created on 2019年5月23日，下午7:52:35*/boolean nodeCompare(T target, T source);/*** 描述：比较节点内容** @return* @author <a href='mailto:xiaomingyang@shulianyikang.com'>xiaomingyang</a>* @created on 2019年5月29日，上午10:42:35*/Comparator<T> nodeEleCompare(FpTreeHeader<T, Integer> header);/*** 描述: 找到的结果处理** @param result 单条记录* @param extArgs 附加参数* @author <a href='mailto:xiaomingyang@shulianyikang.com'>xiaomingyang</a>* Created On 2019年6月2日, 上午1:36:35*/void resultHandler(List<T> result, Object ...extArgs);
}

package com.slyk.sdp.algorithms.externalAlgorithms.fpTree.util;import java.util.Collection;
import java.util.HashSet;
import java.util.Iterator;
import java.util.LinkedHashMap;
import java.util.Map;
import java.util.Set;public class DoubleKeyMap<Key1, Key2, Value> {Map<Key1, Map<Key2, Value>> data = new LinkedHashMap<Key1, Map<Key2, Value>>();public Value put(Key1 k1, Key2 k2, Value v) {Map<Key2, Value> data2 = data.get(k1);Value prev = null;if ( data2==null ) {data2 = new LinkedHashMap<Key2, Value>();data.put(k1, data2);}else {prev = data2.get(k2);}data2.put(k2, v);return prev;}public Value get(Key1 k1, Key2 k2) {Map<Key2, Value> data2 = data.get(k1);if ( data2==null ) return null;return data2.get(k2);}public Map<Key2, Value> get(Key1 k1) { return data.get(k1); }/** Get all values associated with primary key */public Collection<Value> values(Key1 k1) {Map<Key2, Value> data2 = data.get(k1);if ( data2==null ) return null;return data2.values();}/** get all primary keys */public Set<Key1> keySet() {return data.keySet();}/** get all secondary keys associated with a primary key */public Set<Key2> keySet(Key1 k1) {Map<Key2, Value> data2 = data.get(k1);if ( data2==null ) return null;return data2.keySet();}public Collection<Value> values() {Set<Value> s = new HashSet<Value>();for (Map<Key2, Value> k2 : data.values()) {for (Value v : k2.values()) {s.add(v);}}return s;}@SuppressWarnings("unchecked")public void print() {System.out.println("条件模式基集合:");Set<Key1> kset = this.keySet();for (Iterator<Key1> itrKey1 = kset.iterator(); itrKey1.hasNext();) {Key1 key1 = itrKey1.next();for (Iterator<Key2> itrKey2 = this.get(key1).keySet().iterator(); itrKey2.hasNext();) {Object key2 = itrKey2.next();System.out.println(key1 + ":" + key2 + "(" + this.get(key1, (Key2) key2) + ")");}}}
}

package com.slyk.sdp.algorithms.externalAlgorithms.fpTree.util;import java.util.Comparator;
import java.util.List;
import java.util.ListIterator;/*** 描述: 求集合排序，原本集合collections包有排序功能，但是jdk7后改为 timsort排序实现，此类实现存在问题，例如： int[]* sample = new int[]* {0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,* ,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-2,1,0,-2,0,0,0,0};* 如上例子数据在timsort排序将会报错，因此排序算法将参考JDK5的LegacyMergeSort算法封装排序。** @author <a href='mailto:xiaomingyang@aksl.com.cn'>xiaomingyang</a>*         2019年6月2日,下午11:35:16* @version v0.1*/
public class ListSortUtils {/*** 描述：参考Collections.sort()方法** @param list* @param c* @author <a href='mailto:xiaomingyang@shulianyikang.com'>xiaomingyang</a>* @created on 2019年6月3日，下午1:35:04*/@SuppressWarnings({ "rawtypes", "unchecked" })public static <T> void sort(List<T> list, Comparator<? super T> c) {Object[] a = list.toArray();sort(a, (Comparator) c);ListIterator i = list.listIterator();for (int j = 0; j < a.length; j++) {i.next();i.set(a[j]);}}public static <T> void sort(T[] a, Comparator<? super T> c) {T[] aux = (T[]) a.clone();if (c == null)mergeSort(aux, a, 0, a.length, 0);elsemergeSort(aux, a, 0, a.length, 0, c);}private static final int INSERTIONSORT_THRESHOLD = 7;private static void swap(Object[] x, int a, int b) {Object t = x[a];x[a] = x[b];x[b] = t;}@SuppressWarnings({ "unchecked", "rawtypes" })private