mirror of
https://github.com/superseriousbusiness/gotosocial.git
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1638470388
Bumps [golang.org/x/text](https://github.com/golang/text) from 0.3.7 to 0.4.0. - [Release notes](https://github.com/golang/text/releases) - [Commits](https://github.com/golang/text/compare/v0.3.7...v0.4.0) --- updated-dependencies: - dependency-name: golang.org/x/text dependency-type: direct:production update-type: version-update:semver-minor ... Signed-off-by: dependabot[bot] <support@github.com> Signed-off-by: dependabot[bot] <support@github.com> Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>
736 lines
25 KiB
Go
736 lines
25 KiB
Go
// Copyright 2013 The Go Authors. All rights reserved.
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// Use of this source code is governed by a BSD-style
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// license that can be found in the LICENSE file.
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package language
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import (
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"errors"
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"strings"
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"golang.org/x/text/internal/language"
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)
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// A MatchOption configures a Matcher.
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type MatchOption func(*matcher)
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// PreferSameScript will, in the absence of a match, result in the first
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// preferred tag with the same script as a supported tag to match this supported
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// tag. The default is currently true, but this may change in the future.
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func PreferSameScript(preferSame bool) MatchOption {
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return func(m *matcher) { m.preferSameScript = preferSame }
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}
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// TODO(v1.0.0): consider making Matcher a concrete type, instead of interface.
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// There doesn't seem to be too much need for multiple types.
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// Making it a concrete type allows MatchStrings to be a method, which will
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// improve its discoverability.
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// MatchStrings parses and matches the given strings until one of them matches
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// the language in the Matcher. A string may be an Accept-Language header as
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// handled by ParseAcceptLanguage. The default language is returned if no
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// other language matched.
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func MatchStrings(m Matcher, lang ...string) (tag Tag, index int) {
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for _, accept := range lang {
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desired, _, err := ParseAcceptLanguage(accept)
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if err != nil {
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continue
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}
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if tag, index, conf := m.Match(desired...); conf != No {
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return tag, index
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}
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}
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tag, index, _ = m.Match()
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return
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}
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// Matcher is the interface that wraps the Match method.
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//
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// Match returns the best match for any of the given tags, along with
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// a unique index associated with the returned tag and a confidence
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// score.
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type Matcher interface {
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Match(t ...Tag) (tag Tag, index int, c Confidence)
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}
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// Comprehends reports the confidence score for a speaker of a given language
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// to being able to comprehend the written form of an alternative language.
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func Comprehends(speaker, alternative Tag) Confidence {
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_, _, c := NewMatcher([]Tag{alternative}).Match(speaker)
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return c
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}
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// NewMatcher returns a Matcher that matches an ordered list of preferred tags
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// against a list of supported tags based on written intelligibility, closeness
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// of dialect, equivalence of subtags and various other rules. It is initialized
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// with the list of supported tags. The first element is used as the default
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// value in case no match is found.
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//
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// Its Match method matches the first of the given Tags to reach a certain
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// confidence threshold. The tags passed to Match should therefore be specified
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// in order of preference. Extensions are ignored for matching.
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//
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// The index returned by the Match method corresponds to the index of the
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// matched tag in t, but is augmented with the Unicode extension ('u')of the
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// corresponding preferred tag. This allows user locale options to be passed
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// transparently.
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func NewMatcher(t []Tag, options ...MatchOption) Matcher {
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return newMatcher(t, options)
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}
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func (m *matcher) Match(want ...Tag) (t Tag, index int, c Confidence) {
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var tt language.Tag
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match, w, c := m.getBest(want...)
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if match != nil {
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tt, index = match.tag, match.index
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} else {
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// TODO: this should be an option
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tt = m.default_.tag
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if m.preferSameScript {
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outer:
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for _, w := range want {
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script, _ := w.Script()
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if script.scriptID == 0 {
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// Don't do anything if there is no script, such as with
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// private subtags.
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continue
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}
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for i, h := range m.supported {
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if script.scriptID == h.maxScript {
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tt, index = h.tag, i
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break outer
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}
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}
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}
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}
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// TODO: select first language tag based on script.
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}
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if w.RegionID != tt.RegionID && w.RegionID != 0 {
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if w.RegionID != 0 && tt.RegionID != 0 && tt.RegionID.Contains(w.RegionID) {
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tt.RegionID = w.RegionID
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tt.RemakeString()
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} else if r := w.RegionID.String(); len(r) == 2 {
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// TODO: also filter macro and deprecated.
