Bump github.com/hashicorp/terraform-plugin-docs from 0.15.0 to 0.16.0
Bumps [github.com/hashicorp/terraform-plugin-docs](https://github.com/hashicorp/terraform-plugin-docs) from 0.15.0 to 0.16.0. - [Release notes](https://github.com/hashicorp/terraform-plugin-docs/releases) - [Changelog](https://github.com/hashicorp/terraform-plugin-docs/blob/main/CHANGELOG.md) - [Commits](https://github.com/hashicorp/terraform-plugin-docs/compare/v0.15.0...v0.16.0) --- updated-dependencies: - dependency-name: github.com/hashicorp/terraform-plugin-docs dependency-type: direct:production update-type: version-update:semver-minor ... Signed-off-by: dependabot[bot] <support@github.com>main
dependabot[bot]
10 months ago
committed by
GitHub
parent
c1ba34b248
commit
04160fa7a3
37
vendor/github.com/hashicorp/terraform-plugin-docs/internal/provider/generate.go
generated
vendored
37
vendor/github.com/hashicorp/terraform-plugin-docs/internal/provider/generate.go
generated
vendored
1
vendor/github.com/hashicorp/terraform-plugin-docs/internal/provider/validate.go
generated
vendored
1
vendor/github.com/hashicorp/terraform-plugin-docs/internal/provider/validate.go
generated
vendored
@ -0,0 +1,27 @@
|
||||
Copyright (c) 2009 The Go Authors. All rights reserved.
|
||||
|
||||
Redistribution and use in source and binary forms, with or without
|
||||
modification, are permitted provided that the following conditions are
|
||||
met:
|
||||
|
||||
* Redistributions of source code must retain the above copyright
|
||||
notice, this list of conditions and the following disclaimer.
|
||||
* Redistributions in binary form must reproduce the above
|
||||
copyright notice, this list of conditions and the following disclaimer
|
||||
in the documentation and/or other materials provided with the
|
||||
distribution.
|
||||
* Neither the name of Google Inc. nor the names of its
|
||||
contributors may be used to endorse or promote products derived from
|
||||
this software without specific prior written permission.
|
||||
|
||||
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
|
||||
"AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
|
||||
LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
|
||||
A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT
|
||||
OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
|
||||
SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
|
||||
LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
|
||||
DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY
|
||||
THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
|
||||
(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
|
||||
OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
|
||||
@ -0,0 +1,22 @@
|
||||
Additional IP Rights Grant (Patents)
|
||||
|
||||
"This implementation" means the copyrightable works distributed by
|
||||
Google as part of the Go project.
|
||||
|
||||
Google hereby grants to You a perpetual, worldwide, non-exclusive,
|
||||
no-charge, royalty-free, irrevocable (except as stated in this section)
|
||||
patent license to make, have made, use, offer to sell, sell, import,
|
||||
transfer and otherwise run, modify and propagate the contents of this
|
||||
implementation of Go, where such license applies only to those patent
|
||||
claims, both currently owned or controlled by Google and acquired in
|
||||
the future, licensable by Google that are necessarily infringed by this
|
||||
implementation of Go. This grant does not include claims that would be
|
||||
infringed only as a consequence of further modification of this
|
||||
implementation. If you or your agent or exclusive licensee institute or
|
||||
order or agree to the institution of patent litigation against any
|
||||
entity (including a cross-claim or counterclaim in a lawsuit) alleging
|
||||
that this implementation of Go or any code incorporated within this
|
||||
implementation of Go constitutes direct or contributory patent
|
||||
infringement, or inducement of patent infringement, then any patent
|
||||
rights granted to you under this License for this implementation of Go
|
||||
shall terminate as of the date such litigation is filed.
|
||||
@ -0,0 +1,50 @@
|
||||
// Copyright 2021 The Go Authors. All rights reserved.
|
||||
// Use of this source code is governed by a BSD-style
|
||||
// license that can be found in the LICENSE file.
|
||||
|
||||
// Package constraints defines a set of useful constraints to be used
|
||||
// with type parameters.
|
||||
package constraints
|
||||
|
||||
// Signed is a constraint that permits any signed integer type.
|
||||
// If future releases of Go add new predeclared signed integer types,
|
||||
// this constraint will be modified to include them.
|
||||
type Signed interface {
|
||||
~int | ~int8 | ~int16 | ~int32 | ~int64
|
||||
}
|
||||
|
||||
// Unsigned is a constraint that permits any unsigned integer type.
|
||||
// If future releases of Go add new predeclared unsigned integer types,
|
||||
// this constraint will be modified to include them.
|
||||
type Unsigned interface {
|
||||
~uint | ~uint8 | ~uint16 | ~uint32 | ~uint64 | ~uintptr
|
||||
}
|
||||
|
||||
// Integer is a constraint that permits any integer type.
|
||||
// If future releases of Go add new predeclared integer types,
|
||||
// this constraint will be modified to include them.
|
||||
type Integer interface {
|
||||
Signed | Unsigned
|
||||
}
|
||||
|
||||
// Float is a constraint that permits any floating-point type.
|
||||
// If future releases of Go add new predeclared floating-point types,
|
||||
// this constraint will be modified to include them.
|
||||
type Float interface {
|
||||
~float32 | ~float64
|
||||
}
|
||||
|
||||
// Complex is a constraint that permits any complex numeric type.
|
||||
// If future releases of Go add new predeclared complex numeric types,
|
||||
// this constraint will be modified to include them.
|
||||
type Complex interface {
|
||||
~complex64 | ~complex128
|
||||
}
|
||||
|
||||
// Ordered is a constraint that permits any ordered type: any type
|
||||
// that supports the operators < <= >= >.
|
||||
// If future releases of Go add new ordered types,
|
||||
// this constraint will be modified to include them.
|
||||
type Ordered interface {
|
||||
Integer | Float | ~string
|
||||
}
|
||||
@ -0,0 +1,258 @@
|
||||
// Copyright 2021 The Go Authors. All rights reserved.
|
||||
// Use of this source code is governed by a BSD-style
|
||||
// license that can be found in the LICENSE file.
|
||||
|
||||
// Package slices defines various functions useful with slices of any type.
|
||||
// Unless otherwise specified, these functions all apply to the elements
|
||||
// of a slice at index 0 <= i < len(s).
|
||||
//
|
||||
// Note that the less function in IsSortedFunc, SortFunc, SortStableFunc requires a
|
||||
// strict weak ordering (https://en.wikipedia.org/wiki/Weak_ordering#Strict_weak_orderings),
|
||||
// or the sorting may fail to sort correctly. A common case is when sorting slices of
|
||||
// floating-point numbers containing NaN values.
|
||||
package slices
|
||||
|
||||
import "golang.org/x/exp/constraints"
|
||||
|
||||
// Equal reports whether two slices are equal: the same length and all
|
||||
// elements equal. If the lengths are different, Equal returns false.
|
||||
// Otherwise, the elements are compared in increasing index order, and the
|
||||
// comparison stops at the first unequal pair.
|
||||
// Floating point NaNs are not considered equal.
|
||||
func Equal[E comparable](s1, s2 []E) bool {
|
||||
if len(s1) != len(s2) {
|
||||
return false
|
||||
}
|
||||
for i := range s1 {
|
||||
if s1[i] != s2[i] {
|
||||
return false
|
||||
}
|
||||
}
|
||||
return true
|
||||
}
|
||||
|
||||
// EqualFunc reports whether two slices are equal using a comparison
|
||||
// function on each pair of elements. If the lengths are different,
|
||||
// EqualFunc returns false. Otherwise, the elements are compared in
|
||||
// increasing index order, and the comparison stops at the first index
|
||||
// for which eq returns false.
