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gitea/vendor/golang.org/x/text/language/match.go
2018-05-20 18:09:00 +08:00

853 lines
26 KiB
Go

// Copyright 2013 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 language
import "errors"
// Matcher is the interface that wraps the Match method.
//
// Match returns the best match for any of the given tags, along with
// a unique index associated with the returned tag and a confidence
// score.
type Matcher interface {
Match(t ...Tag) (tag Tag, index int, c Confidence)
}
// Comprehends reports the confidence score for a speaker of a given language
// to being able to comprehend the written form of an alternative language.
func Comprehends(speaker, alternative Tag) Confidence {
_, _, c := NewMatcher([]Tag{alternative}).Match(speaker)
return c
}
// NewMatcher returns a Matcher that matches an ordered list of preferred tags
// against a list of supported tags based on written intelligibility, closeness
// of dialect, equivalence of subtags and various other rules. It is initialized
// with the list of supported tags. The first element is used as the default
// value in case no match is found.
//
// Its Match method matches the first of the given Tags to reach a certain
// confidence threshold. The tags passed to Match should therefore be specified
// in order of preference. Extensions are ignored for matching.
//
// The index returned by the Match method corresponds to the index of the
// matched tag in t, but is augmented with the Unicode extension ('u')of the
// corresponding preferred tag. This allows user locale options to be passed
// transparently.
func NewMatcher(t []Tag) Matcher {
return newMatcher(t)
}
func (m *matcher) Match(want ...Tag) (t Tag, index int, c Confidence) {
match, w, c := m.getBest(want...)
if match == nil {
t = m.default_.tag
} else {
t, index = match.tag, match.index
}
// Copy options from the user-provided tag into the result tag. This is hard
// to do after the fact, so we do it here.
// TODO: consider also adding in variants that are compatible with the
// matched language.
// TODO: Add back region if it is non-ambiguous? Or create another tag to
// preserve the region?
if u, ok := w.Extension('u'); ok {
t, _ = Raw.Compose(t, u)
}
return t, index, c
}
type scriptRegionFlags uint8
const (
isList = 1 << iota
scriptInFrom
regionInFrom
)
func (t *Tag) setUndefinedLang(id langID) {
if t.lang == 0 {
t.lang = id
}
}
func (t *Tag) setUndefinedScript(id scriptID) {
if t.script == 0 {
t.script = id
}
}
func (t *Tag) setUndefinedRegion(id regionID) {
if t.region == 0 || t.region.contains(id) {
t.region = id
}
}
// ErrMissingLikelyTagsData indicates no information was available
// to compute likely values of missing tags.
var ErrMissingLikelyTagsData = errors.New("missing likely tags data")
// addLikelySubtags sets subtags to their most likely value, given the locale.
// In most cases this means setting fields for unknown values, but in some
// cases it may alter a value. It returns a ErrMissingLikelyTagsData error
// if the given locale cannot be expanded.
func (t Tag) addLikelySubtags() (Tag, error) {
id, err := addTags(t)
if err != nil {
return t, err
} else if id.equalTags(t) {
return t, nil
}
id.remakeString()
return id, nil
}
// specializeRegion attempts to specialize a group region.
func specializeRegion(t *Tag) bool {
if i := regionInclusion[t.region]; i < nRegionGroups {
x := likelyRegionGroup[i]
if langID(x.lang) == t.lang && scriptID(x.script) == t.script {
t.region = regionID(x.region)
}
return true
}
return false
}
func addTags(t Tag) (Tag, error) {
// We leave private use identifiers alone.
if t.private() {
return t, nil
}
if t.script != 0 && t.region != 0 {
if t.lang != 0 {
// already fully specified
specializeRegion(&t)
return t, nil
}
// Search matches for und-script-region. Note that for these cases
// region will never be a group so there is no need to check for this.
list := likelyRegion[t.region : t.region+1]
if x := list[0]; x.flags&isList != 0 {
list = likelyRegionList[x.lang : x.lang+uint16(x.script)]
}
for _, x := range list {
// Deviating from the spec. See match_test.go for details.
if scriptID(x.script) == t.script {
t.setUndefinedLang(langID(x.lang))
return t, nil
}
}
}
if t.lang != 0 {
// Search matches for lang-script and lang-region, where lang != und.