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tt, _ = tt.SetTypeForKey("rg", strings.ToLower(r)+"zzzz")
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}
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}
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// Copy options from the user-provided tag into the result tag. This is hard
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// to do after the fact, so we do it here.
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// TODO: add in alternative variants to -u-va-.
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// TODO: add preferred region to -u-rg-.
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if e := w.Extensions(); len(e) > 0 {
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b := language.Builder{}
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b.SetTag(tt)
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for _, e := range e {
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b.AddExt(e)
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}
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tt = b.Make()
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}
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return makeTag(tt), index, c
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}
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// ErrMissingLikelyTagsData indicates no information was available
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// to compute likely values of missing tags.
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var ErrMissingLikelyTagsData = errors.New("missing likely tags data")
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// func (t *Tag) setTagsFrom(id Tag) {
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// t.LangID = id.LangID
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// t.ScriptID = id.ScriptID
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// t.RegionID = id.RegionID
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// }
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// Tag Matching
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// CLDR defines an algorithm for finding the best match between two sets of language
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// tags. The basic algorithm defines how to score a possible match and then find
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// the match with the best score
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// (see https://www.unicode.org/reports/tr35/#LanguageMatching).
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// Using scoring has several disadvantages. The scoring obfuscates the importance of
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// the various factors considered, making the algorithm harder to understand. Using
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// scoring also requires the full score to be computed for each pair of tags.
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//
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// We will use a different algorithm which aims to have the following properties:
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// - clarity on the precedence of the various selection factors, and
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// - improved performance by allowing early termination of a comparison.
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//
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// Matching algorithm (overview)
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// Input:
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// - supported: a set of supported tags
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// - default: the default tag to return in case there is no match
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// - desired: list of desired tags, ordered by preference, starting with
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// the most-preferred.
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//
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// Algorithm:
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// 1) Set the best match to the lowest confidence level
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// 2) For each tag in "desired":
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// a) For each tag in "supported":
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// 1) compute the match between the two tags.
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// 2) if the match is better than the previous best match, replace it
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// with the new match. (see next section)
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// b) if the current best match is Exact and pin is true the result will be
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// frozen to the language found thusfar, although better matches may
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// still be found for the same language.
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// 3) If the best match so far is below a certain threshold, return "default".
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//
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// Ranking:
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// We use two phases to determine whether one pair of tags are a better match
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// than another pair of tags. First, we determine a rough confidence level. If the
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// levels are different, the one with the highest confidence wins.
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// Second, if the rough confidence levels are identical, we use a set of tie-breaker
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// rules.
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//
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// The confidence level of matching a pair of tags is determined by finding the
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// lowest confidence level of any matches of the corresponding subtags (the
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// result is deemed as good as its weakest link).
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// We define the following levels:
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// Exact - An exact match of a subtag, before adding likely subtags.
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// MaxExact - An exact match of a subtag, after adding likely subtags.
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// [See Note 2].
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// High - High level of mutual intelligibility between different subtag
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// variants.
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// Low - Low level of mutual intelligibility between different subtag
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// variants.
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// No - No mutual intelligibility.
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//
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// The following levels can occur for each type of subtag:
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// Base: Exact, MaxExact, High, Low, No
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// Script: Exact, MaxExact [see Note 3], Low, No
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// Region: Exact, MaxExact, High
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// Variant: Exact, High
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// Private: Exact, No
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//
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// Any result with a confidence level of Low or higher is deemed a possible match.
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// Once a desired tag matches any of the supported tags with a level of MaxExact
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// or higher, the next desired tag is not considered (see Step 2.b).
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// Note that CLDR provides languageMatching data that defines close equivalence
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// classes for base languages, scripts and regions.
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//
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// Tie-breaking
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// If we get the same confidence level for two matches, we apply a sequence of
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// tie-breaking rules. The first that succeeds defines the result. The rules are
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// applied in the following order.
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// 1) Original language was defined and was identical.
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// 2) Original region was defined and was identical.
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// 3) Distance between two maximized regions was the smallest.
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// 4) Original script was defined and was identical.
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// 5) Distance from want tag to have tag using the parent relation [see Note 5.]
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// If there is still no winner after these rules are applied, the first match
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// found wins.
