// Package summary summarizes the current state of triaging.
package summary

import (
	"sort"

	"go.skia.org/infra/go/metrics2"
	"go.skia.org/infra/go/paramtools"
	"go.skia.org/infra/golden/go/blame"
	"go.skia.org/infra/golden/go/digest_counter"
	"go.skia.org/infra/golden/go/expectations"
	"go.skia.org/infra/golden/go/tiling"
	"go.skia.org/infra/golden/go/types"
)

// TriageStatus contains rolled up digest counts/blames for one test in one corpus.
// It is immutable and should be thread safe.
type TriageStatus struct {
	// TODO(kjlubick) Change Name/Corpus to be a more generic "Grouping"
	Name      types.TestName        `json:"name"`
	Corpus    string                `json:"corpus"`
	Pos       int                   `json:"pos"`
	Neg       int                   `json:"neg"`
	Untriaged int                   `json:"untriaged"`
	Num       int                   `json:"num"`
	UntHashes types.DigestSlice     `json:"untHashes"`
	Blame     []blame.WeightedBlame `json:"blame"`
	// currently unused
	Diameter int `json:"diameter"`
}

// MergeSorted creates a new []*TriageStatus from this and the passed
// in slices. The passed in data will "win" in the event there are tests
// in both. We assume that the two passed in slices are sorted by TestName,Corpus already.
func MergeSorted(existing, newOnes []*TriageStatus) []*TriageStatus {
	ret := make([]*TriageStatus, 0, len(existing)+len(newOnes))

	// Basic algorithm for merging two sorted arrays, with a small tweak to have
	// the second one win for an exact match on Name and Corpus.
	i, j := 0, 0
	for i < len(existing) && j < len(newOnes) {
		e, n := existing[i], newOnes[j]
		if e.Name == n.Name && e.Corpus == n.Corpus {
			ret = append(ret, n)
			i++
			j++
		} else if e.Name > n.Name || (e.Name == n.Name && e.Corpus > n.Corpus) {
			ret = append(ret, n)
			j++
		} else {
			ret = append(ret, e)
			i++
		}
	}
	// Only one of these will actually append something, since j or i are at the end.
	ret = append(ret, newOnes[j:]...)
	ret = append(ret, existing[i:]...)

	return ret
}

// Data is a helper struct containing the data that goes into computing a summary.
type Data struct {
	Traces       []*tiling.TracePair
	Expectations expectations.ReadOnly
	// ByTrace maps all traces in Trace to the counts of digests that appeared
	// in those traces.
	ByTrace map[tiling.TraceID]digest_counter.DigestCount
	Blamer  blame.Blamer
}

// Calculate calculates a slice of TriageStatus for the given data and query options. It will
// summarize only those traces that match the given testNames (if any), the query (if any), and
// optionally be only for those digests at head. At head means just the non-empty digests that
// appear in the most recent commit. The return value will have its entries sorted by TestName
// first, then sorted by Corpus in the event of a tie.
func (s *Data) Calculate(testNames types.TestNameSet, query paramtools.ParamSet, head bool) []*TriageStatus {
	if len(s.Traces) == 0 {
		return nil
	}
	defer metrics2.FuncTimer().Stop()

	// Filter down to just the traces we are interested in, based on query.
	filtered := map[grouping][]*tiling.TracePair{}
	for _, tp := range s.Traces {
		if len(testNames) > 0 && !testNames[tp.Trace.TestName()] {
			continue
		}
		if len(query) == 0 || tp.Trace.Matches(query) {
			k := grouping{test: tp.Trace.TestName(), corpus: tp.Trace.Corpus()}
			if slice, ok := filtered[k]; ok {
				filtered[k] = append(slice, tp)
			} else {
				filtered[k] = []*tiling.TracePair{tp}
			}
		}
	}

	// Now create summaries for each test using the filtered set of traces.
	var ret []*TriageStatus
	for k, traces := range filtered {
		digestMap := types.DigestSet{}
		for _, pair := range traces {
			if head {
				// Find the last non-missing value in the trace.
				if d := pair.Trace.AtHead(); d != tiling.MissingDigest {
					digestMap[d] = true
				}
			} else {
				// Use the digests by trace if available, otherwise just inspect the trace.
				if t, ok := s.ByTrace[pair.ID]; ok {
					for d := range t {
						digestMap[d] = true
					}
				} else {
					for i := len(pair.Trace.Digests) - 1; i >= 0; i-- {
						if !pair.Trace.IsMissing(i) {
							digestMap[pair.Trace.Digests[i]] = true
						}
					}
				}
			}
		}
		ret = append(ret, s.makeSummary(k.test, k.corpus, digestMap.Keys()))
	}

	// Sort for determinism and to allow clients to use binary search.
	sort.Slice(ret, func(i, j int) bool {
		return ret[i].Name < ret[j].Name || (ret[i].Name == ret[j].Name && ret[i].Corpus < ret[j].Corpus)
	})

	return ret
}

// grouping is the set of information used to combine like traces.
type grouping struct {
	test   types.TestName
	corpus string
}

// makeSummary returns a TriageStatus for the given digests.
func (s *Data) makeSummary(name types.TestName, corpus string, digests types.DigestSlice) *TriageStatus {
	pos := 0
	neg := 0
	unt := 0
	diamDigests := types.DigestSlice{}
	untHashes := types.DigestSlice{}
	for _, digest := range digests {
		switch s.Expectations.Classification(name, digest) {
		case expectations.Untriaged:
			unt += 1
			diamDigests = append(diamDigests, digest)
			untHashes = append(untHashes, digest)
		case expectations.Negative:
			neg += 1
		case expectations.Positive:
			pos += 1
			diamDigests = append(diamDigests, digest)
		}
	}

	sort.Sort(diamDigests)
	sort.Sort(untHashes)

	return &TriageStatus{
		Name:      name,
		Pos:       pos,
		Neg:       neg,
		Untriaged: unt,
		UntHashes: untHashes,
		Num:       pos + neg + unt,
		Corpus:    corpus,
		Blame:     s.Blamer.GetBlamesForTest(name),
	}
}