if t.lang < langNoIndexOffset {
x := likelyLang[t.lang]
if x.flags&isList != 0 {
list := likelyLangList[x.region : x.region+uint16(x.script)]
if t.script != 0 {
for _, x := range list {
if scriptID(x.script) == t.script && x.flags&scriptInFrom != 0 {
t.setUndefinedRegion(regionID(x.region))
return t, nil
}
}
} else if t.region != 0 {
count := 0
goodScript := true
tt := t
for _, x := range list {
// We visit all entries for which the script was not
// defined, including the ones where the region was not
// defined. This allows for proper disambiguation within
// regions.
if x.flags&scriptInFrom == 0 && t.region.contains(regionID(x.region)) {
tt.region = regionID(x.region)
tt.setUndefinedScript(scriptID(x.script))
goodScript = goodScript && tt.script == scriptID(x.script)
count++
}
}
if count == 1 {
return tt, nil
}
// Even if we fail to find a unique Region, we might have
// an unambiguous script.
if goodScript {
t.script = tt.script
}
}
}
}
} else {
// Search matches for und-script.
if t.script != 0 {
x := likelyScript[t.script]
if x.region != 0 {
t.setUndefinedRegion(regionID(x.region))
t.setUndefinedLang(langID(x.lang))
return t, nil
}
}
// Search matches for und-region. If und-script-region exists, it would
// have been found earlier.
if t.region != 0 {
if i := regionInclusion[t.region]; i < nRegionGroups {
x := likelyRegionGroup[i]
if x.region != 0 {
t.setUndefinedLang(langID(x.lang))
t.setUndefinedScript(scriptID(x.script))
t.region = regionID(x.region)
}
} else {
x := likelyRegion[t.region]
if x.flags&isList != 0 {
x = likelyRegionList[x.lang]
}
if x.script != 0 && x.flags != scriptInFrom {
t.setUndefinedLang(langID(x.lang))
t.setUndefinedScript(scriptID(x.script))
return t, nil
}
}
}
}
// Search matches for lang.
if t.lang < langNoIndexOffset {
x := likelyLang[t.lang]
if x.flags&isList != 0 {
x = likelyLangList[x.region]
}
if x.region != 0 {
t.setUndefinedScript(scriptID(x.script))
t.setUndefinedRegion(regionID(x.region))
}
specializeRegion(&t)
if t.lang == 0 {
t.lang = _en // default language
}
return t, nil
}
return t, ErrMissingLikelyTagsData
}
func (t *Tag) setTagsFrom(id Tag) {
t.lang = id.lang
t.script = id.script
t.region = id.region
}
// minimize removes the region or script subtags from t such that
// t.addLikelySubtags() == t.minimize().addLikelySubtags().
func (t Tag) minimize() (Tag, error) {
t, err := minimizeTags(t)
if err != nil {
return t, err
}
t.remakeString()
return t, nil
}
// minimizeTags mimics the behavior of the ICU 51 C implementation.
func minimizeTags(t Tag) (Tag, error) {
if t.equalTags(und) {
return t, nil
}
max, err := addTags(t)
if err != nil {
return t, err
}
for _, id := range [...]Tag{
{lang: t.lang},
{lang: t.lang, region: t.region},
{lang: t.lang, script: t.script},
} {
if x, err := addTags(id); err == nil && max.equalTags(x) {
t.setTagsFrom(id)
break
}
}
return t, nil
}
// Tag Matching
// CLDR defines an algorithm for finding the best match between two sets of language
// tags. The basic algorithm defines how to score a possible match and then find
// the match with the best score
// (see http://www.unicode.org/reports/tr35/#LanguageMatching).
// Using scoring has several disadvantages. The scoring obfuscates the importance of
// the various factors considered, making the algorithm harder to understand. Using
// scoring also requires the full score to be computed for each pair of tags.
//
// We will use a different algorithm which aims to have the following properties:
// - clarity on the precedence of the various selection factors, and
// - improved performance by allowing early termination of a comparison.
//
// Matching algorithm (overview)
// Input:
// - supported: a set of supported tags
// - default: the default tag to return in case there is no match
// - desired: list of desired tags, ordered by preference, starting with
// the most-preferred.
