Java Implementation of the classic Sorting Algorithm and java Implementation of the Sorting Algorithm

Java Implementation of the classic Sorting Algorithm and java Implementation of the Sorting Algorithm

1/** 2*3 * @ author yuzhiping 4 * @ version 1.0 5 * function description: typical Computer Algorithms 6*7 */8 public class sortAlgorithm <T extends Comparable <T> {9 10 // exchange index I and index j Values 11 private void swap (T [] data, int I, int j) {12 T tmp; 13 tmp = data [I]; 14 data [I] = data [j]; 15 data [j] = tmp; 16} 17 18 19 // ----- heap sorting time complexity O (nlogn) ----- 20 21 public void heapSort (T [] data) {22 int arrayLength = data. length; 23 // loop parts heap 24 for (int I = 0; I <arrayLength-1; I ++) {25 // build heap 26 builMaxdHeap (data, arrayLength-1-I); 27 // swap heap top and last element 28 swap (data, 0, arrayLength-1-I); 29 30} 31} 32 33 // create a large top heap for the data array from 0 to lastIndex 34 private void builMaxdHeap (T [] data, int lastIndex) {35 // starting from the parent node of the node (last node) at lastIndex 36 for (int I = (lastIndex-1)/2; I> = 0; I --) {37 // k Save the 38 int k = I of the node currently being determined; 39 // if the child node of the current k node has 40 while (k * 2 + 1 <= last Index) {41 // Index of the Left subnode of k node 42 int biggerIndex = 2 * k + 1; 43 // If biggerIndex is smaller than lastIndex, that is, biggerIndex + 1 44 // indicates that the right child node of the k node has 45 if (biggerIndex <lastIndex) {46 // if the value of the right subnode is greater than 47 if (data [biggerIndex]. compareTo (data [biggerIndex + 1]) <0) {48 // biggerIndex always records the index of the large subnode 49 biggerIndex ++; 50} 51} 52 // if the value of k node is smaller than the value of its larger subnode, 53 if (data [k]. compareTo (data [biggerIndex]) <0) {54 // exchange them 55 swap (data, K, biggerIndex); 56 // assign biggerIndex to k to start the next loop of the while loop, 57 // re-ensure that the value of k nodes is greater than the value of its left and right subnodes. 58 k = biggerIndex; 59} else {60 break; 61} 62} 63} 64} 65 66 // ----- time complexity O (n ^ 2) ----- 67 public void bubbleSort (T [] data) {68 int I, j; 69 for (I = 0; I <data. length-1; I ++) {70 for (j = 0; j <data. length-i-1; j ++) {71 if (data [j]. compareTo (data [j + 1])> 0) {72 swap (data, j + 1, j ); 73} 74} 75} 76} 77 78 // ----- select sorting method time complexity O (n ^ 2) ----- 79 public void selectSort (T [] data) {80 int I, j; 81 82 for (I = 0; I <da Ta. length-1; I ++) {83 for (j = I + 1; j <data. length; j ++) {84 if (data [I]. compareTo (data [j])> 0) {85 swap (data, I, j ); 86} 87} 88} 89} 90 91 // ----- the time complexity of the quick sorting method is O (log2n) ----- 92 public void quickSort (T [] data) {93 subQuickSort (data, 0, data. length-1); 94} 95 96 private void subQuickSort (T [] data, int start, int end) {97 if (start <end) {98 // use the first element as the demarcation value 99 T base = data [start]; 100 // I search for an index 101 greater than the demarcation value element from the left Int I = start; 102 // j searches for indexes less than the Boundary Value element from the right side. 103 int j = end + 1; 104 while (true) {105 // The left side skips the element 106 while (I <end & data [++ I]. compareTo (base) <= 0); 107 // The right side skips the element 108 while (j> start & data [-- j]. compareTo (base)> = 0); 109 110 if (j> I) {111 swap (data, I, j); 112} else {113 break; 114} 115} 116 // restore the demarcation value to 117 swap (data, start, j); 118 119 // recursive left sequence 120 subQuickSort (data, start, J-1 ); 121 // recursive Right Sequence 122 subQuickSort (Data, j + 1, end); 123} 124} 125 126 // ----- insertion time complexity of the sort method O (n ^ 2) ----- 127 public void insertSort (T [] data) {128 int arrayLength = data. length; 129 130 for (int I = 1; I <arrayLength; I ++) {131 // ensure that the value of data [I] will not be lost 132 T tmp = data [I] when the overall post migration; 133 // the value at the index has been greater