// Seek implements http.File.
func (f *HTTPFile) Seek(offset int64, whence int) (int64, error) {
	if f.closed {
		return 0, os.ErrInvalid
	}

	if offset < 0 {
		return int64(f.off), fmt.Errorf("cannot seek before start of file")
	}

	switch whence {
	case 0:
		noff := int64(f.off) + offset
		if noff > mathutil.MaxInt {
			return int64(f.off), fmt.Errorf("seek target overflows int: %d", noff)
		}

		f.off = mathutil.Min(int(offset), len(f.content))
		if f.off == int(offset) {
			return offset, nil
		}

		return int64(f.off), io.EOF
	case 1:
		noff := int64(f.off) + offset
		if noff > mathutil.MaxInt {
			return int64(f.off), fmt.Errorf("seek target overflows int: %d", noff)
		}

		off := mathutil.Min(f.off+int(offset), len(f.content))
		if off == f.off+int(offset) {
			f.off = off
			return int64(off), nil
		}

		f.off = off
		return int64(off), io.EOF
	case 2:
		noff := int64(f.off) - offset
		if noff < 0 {
			return int64(f.off), fmt.Errorf("cannot seek before start of file")
		}

		f.off = len(f.content) - int(offset)
		return int64(f.off), nil
	default:
		return int64(f.off), fmt.Errorf("seek: invalid whence %d", whence)
	}
}

//Pick cells to form distal connections to.
func (tm *TemporalMemory) pickCellsToLearnOn(n int, segment int,
	winnerCells []int, connections *TemporalMemoryConnections) []int {

	candidates := make([]int, len(winnerCells))
	copy(candidates, winnerCells)

	for _, val := range connections.SynapsesForSegment(segment) {
		syn := connections.DataForSynapse(val)
		for idx, val := range candidates {
			if val == syn.SourceCell {
				candidates = append(candidates[:idx], candidates[idx+1:]...)
				break
			}
		}
	}

	//Shuffle candidates
	for i := range candidates {
		j := rand.Intn(i + 1)
		candidates[i], candidates[j] = candidates[j], candidates[i]
	}

	n = mathutil.Min(n, len(candidates))
	return candidates[:n]
}

func (f *mem) ReadAt(b []byte, off int64) (n int, err error) {
	avail := f.size - off
	pi := off >> f.pgBits
	po := int(off) & f.pgMask
	rem := len(b)
	if int64(rem) >= avail {
		rem = int(avail)
		err = io.EOF
	}
	var zeroPage *[]byte
	for rem != 0 && avail > 0 {
		pg := f.m[pi]
		if pg == nil {
			if zeroPage == nil {
				zeroPage = buffer.CGet(f.pgSize)
				defer buffer.Put(zeroPage)
			}
			pg = zeroPage
		}
		nc := copy(b[:mathutil.Min(rem, f.pgSize)], (*pg)[po:])
		pi++
		po = 0
		rem -= nc
		n += nc
		b = b[nc:]
	}
	return n, err
}

func (f *bitFiler) ReadAt(b []byte, off int64) (n int, err error) {
	avail := f.size - off
	pgI := off >> bfBits
	pgO := int(off & bfMask)
	rem := len(b)
	if int64(rem) >= avail {
		rem = int(avail)
		err = io.EOF
	}
	for rem != 0 && avail > 0 {
		pg := f.m[pgI]
		if pg == nil {
			pg = &bitPage{}
			pg.pdata = buffer.CGet(bfSize)
			pg.data = *pg.pdata
			if f.parent != nil {
				_, err = f.parent.ReadAt(pg.data, off&^bfMask)
				if err != nil && !fileutil.IsEOF(err) {
					return
				}

				err = nil
			}
			f.m[pgI] = pg
		}
		nc := copy(b[:mathutil.Min(rem, bfSize)], pg.data[pgO:])
		pgI++
		pgO = 0
		rem -= nc
		n += nc
		b = b[nc:]
		off += int64(nc)
	}
	return
}

func (t *treeCache) getTree(db *DB, prefix int, name string, canCreate bool, cacheSize int) (r *lldb.BTree, err error) {
	m := t.get()
	r, ok := m[name]
	if ok {
		return
	}

	root, err := db.root()
	if err != nil {
		return
	}

	val, err := root.get(prefix, name)
	if err != nil {
		return
	}

	switch x := val.(type) {
	case nil:
		if !canCreate {
			return
		}

		var h int64
		r, h, err = lldb.CreateBTree(db.alloc, collate)
		if err != nil {
			return nil, err
		}