//
// Algorithm:
// 1) Set the best match to the lowest confidence level
// 2) For each tag in "desired":
// a) For each tag in "supported":
// 1) compute the match between the two tags.
// 2) if the match is better than the previous best match, replace it
// with the new match. (see next section)
// b) if the current best match is above a certain threshold, return this
// match without proceeding to the next tag in "desired". [See Note 1]
// 3) If the best match so far is below a certain threshold, return "default".
//
// Ranking:
// We use two phases to determine whether one pair of tags are a better match
// than another pair of tags. First, we determine a rough confidence level. If the
// levels are different, the one with the highest confidence wins.
// Second, if the rough confidence levels are identical, we use a set of tie-breaker
// rules.
//
// The confidence level of matching a pair of tags is determined by finding the
// lowest confidence level of any matches of the corresponding subtags (the
// result is deemed as good as its weakest link).
// We define the following levels:
// Exact - An exact match of a subtag, before adding likely subtags.
// MaxExact - An exact match of a subtag, after adding likely subtags.
// [See Note 2].
// High - High level of mutual intelligibility between different subtag
// variants.
// Low - Low level of mutual intelligibility between different subtag
// variants.
// No - No mutual intelligibility.
//
// The following levels can occur for each type of subtag:
// Base: Exact, MaxExact, High, Low, No
// Script: Exact, MaxExact [see Note 3], Low, No
// Region: Exact, MaxExact, High
// Variant: Exact, High
// Private: Exact, No
//
// Any result with a confidence level of Low or higher is deemed a possible match.
// Once a desired tag matches any of the supported tags with a level of MaxExact
// or higher, the next desired tag is not considered (see Step 2.b).
// Note that CLDR provides languageMatching data that defines close equivalence
// classes for base languages, scripts and regions.
//
// Tie-breaking
// If we get the same confidence level for two matches, we apply a sequence of
// tie-breaking rules. The first that succeeds defines the result. The rules are
// applied in the following order.
// 1) Original language was defined and was identical.
// 2) Original region was defined and was identical.
// 3) Distance between two maximized regions was the smallest.
// 4) Original script was defined and was identical.
// 5) Distance from want tag to have tag using the parent relation [see Note 5.]
// If there is still no winner after these rules are applied, the first match
// found wins.
//
// Notes:
// [1] Note that even if we may not have a perfect match, if a match is above a
// certain threshold, it is considered a better match than any other match
// to a tag later in the list of preferred language tags.
// [2] In practice, as matching of Exact is done in a separate phase from
// matching the other levels, we reuse the Exact level to mean MaxExact in
// the second phase. As a consequence, we only need the levels defined by
// the Confidence type. The MaxExact confidence level is mapped to High in
// the public API.
// [3] We do not differentiate between maximized script values that were derived
// from suppressScript versus most likely tag data. We determined that in
// ranking the two, one ranks just after the other. Moreover, the two cannot
// occur concurrently. As a consequence, they are identical for practical
// purposes.
// [4] In case of deprecated, macro-equivalents and legacy mappings, we assign
// the MaxExact level to allow iw vs he to still be a closer match than
// en-AU vs en-US, for example.
// [5] In CLDR a locale inherits fields that are unspecified for this locale
// from its parent. Therefore, if a locale is a parent of another locale,
// it is a strong measure for closeness, especially when no other tie
// breaker rule applies. One could also argue it is inconsistent, for
// example, when pt-AO matches pt (which CLDR equates with pt-BR), even
// though its parent is pt-PT according to the inheritance rules.
//
// Implementation Details:
// There are several performance considerations worth pointing out. Most notably,
// we preprocess as much as possible (within reason) at the time of creation of a
// matcher. This includes:
// - creating a per-language map, which includes data for the raw base language
// and its canonicalized variant (if applicable),
// - expanding entries for the equivalence classes defined in CLDR's
// languageMatch data.
// The per-language map ensures that typically only a very small number of tags
// need to be considered. The pre-expansion of canonicalized subtags and
// equivalence classes reduces the amount of map lookups that need to be done at
// runtime.
