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最近阅读<<我的第一本算法书>>(【日】石田保辉；宫崎修一)
本系列笔记拟采用golang练习之
选择排序
选择排序就是重复“从待排序的数据中寻找最小值，
将其与序列最左边的数字进行交换”这一操作的算法。
在序列中寻找最小值时使用的是线性查找。
选择排序的时间复杂度也和冒泡排序的一样，都为O(n^2)。
摘自 <<我的第一本算法书>> 【日】石田保辉；宫崎修一流程
- 给定待排序数组data[N]
- 设定目标位置i = 0
- 获取n = min(data, i), 即[0-N)区间的最小值的下标
- 判断n是否等于i, 否则交换n, i的数值, 也就是把最小值放到i的位置
- i++
- 循环3-5步, 直到i == N-1
目标
- 实现并测试选择排序
- 通过定义比较函数兼容任意值类型
- 通过调整比较函数实现倒序输出
设计
- ISorter: 定义排序算法接口, 以及值比较函数
- tSelectSorter: 选择排序的实现. 内部定义min函数, 线性查找数组中指定区间的最小值的下标.
单元测试
select_sort_test.go, 测试过程与冒泡排序基本一致. 从测试结果看, 比冒泡排序快近一倍
package sorting
import (
"fmt"
"learning/gooop/sorting"
"learning/gooop/sorting/select_sort"
"math/rand"
"testing"
"time"
)
func Test_SelectSort(t *testing.T) {
fnAssertTrue := func(b bool, msg string) {
if !b {
t.Fatal(msg)
}
}
reversed := false
fnCompare := func(a interface{}, b interface{}) sorting.CompareResult {
i1 := a.(int)
i2 := b.(int)
if i1 < i2 {
if reversed {
return sorting.GREATER
} else {
return sorting.LESS
}
} else if i1 == i2 {
return sorting.EQUAL
} else {
if reversed {
return sorting.LESS
} else {
return sorting.GREATER
}
}
}
sorter := select_sort.SelectSorter
// test 10000 items sorting
rnd := rand.New(rand.NewSource(time.Now().UnixNano()))
sampleCount := 10000
t.Logf("prepare large array with %v items", sampleCount)
samples := make([]interface{}, sampleCount)
for i := 0;i < sampleCount;i++ {
samples[i] = rnd.Intn(sampleCount*10)
}
t.Log("sorting large array")
t0 := time.Now().UnixNano()
sorter.Sort(samples, fnCompare)
cost := time.Now().UnixNano() - t0
for i := 1;i < sampleCount;i++ {
fnAssertTrue(fnCompare(samples[i-1], samples[i]) != sorting.GREATER, "expecting <=")
}
t.Logf("end sorting large array, cost = %v ms", cost / 1000000)
// test 0-20
sampleCount = 20
t.Log("sorting 0-20")
samples = make([]interface{}, sampleCount)
for i := 0;i < sampleCount;i++ {
for {
p := rnd.Intn(sampleCount)
if samples[p] == nil {
samples[p] = i
break
}
}
}
t.Logf("unsort = %v", samples)
sorter.Sort(samples, fnCompare)
t.Logf("sorted = %v", samples)
fnAssertTrue(fmt.Sprintf("%v", samples) == "[0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19]", "expecting 0-20")
t.Log("pass sorting 0-20")
// test special
samples = []interface{} {}
sorter.Sort(samples, fnCompare)
t.Log("pass sorting []")
samples = []interface{} { 1 }
sorter.Sort(samples, fnCompare)
t.Log("pass sorting [1]")
samples = []interface{} { 3,1 }
sorter.Sort(samples, fnCompare)
fnAssertTrue(fmt.Sprintf("%v", samples) == "[1 3]", "expecting 1,3")
t.Log("pass sorting [1 3]")
samples = []interface{} { 2,3,1 }
sorter.Sort(samples, fnCompare)
fnAssertTrue(fmt.Sprintf("%v", samples) == "[1 2 3]", "expecting 1,2,3")
t.Log("pass sorting [1 2 3]")
reversed = true
sorter.Sort(samples, fnCompare)
fnAssertTrue(fmt.Sprintf("%v", samples) == "[3 2 1]", "expecting 3,2,1")
t.Log("pass sorting [3 2 1]")
}测试输出
从测试结果看, 比冒泡排序快近一倍
$ go test -v select_sort_test.go
=== RUN Test_SelectSort
select_sort_test.go:46: prepare large array with 10000 items
select_sort_test.go:52: sorting large array
select_sort_test.go:59: end sorting large array, cost = 293 ms
select_sort_test.go:63: sorting 0-20
select_sort_test.go:74: unsort = [19 6 15 14 16 2 5 11 12 18 8 3 17 4 10 7 1 13 9 0]
select_sort_test.go:77: sorted = [0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19]
select_sort_test.go:79: pass sorting 0-20
select_sort_test.go:84: pass sorting []
select_sort_test.go:88: pass sorting [1]
select_sort_test.go:93: pass sorting [1 3]
select_sort_test.go:98: pass sorting [1 2 3]
select_sort_test.go:103: pass sorting [3 2 1]
--- PASS: Test_SelectSort (0.29s)
PASS
ok command-line-arguments 0.297sISorter.go
定义排序算法接口, 以及值比较函数
package sorting
type ISorter interface {
Sort(data []interface{}, comparator CompareFunction) []interface{}
}
type CompareFunction func(a interface{}, b interface{}) CompareResult
type CompareResult int
const LESS CompareResult = -1
const EQUAL CompareResult = 0
const GREATER CompareResult = 1tSelectSorter.go
选择排序的实现. 内部定义min函数, 线性查找数组中指定区间的最小值的下标.
package select_sort
import "learning/gooop/sorting"
type tSelectSorter struct {
}
func newSelectSorter() sorting.ISorter {
return &tSelectSorter{}
}
// 选择排序
func (me *tSelectSorter) Sort(data []interface{}, comparator sorting.CompareFunction) []interface{} {
if data == nil {
return nil
}
size := len(data)
if size <= 1 {
return data
}
last := size - 1
for i := 0;i < last;i++ {
p := me.min(data, i, size, comparator)
if p != i {
data[i], data[p] = data[p], data[i]
}
}
return data
}
// 使用线性查找法, 获取最小值的索引
func (me *tSelectSorter) min(data []interface{}, from int, to int, comparator sorting.CompareFunction) int {
p := from
v := data[from]
for i := from + 1;i < to;i++ {
v1 := data[i]
if comparator(v1, v) == sorting.LESS {
p = i
v = v1
}
}
return p
}
var SelectSorter = newSelectSorter()(end)