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//
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// Notes:
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// [2] In practice, as matching of Exact is done in a separate phase from
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// matching the other levels, we reuse the Exact level to mean MaxExact in
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// the second phase. As a consequence, we only need the levels defined by
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// the Confidence type. The MaxExact confidence level is mapped to High in
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// the public API.
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// [3] We do not differentiate between maximized script values that were derived
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// from suppressScript versus most likely tag data. We determined that in
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// ranking the two, one ranks just after the other. Moreover, the two cannot
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// occur concurrently. As a consequence, they are identical for practical
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// purposes.
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// [4] In case of deprecated, macro-equivalents and legacy mappings, we assign
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// the MaxExact level to allow iw vs he to still be a closer match than
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// en-AU vs en-US, for example.
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// [5] In CLDR a locale inherits fields that are unspecified for this locale
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// from its parent. Therefore, if a locale is a parent of another locale,
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// it is a strong measure for closeness, especially when no other tie
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// breaker rule applies. One could also argue it is inconsistent, for
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// example, when pt-AO matches pt (which CLDR equates with pt-BR), even
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// though its parent is pt-PT according to the inheritance rules.
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//
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// Implementation Details:
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// There are several performance considerations worth pointing out. Most notably,
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// we preprocess as much as possible (within reason) at the time of creation of a
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// matcher. This includes:
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// - creating a per-language map, which includes data for the raw base language
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// and its canonicalized variant (if applicable),
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// - expanding entries for the equivalence classes defined in CLDR's
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// languageMatch data.
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// The per-language map ensures that typically only a very small number of tags
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// need to be considered. The pre-expansion of canonicalized subtags and
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// equivalence classes reduces the amount of map lookups that need to be done at
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// runtime.
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// matcher keeps a set of supported language tags, indexed by language.
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type matcher struct {
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default_ *haveTag
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supported []*haveTag
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index map[language.Language]*matchHeader
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passSettings bool
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preferSameScript bool
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}
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// matchHeader has the lists of tags for exact matches and matches based on
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// maximized and canonicalized tags for a given language.
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type matchHeader struct {
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haveTags []*haveTag
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original bool
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}
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// haveTag holds a supported Tag and its maximized script and region. The maximized
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// or canonicalized language is not stored as it is not needed during matching.
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type haveTag struct {
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tag language.Tag
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// index of this tag in the original list of supported tags.
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index int
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// conf is the maximum confidence that can result from matching this haveTag.
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// When conf < Exact this means it was inserted after applying a CLDR equivalence rule.
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conf Confidence
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// Maximized region and script.
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maxRegion language.Region
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maxScript language.Script
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// altScript may be checked as an alternative match to maxScript. If altScript
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// matches, the confidence level for this match is Low. Theoretically there
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// could be multiple alternative scripts. This does not occur in practice.
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altScript language.Script
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// nextMax is the index of the next haveTag with the same maximized tags.
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nextMax uint16
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}
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func makeHaveTag(tag language.Tag, index int) (haveTag, language.Language) {
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max := tag
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if tag.LangID != 0 || tag.RegionID != 0 || tag.ScriptID != 0 {
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max, _ = canonicalize(All, max)
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max, _ = max.Maximize()
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max.RemakeString()
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}
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return haveTag{tag, index, Exact, max.RegionID, max.ScriptID, altScript(max.LangID, max.ScriptID), 0}, max.LangID
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}
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// altScript returns an alternative script that may match the given script with
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// a low confidence. At the moment, the langMatch data allows for at most one
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// script to map to another and we rely on this to keep the code simple.
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func altScript(l language.Language, s language.Script) language.Script {
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for _, alt := range matchScript {
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// TODO: also match cases where language is not the same.
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if (language.Language(alt.wantLang) == l || language.Language(alt.haveLang) == l) &&
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language.Script(alt.haveScript) == s {
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return language.Script(alt.wantScript)
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}
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}
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return 0
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}
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// addIfNew adds a haveTag to the list of tags only if it is a unique tag.
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// Tags that have the same maximized values are linked by index.
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func (h *matchHeader) addIfNew(n haveTag, exact bool) {
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h.original = h.original || exact
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// Don't add new exact matches.
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for _, v := range h.haveTags {
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if equalsRest(v.tag, n.tag) {
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return
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}
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}
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// Allow duplicate maximized tags, but create a linked list to allow quickly
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// comparing the equivalents and bail out.
