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package sorts
import (
"sort"
)
// Copyright 2009 The Go Authors.
// Copyright 2014-5 Randall Farmer.
// All rights reserved.
// Use of this source code is governed by a BSD-style license that can be
// found in the LICENSE file.
// This copies code from Go's sort.go because we can't use something like
// sort.SortRange(data, a, b) to sort a range of data. Wrapping incoming
// data in another sort.Interface is possible, but kills speed.
// Insertion sort
func insertionSort(data sort.Interface, a, b int) {
for i := a + 1; i < b; i++ {
for j := i; j > a && data.Less(j, j-1); j-- {
data.Swap(j, j-1)
}
}
}
// siftDown implements the heap property on data[lo, hi).
// first is an offset into the array where the root of the heap lies.
func siftDown(data sort.Interface, lo, hi, first int) {
root := lo
for {
child := 2*root + 1
if child >= hi {
break
}
if child+1 < hi && data.Less(first+child, first+child+1) {
child++
}
if !data.Less(first+root, first+child) {
return
}
data.Swap(first+root, first+child)
root = child
}
}
func heapSort(data sort.Interface, a, b int) {
first := a
lo := 0
hi := b - a
// Build heap with greatest element at top.
for i := (hi - 1) / 2; i >= 0; i-- {
siftDown(data, i, hi, first)
}
// Pop elements, largest first, into end of data.
for i := hi - 1; i >= 0; i-- {
data.Swap(first, first+i)
siftDown(data, lo, i, first)
}
}
// medianOfThree moves the median of the three values data[m0], data[m1], data[m2] into data[m1].
func medianOfThree(data sort.Interface, m1, m0, m2 int) {
// sort 3 elements
if data.Less(m1, m0) {
data.Swap(m1, m0)
}
// data[m0] <= data[m1]
if data.Less(m2, m1) {
data.Swap(m2, m1)
// data[m0] <= data[m2] && data[m1] < data[m2]
if data.Less(m1, m0) {
data.Swap(m1, m0)
}
}
// now data[m0] <= data[m1] <= data[m2]
}
func doPivot(data sort.Interface, lo, hi int) (midlo, midhi int) {
m := lo + (hi-lo)/2 // Written like this to avoid integer overflow.
if hi-lo > 40 {
// Tukey's ``Ninther,'' median of three medians of three.
s := (hi - lo) / 8
medianOfThree(data, lo, lo+s, lo+2*s)
medianOfThree(data, m, m-s, m+s)
medianOfThree(data, hi-1, hi-1-s, hi-1-2*s)
}
medianOfThree(data, lo, m, hi-1)
// Invariants are:
// data[lo] = pivot (set up by ChoosePivot)
// data[lo < i < a] < pivot
// data[a <= i < b] <= pivot
// data[b <= i < c] unexamined
// data[c <= i < hi-1] > pivot
// data[hi-1] >= pivot
pivot := lo
a, c := lo+1, hi-1
for ; a != c && data.Less(a, pivot); a++ {
}
b := a
for {
for ; b != c && !data.Less(pivot, b); b++ { // data[b] <= pivot
}
for ; b != c && data.Less(pivot, c-1); c-- { // data[c-1] > pivot
}
if b == c {
break
}
// data[b] > pivot; data[c-1] <= pivot
data.Swap(b, c-1)
b++
c--
}
// If hi-c<3 then there are duplicates (by property of median of nine).