than all the previous values, indicating that it has been ordered, no need to insert 134 // The value before the index at the I-1 has been ordered, the value of the element at the index at the I-1 is also the maximum 135 if (data [I]. compareTo (data [I-1]) <0) {136 int j = I-1; 137 // The whole moves a 138 while (j> = 0 & data [j]. compareTo (tmp)> 0) {139 data [j + 1] = data [j]; 140 j --; 141} 142 data [j + 1] = tmp; 143} 144} 145 146 147 // ----- time complexity of the semi-insertion sorting method ----- 148 public void binaryInsertSort (T [] data) {149 int arrayLength = data. length; 150 151 for (int I = 1; I <arrayLength; I ++) {152 if (data [I-1]. compareTo (data [I])> 0) {153 // The element value at cache I is 154 T tmp = data [I]; 155 156 // The left boundary of the record search range 157 int low = 0; 158 // The right boundary of the record search range 159 int high = I-1; 160 161 w Hile (high> = low) {162 // record intermediate position 163 int mid = (high + low)/2; 164 // compare the data size between the intermediate position and I, to narrow the search range by 165 if (tmp. compareTo (data [mid])> 0) {167 low = mid + 1; 168} else {169 high = mid-1; 170} 171} 172/set low ~ At I, the data is moved backwards by one 173 for (int j = I; j> low; j --) {174 data [j] = data [j-1]; 175} 176 data [low] = tmp; 177 178} 179} 180 181 182 // ----- time complexity O (nlogn) O (n ^ 2) of the hill sorting method) for details, see the value of h ----- 183 public void shellSort (T [] data) {184 int arrayLength = data. length; 185 // h save variable increment 186 187 int h = 1; 188 while (h <= arrayLength/3) {189 h = h * 3 + 1; 190} 191 192 while (h> 0) {193 // System. out. println (Arrays. toString (data) + "h =" + h); 194 195 for (int I = h; I <arrayLength; I ++) {196 // when the overall move is back, ensure that the value of data [I] is not lost 197 T tmp = data [I]; 198 // the value at the I index is already 199 larger than all previous values // (the value prior to the I-1 index is already ordered, and the value of the element at the I-1 index is the maximum value) 200 if (data [I]. compareTo (data [I-h]) <0) {201 int j = I-h; 202 // The entire backend is 203 while (j> = 0 & data [j]. compareTo (tmp)> 0) {204 data [j + h] = data [j]; 205 j-= h; 206} 207 208 // Insert the tmp value to the appropriate position 209 data [j + h] = tmp; 210} 211} 212 h = (h-1)/3; 213} 214 215} 216 217 // ----- merge sort The time complexity is O (nlog2n) ----- 218 public void mergeSort (T [] data) {219 subMergeSort (data, 0, data. length-1); 220} 221 222 private void subMergeSort (T [] data, int left, int right) {223 if (right> left) {224 // locate the intermediate index 225 // System. out. println (Arrays. toString (data); 226 int center = (left + right)/2; 227 // recursion of the left array 228 subMergeSort (data, left, center ); 229 // recursion 230 subMergeSort (data, center + 1, right) for the right array; 231 // merge 232 merg E (data, left, center, right); 233} 234} 235 236 @ SuppressWarnings ("unchecked") 237 private void merge (T [] data, int left, int center, int right () {238 Object [] tmpArr = new Object [data. length]; 239 int mid = center + 1; 240 // index in the middle of the third record 241 int third = left; 242 int tmp = left; 243 244 while (left <= center & mid <= right) {245 // fetch the smallest value from the two arrays and put it into the intermediate array 246 if (data [left]. compareTo (data [mid]) <=0) {247 tmpArr [Third ++] = data [left ++]; 248} else {249 tmpArr [third ++] = data [mid ++]; 250} 251} 252 253 // Add the remaining part to the intermediate array 254 while (mid <= right) {255 tmpArr [third ++] = data [mid ++]; 256} 257 while (left <= center) {258 tmpArr [third ++] = data [left ++]; 259} 260 261 // copy the content of the intermediate array to the original array 262 // (original left ~ The content in the right range is copied back to the original array.) 263 while (tmp <= right) {264 data [tmp] = (T) tmpArr [tmp ++]; 265} 266} 267 268 269 270 public static void main (String [] args) {271 // TODO Auto-generated method stub272 273} 274 275}