static void mergeSort(Object[] src, Object[] dest, int low,int high, int off) {int length = high - low;// Insertion sort on smallest arraysif (length < INSERTIONSORT_THRESHOLD) {for (int i = low; i < high; i++)for (int j = i; j > low&& ((Comparable) dest[j - 1]).compareTo(dest[j]) > 0; j--)swap(dest, j, j - 1);return;}// Recursively sort halves of dest into srcint destLow = low;int destHigh = high;low += off;high += off;int mid = (low + high) >> 1;mergeSort(dest, src, low, mid, -off);mergeSort(dest, src, mid, high, -off);// If list is already sorted, just copy from src to dest. This is an// optimization that results in faster sorts for nearly ordered lists.if (((Comparable) src[mid - 1]).compareTo(src[mid]) <= 0) {System.arraycopy(src, low, dest, destLow, length);return;}// Merge sorted halves (now in src) into destfor (int i = destLow, p = low, q = mid; i < destHigh; i++) {if (q >= high || p < mid&& ((Comparable) src[p]).compareTo(src[q]) <= 0)dest[i] = src[p++];elsedest[i] = src[q++];}}@SuppressWarnings({ "unchecked", "rawtypes" })private static void mergeSort(Object[] src, Object[] dest, int low,int high, int off, Comparator c) {int length = high - low;// Insertion sort on smallest arraysif (length < INSERTIONSORT_THRESHOLD) {for (int i = low; i < high; i++)for (int j = i; j > low && c.compare(dest[j - 1], dest[j]) > 0; j--)swap(dest, j, j - 1);return;}// Recursively sort halves of dest into srcint destLow = low;int destHigh = high;low += off;high += off;int mid = (low + high) >> 1;mergeSort(dest, src, low, mid, -off, c);mergeSort(dest, src, mid, high, -off, c);// If list is already sorted, just copy from src to dest. This is an// optimization that results in faster sorts for nearly ordered lists.if (c.compare(src[mid - 1], src[mid]) <= 0) {System.arraycopy(src, low, dest, destLow, length);return;}// Merge sorted halves (now in src) into destfor (int i = destLow, p = low, q = mid; i < destHigh; i++) {if (q >= high || p < mid && c.compare(src[p], src[q]) <= 0)dest[i] = src[p++];elsedest[i] = src[q++];}}
}

package com.slyk.sdp.algorithms;import java.io.BufferedReader;
import java.io.BufferedWriter;
import java.io.File;
import java.io.FileInputStream;
import java.io.FileNotFoundException;
import java.io.FileOutputStream;
import java.io.IOException;
import java.io.InputStreamReader;
import java.io.OutputStreamWriter;
import java.util.ArrayList;
import java.util.Arrays;
import java.util.Comparator;
import java.util.LinkedHashMap;
import java.util.List;
import java.util.Map;import org.apache.commons.lang3.StringUtils;import com.slyk.sdp.algorithms.externalAlgorithms.fpTree.FpTree;
import com.slyk.sdp.algorithms.externalAlgorithms.fpTree.FpTreeHeader;
import com.slyk.sdp.algorithms.externalAlgorithms.fpTree.FpTreeHelper;/*** Hello world!**/
public class App {private BufferedReader br;private static int frequency = 2;private static int confident = 3;public void getSourceData() throws IOException {Map<String, List<String>> inputMap = ReadFile();System.out.println(inputMap);}private Map<String, List<String>> ReadFile() throws IOException {Map<String, List<String>> inputMap = new LinkedHashMap<String, List<String>>();br = new BufferedReader(new InputStreamReader(this.getClass().getResourceAsStream("/input.csv")));