// Let be a bit more conservative, and set border to 5.
protect := hi-c < 5
if !protect && hi-c < (hi-lo)/4 {
// Lets test some points for equality to pivot
dups := 0
if !data.Less(pivot, hi-1) { // data[hi-1] = pivot
data.Swap(c, hi-1)
c++
dups++
}
if !data.Less(b-1, pivot) { // data[b-1] = pivot
b--
dups++
}
// m-lo = (hi-lo)/2 > 6
// b-lo > (hi-lo)*3/4-1 > 8
// ==> m < b ==> data[m] <= pivot
if !data.Less(m, pivot) { // data[m] = pivot
data.Swap(m, b-1)
b--
dups++
}
// if at least 2 points are equal to pivot, assume skewed distribution
protect = dups > 1
}
if protect {
// Protect against a lot of duplicates
// Add invariant:
// data[a <= i < b] unexamined
// data[b <= i < c] = pivot
for {
for ; a != b && !data.Less(b-1, pivot); b-- { // data[b] == pivot
}
for ; a != b && data.Less(a, pivot); a++ { // data[a] < pivot
}
if a == b {
break
}
// data[a] == pivot; data[b-1] < pivot
data.Swap(a, b-1)
a++
b--
}
}
// Swap pivot into middle
data.Swap(pivot, b-1)
return b - 1, c
}
func quickSort(data sort.Interface, a, b, maxDepth int) {
for b-a > 12 {
if maxDepth == 0 {
heapSort(data, a, b)
return
}
maxDepth--
mlo, mhi := doPivot(data, a, b)
// Avoiding recursion on the larger subproblem guarantees
// a stack depth of at most lg(b-a).
if mlo-a < b-mhi {
quickSort(data, a, mlo, maxDepth)
a = mhi // i.e., quickSort(data, mhi, b)
} else {
quickSort(data, mhi, b, maxDepth)
b = mlo // i.e., quickSort(data, a, mlo)
}
}
if b-a > 1 {
// Do ShellSort pass with gap 6
// It could be written in this simplified form cause b-a <= 12
for i := a + 6; i < b; i++ {
if data.Less(i, i-6) {
data.Swap(i, i-6)
}
}
insertionSort(data, a, b)
}
}
// qSort quicksorts data immediately.
// It performs O(n*log(n)) comparisons and swaps. The sort is not stable.
func qSort(data sort.Interface, a, b int) {
// Switch to heapsort if depth of 2*ceil(lg(n+1)) is reached.
n := b - a
maxDepth := 0
for i := n; i > 0; i >>= 1 {
maxDepth++
}
maxDepth *= 2
quickSort(data, a, b, maxDepth)
}
// Quicksort performs a parallel quicksort on data.
func Quicksort(data sort.Interface) {
a, b := 0, data.Len()
n := b - a
maxDepth := 0
for i := n; i > 0; i >>= 1 {
maxDepth++
}
maxDepth *= 2
parallelSort(data, quickSortWorker, task{-maxDepth - 1, a, b})
}
// qSortPar starts a parallel quicksort.
func qSortPar(data sort.Interface, t task, sortRange func(task)) {
a, b := t.pos, t.end
n := b - a
maxDepth := 0
for i := n; i > 0; i >>= 1 {
maxDepth++
}
maxDepth *= 2
quickSortWorker(data, task{-maxDepth - 1, a, b}, sortRange)
}
// quickSortWorker is a parallel analogue of quickSort: it performs a pivot
// and might asynchronously sort one of the halves if it's large enough.
func quickSortWorker(data sort.Interface, t task, sortRange func(task)) {
maxDepth, a, b := 1-t.offs, t.pos, t.end
for b-a > minOffload {
if maxDepth == 0 {
heapSort(data, a, b)
return
}
maxDepth--
mlo, mhi := doPivot(data, a, b)
// Avoiding recursion on the larger subproblem guarantees
// a stack depth of at most lg(b-a).
if mlo-a < b-mhi {
sortRange(task{-maxDepth - 1, a, mlo})
a = mhi // i.e., quickSortWorker(data, mhi, b)
} else {
sortRange(task{-maxDepth - 1, mhi, b})
b = mlo // i.e., quickSortWorker(data, a, mlo)
}
}
if b-a > 7 {
quickSort(data, a, b, maxDepth)
} else if b-a > 1 {
insertionSort(data, a, b)
}
}
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