|
||||
func EqualFunc[E1, E2 any](s1 []E1, s2 []E2, eq func(E1, E2) bool) bool {
|
||||
if len(s1) != len(s2) {
|
||||
return false
|
||||
}
|
||||
for i, v1 := range s1 {
|
||||
v2 := s2[i]
|
||||
if !eq(v1, v2) {
|
||||
return false
|
||||
}
|
||||
}
|
||||
return true
|
||||
}
|
||||
|
||||
// Compare compares the elements of s1 and s2.
|
||||
// The elements are compared sequentially, starting at index 0,
|
||||
// until one element is not equal to the other.
|
||||
// The result of comparing the first non-matching elements is returned.
|
||||
// If both slices are equal until one of them ends, the shorter slice is
|
||||
// considered less than the longer one.
|
||||
// The result is 0 if s1 == s2, -1 if s1 < s2, and +1 if s1 > s2.
|
||||
// Comparisons involving floating point NaNs are ignored.
|
||||
func Compare[E constraints.Ordered](s1, s2 []E) int {
|
||||
s2len := len(s2)
|
||||
for i, v1 := range s1 {
|
||||
if i >= s2len {
|
||||
return +1
|
||||
}
|
||||
v2 := s2[i]
|
||||
switch {
|
||||
case v1 < v2:
|
||||
return -1
|
||||
case v1 > v2:
|
||||
return +1
|
||||
}
|
||||
}
|
||||
if len(s1) < s2len {
|
||||
return -1
|
||||
}
|
||||
return 0
|
||||
}
|
||||
|
||||
// CompareFunc is like Compare but uses a comparison function
|
||||
// on each pair of elements. The elements are compared in increasing
|
||||
// index order, and the comparisons stop after the first time cmp
|
||||
// returns non-zero.
|
||||
// The result is the first non-zero result of cmp; if cmp always
|
||||
// returns 0 the result is 0 if len(s1) == len(s2), -1 if len(s1) < len(s2),
|
||||
// and +1 if len(s1) > len(s2).
|
||||
func CompareFunc[E1, E2 any](s1 []E1, s2 []E2, cmp func(E1, E2) int) int {
|
||||
s2len := len(s2)
|
||||
for i, v1 := range s1 {
|
||||
if i >= s2len {
|
||||
return +1
|
||||
}
|
||||
v2 := s2[i]
|
||||
if c := cmp(v1, v2); c != 0 {
|
||||
return c
|
||||
}
|
||||
}
|
||||
if len(s1) < s2len {
|
||||
return -1
|
||||
}
|
||||
return 0
|
||||
}
|
||||
|
||||
// Index returns the index of the first occurrence of v in s,
|
||||
// or -1 if not present.
|
||||
func Index[E comparable](s []E, v E) int {
|
||||
for i := range s {
|
||||
if v == s[i] {
|
||||
return i
|
||||
}
|
||||
}
|
||||
return -1
|
||||
}
|
||||
|
||||
// IndexFunc returns the first index i satisfying f(s[i]),
|
||||
// or -1 if none do.
|
||||
func IndexFunc[E any](s []E, f func(E) bool) int {
|
||||
for i := range s {
|
||||
if f(s[i]) {
|
||||
return i
|
||||
}
|
||||
}
|
||||
return -1
|
||||
}
|
||||
|
||||
// Contains reports whether v is present in s.
|
||||
func Contains[E comparable](s []E, v E) bool {
|
||||
return Index(s, v) >= 0
|
||||
}
|
||||
|
||||
// ContainsFunc reports whether at least one
|
||||
// element e of s satisfies f(e).
|
||||
func ContainsFunc[E any](s []E, f func(E) bool) bool {
|
||||
return IndexFunc(s, f) >= 0
|
||||
}
|
||||
|
||||
// Insert inserts the values v... into s at index i,
|
||||
// returning the modified slice.
|
||||
// In the returned slice r, r[i] == v[0].
|
||||
// Insert panics if i is out of range.
|
||||
// This function is O(len(s) + len(v)).
|
||||
func Insert[S ~[]E, E any](s S, i int, v ...E) S {
|
||||
tot := len(s) + len(v)
|
||||
if tot <= cap(s) {
|
||||
s2 := s[:tot]
|
||||
copy(s2[i+len(v):], s[i:])
|
||||
copy(s2[i:], v)
|
||||
return s2
|
||||
}
|
||||
s2 := make(S, tot)
|
||||
copy(s2, s[:i])
|
||||
copy(s2[i:], v)
|
||||
copy(s2[i+len(v):], s[i:])
|
||||
return s2
|
||||
}
|
||||
|
||||
// Delete removes the elements s[i:j] from s, returning the modified slice.
|
||||
// Delete panics if s[i:j] is not a valid slice of s.
|
||||
// Delete modifies the contents of the slice s; it does not create a new slice.
|
||||
// Delete is O(len(s)-j), so if many items must be deleted, it is better to
|
||||
// make a single call deleting them all together than to delete one at a time.
|
||||
// Delete might not modify the elements s[len(s)-(j-i):len(s)]. If those
|
||||
// elements contain pointers you might consider zeroing those elements so that
|
||||
// objects they reference can be garbage collected.
|
||||
func Delete[S ~[]E, E any](s S, i, j int) S {
|
||||
_ = s[i:j] // bounds check
|
||||
|
||||
return append(s[:i], s[j:]...)
|
||||
}
|
||||
|
||||
// Replace replaces the elements s[i:j] by the given v, and returns the
|
||||
// modified slice. Replace panics if s[i:j] is not a valid slice of s.
|
||||
func Replace[S ~[]E, E any](s S, i, j int, v ...E) S {
|
||||
_ = s[i:j] // verify that i:j is a valid subslice
|
||||
tot := len(s[:i]) + len(v) + len(s[j:])
|
||||
if tot <= cap(s) {
|
||||
s2 := s[:tot]
|
||||
copy(s2[i+len(v):], s[j:])
|
||||
copy(s2[i:], v)
|
||||
return s2
|
||||
}
|
||||
s2 := make(S, tot)
|
||||
copy(s2, s[:i])
|
||||
copy(s2[i:], v)
|
||||
copy(s2[i+len(v):], s[j:])
|
||||
return s2
|
||||
}
|
||||
|
||||
// Clone returns a copy of the slice.
|
||||
// The elements are copied using assignment, so this is a shallow clone.
|
||||
func Clone[S ~[]E, E any](s S) S {
|
||||
// Preserve nil in case it matters.
|
||||
if s == nil {
|
||||
return nil
|
||||
}
|
||||
return append(S([]E{}), s...)
|
||||
}
|
||||
|
||||
// Compact replaces consecutive runs of equal elements with a single copy.
|
||||
// This is like the uniq command found on Unix.
|
||||
// Compact modifies the contents of the slice s; it does not create a new slice.
|
||||
// When Compact discards m elements in total, it might not modify the elements
|
||||
// s[len(s)-m:len(s)]. If those elements contain pointers you might consider
|
||||
// zeroing those elements so that objects they reference can be garbage collected.
|
||||
func Compact[S ~[]E, E comparable](s S) S {
|
||||
if len(s) < 2 {
|
||||
return s
|
||||
}
|
||||
i := 1
|
||||
for k := 1; k < len(s); k++ {
|
||||
if s[k] != s[k-1] {
|
||||
if i != k {
|
||||
s[i] = s[k]
|
||||
}
|
||||
i++
|
||||
}
|
||||
}
|
||||
return s[:i]
|
||||
}
|
||||
|
||||
// CompactFunc is like Compact but uses a comparison function.
|
||||
func CompactFunc[S ~[]E, E any](s S, eq func(E, E) bool) S {
|
||||
if len(s) < 2 {
|
||||
return s
|
||||
}
|
||||
i := 1
|
||||
for k := 1; k < len(s); k++ {
|
||||
if !eq(s[k], s[k-1]) {
|
||||
if i != k {
|
||||
s[i] = s[k]
|
||||
}
|
||||
i++
|
||||
}
|
||||
}
|
||||
return s[:i]
|
||||
}
|
||||
|
||||
// Grow increases the slice's capacity, if necessary, to guarantee space for
|
||||
// another n elements. After Grow(n), at least n elements can be appended
|
||||
// to the slice without another allocation. If n is negative or too large to
|
||||
// allocate the memory, Grow panics.