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for i, v := range h.haveTags {
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if v.maxScript == n.maxScript &&
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v.maxRegion == n.maxRegion &&
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v.tag.VariantOrPrivateUseTags() == n.tag.VariantOrPrivateUseTags() {
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for h.haveTags[i].nextMax != 0 {
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i = int(h.haveTags[i].nextMax)
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}
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h.haveTags[i].nextMax = uint16(len(h.haveTags))
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break
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}
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}
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h.haveTags = append(h.haveTags, &n)
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}
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// header returns the matchHeader for the given language. It creates one if
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// it doesn't already exist.
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func (m *matcher) header(l language.Language) *matchHeader {
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if h := m.index[l]; h != nil {
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return h
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}
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h := &matchHeader{}
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m.index[l] = h
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return h
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}
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func toConf(d uint8) Confidence {
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if d <= 10 {
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return High
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}
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if d < 30 {
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return Low
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}
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return No
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}
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// newMatcher builds an index for the given supported tags and returns it as
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// a matcher. It also expands the index by considering various equivalence classes
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// for a given tag.
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func newMatcher(supported []Tag, options []MatchOption) *matcher {
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m := &matcher{
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index: make(map[language.Language]*matchHeader),
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preferSameScript: true,
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}
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for _, o := range options {
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o(m)
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}
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if len(supported) == 0 {
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m.default_ = &haveTag{}
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return m
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}
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// Add supported languages to the index. Add exact matches first to give
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// them precedence.
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for i, tag := range supported {
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tt := tag.tag()
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pair, _ := makeHaveTag(tt, i)
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m.header(tt.LangID).addIfNew(pair, true)
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m.supported = append(m.supported, &pair)
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}
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m.default_ = m.header(supported[0].lang()).haveTags[0]
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// Keep these in two different loops to support the case that two equivalent
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// languages are distinguished, such as iw and he.
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for i, tag := range supported {
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tt := tag.tag()
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pair, max := makeHaveTag(tt, i)
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if max != tt.LangID {
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m.header(max).addIfNew(pair, true)
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}
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}
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// update is used to add indexes in the map for equivalent languages.
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// update will only add entries to original indexes, thus not computing any
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// transitive relations.
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update := func(want, have uint16, conf Confidence) {
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if hh := m.index[language.Language(have)]; hh != nil {
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if !hh.original {
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return
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}
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hw := m.header(language.Language(want))
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for _, ht := range hh.haveTags {
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v := *ht
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if conf < v.conf {
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v.conf = conf
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}
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v.nextMax = 0 // this value needs to be recomputed
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if v.altScript != 0 {
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v.altScript = altScript(language.Language(want), v.maxScript)
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}
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hw.addIfNew(v, conf == Exact && hh.original)
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}
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}
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}
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// Add entries for languages with mutual intelligibility as defined by CLDR's
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// languageMatch data.
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for _, ml := range matchLang {
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update(ml.want, ml.have, toConf(ml.distance))
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if !ml.oneway {
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update(ml.have, ml.want, toConf(ml.distance))
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}
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}
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// Add entries for possible canonicalizations. This is an optimization to
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// ensure that only one map lookup needs to be done at runtime per desired tag.
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// First we match deprecated equivalents. If they are perfect equivalents
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// (their canonicalization simply substitutes a different language code, but
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// nothing else), the match confidence is Exact, otherwise it is High.
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for i, lm := range language.AliasMap {
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// If deprecated codes match and there is no fiddling with the script or
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// or region, we consider it an exact match.
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conf := Exact
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if language.AliasTypes[i] != language.Macro {
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if !isExactEquivalent(language.Language(lm.From)) {
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conf = High
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}
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update(lm.To, lm.From, conf)
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}
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update(lm.From, lm.To, conf)
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}
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return m
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}
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// getBest gets the best matching tag in m for any of the given tags, taking into
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// account the order of preference of the given tags.
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func (m *matcher) getBest(want ...Tag) (got *haveTag, orig language.Tag, c Confidence) {
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best := bestMatch{}
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for i, ww := range want {
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w := ww.tag()
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var max language.Tag
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// Check for exact match first.
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h := m.index[w.LangID]
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if w.LangID != 0 {
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if h == nil {
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continue
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}
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// Base language is defined.
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max, _ = canonicalize(Legacy|Deprecated|Macro, w)
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// A region that is added through canonicalization is stronger than
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// a maximized region: set it in the original (e.g. mo -> ro-MD).
