)

const delta64 = maxFloat64/(1 << 52)

const (
	_ float64 = - /* ERROR "overflow" */ (maxFloat64 + delta64)
	_ float64 = -maxFloat64
	_ float64 = maxFloat64
	_ float64 = maxFloat64 /* ERROR "overflow" */ + delta64

	_ = float64(- /* ERROR "cannot convert" */ (maxFloat64 + delta64))
	_ = float64(-maxFloat64)
	_ = float64(maxFloat64)
	_ = float64(maxFloat64 /* ERROR "cannot convert" */ + delta64)

)

// Inputs to test trig_reduce
var trigHuge = []float64{
	1 << 28,
	1 << 29,
	1 << 30,
	1 << 35,
	1 << 120,
	1 << 240,
	1 << 480,
	1234567891234567 << 180,
	1234567891234567 << 300,
	MaxFloat64,
}

// Results for trigHuge[i] calculated with https://github.com/robpike/ivy
// using 4096 bits of working precision.   Values requiring less than

)

func absInt32(i int32) uint32 {
	if i < 0 {
		return uint32(-i)
	}
	return uint32(i)
}

// NormFloat64 returns a normally distributed float64 in
// the range -[math.MaxFloat64] through +[math.MaxFloat64] inclusive,
// with standard normal distribution (mean = 0, stddev = 1).
// To produce a different normal distribution, callers can
// adjust the output using:
//

	rn = 3.442619855899
)

func absInt32(i int32) uint32 {
	if i < 0 {
		return uint32(-i)
	}
	return uint32(i)
}

// NormFloat64 returns a normally distributed float64 in
// the range -math.MaxFloat64 through +math.MaxFloat64 inclusive,
// with standard normal distribution (mean = 0, stddev = 1).
// To produce a different normal distribution, callers can
// adjust the output using:
//

// swap swaps the elements with indexes i and j.
func Shuffle(n int, swap func(i, j int)) { globalRand.Shuffle(n, swap) }

// NormFloat64 returns a normally distributed float64 in the range
// [-math.MaxFloat64, +math.MaxFloat64] with
// standard normal distribution (mean = 0, stddev = 1)
// from the default Source.
// To produce a different normal distribution, callers can
// adjust the output using:
//

func Read(p []byte) (n int, err error) { return globalRand().Read(p) }

// NormFloat64 returns a normally distributed float64 in the range
// [-[math.MaxFloat64], +[math.MaxFloat64]] with
// standard normal distribution (mean = 0, stddev = 1)
// from the default [Source].
// To produce a different normal distribution, callers can
// adjust the output using:
//

		},
		{
			name: "uint8 zero",
			obj:  uint8(0),
		},
		{
			name: "float64",
			obj:  float64(2.71),
		},
		{
			name: "float64 max",
			obj:  float64(math.MaxFloat64),
		},
		{
			name: "float64 smallest nonzero",
			obj:  float64(math.SmallestNonzeroFloat64),
		},
		{
			name: "float64 no fractional component",
			obj:  float64(5),
		},
		{

	case uint64:
		vals[i] = m.mutateUInt(v, maxUint)
	case float32:
		vals[i] = float32(m.mutateFloat(float64(v), math.MaxFloat32))
	case float64:
		vals[i] = m.mutateFloat(v, math.MaxFloat64)
	case bool:
		if m.rand(2) == 1 {
			vals[i] = !v // 50% chance of flipping the bool
		}
	case rune: // int32
		vals[i] = rune(m.mutateInt(int64(v), math.MaxInt32))
	case byte: // uint8

 * (Marsaglia & Tsang, 2000)
 * https://www.jstatsoft.org/v05/i08/paper [pdf]
 */

const (
	re = 7.69711747013104972
)

// ExpFloat64 returns an exponentially distributed float64 in the range
// (0, +math.MaxFloat64] with an exponential distribution whose rate parameter
// (lambda) is 1 and whose mean is 1/lambda (1).
// To produce a distribution with a different rate parameter,
// callers can adjust the output using:
//

 * (Marsaglia & Tsang, 2000)
 * https://www.jstatsoft.org/v05/i08/paper [pdf]
 */

const (
	re = 7.69711747013104972
)

// ExpFloat64 returns an exponentially distributed float64 in the range
// (0, +[math.MaxFloat64]] with an exponential distribution whose rate parameter
// (lambda) is 1 and whose mean is 1/lambda (1).
// To produce a distribution with a different rate parameter,
// callers can adjust the output using:
//