// matcher keeps a set of supported language tags, indexed by language.
type matcher struct {
default_ *haveTag
index map[langID]*matchHeader
passSettings bool
}
// matchHeader has the lists of tags for exact matches and matches based on
// maximized and canonicalized tags for a given language.
type matchHeader struct {
exact []*haveTag
max []*haveTag
}
// haveTag holds a supported Tag and its maximized script and region. The maximized
// or canonicalized language is not stored as it is not needed during matching.
type haveTag struct {
tag Tag
// index of this tag in the original list of supported tags.
index int
// conf is the maximum confidence that can result from matching this haveTag.
// When conf < Exact this means it was inserted after applying a CLDR equivalence rule.
conf Confidence
// Maximized region and script.
maxRegion regionID
maxScript scriptID
// altScript may be checked as an alternative match to maxScript. If altScript
// matches, the confidence level for this match is Low. Theoretically there
// could be multiple alternative scripts. This does not occur in practice.
altScript scriptID
// nextMax is the index of the next haveTag with the same maximized tags.
nextMax uint16
}
func makeHaveTag(tag Tag, index int) (haveTag, langID) {
max := tag
if tag.lang != 0 {
max, _ = max.canonicalize(All)
max, _ = addTags(max)
max.remakeString()
}
return haveTag{tag, index, Exact, max.region, max.script, altScript(max.lang, max.script), 0}, max.lang
}
// altScript returns an alternative script that may match the given script with
// a low confidence. At the moment, the langMatch data allows for at most one
// script to map to another and we rely on this to keep the code simple.
func altScript(l langID, s scriptID) scriptID {
for _, alt := range matchScript {
// TODO: also match cases where language is not the same.
if (langID(alt.wantLang) == l || langID(alt.haveLang) == l) &&
scriptID(alt.haveScript) == s {
return scriptID(alt.wantScript)
}
}
return 0
}
// addIfNew adds a haveTag to the list of tags only if it is a unique tag.
// Tags that have the same maximized values are linked by index.
func (h *matchHeader) addIfNew(n haveTag, exact bool) {
// Don't add new exact matches.
for _, v := range h.exact {
if v.tag.equalsRest(n.tag) {
return
}
}
if exact {
h.exact = append(h.exact, &n)
}
// Allow duplicate maximized tags, but create a linked list to allow quickly
// comparing the equivalents and bail out.
for i, v := range h.max {
if v.maxScript == n.maxScript &&
v.maxRegion == n.maxRegion &&
v.tag.variantOrPrivateTagStr() == n.tag.variantOrPrivateTagStr() {
for h.max[i].nextMax != 0 {
i = int(h.max[i].nextMax)
}
h.max[i].nextMax = uint16(len(h.max))
break
}
}
h.max = append(h.max, &n)
}
// header returns the matchHeader for the given language. It creates one if
// it doesn't already exist.
func (m *matcher) header(l langID) *matchHeader {
if h := m.index[l]; h != nil {
return h
}
h := &matchHeader{}
m.index[l] = h
return h
}
func toConf(d uint8) Confidence {
if d <= 10 {
return High
}
if d < 30 {
return Low
}
return No
}
// newMatcher builds an index for the given supported tags and returns it as
// a matcher. It also expands the index by considering various equivalence classes
// for a given tag.
func newMatcher(supported []Tag) *matcher {
m := &matcher{
index: make(map[langID]*matchHeader),
}
if len(supported) == 0 {
m.default_ = &haveTag{}
return m
}
// Add supported languages to the index. Add exact matches first to give
// them precedence.
for i, tag := range supported {
pair, _ := makeHaveTag(tag, i)
m.header(tag.lang).addIfNew(pair, true)
}
m.default_ = m.header(supported[0].lang).exact[0]
for i, tag := range supported {
pair, max := makeHaveTag(tag, i)
if max != tag.lang {
m.header(max).addIfNew(pair, false)
}
}
// update is used to add indexes in the map for equivalent languages.