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if w.RegionID != max.RegionID {
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w.RegionID = max.RegionID
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}
|
|
// TODO: should we do the same for scripts?
|
|
// See test case: en, sr, nl ; sh ; sr
|
|
max, _ = max.Maximize()
|
|
} else {
|
|
// Base language is not defined.
|
|
if h != nil {
|
|
for i := range h.haveTags {
|
|
have := h.haveTags[i]
|
|
if equalsRest(have.tag, w) {
|
|
return have, w, Exact
|
|
}
|
|
}
|
|
}
|
|
if w.ScriptID == 0 && w.RegionID == 0 {
|
|
// We skip all tags matching und for approximate matching, including
|
|
// private tags.
|
|
continue
|
|
}
|
|
max, _ = w.Maximize()
|
|
if h = m.index[max.LangID]; h == nil {
|
|
continue
|
|
}
|
|
}
|
|
pin := true
|
|
for _, t := range want[i+1:] {
|
|
if w.LangID == t.lang() {
|
|
pin = false
|
|
break
|
|
}
|
|
}
|
|
// Check for match based on maximized tag.
|
|
for i := range h.haveTags {
|
|
have := h.haveTags[i]
|
|
best.update(have, w, max.ScriptID, max.RegionID, pin)
|
|
if best.conf == Exact {
|
|
for have.nextMax != 0 {
|
|
have = h.haveTags[have.nextMax]
|
|
best.update(have, w, max.ScriptID, max.RegionID, pin)
|
|
}
|
|
return best.have, best.want, best.conf
|
|
}
|
|
}
|
|
}
|
|
if best.conf <= No {
|
|
if len(want) != 0 {
|
|
return nil, want[0].tag(), No
|
|
}
|
|
return nil, language.Tag{}, No
|
|
}
|
|
return best.have, best.want, best.conf
|
|
}
|
|
|
|
// bestMatch accumulates the best match so far.
|
|
type bestMatch struct {
|
|
have *haveTag
|
|
want language.Tag
|
|
conf Confidence
|
|
pinnedRegion language.Region
|
|
pinLanguage bool
|
|
sameRegionGroup bool
|
|
// Cached results from applying tie-breaking rules.
|
|
origLang bool
|
|
origReg bool
|
|
paradigmReg bool
|
|
regGroupDist uint8
|
|
origScript bool
|
|
}
|
|
|
|
// 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.
|
|
//
|
|
// If pin is true and have and tag are a strong match, it will henceforth only
|
|
// consider matches for this language. This corresponds to the idea that most
|
|
// users have a strong preference for the first defined language. A user can
|
|
// still prefer a second language over a dialect of the preferred language by
|
|
// explicitly specifying dialects, e.g. "en, nl, en-GB". In this case pin should
|
|
// be false.
|
|
func (m *bestMatch) update(have *haveTag, tag language.Tag, maxScript language.Script, maxRegion language.Region, pin bool) {
|
|
// Bail if the maximum attainable confidence is below that of the current best match.
|
|
c := have.conf
|
|
if c < m.conf {
|
|
return
|
|
}
|
|
// Don't change the language once we already have found an exact match.
|
|
if m.pinLanguage && tag.LangID != m.want.LangID {
|
|
return
|
|
}
|
|
// Pin the region group if we are comparing tags for the same language.
|
|
if tag.LangID == m.want.LangID && m.sameRegionGroup {
|
|
_, sameGroup := regionGroupDist(m.pinnedRegion, have.maxRegion, have.maxScript, m.want.LangID)
|
|
if !sameGroup {
|
|
return
|
|
}
|
|
}
|
|
if c == Exact && have.maxScript == maxScript {
|
|
// If there is another language and then another entry of this language,
|
|
// don't pin anything, otherwise pin the language.
|
|
m.pinLanguage = pin
|
|
}
|
|
if equalsRest(have.tag, tag) {
|
|
} else 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 {
|
|
if High < c {
|
|
// There is usually a small difference between languages across regions.
|
|
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.LangID == tag.LangID && tag.LangID != 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.RegionID == tag.RegionID && tag.RegionID != 0
|
|
if !beaten && m.origReg != origReg {
|
|
if m.origReg {
|
|
return
|
|
}
|
|
beaten = true
|
|
}
|
|
|
|
regGroupDist, sameGroup := regionGroupDist(have.maxRegion, maxRegion, maxScript, tag.LangID)
|
|
if !beaten && m.regGroupDist != regGroupDist {
|
|
if regGroupDist > m.regGroupDist {
|
|
return
|
|
}
|
|
beaten = true
|
|
}
|
|
|
|
paradigmReg := isParadigmLocale(tag.LangID, have.maxRegion)
|
|
if !beaten && m.paradigmReg != paradigmReg {
|
|
if !paradigmReg {
|
|
return
|
|
}
|
|
beaten = true
|
|
}
|
|
|
|
// Next we prefer if the pre-maximized script was specified and identical.