        String line = null;int lineNum = 0;while (null != (line = br.readLine())) {// System.out.println("T" + lineNum + ":" + line);lineNum += 1;List<String> list = Arrays.asList(line.split(","));inputMap.put("T" + lineNum, new ArrayList<String>(list));}return inputMap;}public void fpGrowth() throws IOException, ClassNotFoundException {List<List<String>> resultList = new ArrayList<List<String>>();Map<String, List<String>> inputMap = ReadFile();FpTree<String> tree = new FpTree<String>();tree.setHelper(new FpTreeHelper<String>() {private Comparator<String> comparetor = null;private File resultFile = new File("./result.txt");private BufferedWriter writer = null;private FileOutputStream fos = null;@Overridepublic boolean nodeCompare(String target, String source) {return StringUtils.equals(target, source);}/*** 节点内容需要按项头表统计数量逆序排序*/@Overridepublic Comparator<String> nodeEleCompare(FpTreeHeader<String, Integer> header) {if (comparetor == null) {comparetor = new Comparator<String>() {@Overridepublic int compare(String o1, String o2) {int i = header.get(o2) - header.get(o1);return i;}  };}return comparetor;}@Overridepublic void resultHandler(List<String> result, Object ...extArgs) {try {if (result.size() < (int) extArgs[0]) {return ;}resultList.add(result);fos = new FileOutputStream(resultFile, true);writer = new BufferedWriter(new OutputStreamWriter(fos));writer.write(result.toString() + "   " + (int)extArgs[1] + "\r\n");writer.flush();fos.flush();writer.close();fos.close();System.out.println(result);} catch (FileNotFoundException e) {e.printStackTrace();} catch (IOException e) {e.printStackTrace();}}});tree.fpGrowth(new ArrayList<List<String>>(), tree.init(2, 2, inputMap), new ArrayList<String>());tree.display(tree.getRoot(), 2);System.out.println("===========================");for (Object o : resultList) {System.out.println(o);}}public static void main(String[] args) throws IOException, ClassNotFoundException {App app = new App();app.fpGrowth();}
}

[4e953a9700fc3a4de58eb3b066eb4c74, 6d7e042a000deca140c330ab99896ebd]
[4e953a9700fc3a4de58eb3b066eb4c74, 6d7e042a000deca140c330ab99896ebd, 6f9ef114e4478a961bf3e59d6441f243]
[4e953a9700fc3a4de58eb3b066eb4c74, 40b0229cbf83c8857e8c9e7d79bec8e9]
[4e953a9700fc3a4de58eb3b066eb4c74, 40b0229cbf83c8857e8c9e7d79bec8e9, a0a5dff287d5f43498a81934df34f6e1]
[4e953a9700fc3a4de58eb3b066eb4c74, 40b0229cbf83c8857e8c9e7d79bec8e9, a0a5dff287d5f43498a81934df34f6e1, 6f9ef114e4478a961bf3e59d6441f243]
[4e953a9700fc3a4de58eb3b066eb4c74, 40b0229cbf83c8857e8c9e7d79bec8e9, 6f9ef114e4478a961bf3e59d6441f243]
[4e953a9700fc3a4de58eb3b066eb4c74, a0a5dff287d5f43498a81934df34f6e1]
[4e953a9700fc3a4de58eb3b066eb4c74, a0a5dff287d5f43498a81934df34f6e1, 6f9ef114e4478a961bf3e59d6441f243]
[4e953a9700fc3a4de58eb3b066eb4c74, 6f9ef114e4478a961bf3e59d6441f243]
[157d68a0e73262e443ad843e7d29195f, 4f312b0f37bf9d86333114a4f467ddc3]
[6d7e042a000deca140c330ab99896ebd, 6f9ef114e4478a961bf3e59d6441f243]
[60dec45d8b4bbda8681e85f05e979f95, 4b041b8fab2bd834e6acc34a541520cb]
[dd416340a4613c46ed12b87717e4a8ac, 40b0229cbf83c8857e8c9e7d79bec8e9]
[dd416340a4613c46ed12b87717e4a8ac, 40b0229cbf83c8857e8c9e7d79bec8e9, a0a5dff287d5f43498a81934df34f6e1]
[dd416340a4613c46ed12b87717e4a8ac, a0a5dff287d5f43498a81934df34f6e1]
[40b0229cbf83c8857e8c9e7d79bec8e9, a0a5dff287d5f43498a81934df34f6e1]
[40b0229cbf83c8857e8c9e7d79bec8e9, 6f9ef114e4478a961bf3e59d6441f243]
[40b0229cbf83c8857e8c9e7d79bec8e9, 6f9ef114e4478a961bf3e59d6441f243, a0a5dff287d5f43498a81934df34f6e1]
[a0a5dff287d5f43498a81934df34f6e1, 6f9ef114e4478a961bf3e59d6441f243]

'''
Created on Jun 14, 2011
FP-Growth FP means frequent pattern
the FP-Growth algorithm needs:
1. FP-tree (class treeNode)
2. header table (use dict)This finds frequent itemsets similar to apriori but does not
find association rules.  @author: Peter
'''