// If force is true, the update will also apply to derived entries. To
// avoid applying a "transitive closure", use false.
update := func(want, have uint16, conf Confidence, force bool) {
if hh := m.index[langID(have)]; hh != nil {
if !force && len(hh.exact) == 0 {
return
}
hw := m.header(langID(want))
for _, ht := range hh.max {
v := *ht
if conf < v.conf {
v.conf = conf
}
v.nextMax = 0 // this value needs to be recomputed
if v.altScript != 0 {
v.altScript = altScript(langID(want), v.maxScript)
}
hw.addIfNew(v, conf == Exact && len(hh.exact) > 0)
}
}
}
// Add entries for languages with mutual intelligibility as defined by CLDR's
// languageMatch data.
for _, ml := range matchLang {
update(ml.want, ml.have, toConf(ml.distance), false)
if !ml.oneway {
update(ml.have, ml.want, toConf(ml.distance), false)
}
}
// Add entries for possible canonicalizations. This is an optimization to
// ensure that only one map lookup needs to be done at runtime per desired tag.
// First we match deprecated equivalents. If they are perfect equivalents
// (their canonicalization simply substitutes a different language code, but
// nothing else), the match confidence is Exact, otherwise it is High.
for i, lm := range langAliasMap {
if lm.from == _sh {
continue
}
// If deprecated codes match and there is no fiddling with the script or
// or region, we consider it an exact match.
conf := Exact
if langAliasTypes[i] != langMacro {
if !isExactEquivalent(langID(lm.from)) {
conf = High
}
update(lm.to, lm.from, conf, true)
}
update(lm.from, lm.to, conf, true)
}
return m
}
// getBest gets the best matching tag in m for any of the given tags, taking into
// account the order of preference of the given tags.
func (m *matcher) getBest(want ...Tag) (got *haveTag, orig Tag, c Confidence) {
best := bestMatch{}
for _, w := range want {
var max Tag
// Check for exact match first.
h := m.index[w.lang]
if w.lang != 0 {
// Base language is defined.
if h == nil {
continue
}
for i := range h.exact {
have := h.exact[i]
if have.tag.equalsRest(w) {
return have, w, Exact
}
}
max, _ = w.canonicalize(Legacy | Deprecated)
max, _ = addTags(max)
} else {
// Base language is not defined.
if h != nil {
for i := range h.exact {
have := h.exact[i]
if have.tag.equalsRest(w) {
return have, w, Exact
}
}
}
if w.script == 0 && w.region == 0 {
// We skip all tags matching und for approximate matching, including
// private tags.
continue
}
max, _ = addTags(w)
if h = m.index[max.lang]; h == nil {
continue
}
}
// Check for match based on maximized tag.
for i := range h.max {
have := h.max[i]
best.update(have, w, max.script, max.region)
if best.conf == Exact {
for have.nextMax != 0 {
have = h.max[have.nextMax]
best.update(have, w, max.script, max.region)
}
return best.have, best.want, High
}
}
}
if best.conf <= No {
if len(want) != 0 {
return nil, want[0], No
}
return nil, Tag{}, No
}
return best.have, best.want, best.conf
}
// bestMatch accumulates the best match so far.
type bestMatch struct {
have *haveTag
want Tag
conf Confidence
// Cached results from applying tie-breaking rules.
origLang bool
origReg bool
regDist uint8
origScript bool
parentDist uint8 // 255 if have is not an ancestor of want tag.
}
// update updates the existing best match if the new pair is considered to be a
// better match.
// To determine if the given pair is a better match, it first computes the rough
// confidence level. If this surpasses the current match, it will replace it and
// update the tie-breaker rule cache. If there is a tie, it proceeds with applying
// a series of tie-breaker rules. If there is no conclusive winner after applying
// the tie-breaker rules, it leaves the current match as the preferred match.
func (m *bestMatch) update(have *haveTag, tag Tag, maxScript scriptID, maxRegion regionID) {
// Bail if the maximum attainable confidence is below that of the current best match.
c := have.conf
if c < m.conf {
return
}
if have.maxScript != maxScript {
// There is usually very little comprehension between different scripts.
// In a few cases there may still be Low comprehension. This possibility is
// pre-computed and stored in have.altScript.
if Low < m.conf || have.altScript != maxScript {
return
}
c = Low
} else if have.maxRegion != maxRegion {
// There is usually a small difference between languages across regions.
// We use the region distance (below) to disambiguate between equal matches.
if High < c {
c = High
}
}
// We store the results of the computations of the tie-breaker rules along
// with the best match. There is no need to do the checks once we determine
// we have a winner, but we do still need to do the tie-breaker computations.