|
|
origScript := have.tag.ScriptID == tag.ScriptID && tag.ScriptID != 0
|
|
if !beaten && m.origScript != origScript {
|
|
if m.origScript {
|
|
return
|
|
}
|
|
beaten = true
|
|
}
|
|
|
|
// Update m to the newly found best match.
|
|
if beaten {
|
|
m.have = have
|
|
m.want = tag
|
|
m.conf = c
|
|
m.pinnedRegion = maxRegion
|
|
m.sameRegionGroup = sameGroup
|
|
m.origLang = origLang
|
|
m.origReg = origReg
|
|
m.paradigmReg = paradigmReg
|
|
m.origScript = origScript
|
|
m.regGroupDist = regGroupDist
|
|
}
|
|
}
|
|
|
|
func isParadigmLocale(lang language.Language, r language.Region) bool {
|
|
for _, e := range paradigmLocales {
|
|
if language.Language(e[0]) == lang && (r == language.Region(e[1]) || r == language.Region(e[2])) {
|
|
return true
|
|
}
|
|
}
|
|
return false
|
|
}
|
|
|
|
// regionGroupDist computes the distance between two regions based on their
|
|
// CLDR grouping.
|
|
func regionGroupDist(a, b language.Region, script language.Script, lang language.Language) (dist uint8, same bool) {
|
|
const defaultDistance = 4
|
|
|
|
aGroup := uint(regionToGroups[a]) << 1
|
|
bGroup := uint(regionToGroups[b]) << 1
|
|
for _, ri := range matchRegion {
|
|
if language.Language(ri.lang) == lang && (ri.script == 0 || language.Script(ri.script) == script) {
|
|
group := uint(1 << (ri.group &^ 0x80))
|
|
if 0x80&ri.group == 0 {
|
|
if aGroup&bGroup&group != 0 { // Both regions are in the group.
|
|
return ri.distance, ri.distance == defaultDistance
|
|
}
|
|
} else {
|
|
if (aGroup|bGroup)&group == 0 { // Both regions are not in the group.
|
|
return ri.distance, ri.distance == defaultDistance
|
|
}
|
|
}
|
|
}
|
|
}
|
|
return defaultDistance, true
|
|
}
|
|
|
|
// equalsRest compares everything except the language.
|
|
func equalsRest(a, b language.Tag) bool {
|
|
// TODO: don't include extensions in this comparison. To do this efficiently,
|
|
// though, we should handle private tags separately.
|
|
return a.ScriptID == b.ScriptID && a.RegionID == b.RegionID && a.VariantOrPrivateUseTags() == b.VariantOrPrivateUseTags()
|
|
}
|
|
|
|
// isExactEquivalent returns true if canonicalizing the language will not alter
|
|
// the script or region of a tag.
|
|
func isExactEquivalent(l language.Language) bool {
|
|
for _, o := range notEquivalent {
|
|
if o == l {
|
|
return false
|
|
}
|
|
}
|
|
return true
|
|
}
|
|
|
|
var notEquivalent []language.Language
|
|
|
|
func init() {
|
|
// Create a list of all languages for which canonicalization may alter the
|
|
// script or region.
|
|
for _, lm := range language.AliasMap {
|
|
tag := language.Tag{LangID: language.Language(lm.From)}
|
|
if tag, _ = canonicalize(All, tag); tag.ScriptID != 0 || tag.RegionID != 0 {
|
|
notEquivalent = append(notEquivalent, language.Language(lm.From))
|
|
}
|
|
}
|
|
// Maximize undefined regions of paradigm locales.
|
|
for i, v := range paradigmLocales {
|
|
t := language.Tag{LangID: language.Language(v[0])}
|
|
max, _ := t.Maximize()
|
|
if v[1] == 0 {
|
|
paradigmLocales[i][1] = uint16(max.RegionID)
|
|
}
|
|
if v[2] == 0 {
|
|
paradigmLocales[i][2] = uint16(max.RegionID)
|
|
}
|
|
}
|
|
}
|