|
||||
func Grow[S ~[]E, E any](s S, n int) S {
|
||||
if n < 0 {
|
||||
panic("cannot be negative")
|
||||
}
|
||||
if n -= cap(s) - len(s); n > 0 {
|
||||
// TODO(https://go.dev/issue/53888): Make using []E instead of S
|
||||
// to workaround a compiler bug where the runtime.growslice optimization
|
||||
// does not take effect. Revert when the compiler is fixed.
|
||||
s = append([]E(s)[:cap(s)], make([]E, n)...)[:len(s)]
|
||||
}
|
||||
return s
|
||||
}
|
||||
|
||||
// Clip removes unused capacity from the slice, returning s[:len(s):len(s)].
|
||||
func Clip[S ~[]E, E any](s S) S {
|
||||
return s[:len(s):len(s)]
|
||||
}
|
||||
@ -0,0 +1,128 @@
|
||||
// Copyright 2022 The Go Authors. All rights reserved.
|
||||
// Use of this source code is governed by a BSD-style
|
||||
// license that can be found in the LICENSE file.
|
||||
|
||||
package slices
|
||||
|
||||
import (
|
||||
"math/bits"
|
||||
|
||||
"golang.org/x/exp/constraints"
|
||||
)
|
||||
|
||||
// Sort sorts a slice of any ordered type in ascending order.
|
||||
// Sort may fail to sort correctly when sorting slices of floating-point
|
||||
// numbers containing Not-a-number (NaN) values.
|
||||
// Use slices.SortFunc(x, func(a, b float64) bool {return a < b || (math.IsNaN(a) && !math.IsNaN(b))})
|
||||
// instead if the input may contain NaNs.
|
||||
func Sort[E constraints.Ordered](x []E) {
|
||||
n := len(x)
|
||||
pdqsortOrdered(x, 0, n, bits.Len(uint(n)))
|
||||
}
|
||||
|
||||
// SortFunc sorts the slice x in ascending order as determined by the less function.
|
||||
// This sort is not guaranteed to be stable.
|
||||
//
|
||||
// SortFunc requires that less is a strict weak ordering.
|
||||
// See https://en.wikipedia.org/wiki/Weak_ordering#Strict_weak_orderings.
|
||||
func SortFunc[E any](x []E, less func(a, b E) bool) {
|
||||
n := len(x)
|
||||
pdqsortLessFunc(x, 0, n, bits.Len(uint(n)), less)
|
||||
}
|
||||
|
||||
// SortStableFunc sorts the slice x while keeping the original order of equal
|
||||
// elements, using less to compare elements.
|
||||
func SortStableFunc[E any](x []E, less func(a, b E) bool) {
|
||||
stableLessFunc(x, len(x), less)
|
||||
}
|
||||
|
||||
// IsSorted reports whether x is sorted in ascending order.
|
||||
func IsSorted[E constraints.Ordered](x []E) bool {
|
||||
for i := len(x) - 1; i > 0; i-- {
|
||||
if x[i] < x[i-1] {
|
||||
return false
|
||||
}
|
||||
}
|
||||
return true
|
||||
}
|
||||
|
||||
// IsSortedFunc reports whether x is sorted in ascending order, with less as the
|
||||
// comparison function.
|
||||
func IsSortedFunc[E any](x []E, less func(a, b E) bool) bool {
|
||||
for i := len(x) - 1; i > 0; i-- {
|
||||
if less(x[i], x[i-1]) {
|
||||
return false
|
||||
}
|
||||
}
|
||||
return true
|
||||
}
|
||||
|
||||
// BinarySearch searches for target in a sorted slice and returns the position
|
||||
// where target is found, or the position where target would appear in the
|
||||
// sort order; it also returns a bool saying whether the target is really found
|
||||
// in the slice. The slice must be sorted in increasing order.
|
||||
func BinarySearch[E constraints.Ordered](x []E, target E) (int, bool) {
|
||||
// Inlining is faster than calling BinarySearchFunc with a lambda.
|
||||
n := len(x)
|
||||
// Define x[-1] < target and x[n] >= target.
|
||||
// Invariant: x[i-1] < target, x[j] >= target.
|
||||
i, j := 0, n
|
||||
for i < j {
|
||||
h := int(uint(i+j) >> 1) // avoid overflow when computing h
|
||||
// i ≤ h < j
|
||||
if x[h] < target {
|
||||
i = h + 1 // preserves x[i-1] < target
|
||||
} else {
|
||||
j = h // preserves x[j] >= target
|
||||
}
|
||||
}
|
||||
// i == j, x[i-1] < target, and x[j] (= x[i]) >= target => answer is i.
|
||||
return i, i < n && x[i] == target
|
||||
}
|
||||
|
||||
// BinarySearchFunc works like BinarySearch, but uses a custom comparison
|
||||
// function. The slice must be sorted in increasing order, where "increasing"
|
||||
// is defined by cmp. cmp should return 0 if the slice element matches
|
||||
// the target, a negative number if the slice element precedes the target,
|
||||
// or a positive number if the slice element follows the target.
|
||||
// cmp must implement the same ordering as the slice, such that if
|
||||
// cmp(a, t) < 0 and cmp(b, t) >= 0, then a must precede b in the slice.
|
||||
func BinarySearchFunc[E, T any](x []E, target T, cmp func(E, T) int) (int, bool) {
|
||||
n := len(x)
|
||||
// Define cmp(x[-1], target) < 0 and cmp(x[n], target) >= 0 .
|
||||
// Invariant: cmp(x[i - 1], target) < 0, cmp(x[j], target) >= 0.
|
||||
i, j := 0, n
|
||||
for i < j {
|
||||
h := int(uint(i+j) >> 1) // avoid overflow when computing h
|
||||
// i ≤ h < j
|
||||
if cmp(x[h], target) < 0 {
|
||||
i = h + 1 // preserves cmp(x[i - 1], target) < 0
|
||||
} else {
|
||||
j = h // preserves cmp(x[j], target) >= 0
|
||||
}
|
||||
}
|
||||
// i == j, cmp(x[i-1], target) < 0, and cmp(x[j], target) (= cmp(x[i], target)) >= 0 => answer is i.
|
||||
return i, i < n && cmp(x[i], target) == 0
|
||||
}
|
||||
|
||||
type sortedHint int // hint for pdqsort when choosing the pivot
|
||||
|
||||
const (
|
||||
unknownHint sortedHint = iota
|
||||
increasingHint
|
||||
decreasingHint
|
||||
)
|
||||
|
||||
// xorshift paper: https://www.jstatsoft.org/article/view/v008i14/xorshift.pdf
|
||||
type xorshift uint64
|
||||
|
||||
func (r *xorshift) Next() uint64 {
|
||||
*r ^= *r << 13
|
||||
*r ^= *r >> 17
|
||||
*r ^= *r << 5
|
||||
return uint64(*r)
|
||||
}
|
||||
|
||||
func nextPowerOfTwo(length int) uint {
|
||||
return 1 << bits.Len(uint(length))
|
||||
}
|
||||
@ -0,0 +1,479 @@
|
||||
// Code generated by gen_sort_variants.go; DO NOT EDIT.
|
||||
|
||||
// Copyright 2022 The Go Authors. All rights reserved.
|
||||
// Use of this source code is governed by a BSD-style
|
||||
// license that can be found in the LICENSE file.
|
||||
|
||||
package slices
|
||||
|
||||
// insertionSortLessFunc sorts data[a:b] using insertion sort.