		if err = root.set(h, prefix, name); err != nil {
			return nil, err
		}
	case int64:
		if r, err = lldb.OpenBTree(db.alloc, collate, x); err != nil {
			return nil, err
		}
	default:
		return nil, &lldb.ErrINVAL{Src: "corrupted root directory value for", Val: fmt.Sprintf("%q, %q", prefix, name)}
	}

	if len(m) > cacheSize {
		i, j, n := 0, cacheSize/2, mathutil.Min(cacheSize/20, 10)
	loop:
		for k := range m {
			if i++; i >= j {
				delete(m, k)
				if n == 0 {
					break loop
				}

				n--
			}
		}
	}

	m[name] = r
	return
}

func (c *cache) get2(n int) (r *node, isZeroed bool) {
	s := *c
	lens := len(s)
	if lens == 0 {
		return &node{b: make([]byte, n, mathutil.Min(2*n, maxBuf))}, true
	}

	i := sort.Search(lens, func(x int) bool { return len(s[x].b) >= n })
	if i == lens {
		i--
		s[i].b, isZeroed = make([]byte, n, mathutil.Min(2*n, maxBuf)), true
	}

	r = s[i]
	r.b = r.b[:n]
	copy(s[i:], s[i+1:])
	s = s[:lens-1]
	*c = s
	return
}

// Execute implements Instruction.
//
// Stack frame before Execute:
//
//	        +----------------+
//	        | Return address |
//	        +----------------+
//	  SP -> |                |
//
//
// Stack frame after Execute:
//
//	        +----------------+
//	        | Return address |
//	        +----------------+
//	        | Previous FP    |
//	        +----------------+
//	        | [LNL]int       | Parent Frame Pointers
//	        +----------------+
//	        | LNL            | Lexical Nesting Level
//	        +----------------+
//	  FP -> | [NVars]int     | Local variables
//	        +----------------+
//	  SP -> |                ! Evaluation stack
func (n *Enter) Execute(m *VM) {
	m.push(m.FP)
	cur := 0
	if n.LNL != 0 {
		cur = m.read(m.FP - 1)
		fp0x := m.FP - 1 - cur
		for i := 0; i < mathutil.Min(cur, n.LNL); i++ {
			m.push(m.read(fp0x))
			fp0x++
		}
	}
	if n.LNL > cur {
		m.push(m.FP)
	}
	m.push(n.LNL)
	m.FP = m.SP()
	m.Stack = append(m.Stack, make([]int, n.NVars)...)
}

// PutBytes stores b in the DB and returns its id.  Zero length byte slices are
// guaranteed to return zero ID. PutBytes Locks the DB before updating it.
func (d *MemDB) PutBytes(b []byte) int {
	if len(b) == 0 {
		return 0
	}

	if len(b) == 1 {
		return int(b[0]) + 1
	}

	d.mu.Lock() // W+

	id := d.nextID
	pi := id >> dbPageShift
	if pi < len(d.pages) {
		p := d.pages[pi]
		off := id & dbPageMask
		if n := cap(p) - off - maxUvarint; n >= len(b) {
			p = p[:cap(p)]
			l := binary.PutUvarint(p[off:], uint64(len(b)))
			copy(p[off+l:], b)
			n = l + len(b)
			d.pages[pi] = p[:off+n]
			d.nextID += n

			d.mu.Unlock() // W-

			return id + 257
		}

		pi++
	}

	p := make([]byte, mathutil.Max(dbPageSize, maxUvarint+len(b)))
	p = p[:binary.PutUvarint(p, uint64(len(b)))]
	p = append(p, b...)
	d.pages = append(d.pages, p)
	id = pi << dbPageShift
	d.nextID = id + mathutil.Min(dbPageSize, len(p))

	d.mu.Unlock() // W-

	return id + 257
}

// Readdir implements http.File.
func (f *HTTPFile) Readdir(count int) ([]os.FileInfo, error) {
	if f.isFile {
		return nil, fmt.Errorf("not a directory: %s", f.name)
	}

	if count <= 0 {
		r := f.dirEntries
		f.dirEntries = f.dirEntries[:0]
		return r, nil
	}

	rq := mathutil.Min(count, len(f.dirEntries))
	r := f.dirEntries[:rq]
	f.dirEntries = f.dirEntries[rq:]
	if len(r) != 0 {
		return r, nil
	}