class treeNode:def __init__(self, nameValue, numOccur, parentNode):self.name = nameValueself.count = numOccurself.nodeLink = Noneself.parent = parentNode      #needs to be updatedself.children = {} def inc(self, numOccur):self.count += numOccurdef disp(self, ind=1):print '  '*ind, self.name, ' ', self.countfor child in self.children.values():child.disp(ind+1)def createTree(dataSet, minSup=1): #create FP-tree from dataset but don't mineheaderTable = {}#go over dataSet twicefor trans in dataSet:#first pass counts frequency of occurancefor item in trans:headerTable[item] = headerTable.get(item, 0) + dataSet[trans]for k in headerTable.keys():  #remove items not meeting minSupif headerTable[k] < minSup: del(headerTable[k])freqItemSet = set(headerTable.keys())#print 'freqItemSet: ',freqItemSetif len(freqItemSet) == 0: return None, None  #if no items meet min support -->get outfor k in headerTable:headerTable[k] = [headerTable[k], None] #reformat headerTable to use Node link #print 'headerTable: ',headerTableretTree = treeNode('Null Set', 1, None) #create treefor tranSet, count in dataSet.items():  #go through dataset 2nd timelocalD = {}for item in tranSet:  #put transaction items in orderif item in freqItemSet:localD[item] = headerTable[item][0]if len(localD) > 0:orderedItems = [v[0] for v in sorted(localD.items(), key=lambda p: p[1], reverse=True)]updateTree(orderedItems, retTree, headerTable, count)#populate tree with ordered freq itemsetreturn retTree, headerTable #return tree and header tabledef updateTree(items, inTree, headerTable, count):if items[0] in inTree.children:#check if orderedItems[0] in retTree.childreninTree.children[items[0]].inc(count) #incrament countelse:   #add items[0] to inTree.childreninTree.children[items[0]] = treeNode(items[0], count, inTree)if headerTable[items[0]][1] == None: #update header table headerTable[items[0]][1] = inTree.children[items[0]]else:updateHeader(headerTable[items[0]][1], inTree.children[items[0]])if len(items) > 1:#call updateTree() with remaining ordered itemsupdateTree(items[1::], inTree.children[items[0]], headerTable, count)def updateHeader(nodeToTest, targetNode):   #this version does not use recursionwhile (nodeToTest.nodeLink != None):    #Do not use recursion to traverse a linked list!nodeToTest = nodeToTest.nodeLinknodeToTest.nodeLink = targetNodedef ascendTree(leafNode, prefixPath): #ascends from leaf node to rootif leafNode.parent != None:prefixPath.append(leafNode.name)ascendTree(leafNode.parent, prefixPath)def findPrefixPath(basePat, treeNode): #treeNode comes from header tablecondPats = {}while treeNode != None:prefixPath = []ascendTree(treeNode, prefixPath)if len(prefixPath) > 1: condPats[frozenset(prefixPath[1:])] = treeNode.counttreeNode = treeNode.nodeLinkreturn condPatsdef mineTree(inTree, headerTable, minSup, preFix, freqItemList):bigL = [v[0] for v in sorted(headerTable.items(), key=lambda p: p[1])]#(sort header table)for basePat in bigL:  #start from bottom of header tablenewFreqSet = preFix.copy()newFreqSet.add(basePat)#print 'finalFrequent Item: ',newFreqSet    #append to set
        freqItemList.append(newFreqSet)condPattBases = findPrefixPath(basePat, headerTable[basePat][1])#print 'condPattBases :',basePat, condPattBases#2. construct cond FP-tree from cond. pattern basemyCondTree, myHead = createTree(condPattBases, minSup)#print 'head from conditional tree: ', myHeadif myHead != None: #3. mine cond. FP-tree#print 'conditional tree for: ',newFreqSet#myCondTree.disp(1)
            mineTree(myCondTree, myHead, minSup, newFreqSet, freqItemList)def loadSimpDat():simpDat = [['r', 'z', 'h', 'j', 'p'],['z', 'y', 'x', 'w', 'v', 'u', 't', 's'],['z'],['r', 'x', 'n', 'o', 's'],['y', 'r', 'x', 'z', 'q', 't', 'p'],['y', 'z', 'x', 'e', 'q', 's', 't', 'm']]return simpDatdef createInitSet(dataSet):retDict = {}for trans in dataSet:# retDict[frozenset(trans)] = 1retDict[frozenset(trans)] = retDict.get(frozenset(trans), 0) + 1return retDictimport twitter