|
||||
func insertionSortLessFunc[E any](data []E, a, b int, less func(a, b E) bool) {
|
||||
for i := a + 1; i < b; i++ {
|
||||
for j := i; j > a && less(data[j], data[j-1]); j-- {
|
||||
data[j], data[j-1] = data[j-1], data[j]
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// siftDownLessFunc implements the heap property on data[lo:hi].
|
||||
// first is an offset into the array where the root of the heap lies.
|
||||
func siftDownLessFunc[E any](data []E, lo, hi, first int, less func(a, b E) bool) {
|
||||
root := lo
|
||||
for {
|
||||
child := 2*root + 1
|
||||
if child >= hi {
|
||||
break
|
||||
}
|
||||
if child+1 < hi && less(data[first+child], data[first+child+1]) {
|
||||
child++
|
||||
}
|
||||
if !less(data[first+root], data[first+child]) {
|
||||
return
|
||||
}
|
||||
data[first+root], data[first+child] = data[first+child], data[first+root]
|
||||
root = child
|
||||
}
|
||||
}
|
||||
|
||||
func heapSortLessFunc[E any](data []E, a, b int, less func(a, b E) bool) {
|
||||
first := a
|
||||
lo := 0
|
||||
hi := b - a
|
||||
|
||||
// Build heap with greatest element at top.
|
||||
for i := (hi - 1) / 2; i >= 0; i-- {
|
||||
siftDownLessFunc(data, i, hi, first, less)
|
||||
}
|
||||
|
||||
// Pop elements, largest first, into end of data.
|
||||
for i := hi - 1; i >= 0; i-- {
|
||||
data[first], data[first+i] = data[first+i], data[first]
|
||||
siftDownLessFunc(data, lo, i, first, less)
|
||||
}
|
||||
}
|
||||
|
||||
// pdqsortLessFunc sorts data[a:b].
|
||||
// The algorithm based on pattern-defeating quicksort(pdqsort), but without the optimizations from BlockQuicksort.
|
||||
// pdqsort paper: https://arxiv.org/pdf/2106.05123.pdf
|
||||
// C++ implementation: https://github.com/orlp/pdqsort
|
||||
// Rust implementation: https://docs.rs/pdqsort/latest/pdqsort/
|
||||
// limit is the number of allowed bad (very unbalanced) pivots before falling back to heapsort.
|
||||
func pdqsortLessFunc[E any](data []E, a, b, limit int, less func(a, b E) bool) {
|
||||
const maxInsertion = 12
|
||||
|
||||
var (
|
||||
wasBalanced = true // whether the last partitioning was reasonably balanced
|
||||
wasPartitioned = true // whether the slice was already partitioned
|
||||
)
|
||||
|
||||
for {
|
||||
length := b - a
|
||||
|
||||
if length <= maxInsertion {
|
||||
insertionSortLessFunc(data, a, b, less)
|
||||
return
|
||||
}
|
||||
|
||||
// Fall back to heapsort if too many bad choices were made.
|
||||
if limit == 0 {
|
||||
heapSortLessFunc(data, a, b, less)
|
||||
return
|
||||
}
|
||||
|
||||
// If the last partitioning was imbalanced, we need to breaking patterns.
|
||||
if !wasBalanced {
|
||||
breakPatternsLessFunc(data, a, b, less)
|
||||
limit--
|
||||
}
|
||||
|
||||
pivot, hint := choosePivotLessFunc(data, a, b, less)
|
||||
if hint == decreasingHint {
|
||||
reverseRangeLessFunc(data, a, b, less)
|
||||
// The chosen pivot was pivot-a elements after the start of the array.
|
||||
// After reversing it is pivot-a elements before the end of the array.
|
||||
// The idea came from Rust's implementation.
|
||||
pivot = (b - 1) - (pivot - a)
|
||||
hint = increasingHint
|
||||
}
|
||||
|
||||
// The slice is likely already sorted.
|
||||
if wasBalanced && wasPartitioned && hint == increasingHint {
|
||||
if partialInsertionSortLessFunc(data, a, b, less) {
|
||||
return
|
||||
}
|
||||
}
|
||||
|
||||
// Probably the slice contains many duplicate elements, partition the slice into
|
||||
// elements equal to and elements greater than the pivot.
|
||||
if a > 0 && !less(data[a-1], data[pivot]) {
|
||||
mid := partitionEqualLessFunc(data, a, b, pivot, less)
|
||||
a = mid
|
||||
continue
|
||||
}
|
||||
|
||||
mid, alreadyPartitioned := partitionLessFunc(data, a, b, pivot, less)
|
||||
wasPartitioned = alreadyPartitioned
|
||||
|
||||
leftLen, rightLen := mid-a, b-mid
|
||||
balanceThreshold := length / 8
|
||||
if leftLen < rightLen {
|
||||
wasBalanced = leftLen >= balanceThreshold
|
||||
pdqsortLessFunc(data, a, mid, limit, less)
|
||||
a = mid + 1
|
||||
} else {
|
||||
wasBalanced = rightLen >= balanceThreshold
|
||||
pdqsortLessFunc(data, mid+1, b, limit, less)
|
||||
b = mid
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// partitionLessFunc does one quicksort partition.
|
||||
// Let p = data[pivot]
|
||||
// Moves elements in data[a:b] around, so that data[i]<p and data[j]>=p for i<newpivot and j>newpivot.
|
||||
// On return, data[newpivot] = p
|
||||
func partitionLessFunc[E any](data []E, a, b, pivot int, less func(a, b E) bool) (newpivot int, alreadyPartitioned bool) {
|
||||
data[a], data[pivot] = data[pivot], data[a]
|
||||
i, j := a+1, b-1 // i and j are inclusive of the elements remaining to be partitioned
|
||||
|
||||
for i <= j && less(data[i], data[a]) {
|
||||
i++
|
||||
}
|
||||
for i <= j && !less(data[j], data[a]) {
|
||||
j--
|
||||
}
|
||||
if i > j {
|
||||
data[j], data[a] = data[a], data[j]
|
||||
return j, true
|
||||
}
|
||||
data[i], data[j] = data[j], data[i]
|
||||
i++
|
||||
j--
|
||||
|
||||
for {
|
||||
for i <= j && less(data[i], data[a]) {
|
||||
i++
|
||||
}
|
||||
for i <= j && !less(data[j], data[a]) {
|
||||
j--
|
||||
}
|
||||
if i > j {
|
||||
break
|
||||
}
|
||||
data[i], data[j] = data[j], data[i]
|
||||
i++
|
||||
j--
|
||||
}
|
||||
data[j], data[a] = data[a], data[j]
|
||||
return j, false
|
||||
}
|
||||
|
||||
// partitionEqualLessFunc partitions data[a:b] into elements equal to data[pivot] followed by elements greater than data[pivot].
|
||||
// It assumed that data[a:b] does not contain elements smaller than the data[pivot].
|
||||
func partitionEqualLessFunc[E any](data []E, a, b, pivot int, less func(a, b E) bool) (newpivot int) {
|
||||
data[a], data[pivot] = data[pivot], data[a]
|
||||
i, j := a+1, b-1 // i and j are inclusive of the elements remaining to be partitioned
|
||||
|
||||
for {
|
||||
for i <= j && !less(data[a], data[i]) {
|
||||
i++
|
||||
}
|
||||
for i <= j && less(data[a], data[j]) {
|
||||
j--
|
||||
}
|
||||
if i > j {
|
||||
break
|
||||
}
|
||||
data[i], data[j] = data[j], data[i]
|
||||
i++
|
||||
j--
|
||||
}
|
||||
return i
|
||||
}
|
||||
|
||||
// partialInsertionSortLessFunc partially sorts a slice, returns true if the slice is sorted at the end.
