Glang 数组的排序和查找:快速丶希尔丶堆丶选择丶冒泡...
一.数组的排序与查找
1 // 数组的排序和查找 2 func testArrSort() { 3 // 内部排序：将需要处理的所有数据都加载到内部存储器中进行排序（交换式排序法、选择式排序法、插入式排序） 4 5 // 交换式排序法-冒泡排序:递归将最大或最小值冒泡到数组尾 6 BubbleSort := func(arr1 []int32) (result bool) { 7 result = false 8 for i := 0; i < len(arr1); i++ { 9 tmpb := false 10 for j := 0; j < len(arr1)-i-1; j++ { 11 if (arr1)[j] > (arr1)[j+1] { 12 tem := (arr1)[j] 13 (arr1)[j] = (arr1)[j+1] 14 (arr1)[j+1] = tem 15 tmpb = true 16 } 17 } 18 if !tmpb { 19 break 20 } 21 } 22 result = true 23 return 24 } 25 // 插入式排序法:将无序的数组插入到有序的数组 26 InserSort := func(arr1 []int32) (result bool) { 27 result = false 28 for i := 1; i < len(arr1); i++ { 29 for j := i; j > 0; j-- { 30 if arr1[j] < arr1[j-1] { 31 tmp := arr1[j] 32 arr1[j] = arr1[j-1] 33 arr1[j-1] = tmp 34 } 35 } 36 } 37 result = true 38 return 39 } 40 41 // 希尔式排序(交换式排序):高效的利用每次的比较成果 42 type funXierOrderType func([]int32, int) bool 43 var XierOrder funXierOrderType 44 XierOrder = func(arr1 []int32, step int) (result bool) { 45 result = false 46 for i := 0; i < len(arr1); i++ { 47 if (i + step) >= len(arr1) { 48 break 49 } 50 for j := 0; ; { 51 j += step 52 if j >= len(arr1) { 53 break 54 } 55 if arr1[j-step] > arr1[j] { 56 tem := arr1[j-step] 57 arr1[j-step] = arr1[j] 58 arr1[j] = tem 59 } 60 } 61 } 62 if step == 1 { 63 result = true 64 return 65 } 66 67 return XierOrder(arr1, step/2) 68 } 69 70 // 快速排序法:选数组第0个元素作为参考,将其他元素与之比较,比他大的放左侧比他小的放右侧,以此分割数组作递归 71 type funQuickSortType func([]int32) bool 72 var QuickSort funQuickSortType 73 QuickSort = func(arr1 []int32) (result bool) { 74 result = false 75 leftIndex := 0 76 rightIndex := len(arr1) - 1 77 if len(arr1) < 1 { 78 return true 79 } 80 81 type Pivot struct { 82 pivot int32 83 status string 84 } 85 86 if rightIndex == 0 { 87 result = true 88 return 89 } 90 if rightIndex == 1 { 91 if arr1[0] > arr1[1] { 92 tem := arr1[0] 93 arr1[0] = arr1[1] 94 arr1[1] = tem 95 } 96 result = true 97 return 98 } 99 var pivot Pivot = Pivot{pivot: arr1[0], status: "R"} 100 for leftIndex != rightIndex { 101 if pivot.status == "R" { 102 if arr1[rightIndex] < pivot.pivot { 103 arr1[leftIndex] = arr1[rightIndex] 104 pivot.status = "L" 105 leftIndex++ 106 } else { 107 pivot.status = "R" 108 rightIndex-- 109 } 110 } else if pivot.status == "L" { 111 if arr1[leftIndex] < pivot.pivot { 112 pivot.status = "L" 113 leftIndex++ 114 } else { 115 arr1[rightIndex] = arr1[leftIndex] 116 pivot.status = "R" 117 rightIndex-- 118 } 119 } 120 } 121 arr1[leftIndex] = pivot.pivot 122 QuickSort(arr1[:leftIndex]) 123 QuickSort(arr1[leftIndex+1:]) 124 return true 125 } 126 127 // 堆排序:二叉树,大小堆.步骤:1.建堆 2.堆顶与堆尾交换固定堆尾 3.继续重复做建堆 128 type funBuildHeapType func([]int32) 129 type funHeapifyType func([]int32, int, int) 130 var BuildHeap funBuildHeapType 131 var Heapify funHeapifyType 132 Heapify = func(arr1 []int32, n int, i int) { 133 maxIndex := n - 1 134 c1 := (i * 2) + 1 135 c2 := c1 + 1 136 if c1 > maxIndex { 137 return 138 } 139 if arr1[i] < arr1[c1] { 140 tem := arr1[i] 141 arr1[i] = arr1[c1] 142 arr1[c1] = tem 143 Heapify(arr1, n, c1) 144 } 145 if (c2 <= maxIndex) && (arr1[i] < arr1[c2]) { 146 tem := arr1[i] 147 arr1[i] = arr1[c2] 148 arr1[c2] = tem 149 Heapify(arr1, n, c1) 150 } 151 152 } 153 BuildHeap = func(arr1 []int32) { 154 if len(arr1) < 2 { 155 return 156 } 157 maxIndex := len(arr1) - 1 158 heapIndex := (maxIndex - 1) / 2 159 160 for i := heapIndex; i >= 0; i-- { 161 Heapify(arr1, len(arr1), i) 162 } 163 } 164 HeapSort := func(arr1 []int32) { 165 BuildHeap(arr1) 166 // fmt.Println("BuildHeap=", arr1) 167 for i := len(arr1) - 1; i > 0; i-- { 168 tem := arr1[i] 169 arr1[i] = arr1[0] 170 arr1[0] = tem 171 Heapify(arr1, i, 0) 172 } 173 // fmt.Println("BuildHeap=", arr1) 174 } 175 176 // 选择排序:不停的找出最大或最小的元素放前面 177 var SelectSort funBuildHeapType 178 SelectSort = func(arr1 []int32) { 179 for i := 0; i < len(arr1); i++ { 180 for j := i + 1; j < len(arr1); j++ { 181 if arr1[i] > arr1[j] { 182 tem := arr1[i] 183 arr1[i] = arr1[j] 184 arr1[j] = tem 185 } 186 } 187 } 188 } 189 190 // 合并排序算法 191 type MergeTable struct { 192 startIndex int 193 endIndex int 194 len int 195 } 196 MergeArray := func(arr []int32, tab1 MergeTable, tab2 MergeTable) { 197 var arr1 []int32 = make([]int32, tab1.len+tab2.len) 198 for tab1Index, tab2Index, i := tab1.startIndex, tab2.startIndex, 0; ; i++ { 199 if (tab1Index > tab1.endIndex) && (tab2Index > tab2.endIndex) { 200 break 201 } 202 if tab1Index > tab1.endIndex { 203 arr1[i] = arr[tab2Index] 204 tab2Index++ 205 continue 206 } 207 if tab2Index > tab2.endIndex { 208 arr1[i] = arr[tab1Index] 209 tab1Index++ 210 continue 211 } 212 if arr[tab1Index] < arr[tab2Index] { 213 arr1[i] = arr[tab1Index] 214 tab1Index++ 215 } else { 216 arr1[i] = arr[tab2Index] 217 tab2Index++ 218 } 219 } 220 index := 0 221 for i := tab1.startIndex; i <= tab1.endIndex; i++ { 222 arr[i] = arr1[index] 223 index++ 224 } 225 for i := tab2.startIndex; i <= tab2.endIndex; i++ { 226 arr[i] = arr1[index] 227 index++ 228 } 229 } 230 var MergeSort funBuildHeapType 231 MergeSort = func(arr []int32) { 232 alen := len(arr) 233 if alen == 1 { 234 return 235 } 236 for step := 1; ; step *= 2 { 237 for i := 0; i < len(arr); { 238 tab1 := MergeTable{i, i + step - 1, step} 239 tab2 := MergeTable{(i + step), i + step*2 - 1, step} 240 if tab1.endIndex > (len(arr) - 1) { 241 tab1.endIndex = len(arr) - 1 242 tab1.len = tab1.endIndex - tab1.startIndex + 1 243 244 tab2.len = 0 245 tab2.startIndex = 0 246 tab2.endIndex = -1 247 } else if tab2.endIndex > (len(arr) - 1) { 248 if tab2.startIndex > (len(arr) - 1) { 249 tab2.len = 0 250 tab2.startIndex = 0 251 tab2.endIndex = -1 252 } else { 253 tab2.endIndex = len(arr) - 1 254 tab2.len = tab2.endIndex - tab2.startIndex + 1 255 } 256 } 257 fmt.Println(tab1, tab2) 258 MergeArray(arr, tab1, tab2) 259 i = i + step*2 260 } 261 fmt.Println("step=", step, " :", arr) 262 if step >= len(arr)-1 { 263 break 264 } 265 } 266 267 } 268 269 // 基数排序(待) 270 // 计数排序(待) 271 // 桶排序(待) 272 var arr [9]int32 = [9]int32{14, 2, 5, 12, 68, 6, 8, 99, 61} 273 // var arr [6]int32 = [6]int32{2, 5, 3, 1, 10, 4} 274 fmt.Println(arr) 275 MergeSort(arr[:]) 276 fmt.Println(arr) 277 SelectSort(arr[:]) 278 HeapSort(arr[:]) 279 rb := QuickSort(arr[:]) 280 rb = XierOrder(arr[:], len(arr)/2) 281 rb = BubbleSort(arr[:]) 282 rb = InserSort(arr[:]) 283 fmt.Println(rb) 284 285 type funType func([]int32, int32) (int32, string) 286 var BunaryFind funType 287 // 二分查找法:以下代码针对必须从小到大排序好了的数组 288 BunaryFind = func(arr1 []int32, findValue int32) (result int32, err string) { 289 err = "error!" 290 result = findValue 291 if len(arr1) == 1 { 292 if arr1[0] == findValue { 293 result = findValue 294 err = "" 295 return 296 } else { 297 err = "not find value!" 298 return 299 } 300 } else { 301 if arr1[len(arr1)/2] > findValue { 302 result, err = BunaryFind(arr1[:len(arr1)/2], findValue) 303 } else { 304 result, err = BunaryFind(arr1[len(arr1)/2:], findValue) 305 } 306 } 307 return 308 } 309 310 result, err := BunaryFind(arr[:], 99) 311 fmt.Println("result:", result, err) 312 // 外部排序：数据量过大，无法全部家在到内存，需借助外部存储进行排序。（合并排序法(二路归并 多路归并...路多耗CPU,路少耗IO,需根据情况选择)、直接合并排序法） 313 314 }
