sb7 = -2.24409524465858183362e+01 // 0xC03670E242712D62
)

// Erf returns the error function of x.
//
// Special cases are:
//
//	Erf(+Inf) = 1
//	Erf(-Inf) = -1
//	Erf(NaN) = NaN
func Erf(x float64) float64 {
	if haveArchErf {
		return archErf(x)
	}
	return erf(x)
}

func erf(x float64) float64 {
	const (
		VeryTiny = 2.848094538889218e-306 // 0x0080000000000000

// Outlines non-approximate GELU into a stablehlo composite.
//
//    -> mul 1/sqrt(2) -> erf -> add 1 ->
// in                                    mul
//    ---------> mul 0.5 --------------->
//
// This pattern assumes all binary ewise ops with one constant argument
// have that constant argument as the second operand. It works by
// identifying `erf` ops and validate the structure around them.
class OutlineGELU : public RewritePattern {

*/

// This implementation is based on the rational approximation
// of percentage points of normal distribution available from
// https://www.jstor.org/stable/2347330.

const (
	// Coefficients for approximation to erf in |x| <= 0.85
	a0 = 1.1975323115670912564578e0
	a1 = 4.7072688112383978012285e1
	a2 = 6.9706266534389598238465e2
	a3 = 4.8548868893843886794648e3
	a4 = 1.6235862515167575384252e4
	a5 = 2.3782041382114385731252e4

var SinNoVec = sin
var SinhNoVec = sinh
var TanhNoVec = tanh
var Log1pNovec = log1p
var AtanhNovec = atanh
var AcosNovec = acos
var AcoshNovec = acosh
var AsinNovec = asin
var AsinhNovec = asinh
var ErfNovec = erf
var ErfcNovec = erfc
var AtanNovec = atan
var Atan2Novec = atan2
var CbrtNovec = cbrt
var LogNovec = log
var TanNovec = tan
var ExpNovec = exp
var Expm1Novec = expm1
var PowNovec = pow
var HypotNovec = hypot

// Table of +/- 1.0
DATA ·erftab12067<> + 0(SB)/8, $1.0
DATA ·erftab12067<> + 8(SB)/8, $-1.0
GLOBL ·erftab12067<> + 0(SB), RODATA, $16

// Erf returns the error function of the argument.
//
// Special cases are:
//      Erf(+Inf) = 1
//      Erf(-Inf) = -1
//      Erf(NaN) = NaN
// The algorithm used is minimax polynomial approximation
// with coefficients determined with a Remez exchange algorithm.

        y = Complex(scope_, x, x);
        break;
      case ANGLE:
        y = Angle(scope_, x);
        break;
      case LGAMMA:
        y = Lgamma(scope_, x);
        break;
      case ERF:
        y = Erf(scope_, x);
        break;
      case ERFINV:
        y = Erfinv(scope_, x);
        break;
      case NDTRI:
        y = Ndtri(scope_, x);
        break;
    }

    float max_error;

		t.Skipf("no vector support")
	}
	for i := 0; i < len(vf); i++ {
		a := vf[i] / 10
		if f := ErfNovec(a); !veryclose(erf[i], f) {
			t.Errorf("Erf(%g) = %g, want %g", a, f, erf[i])
		}
	}
	for i := 0; i < len(vferfSC); i++ {
		if f := ErfNovec(vferfSC[i]); !alike(erfSC[i], f) {
			t.Errorf("Erf(%g) = %g, want %g", vferfSC[i], f, erfSC[i])
		}
	}
}

func TestErfcNovec(t *testing.T) {
	if !HasVX {

	}
}

func TestErf(t *testing.T) {
	for i := 0; i < len(vf); i++ {
		a := vf[i] / 10
		if f := Erf(a); !veryclose(erf[i], f) {
			t.Errorf("Erf(%g) = %g, want %g", a, f, erf[i])
		}
	}
	for i := 0; i < len(vferfSC); i++ {
		if f := Erf(vferfSC[i]); !alike(erfSC[i], f) {
			t.Errorf("Erf(%g) = %g, want %g", vferfSC[i], f, erfSC[i])
		}
	}
}

func TestErfc(t *testing.T) {

TEXT ·erfTrampolineSetup(SB), NOSPLIT, $0
	MOVB   ·hasVX(SB), R1
	CMPBEQ R1, $1, vectorimpl               // vectorfacility = 1, vector supported
	MOVD   $·erfvectorfacility+0x00(SB), R1
	MOVD   $·erf(SB), R2
	MOVD   R2, 0(R1)
	BR     ·erf(SB)

vectorimpl:
	MOVD $·erfvectorfacility+0x00(SB), R1
	MOVD $·erfAsm(SB), R2
	MOVD R2, 0(R1)
	BR   ·erfAsm(SB)

GLOBL ·erfvectorfacility+0x00(SB), NOPTR, $8

	// all sums inside those bounds with 99% probability.
	N := n * hashSize
	var c float64
	// find c such that Prob(mean-c*stddev < x < mean+c*stddev)^N > .9999
	for c = 0.0; math.Pow(math.Erf(c/math.Sqrt(2)), float64(N)) < .9999; c += .1 {
	}
	c *= 11.0 // allowed slack: 40% to 60% - we don't need to be perfectly random
	mean := .5 * REP
	stddev := .5 * math.Sqrt(REP)
	low := int(mean - c*stddev)