|
||||
func partialInsertionSortLessFunc[E any](data []E, a, b int, less func(a, b E) bool) bool {
|
||||
const (
|
||||
maxSteps = 5 // maximum number of adjacent out-of-order pairs that will get shifted
|
||||
shortestShifting = 50 // don't shift any elements on short arrays
|
||||
)
|
||||
i := a + 1
|
||||
for j := 0; j < maxSteps; j++ {
|
||||
for i < b && !less(data[i], data[i-1]) {
|
||||
i++
|
||||
}
|
||||
|
||||
if i == b {
|
||||
return true
|
||||
}
|
||||
|
||||
if b-a < shortestShifting {
|
||||
return false
|
||||
}
|
||||
|
||||
data[i], data[i-1] = data[i-1], data[i]
|
||||
|
||||
// Shift the smaller one to the left.
|
||||
if i-a >= 2 {
|
||||
for j := i - 1; j >= 1; j-- {
|
||||
if !less(data[j], data[j-1]) {
|
||||
break
|
||||
}
|
||||
data[j], data[j-1] = data[j-1], data[j]
|
||||
}
|
||||
}
|
||||
// Shift the greater one to the right.
|
||||
if b-i >= 2 {
|
||||
for j := i + 1; j < b; j++ {
|
||||
if !less(data[j], data[j-1]) {
|
||||
break
|
||||
}
|
||||
data[j], data[j-1] = data[j-1], data[j]
|
||||
}
|
||||
}
|
||||
}
|
||||
return false
|
||||
}
|
||||
|
||||
// breakPatternsLessFunc scatters some elements around in an attempt to break some patterns
|
||||
// that might cause imbalanced partitions in quicksort.
|
||||
func breakPatternsLessFunc[E any](data []E, a, b int, less func(a, b E) bool) {
|
||||
length := b - a
|
||||
if length >= 8 {
|
||||
random := xorshift(length)
|
||||
modulus := nextPowerOfTwo(length)
|
||||
|
||||
for idx := a + (length/4)*2 - 1; idx <= a+(length/4)*2+1; idx++ {
|
||||
other := int(uint(random.Next()) & (modulus - 1))
|
||||
if other >= length {
|
||||
other -= length
|
||||
}
|
||||
data[idx], data[a+other] = data[a+other], data[idx]
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// choosePivotLessFunc chooses a pivot in data[a:b].
|
||||
//
|
||||
// [0,8): chooses a static pivot.
|
||||
// [8,shortestNinther): uses the simple median-of-three method.
|
||||
// [shortestNinther,∞): uses the Tukey ninther method.
|
||||
func choosePivotLessFunc[E any](data []E, a, b int, less func(a, b E) bool) (pivot int, hint sortedHint) {
|
||||
const (
|
||||
shortestNinther = 50
|
||||
maxSwaps = 4 * 3
|
||||
)
|
||||
|
||||
l := b - a
|
||||
|
||||
var (
|
||||
swaps int
|
||||
i = a + l/4*1
|
||||
j = a + l/4*2
|
||||
k = a + l/4*3
|
||||
)
|
||||
|
||||
if l >= 8 {
|
||||
if l >= shortestNinther {
|
||||
// Tukey ninther method, the idea came from Rust's implementation.
|
||||
i = medianAdjacentLessFunc(data, i, &swaps, less)
|
||||
j = medianAdjacentLessFunc(data, j, &swaps, less)
|
||||
k = medianAdjacentLessFunc(data, k, &swaps, less)
|
||||
}
|
||||
// Find the median among i, j, k and stores it into j.
|
||||
j = medianLessFunc(data, i, j, k, &swaps, less)
|
||||
}
|
||||
|
||||
switch swaps {
|
||||
case 0:
|
||||
return j, increasingHint
|
||||
case maxSwaps:
|
||||
return j, decreasingHint
|
||||
default:
|
||||
return j, unknownHint
|
||||
}
|
||||
}
|
||||
|
||||
// order2LessFunc returns x,y where data[x] <= data[y], where x,y=a,b or x,y=b,a.
|
||||
func order2LessFunc[E any](data []E, a, b int, swaps *int, less func(a, b E) bool) (int, int) {
|
||||
if less(data[b], data[a]) {
|
||||
*swaps++
|
||||
return b, a
|
||||
}
|
||||
return a, b
|
||||
}
|
||||
|
||||
// medianLessFunc returns x where data[x] is the median of data[a],data[b],data[c], where x is a, b, or c.
|
||||
func medianLessFunc[E any](data []E, a, b, c int, swaps *int, less func(a, b E) bool) int {
|
||||
a, b = order2LessFunc(data, a, b, swaps, less)
|
||||
b, c = order2LessFunc(data, b, c, swaps, less)
|
||||
a, b = order2LessFunc(data, a, b, swaps, less)
|
||||
return b
|
||||
}
|
||||
|
||||
// medianAdjacentLessFunc finds the median of data[a - 1], data[a], data[a + 1] and stores the index into a.
|
||||
func medianAdjacentLessFunc[E any](data []E, a int, swaps *int, less func(a, b E) bool) int {
|
||||
return medianLessFunc(data, a-1, a, a+1, swaps, less)
|
||||
}
|
||||
|
||||
func reverseRangeLessFunc[E any](data []E, a, b int, less func(a, b E) bool) {
|
||||
i := a
|
||||
j := b - 1
|
||||
for i < j {
|
||||
data[i], data[j] = data[j], data[i]
|
||||
i++
|
||||
j--
|
||||
}
|
||||
}
|
||||
|
||||
func swapRangeLessFunc[E any](data []E, a, b, n int, less func(a, b E) bool) {
|
||||
for i := 0; i < n; i++ {
|
||||
data[a+i], data[b+i] = data[b+i], data[a+i]
|
||||
}
|
||||
}
|
||||
|
||||
func stableLessFunc[E any](data []E, n int, less func(a, b E) bool) {
|
||||
blockSize := 20 // must be > 0
|
||||
a, b := 0, blockSize
|
||||
for b <= n {
|
||||
insertionSortLessFunc(data, a, b, less)
|
||||
a = b
|
||||
b += blockSize
|
||||
}
|
||||
insertionSortLessFunc(data, a, n, less)
|
||||
|
||||
for blockSize < n {
|
||||
a, b = 0, 2*blockSize
|
||||
for b <= n {
|
||||
symMergeLessFunc(data, a, a+blockSize, b, less)
|
||||
a = b
|
||||
b += 2 * blockSize
|
||||
}
|
||||
if m := a + blockSize; m < n {
|
||||
symMergeLessFunc(data, a, m, n, less)
|
||||
}
|
||||
blockSize *= 2
|
||||
}
|
||||
}
|
||||
|
||||
// symMergeLessFunc merges the two sorted subsequences data[a:m] and data[m:b] using
|
||||
// the SymMerge algorithm from Pok-Son Kim and Arne Kutzner, "Stable Minimum
|
||||
// Storage Merging by Symmetric Comparisons", in Susanne Albers and Tomasz
|
||||
// Radzik, editors, Algorithms - ESA 2004, volume 3221 of Lecture Notes in
|
||||
// Computer Science, pages 714-723. Springer, 2004.
|
||||
//
|
||||
// Let M = m-a and N = b-n. Wolog M < N.
|
||||
// The recursion depth is bound by ceil(log(N+M)).
|
||||
// The algorithm needs O(M*log(N/M + 1)) calls to data.Less.
|
||||
// The algorithm needs O((M+N)*log(M)) calls to data.Swap.
|
||||
//
|
||||
// The paper gives O((M+N)*log(M)) as the number of assignments assuming a
|
||||
// rotation algorithm which uses O(M+N+gcd(M+N)) assignments. The argumentation
|
||||
// in the paper carries through for Swap operations, especially as the block
|
||||
// swapping rotate uses only O(M+N) Swaps.
|
||||
//
|
||||
// symMerge assumes non-degenerate arguments: a < m && m < b.