// We use "beaten" to keep track if we still need to do the checks.
beaten := false // true if the new pair defeats the current one.
if c != m.conf {
if c < m.conf {
return
}
beaten = true
}
// Tie-breaker rules:
// We prefer if the pre-maximized language was specified and identical.
origLang := have.tag.lang == tag.lang && tag.lang != 0
if !beaten && m.origLang != origLang {
if m.origLang {
return
}
beaten = true
}
// We prefer if the pre-maximized region was specified and identical.
origReg := have.tag.region == tag.region && tag.region != 0
if !beaten && m.origReg != origReg {
if m.origReg {
return
}
beaten = true
}
// Next we prefer smaller distances between regions, as defined by regionDist.
regDist := regionDist(have.maxRegion, maxRegion, tag.lang)
if !beaten && m.regDist != regDist {
if regDist > m.regDist {
return
}
beaten = true
}
// Next we prefer if the pre-maximized script was specified and identical.
origScript := have.tag.script == tag.script && tag.script != 0
if !beaten && m.origScript != origScript {
if m.origScript {
return
}
beaten = true
}
// Finally we prefer tags which have a closer parent relationship.
parentDist := parentDistance(have.tag.region, tag)
if !beaten && m.parentDist != parentDist {
if parentDist > m.parentDist {
return
}
beaten = true
}
// Update m to the newly found best match.
if beaten {
m.have = have
m.want = tag
m.conf = c
m.origLang = origLang
m.origReg = origReg
m.origScript = origScript
m.regDist = regDist
m.parentDist = parentDist
}
}
// parentDistance returns the number of times Parent must be called before the
// regions match. It is assumed that it has already been checked that lang and
// script are identical. If haveRegion does not occur in the ancestor chain of
// tag, it returns 255.
func parentDistance(haveRegion regionID, tag Tag) uint8 {
p := tag.Parent()
d := uint8(1)
for haveRegion != p.region {
if p.region == 0 {
return 255
}
p = p.Parent()
d++
}
return d
}
// regionDist wraps regionDistance with some exceptions to the algorithmic distance.
func regionDist(a, b regionID, lang langID) uint8 {
if lang == _en {
// Two variants of non-US English are close to each other, regardless of distance.
if a != _US && b != _US {
return 2
}
}
return uint8(regionDistance(a, b))
}
// regionDistance computes the distance between two regions based on the
// distance in the graph of region containments as defined in CLDR. It iterates
// over increasingly inclusive sets of groups, represented as bit vectors, until
// the source bit vector has bits in common with the destination vector.
func regionDistance(a, b regionID) int {
if a == b {
return 0
}
p, q := regionInclusion[a], regionInclusion[b]
if p < nRegionGroups {
p, q = q, p
}
set := regionInclusionBits
if q < nRegionGroups && set[p]&(1<<q) != 0 {
return 1
}
d := 2
for goal := set[q]; set[p]&goal == 0; p = regionInclusionNext[p] {
d++
}
return d
}
func (t Tag) variants() string {
if t.pVariant == 0 {
return ""
}
return t.str[t.pVariant:t.pExt]
}
// variantOrPrivateTagStr returns variants or private use tags.
func (t Tag) variantOrPrivateTagStr() string {
if t.pExt > 0 {
return t.str[t.pVariant:t.pExt]
}
return t.str[t.pVariant:]
}
// equalsRest compares everything except the language.
func (a Tag) equalsRest(b Tag) bool {
// TODO: don't include extensions in this comparison. To do this efficiently,
// though, we should handle private tags separately.
return a.script == b.script && a.region == b.region && a.variantOrPrivateTagStr() == b.variantOrPrivateTagStr()
}
// isExactEquivalent returns true if canonicalizing the language will not alter
// the script or region of a tag.
func isExactEquivalent(l langID) bool {
for _, o := range notEquivalent {
if o == l {
return false
}
}
return true
}
var notEquivalent []langID
func init() {
// Create a list of all languages for which canonicalization may alter the
// script or region.
for _, lm := range langAliasMap {
tag := Tag{lang: langID(lm.from)}
if tag, _ = tag.canonicalize(All); tag.script != 0 || tag.region != 0 {
notEquivalent = append(notEquivalent, langID(lm.from))
}
}
}