	return nil, io.EOF
}

// ReadAt implements Filer.
func (f *MemFiler) ReadAt(b []byte, off int64) (n int, err error) {
	avail := f.size - off
	pgI := off >> pgBits
	pgO := int(off & pgMask)
	rem := len(b)
	if int64(rem) >= avail {
		rem = int(avail)
		err = io.EOF
	}
	for rem != 0 && avail > 0 {
		pg := f.m[pgI]
		if pg == nil {
			pg = &zeroPage
		}
		nc := copy(b[:mathutil.Min(rem, pgSize)], pg[pgO:])
		pgI++
		pgO = 0
		rem -= nc
		n += nc
		b = b[nc:]
	}
	return
}

func (f *File) readAt(b []byte, off int64, bits bool) (n int, err error) {
	var fsize int64
	if !bits {
		fsize, err = f.Size()
		if err != nil {
			return
		}
	}

	avail := fsize - off
	pgI := off >> pgBits
	pgO := int(off & pgMask)
	rem := len(b)
	if !bits && int64(rem) >= avail {
		rem = int(avail)
		err = io.EOF
	}
	for rem != 0 && (bits || avail > 0) {
		v, err := (*Array)(f).Get(pgI)
		if err != nil {
			return n, err
		}

		pg, _ := v.([]byte)
		if len(pg) == 0 {
			pg = zeroPage[:]
		}

		nc := copy(b[:mathutil.Min(rem, pgSize)], pg[pgO:])
		pgI++
		pgO = 0
		rem -= nc
		n += nc
		b = b[nc:]
	}
	return
}

func BenchmarkRollbackFiler(b *testing.B) {
	rng := rand.New(rand.NewSource(42))
	type t struct {
		off int64
		b   []byte
	}
	a := []t{}
	for rem := b.N; rem > 0; {
		off := rng.Int63()
		n := mathutil.Min(rng.Intn(1e3)+1, rem)
		a = append(a, t{off, rndBytes(rng, n)})
		rem -= n
	}

	var r *RollbackFiler
	f := NewMemFiler()

	checkpoint := func(sz int64) (err error) {
		return f.Truncate(sz)
	}

	r, err := NewRollbackFiler(f, checkpoint, f)
	if err != nil {
		b.Fatal(err)
	}

	if err := r.BeginUpdate(); err != nil {
		b.Fatal(err)
	}

	b.ResetTimer()
	for _, v := range a {
		if _, err := r.WriteAt(v.b, v.off); err != nil {
			b.Fatal(err)
		}
	}
}

//.........这里部分代码省略.........
		if err := p.SkeletonXErrors(b); err != nil {
			return err
		}

		if err := b.Flush(); err != nil {
			return err
		}

		if err := f.Close(); err != nil {
			return err
		}
	}

	msu := make(map[*y.Symbol]int, len(p.Syms)) // sym -> usage
	for nm, sym := range p.Syms {
		if nm == "" || nm == "ε" || nm == "$accept" || nm == "#" {
			continue
		}

		msu[sym] = 0
	}
	var minArg, maxArg int
	for _, state := range p.Table {
		for _, act := range state {
			msu[act.Sym]++
			k, arg := act.Kind()
			if k == 'a' {
				continue
			}

			if k == 'r' {
				arg = -arg
			}
			minArg, maxArg = mathutil.Min(minArg, arg), mathutil.Max(maxArg, arg)
		}
	}
	su := make(symsUsed, 0, len(msu))
	for sym, used := range msu {
		su = append(su, symUsed{sym, used})
	}
	sort.Sort(su)

	// ----------------------------------------------------------- Prologue
	f := strutil.IndentFormatter(out, "\t")
	f.Format("// CAUTION: Generated file - DO NOT EDIT.\n\n")
	f.Format("%s", injectImport(p.Prologue))
	f.Format(`
type %[1]sSymType %i%s%u

type %[1]sXError struct {
	state, xsym int
}
`, *oPref, p.UnionSrc)

	// ---------------------------------------------------------- Constants
	nsyms := map[string]*y.Symbol{}
	a := make([]string, 0, len(msu))
	maxTokName := 0
	for sym := range msu {
		nm := sym.Name
		if nm == "$default" || nm == "$end" || sym.IsTerminal && nm[0] != '\'' && sym.Value > 0 {
			maxTokName = mathutil.Max(maxTokName, len(nm))
			a = append(a, nm)
		}
		nsyms[nm] = sym
	}