|
||||
// Having the caller check this condition eliminates many leaf recursion calls,
|
||||
// which improves performance.
|
||||
func symMergeLessFunc[E any](data []E, a, m, b int, less func(a, b E) bool) {
|
||||
// Avoid unnecessary recursions of symMerge
|
||||
// by direct insertion of data[a] into data[m:b]
|
||||
// if data[a:m] only contains one element.
|
||||
if m-a == 1 {
|
||||
// Use binary search to find the lowest index i
|
||||
// such that data[i] >= data[a] for m <= i < b.
|
||||
// Exit the search loop with i == b in case no such index exists.
|
||||
i := m
|
||||
j := b
|
||||
for i < j {
|
||||
h := int(uint(i+j) >> 1)
|
||||
if less(data[h], data[a]) {
|
||||
i = h + 1
|
||||
} else {
|
||||
j = h
|
||||
}
|
||||
}
|
||||
// Swap values until data[a] reaches the position before i.
|
||||
for k := a; k < i-1; k++ {
|
||||
data[k], data[k+1] = data[k+1], data[k]
|
||||
}
|
||||
return
|
||||
}
|
||||
|
||||
// Avoid unnecessary recursions of symMerge
|
||||
// by direct insertion of data[m] into data[a:m]
|
||||
// if data[m:b] only contains one element.
|
||||
if b-m == 1 {
|
||||
// Use binary search to find the lowest index i
|
||||
// such that data[i] > data[m] for a <= i < m.
|
||||
// Exit the search loop with i == m in case no such index exists.
|
||||
i := a
|
||||
j := m
|
||||
for i < j {
|
||||
h := int(uint(i+j) >> 1)
|
||||
if !less(data[m], data[h]) {
|
||||
i = h + 1
|
||||
} else {
|
||||
j = h
|
||||
}
|
||||
}
|
||||
// Swap values until data[m] reaches the position i.
|
||||
for k := m; k > i; k-- {
|
||||
data[k], data[k-1] = data[k-1], data[k]
|
||||
}
|
||||
return
|
||||
}
|
||||
|
||||
mid := int(uint(a+b) >> 1)
|
||||
n := mid + m
|
||||
var start, r int
|
||||
if m > mid {
|
||||
start = n - b
|
||||
r = mid
|
||||
} else {
|
||||
start = a
|
||||
r = m
|
||||
}
|
||||
p := n - 1
|
||||
|
||||
for start < r {
|
||||
c := int(uint(start+r) >> 1)
|
||||
if !less(data[p-c], data[c]) {
|
||||
start = c + 1
|
||||
} else {
|
||||
r = c
|
||||
}
|
||||
}
|
||||
|
||||
end := n - start
|
||||
if start < m && m < end {
|
||||
rotateLessFunc(data, start, m, end, less)
|
||||
}
|
||||
if a < start && start < mid {
|
||||
symMergeLessFunc(data, a, start, mid, less)
|
||||
}
|
||||
if mid < end && end < b {
|
||||
symMergeLessFunc(data, mid, end, b, less)
|
||||
}
|
||||
}
|
||||
|
||||
// rotateLessFunc rotates two consecutive blocks u = data[a:m] and v = data[m:b] in data:
|
||||
// Data of the form 'x u v y' is changed to 'x v u y'.
|
||||
// rotate performs at most b-a many calls to data.Swap,
|
||||
// and it assumes non-degenerate arguments: a < m && m < b.
|
||||
func rotateLessFunc[E any](data []E, a, m, b int, less func(a, b E) bool) {
|
||||
i := m - a
|
||||
j := b - m
|
||||
|
||||
for i != j {
|
||||
if i > j {
|
||||
swapRangeLessFunc(data, m-i, m, j, less)
|
||||
i -= j
|
||||
} else {
|
||||
swapRangeLessFunc(data, m-i, m+j-i, i, less)
|
||||
j -= i
|
||||
}
|
||||
}
|
||||
// i == j
|
||||
swapRangeLessFunc(data, m-i, m, i, less)
|
||||
}
|
||||
@ -0,0 +1,481 @@
|
||||
// Code generated by gen_sort_variants.go; DO NOT EDIT.
|
||||
|
||||
// Copyright 2022 The Go Authors. All rights reserved.
|
||||
// Use of this source code is governed by a BSD-style
|
||||
// license that can be found in the LICENSE file.
|
||||
|
||||
package slices
|
||||
|
||||
import "golang.org/x/exp/constraints"
|
||||
|
||||
// insertionSortOrdered sorts data[a:b] using insertion sort.
|
||||
func insertionSortOrdered[E constraints.Ordered](data []E, a, b int) {
|
||||
for i := a + 1; i < b; i++ {
|
||||
for j := i; j > a && (data[j] < data[j-1]); j-- {
|
||||
data[j], data[j-1] = data[j-1], data[j]
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// siftDownOrdered implements the heap property on data[lo:hi].
|
||||
// first is an offset into the array where the root of the heap lies.
|
||||
func siftDownOrdered[E constraints.Ordered](data []E, lo, hi, first int) {
|
||||
root := lo
|
||||
for {
|
||||
child := 2*root + 1
|
||||
if child >= hi {
|
||||
break
|
||||
}
|
||||
if child+1 < hi && (data[first+child] < data[first+child+1]) {
|
||||
child++
|
||||
}
|
||||
if !(data[first+root] < data[first+child]) {
|
||||
return
|
||||
}
|
||||
data[first+root], data[first+child] = data[first+child], data[first+root]
|
||||
root = child
|
||||
}
|
||||
}
|
||||
|
||||
func heapSortOrdered[E constraints.Ordered](data []E, 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-- {
|
||||
siftDownOrdered(data, i, hi, first)
|
||||
}
|
||||
|
||||
// Pop elements, largest first, into end of data.
|
||||
for i := hi - 1; i >= 0; i-- {
|
||||
data[first], data[first+i] = data[first+i], data[first]
|
||||
siftDownOrdered(data, lo, i, first)
|
||||
}
|
||||
}
|
||||
|
||||
// pdqsortOrdered sorts data[a:b].
|
||||
// The algorithm based on pattern-defeating quicksort(pdqsort), but without the optimizations from BlockQuicksort.
|
||||
// pdqsort paper: https://arxiv.org/pdf/2106.05123.pdf
|
||||
// C++ implementation: https://github.com/orlp/pdqsort
|
||||
// Rust implementation: https://docs.rs/pdqsort/latest/pdqsort/
|
||||
// limit is the number of allowed bad (very unbalanced) pivots before falling back to heapsort.
|
||||
func pdqsortOrdered[E constraints.Ordered](data []E, a, b, limit int) {
|
||||
const maxInsertion = 12
|
||||
|
||||
var (
|
||||
wasBalanced = true // whether the last partitioning was reasonably balanced
|
||||
wasPartitioned = true // whether the slice was already partitioned
|
||||
)
|
||||
|
||||
for {
|
||||
length := b - a
|
||||
|
||||
if length <= maxInsertion {
|
||||
insertionSortOrdered(data, a, b)
|
||||
return
|
||||
}
|
||||
|
||||
// Fall back to heapsort if too many bad choices were made.
|
||||
if limit == 0 {
|
||||
heapSortOrdered(data, a, b)
|
||||
return
|
||||
}
|
||||
|
||||
// If the last partitioning was imbalanced, we need to breaking patterns.
|
||||
if !wasBalanced {
|
||||
breakPatternsOrdered(data, a, b)
|
||||
limit--
|
||||
}
|
||||
|
||||
pivot, hint := choosePivotOrdered(data, a, b)
|
||||
if hint == decreasingHint {
|
||||
reverseRangeOrdered(data, a, b)
|
||||
// The chosen pivot was pivot-a elements after the start of the array.
|
||||
// After reversing it is pivot-a elements before the end of the array.
|
||||
// The idea came from Rust's implementation.