from time import sleep
import redef textParse(bigString):urlsRemoved = re.sub('(http:[/][/]|www.)([a-z]|[A-Z]|[0-9]|[/.]|[~])*', '', bigString)    listOfTokens = re.split(r'\W*', urlsRemoved)return [tok.lower() for tok in listOfTokens if len(tok) > 2]def getLotsOfTweets(searchStr):CONSUMER_KEY = ''CONSUMER_SECRET = ''ACCESS_TOKEN_KEY = ''ACCESS_TOKEN_SECRET = ''api = twitter.Api(consumer_key=CONSUMER_KEY, consumer_secret=CONSUMER_SECRET,access_token_key=ACCESS_TOKEN_KEY, access_token_secret=ACCESS_TOKEN_SECRET)#you can get 1500 results 15 pages * 100 per pageresultsPages = []for i in range(1,15):print "fetching page %d" % isearchResults = api.GetSearch(searchStr, per_page=100, page=i)resultsPages.append(searchResults)sleep(6)return resultsPagesdef mineTweets(tweetArr, minSup=5):parsedList = []for i in range(14):for j in range(100):parsedList.append(textParse(tweetArr[i][j].text))initSet = createInitSet(parsedList)myFPtree, myHeaderTab = createTree(initSet, minSup)myFreqList = []mineTree(myFPtree, myHeaderTab, minSup, set([]), myFreqList)return myFreqListsimpDat = []
for line in open('/home/xxxxxxx/yyyyyy/input.csv', 'r'):simpDat.append(line.replace("\n", "").split(","))minSup = 2
initSet = createInitSet(simpDat)
myFPtree, myHeaderTab = createTree(initSet, minSup)
myFreqList = []
mineTree(myFPtree, myHeaderTab, minSup, set([]), myFreqList)
for i in myFreqList:if len(i) < 2:continueprint iprint '============================'
myFPtree.disp()
#############################333
#minSup = 3
#simpDat = loadSimpDat()
#initSet = createInitSet(simpDat)
#myFPtree, myHeaderTab = createTree(initSet, minSup)
#myFPtree.disp()
#myFreqList = []
#mineTree(myFPtree, myHeaderTab, minSup, set([]), myFreqList)
#for i in myFreqList:
#    print i

set(['157d68a0e73262e443ad843e7d29195f', '4f312b0f37bf9d86333114a4f467ddc3'])
set(['6f9ef114e4478a961bf3e59d6441f243', '40b0229cbf83c8857e8c9e7d79bec8e9'])
set(['a0a5dff287d5f43498a81934df34f6e1', '6f9ef114e4478a961bf3e59d6441f243', '40b0229cbf83c8857e8c9e7d79bec8e9'])
set(['a0a5dff287d5f43498a81934df34f6e1', '40b0229cbf83c8857e8c9e7d79bec8e9'])
set(['a0a5dff287d5f43498a81934df34f6e1', 'dd416340a4613c46ed12b87717e4a8ac'])
set(['40b0229cbf83c8857e8c9e7d79bec8e9', 'dd416340a4613c46ed12b87717e4a8ac'])
set(['a0a5dff287d5f43498a81934df34f6e1', '40b0229cbf83c8857e8c9e7d79bec8e9', 'dd416340a4613c46ed12b87717e4a8ac'])
set(['a0a5dff287d5f43498a81934df34f6e1', '4e953a9700fc3a4de58eb3b066eb4c74'])
set(['a0a5dff287d5f43498a81934df34f6e1', '6f9ef114e4478a961bf3e59d6441f243', '4e953a9700fc3a4de58eb3b066eb4c74'])
set(['4e953a9700fc3a4de58eb3b066eb4c74', '40b0229cbf83c8857e8c9e7d79bec8e9'])
set(['a0a5dff287d5f43498a81934df34f6e1', '4e953a9700fc3a4de58eb3b066eb4c74', '40b0229cbf83c8857e8c9e7d79bec8e9'])
set(['6f9ef114e4478a961bf3e59d6441f243', '4e953a9700fc3a4de58eb3b066eb4c74', '40b0229cbf83c8857e8c9e7d79bec8e9'])
set(['a0a5dff287d5f43498a81934df34f6e1', '6f9ef114e4478a961bf3e59d6441f243', '4e953a9700fc3a4de58eb3b066eb4c74', '40b0229cbf83c8857e8c9e7d79bec8e9'])
set(['6f9ef114e4478a961bf3e59d6441f243', '4e953a9700fc3a4de58eb3b066eb4c74'])
set(['60dec45d8b4bbda8681e85f05e979f95', '4b041b8fab2bd834e6acc34a541520cb'])
set(['6f9ef114e4478a961bf3e59d6441f243', '6d7e042a000deca140c330ab99896ebd'])
set(['4e953a9700fc3a4de58eb3b066eb4c74', '6d7e042a000deca140c330ab99896ebd'])
set(['6f9ef114e4478a961bf3e59d6441f243', '4e953a9700fc3a4de58eb3b066eb4c74', '6d7e042a000deca140c330ab99896ebd'])
set(['a0a5dff287d5f43498a81934df34f6e1', '6f9ef114e4478a961bf3e59d6441f243'])

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