// []interface{}{qltype, ...}->[]interface{}{lldb scalar type, ...}
// + long blobs are (pre)written to a chain of chunks.
func (s *file) flatten(data []interface{}) (err error) {
	for i, v := range data {
		tag := 0
		var b []byte
		switch x := v.(type) {
		case []byte:
			tag = qBlob
			b = x
		case *big.Int:
			tag = qBigInt
			b, err = s.codec.encode(x)
		case *big.Rat:
			tag = qBigRat
			b, err = s.codec.encode(x)
		case time.Time:
			tag = qTime
			b, err = s.codec.encode(x)
		case time.Duration:
			tag = qDuration
			b, err = s.codec.encode(x)
		default:
			continue
		}
		if err != nil {
			return
		}

		const chunk = 1 << 16
		chunks := 0
		var next int64
		var buf []byte
		for rem := len(b); rem > shortBlob; {
			n := mathutil.Min(rem, chunk)
			part := b[rem-n:]
			b = b[:rem-n]
			rem -= n
			switch next {
			case 0: // last chunk
				buf, err = lldb.EncodeScalars([]interface{}{part}...)
			default: // middle chunk
				buf, err = lldb.EncodeScalars([]interface{}{next, part}...)
			}
			if err != nil {
				return
			}

			h, err := s.a.Alloc(buf)
			if err != nil {
				return err
			}

			next = h
			chunks++
		}

		switch next {
		case 0: // single chunk
			buf, err = lldb.EncodeScalars([]interface{}{tag, b}...)
		default: // multi chunks
			buf, err = lldb.EncodeScalars([]interface{}{tag, next, b}...)
		}
		if err != nil {
			return
		}

		data[i] = buf
	}
	return
}

/*
Free up some synapses in this segment. We always free up inactive
synapses (lowest permanence freed up first) before we start to free up
active ones.

param numToFree number of synapses to free up
param inactiveSynapseIndices list of the inactive synapse indices.
*/
func (s *Segment) freeNSynapses(numToFree int, inactiveSynapseIndices []int) {
	//Make sure numToFree isn't larger than the total number of syns we have
	if numToFree > len(s.syns) {
		panic("Number to free cannot be larger than existing synapses.")
	}

	if s.tp.params.Verbosity >= 5 {
		fmt.Println("freeNSynapses with numToFree=", numToFree)
		fmt.Println("inactiveSynapseIndices= ", inactiveSynapseIndices)
	}

	var candidates []int
	// Remove the lowest perm inactive synapses first
	if len(inactiveSynapseIndices) > 0 {
		perms := make([]float64, len(inactiveSynapseIndices))
		for idx, _ := range perms {
			perms[idx] = s.syns[idx].Permanence
		}
		var indexes []int
		floats.Argsort(perms, indexes)
		//sort perms
		cSize := mathutil.Min(numToFree, len(perms))
		candidates = make([]int, cSize)
		//indexes[0:cSize]
		for i := 0; i < cSize; i++ {
			candidates[i] = inactiveSynapseIndices[indexes[i]]
		}
	}

	// Do we need more? if so, remove the lowest perm active synapses too
	var activeSynIndices []int
	if len(candidates) < numToFree {
		for i := 0; i < len(s.syns); i++ {
			if !utils.ContainsInt(i, inactiveSynapseIndices) {
				activeSynIndices = append(activeSynIndices, i)
			}
		}

		perms := make([]float64, len(activeSynIndices))
		for i := range perms {
			perms[i] = s.syns[i].Permanence
		}
		var indexes []int
		floats.Argsort(perms, indexes)

		moreToFree := numToFree - len(candidates)
		//moreCandidates := make([]int, moreToFree)
		for i := 0; i < moreToFree; i++ {
			candidates = append(candidates, activeSynIndices[indexes[i]])
		}
	}

	if s.tp.params.Verbosity >= 4 {
		fmt.Printf("Deleting %v synapses from segment to make room for new ones: %v \n",
			len(candidates), candidates)
		fmt.Println("Before:", s.ToString())
	}

	// Delete candidate syns by copying undeleted to new slice
	var newSyns []Synapse
	for idx, val := range s.syns {
		if !utils.ContainsInt(idx, candidates) {
			newSyns = append(newSyns, val)
		}
	}
	s.syns = newSyns

	if s.tp.params.Verbosity >= 4 {
		fmt.Println("After:", s.ToString())
	}

}

func minmax(a, b int) {
	fmt.Println("Min:", mathutil.Min(a, b))
	fmt.Println("Max:", mathutil.Max(a, b))
}

func (tp *TrivialPredictor) infer(activeColumns []int) {

	numColsToPredict := int(0.5 + tp.AverageDensity*float64(tp.NumOfCols))