|
||||
pivot = (b - 1) - (pivot - a)
|
||||
hint = increasingHint
|
||||
}
|
||||
|
||||
// The slice is likely already sorted.
|
||||
if wasBalanced && wasPartitioned && hint == increasingHint {
|
||||
if partialInsertionSortOrdered(data, a, b) {
|
||||
return
|
||||
}
|
||||
}
|
||||
|
||||
// Probably the slice contains many duplicate elements, partition the slice into
|
||||
// elements equal to and elements greater than the pivot.
|
||||
if a > 0 && !(data[a-1] < data[pivot]) {
|
||||
mid := partitionEqualOrdered(data, a, b, pivot)
|
||||
a = mid
|
||||
continue
|
||||
}
|
||||
|
||||
mid, alreadyPartitioned := partitionOrdered(data, a, b, pivot)
|
||||
wasPartitioned = alreadyPartitioned
|
||||
|
||||
leftLen, rightLen := mid-a, b-mid
|
||||
balanceThreshold := length / 8
|
||||
if leftLen < rightLen {
|
||||
wasBalanced = leftLen >= balanceThreshold
|
||||
pdqsortOrdered(data, a, mid, limit)
|
||||
a = mid + 1
|
||||
} else {
|
||||
wasBalanced = rightLen >= balanceThreshold
|
||||
pdqsortOrdered(data, mid+1, b, limit)
|
||||
b = mid
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// partitionOrdered does one quicksort partition.
|
||||
// Let p = data[pivot]
|
||||
// Moves elements in data[a:b] around, so that data[i]<p and data[j]>=p for i<newpivot and j>newpivot.
|
||||
// On return, data[newpivot] = p
|
||||
func partitionOrdered[E constraints.Ordered](data []E, a, b, pivot int) (newpivot int, alreadyPartitioned bool) {
|
||||
data[a], data[pivot] = data[pivot], data[a]
|
||||
i, j := a+1, b-1 // i and j are inclusive of the elements remaining to be partitioned
|
||||
|
||||
for i <= j && (data[i] < data[a]) {
|
||||
i++
|
||||
}
|
||||
for i <= j && !(data[j] < data[a]) {
|
||||
j--
|
||||
}
|
||||
if i > j {
|
||||
data[j], data[a] = data[a], data[j]
|
||||
return j, true
|
||||
}
|
||||
data[i], data[j] = data[j], data[i]
|
||||
i++
|
||||
j--
|
||||
|
||||
for {
|
||||
for i <= j && (data[i] < data[a]) {
|
||||
i++
|
||||
}
|
||||
for i <= j && !(data[j] < data[a]) {
|
||||
j--
|
||||
}
|
||||
if i > j {
|
||||
break
|
||||
}
|
||||
data[i], data[j] = data[j], data[i]
|
||||
i++
|
||||
j--
|
||||
}
|
||||
data[j], data[a] = data[a], data[j]
|
||||
return j, false
|
||||
}
|
||||
|
||||
// partitionEqualOrdered partitions data[a:b] into elements equal to data[pivot] followed by elements greater than data[pivot].
|
||||
// It assumed that data[a:b] does not contain elements smaller than the data[pivot].
|
||||
func partitionEqualOrdered[E constraints.Ordered](data []E, a, b, pivot int) (newpivot int) {
|
||||
data[a], data[pivot] = data[pivot], data[a]
|
||||
i, j := a+1, b-1 // i and j are inclusive of the elements remaining to be partitioned
|
||||
|
||||
for {
|
||||
for i <= j && !(data[a] < data[i]) {
|
||||
i++
|
||||
}
|
||||
for i <= j && (data[a] < data[j]) {
|
||||
j--
|
||||
}
|
||||
if i > j {
|
||||
break
|
||||
}
|
||||
data[i], data[j] = data[j], data[i]
|
||||
i++
|
||||
j--
|
||||
}
|
||||
return i
|
||||
}
|
||||
|
||||
// partialInsertionSortOrdered partially sorts a slice, returns true if the slice is sorted at the end.
|
||||
func partialInsertionSortOrdered[E constraints.Ordered](data []E, a, b int) bool {
|
||||
const (
|
||||
maxSteps = 5 // maximum number of adjacent out-of-order pairs that will get shifted
|
||||
shortestShifting = 50 // don't shift any elements on short arrays
|
||||
)
|
||||
i := a + 1
|
||||
for j := 0; j < maxSteps; j++ {
|
||||
for i < b && !(data[i] < data[i-1]) {
|
||||
i++
|
||||
}
|
||||
|
||||
if i == b {
|
||||
return true
|
||||
}
|
||||
|
||||
if b-a < shortestShifting {
|
||||
return false
|
||||
}
|
||||
|
||||
data[i], data[i-1] = data[i-1], data[i]
|
||||
|
||||
// Shift the smaller one to the left.
|
||||
if i-a >= 2 {
|
||||
for j := i - 1; j >= 1; j-- {
|
||||
if !(data[j] < data[j-1]) {
|
||||
break
|
||||
}
|
||||
data[j], data[j-1] = data[j-1], data[j]
|
||||
}
|
||||
}
|
||||
// Shift the greater one to the right.
|
||||
if b-i >= 2 {
|
||||
for j := i + 1; j < b; j++ {
|
||||
if !(data[j] < data[j-1]) {
|
||||
break
|
||||
}
|
||||
data[j], data[j-1] = data[j-1], data[j]
|
||||
}
|
||||
}
|
||||
}
|
||||
return false
|
||||
}
|
||||
|
||||
// breakPatternsOrdered scatters some elements around in an attempt to break some patterns
|
||||
// that might cause imbalanced partitions in quicksort.
|
||||
func breakPatternsOrdered[E constraints.Ordered](data []E, a, b int) {
|
||||
length := b - a
|
||||
if length >= 8 {
|
||||
random := xorshift(length)
|
||||
modulus := nextPowerOfTwo(length)
|
||||
|
||||
for idx := a + (length/4)*2 - 1; idx <= a+(length/4)*2+1; idx++ {
|
||||
other := int(uint(random.Next()) & (modulus - 1))
|
||||
if other >= length {
|
||||
other -= length
|
||||
}
|
||||
data[idx], data[a+other] = data[a+other], data[idx]
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// choosePivotOrdered chooses a pivot in data[a:b].
|
||||
//
|
||||
// [0,8): chooses a static pivot.
|
||||
// [8,shortestNinther): uses the simple median-of-three method.
|
||||
// [shortestNinther,∞): uses the Tukey ninther method.
|
||||
func choosePivotOrdered[E constraints.Ordered](data []E, a, b int) (pivot int, hint sortedHint) {
|
||||
const (
|
||||
shortestNinther = 50
|
||||
maxSwaps = 4 * 3
|
||||
)
|
||||
|
||||
l := b - a
|
||||
|
||||
var (
|
||||
swaps int
|
||||
i = a + l/4*1
|
||||
j = a + l/4*2
|
||||
k = a + l/4*3
|
||||
)
|
||||
|
||||
if l >= 8 {
|
||||
if l >= shortestNinther {
|
||||
// Tukey ninther method, the idea came from Rust's implementation.
|
||||
i = medianAdjacentOrdered(data, i, &swaps)
|
||||
j = medianAdjacentOrdered(data, j, &swaps)
|
||||
k = medianAdjacentOrdered(data, k, &swaps)
|
||||
}
|
||||
// Find the median among i, j, k and stores it into j.
|
||||
j = medianOrdered(data, i, j, k, &swaps)
|
||||
}
|
||||
|
||||
switch swaps {
|
||||
case 0:
|
||||
return j, increasingHint
|
||||
case maxSwaps:
|
||||
return j, decreasingHint
|
||||
default:
|
||||
return j, unknownHint
|
||||
}
|
||||
}
|
||||
|
||||
// order2Ordered returns x,y where data[x] <= data[y], where x,y=a,b or x,y=b,a.
|
||||
func order2Ordered[E constraints.Ordered](data []E, a, b int, swaps *int) (int, int) {
|
||||
if data[b] < data[a] {
|
||||
*swaps++
|
||||
return b, a
|
||||
}
|
||||
return a, b
|
||||
}
|
||||
|
||||
// medianOrdered returns x where data[x] is the median of data[a],data[b],data[c], where x is a, b, or c.
|
||||
func medianOrdered[E constraints.Ordered](data []E, a, b, c int, swaps *int) int {
|
||||
a, b = order2Ordered(data, a, b, swaps)
|
||||
b, c = order2Ordered(data, b, c, swaps)
|
||||
a, b = order2Ordered(data, a, b, swaps)
|
||||
return b
|
||||
}
|
||||
|
||||
// medianAdjacentOrdered finds the median of data[a - 1], data[a], data[a + 1] and stores the index into a.
|
||||
func medianAdjacentOrdered[E constraints.Ordered](data []E, a int, swaps *int) int {
|
||||
return medianOrdered(data, a-1, a, a+1, swaps)
|
||||
}
|
||||
|
||||
func reverseRangeOrdered[E constraints.Ordered](data []E, a, b int) {
|
||||
i := a
|
||||
j := b - 1
|
||||
for i < j {
|
||||
data[i], data[j] = data[j], data[i]
|
||||
i++
|
||||
j--
|
||||
}
|
||||
}
|
||||
|
||||
func swapRangeOrdered[E constraints.Ordered](data []E, a, b, n int) {
|
||||
for i := 0; i < n; i++ {
|
||||
data[a+i], data[b+i] = data[b+i], data[a+i]
|
||||
}
|
||||
}
|
||||
|
||||
func stableOrdered[E constraints.Ordered](data []E, n int) {
|
||||
blockSize := 20 // must be > 0
|
||||
a, b := 0, blockSize
|
||||
for b <= n {
|
||||
insertionSortOrdered(data, a, b)
|
||||
a = b
|
||||
b += blockSize
|
||||
}
|
||||
insertionSortOrdered(data, a, n)
|
||||
|
||||
for blockSize < n {
|
||||
a, b = 0, 2*blockSize
|
||||
for b <= n {
|
||||
symMergeOrdered(data, a, a+blockSize, b)
|
||||
a = b
|
||||
b += 2 * blockSize
|
||||
}
|
||||
if m := a + blockSize; m < n {
|
||||
symMergeOrdered(data, a, m, n)
|
||||
}
|
||||
blockSize *= 2
|
||||
}
|
||||
}
|
||||
|
||||
// symMergeOrdered merges the two sorted subsequences data[a:m] and data[m:b] using
|
||||
// the SymMerge algorithm from Pok-Son Kim and Arne Kutzner, "Stable Minimum
|
||||
// Storage Merging by Symmetric Comparisons", in Susanne Albers and Tomasz
|
||||
// Radzik, editors, Algorithms - ESA 2004, volume 3221 of Lecture Notes in
|
||||
// Computer Science, pages 714-723. Springer, 2004.
|
||||
//
|
||||
// Let M = m-a and N = b-n. Wolog M < N.
|
||||
// The recursion depth is bound by ceil(log(N+M)).
|
||||
// The algorithm needs O(M*log(N/M + 1)) calls to data.Less.
|
||||
// The algorithm needs O((M+N)*log(M)) calls to data.Swap.
|
||||
//
|
||||
// The paper gives O((M+N)*log(M)) as the number of assignments assuming a
|
||||
// rotation algorithm which uses O(M+N+gcd(M+N)) assignments. The argumentation
|
||||
// in the paper carries through for Swap operations, especially as the block
|
||||
// swapping rotate uses only O(M+N) Swaps.
|
||||
//
|
||||
// symMerge assumes non-degenerate arguments: a < m && m < b.
|
||||
// Having the caller check this condition eliminates many leaf recursion calls,
|
||||
// which improves performance.
|
||||
func symMergeOrdered[E constraints.Ordered](data []E, a, m, b int) {
|
||||
// Avoid unnecessary recursions of symMerge
|
||||
// by direct insertion of data[a] into data[m:b]
|
||||
// if data[a:m] only contains one element.
|
||||
if m-a == 1 {
|
||||
// Use binary search to find the lowest index i
|
||||
// such that data[i] >= data[a] for m <= i < b.
|
||||
// Exit the search loop with i == b in case no such index exists.
|
||||
i := m
|
||||
j := b
|
||||
for i < j {
|
||||
h := int(uint(i+j) >> 1)
|
||||
if data[h] < data[a] {
|
||||
i = h + 1
|
||||
} else {
|
||||
j = h
|
||||
}
|
||||
}
|
||||
// Swap values until data[a] reaches the position before i.
|
||||
for k := a; k < i-1; k++ {
|
||||
data[k], data[k+1] = data[k+1], data[k]
|
||||
}
|
||||
return
|
||||
}
|
||||
|
||||
// Avoid unnecessary recursions of symMerge
|
||||
// by direct insertion of data[m] into data[a:m]
|
||||
// if data[m:b] only contains one element.
|
||||
if b-m == 1 {
|
||||
// Use binary search to find the lowest index i
|
||||
// such that data[i] > data[m] for a <= i < m.
|
||||
// Exit the search loop with i == m in case no such index exists.
|
||||
i := a
|
||||
j := m
|
||||
for i < j {
|
||||
h := int(uint(i+j) >> 1)
|
||||
if !(data[m] < data[h]) {
|
||||
i = h + 1
|
||||
} else {
|
||||
j = h
|
||||
}
|
||||
}
|
||||
// Swap values until data[m] reaches the position i.
|
||||
for k := m; k > i; k-- {
|
||||
data[k], data[k-1] = data[k-1], data[k]
|
||||
}
|
||||
return
|
||||
}
|
||||
|
||||
mid := int(uint(a+b) >> 1)
|
||||
n := mid + m
|
||||
var start, r int
|
||||
if m > mid {
|
||||
start = n - b
|
||||
r = mid
|
||||
} else {
|
||||
start = a
|
||||
r = m
|
||||
}
|
||||
p := n - 1
|
||||
|
||||
for start < r {
|
||||
c := int(uint(start+r) >> 1)
|
||||
if !(data[p-c] < data[c]) {
|
||||
start = c + 1
|
||||
} else {
|
||||
r = c
|
||||
}
|
||||
}
|
||||
|
||||
end := n - start
|
||||
if start < m && m < end {
|
||||
rotateOrdered(data, start, m, end)
|
||||
}
|
||||
if a < start && start < mid {
|
||||
symMergeOrdered(data, a, start, mid)
|
||||
}
|
||||
if mid < end && end < b {
|
||||
symMergeOrdered(data, mid, end, b)
|
||||
}
|
||||
}
|
||||
|
||||
// rotateOrdered rotates two consecutive blocks u = data[a:m] and v = data[m:b] in data:
|
||||
// Data of the form 'x u v y' is changed to 'x v u y'.
|
||||
// rotate performs at most b-a many calls to data.Swap,
|
||||
// and it assumes non-degenerate arguments: a < m && m < b.
|
||||
func rotateOrdered[E constraints.Ordered](data []E, a, m, b int) {
|
||||
i := m - a
|
||||
j := b - m
|
||||
|
||||
for i != j {
|
||||
if i > j {
|
||||
swapRangeOrdered(data, m-i, m, j)
|
||||
i -= j
|
||||
} else {
|
||||
swapRangeOrdered(data, m-i, m+j-i, i)
|
||||
j -= i
|
||||
}
|
||||
}
|
||||
// i == j
|
||||
swapRangeOrdered(data, m-i, m, i)
|
||||
}
|
||||
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
Loading…
Reference in New Issue