	//for method in self.methods:
	for _, method := range tp.Methods {
		// Copy t-1 into t
		copy(tp.State[method].ActiveStateLast, tp.State[method].ActiveState)
		copy(tp.State[method].PredictedStateLast, tp.State[method].PredictedState)
		copy(tp.State[method].ConfidenceLast, tp.State[method].Confidence)

		utils.FillSliceBool(tp.State[method].ActiveState, false)
		utils.FillSliceBool(tp.State[method].PredictedState, false)
		utils.FillSliceFloat64(tp.State[method].Confidence, 0.0)

		for _, val := range activeColumns {
			tp.State[method].ActiveState[val] = true
		}

		var predictedCols []int

		switch method {
		case Random:
			// Randomly predict N columns
			//predictedCols = RandomInts(numColsToPredict, tp.NumOfCols)
			break
		case Zeroth:
			// Always predict the top N most frequent columns
			var inds []int
			ints.Argsort(tp.ColumnCount, inds)
			predictedCols = inds[len(inds)-numColsToPredict:]
			break
		case Last:
			// Always predict the last input
			for idx, val := range tp.State[method].ActiveState {
				if val {
					predictedCols = append(predictedCols, idx)
				}
			}
			break
		case All:
			// Always predict all columns
			for i := 0; i < tp.NumOfCols; i++ {
				predictedCols = append(predictedCols, i)
			}
			break
		case Lots:
			// Always predict 2 * the top N most frequent columns
			numColsToPredict := mathutil.Min(2*numColsToPredict, tp.NumOfCols)
			var inds []int
			ints.Argsort(tp.ColumnCount, inds)
			predictedCols = inds[len(inds)-numColsToPredict:]

			break
		default:
			panic("prediction method not implemented")
		}

		for _, val := range predictedCols {
			tp.State[method].PredictedState[val] = true
			tp.State[method].Confidence[val] = 1.0
		}

		if tp.Verbosity > 1 {
			fmt.Println("Random prediction:", method)
			fmt.Println(" numColsToPredict:", numColsToPredict)
			fmt.Println(predictedCols)
		}

	}

}

//Creates a new spatial pooler
func NewSpatialPooler(spParams SpParams) *SpatialPooler {
	sp := SpatialPooler{}
	//Validate inputs
	sp.numColumns = utils.ProdInt(spParams.ColumnDimensions)
	sp.numInputs = utils.ProdInt(spParams.InputDimensions)

	if sp.numColumns < 1 {
		panic("Must have at least 1 column")
	}
	if sp.numInputs < 1 {
		panic("must have at least 1 input")
	}
	if spParams.NumActiveColumnsPerInhArea < 1 && (spParams.LocalAreaDensity < 1) && (spParams.LocalAreaDensity >= 0.5) {
		panic("Num active colums invalid")
	}

	sp.InputDimensions = spParams.InputDimensions
	sp.ColumnDimensions = spParams.ColumnDimensions
	sp.PotentialRadius = int(mathutil.Min(spParams.PotentialRadius, sp.numInputs))
	sp.PotentialPct = spParams.PotentialPct
	sp.GlobalInhibition = spParams.GlobalInhibition
	sp.LocalAreaDensity = spParams.LocalAreaDensity
	sp.NumActiveColumnsPerInhArea = spParams.NumActiveColumnsPerInhArea
	sp.StimulusThreshold = spParams.StimulusThreshold
	sp.SynPermInactiveDec = spParams.SynPermInactiveDec
	sp.SynPermActiveInc = spParams.SynPermActiveInc
	sp.SynPermBelowStimulusInc = spParams.SynPermConnected / 10.0
	sp.SynPermConnected = spParams.SynPermConnected
	sp.MinPctOverlapDutyCycles = spParams.MinPctOverlapDutyCycle
	sp.MinPctActiveDutyCycles = spParams.MinPctActiveDutyCycle
	sp.DutyCyclePeriod = spParams.DutyCyclePeriod
	sp.MaxBoost = spParams.MaxBoost
	sp.Seed = spParams.Seed
	sp.SpVerbosity = spParams.SpVerbosity

	// Extra parameter settings
	sp.SynPermMin = 0
	sp.SynPermMax = 1
	sp.SynPermTrimThreshold = sp.SynPermActiveInc / 2.0
	if sp.SynPermTrimThreshold >= sp.SynPermConnected {
		panic("Syn perm threshold >= syn connected.")
	}
	sp.UpdatePeriod = 50
	sp.InitConnectedPct = 0.5

	/*
			# Internal state
		    version = 1.0
		    iterationNum = 0
		    iterationLearnNum = 0
	*/

	/*
			 Store the set of all inputs that are within each column's potential pool.
		     'potentialPools' is a matrix, whose rows represent cortical columns, and
		     whose columns represent the input bits. if potentialPools[i][j] == 1,
		     then input bit 'j' is in column 'i's potential pool. A column can only be
		     connected to inputs in its potential pool. The indices refer to a
		     falttenned version of both the inputs and columns. Namely, irrespective
		     of the topology of the inputs and columns, they are treated as being a
		     one dimensional array. Since a column is typically connected to only a
		     subset of the inputs, many of the entries in the matrix are 0. Therefore
		     the the potentialPool matrix is stored using the SparseBinaryMatrix
		     class, to reduce memory footprint and compuation time of algorithms that
		     require iterating over the data strcuture.
	*/
	sp.potentialPools = NewDenseBinaryMatrix(sp.numColumns, sp.numInputs)

	/*
			 Initialize the permanences for each column. Similar to the
		     'potentialPools', the permances are stored in a matrix whose rows
		     represent the cortial columns, and whose columns represent the input
		     bits. if permanences[i][j] = 0.2, then the synapse connecting
		     cortical column 'i' to input bit 'j' has a permanence of 0.2. Here we
		     also use the SparseMatrix class to reduce the memory footprint and
		     computation time of algorithms that require iterating over the data
		     structure. This permanence matrix is only allowed to have non-zero
		     elements where the potential pool is non-zero.
	*/
	//Assumes 70% sparsity
	elms := make(map[int]float64, int(float64(sp.numColumns*sp.numInputs)*0.3))
	sp.permanences = matrix.MakeSparseMatrix(elms, sp.numColumns, sp.numInputs)

	/*
			 Initialize a tiny random tie breaker. This is used to determine winning
		     columns where the overlaps are identical.
	*/

	sp.tieBreaker = make([]float64, sp.numColumns)
	for i := 0; i < len(sp.tieBreaker); i++ {
		sp.tieBreaker[i] = 0.01 * rand.Float64()
	}

	/*
			 'connectedSynapses' is a similar matrix to 'permanences'
		     (rows represent cortial columns, columns represent input bits) whose
		     entries represent whether the cortial column is connected to the input
		     bit, i.e. its permanence value is greater than 'synPermConnected'. While
		     this information is readily available from the 'permanence' matrix,
//.........这里部分代码省略.........

//.........这里部分代码省略.........
			//int64(1),
			int8(2),
			int16(3),
			int32(4),
			int64(5),
			//uint64(6),
			uint8(7),
			uint16(8),
			uint32(9),
			uint64(10),
			float32(11),
			float64(12),
			complex64(-1),
			complex128(-2),
			[]byte("abc"),
			*big.NewInt(1),
			*big.NewRat(3, 2),
			"string",
			now,
			dur,
		}},
	}
	for iTest, test := range tab {
		r, err := Marshal(test.inst)
		if g, e := err != nil, test.err; g != e {
			t.Fatal(iTest, g, e)
		}

		if err != nil {
			t.Log(err)
			continue
		}

		for i := 0; i < mathutil.Min(len(r), len(test.r)); i++ {
			g, e := r[i], test.r[i]
			use(e)
			switch x := g.(type) {
			case bool:
				switch y := e.(type) {
				case bool:
					if x != y {
						t.Fatal(iTest, x, y)
					}
				default:
					t.Fatalf("%d: %T <-> %T", iTest, x, y)
				}
			case int:
				switch y := e.(type) {
				case int64:
					if int64(x) != y {
						t.Fatal(iTest, x, y)
					}
				default:
					t.Fatalf("%d: %T <-> %T", iTest, x, y)
				}
			case int8:
				switch y := e.(type) {
				case int8:
					if x != y {
						t.Fatal(iTest, x, y)
					}
				default:
					t.Fatalf("%d: %T <-> %T", iTest, x, y)
				}
			case int16:
				switch y := e.(type) {