
(FPCore (A B C F)
:precision binary64
(let* ((t_0 (- (pow B 2.0) (* (* 4.0 A) C))))
(/
(-
(sqrt
(*
(* 2.0 (* t_0 F))
(- (+ A C) (sqrt (+ (pow (- A C) 2.0) (pow B 2.0)))))))
t_0)))
double code(double A, double B, double C, double F) {
double t_0 = pow(B, 2.0) - ((4.0 * A) * C);
return -sqrt(((2.0 * (t_0 * F)) * ((A + C) - sqrt((pow((A - C), 2.0) + pow(B, 2.0)))))) / t_0;
}
real(8) function code(a, b, c, f)
real(8), intent (in) :: a
real(8), intent (in) :: b
real(8), intent (in) :: c
real(8), intent (in) :: f
real(8) :: t_0
t_0 = (b ** 2.0d0) - ((4.0d0 * a) * c)
code = -sqrt(((2.0d0 * (t_0 * f)) * ((a + c) - sqrt((((a - c) ** 2.0d0) + (b ** 2.0d0)))))) / t_0
end function
public static double code(double A, double B, double C, double F) {
double t_0 = Math.pow(B, 2.0) - ((4.0 * A) * C);
return -Math.sqrt(((2.0 * (t_0 * F)) * ((A + C) - Math.sqrt((Math.pow((A - C), 2.0) + Math.pow(B, 2.0)))))) / t_0;
}
def code(A, B, C, F): t_0 = math.pow(B, 2.0) - ((4.0 * A) * C) return -math.sqrt(((2.0 * (t_0 * F)) * ((A + C) - math.sqrt((math.pow((A - C), 2.0) + math.pow(B, 2.0)))))) / t_0
function code(A, B, C, F) t_0 = Float64((B ^ 2.0) - Float64(Float64(4.0 * A) * C)) return Float64(Float64(-sqrt(Float64(Float64(2.0 * Float64(t_0 * F)) * Float64(Float64(A + C) - sqrt(Float64((Float64(A - C) ^ 2.0) + (B ^ 2.0))))))) / t_0) end
function tmp = code(A, B, C, F) t_0 = (B ^ 2.0) - ((4.0 * A) * C); tmp = -sqrt(((2.0 * (t_0 * F)) * ((A + C) - sqrt((((A - C) ^ 2.0) + (B ^ 2.0)))))) / t_0; end
code[A_, B_, C_, F_] := Block[{t$95$0 = N[(N[Power[B, 2.0], $MachinePrecision] - N[(N[(4.0 * A), $MachinePrecision] * C), $MachinePrecision]), $MachinePrecision]}, N[((-N[Sqrt[N[(N[(2.0 * N[(t$95$0 * F), $MachinePrecision]), $MachinePrecision] * N[(N[(A + C), $MachinePrecision] - N[Sqrt[N[(N[Power[N[(A - C), $MachinePrecision], 2.0], $MachinePrecision] + N[Power[B, 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]) / t$95$0), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {B}^{2} - \left(4 \cdot A\right) \cdot C\\
\frac{-\sqrt{\left(2 \cdot \left(t\_0 \cdot F\right)\right) \cdot \left(\left(A + C\right) - \sqrt{{\left(A - C\right)}^{2} + {B}^{2}}\right)}}{t\_0}
\end{array}
\end{array}
Sampling outcomes in binary64 precision:
Herbie found 12 alternatives:
| Alternative | Accuracy | Speedup |
|---|
(FPCore (A B C F)
:precision binary64
(let* ((t_0 (- (pow B 2.0) (* (* 4.0 A) C))))
(/
(-
(sqrt
(*
(* 2.0 (* t_0 F))
(- (+ A C) (sqrt (+ (pow (- A C) 2.0) (pow B 2.0)))))))
t_0)))
double code(double A, double B, double C, double F) {
double t_0 = pow(B, 2.0) - ((4.0 * A) * C);
return -sqrt(((2.0 * (t_0 * F)) * ((A + C) - sqrt((pow((A - C), 2.0) + pow(B, 2.0)))))) / t_0;
}
real(8) function code(a, b, c, f)
real(8), intent (in) :: a
real(8), intent (in) :: b
real(8), intent (in) :: c
real(8), intent (in) :: f
real(8) :: t_0
t_0 = (b ** 2.0d0) - ((4.0d0 * a) * c)
code = -sqrt(((2.0d0 * (t_0 * f)) * ((a + c) - sqrt((((a - c) ** 2.0d0) + (b ** 2.0d0)))))) / t_0
end function
public static double code(double A, double B, double C, double F) {
double t_0 = Math.pow(B, 2.0) - ((4.0 * A) * C);
return -Math.sqrt(((2.0 * (t_0 * F)) * ((A + C) - Math.sqrt((Math.pow((A - C), 2.0) + Math.pow(B, 2.0)))))) / t_0;
}
def code(A, B, C, F): t_0 = math.pow(B, 2.0) - ((4.0 * A) * C) return -math.sqrt(((2.0 * (t_0 * F)) * ((A + C) - math.sqrt((math.pow((A - C), 2.0) + math.pow(B, 2.0)))))) / t_0
function code(A, B, C, F) t_0 = Float64((B ^ 2.0) - Float64(Float64(4.0 * A) * C)) return Float64(Float64(-sqrt(Float64(Float64(2.0 * Float64(t_0 * F)) * Float64(Float64(A + C) - sqrt(Float64((Float64(A - C) ^ 2.0) + (B ^ 2.0))))))) / t_0) end
function tmp = code(A, B, C, F) t_0 = (B ^ 2.0) - ((4.0 * A) * C); tmp = -sqrt(((2.0 * (t_0 * F)) * ((A + C) - sqrt((((A - C) ^ 2.0) + (B ^ 2.0)))))) / t_0; end
code[A_, B_, C_, F_] := Block[{t$95$0 = N[(N[Power[B, 2.0], $MachinePrecision] - N[(N[(4.0 * A), $MachinePrecision] * C), $MachinePrecision]), $MachinePrecision]}, N[((-N[Sqrt[N[(N[(2.0 * N[(t$95$0 * F), $MachinePrecision]), $MachinePrecision] * N[(N[(A + C), $MachinePrecision] - N[Sqrt[N[(N[Power[N[(A - C), $MachinePrecision], 2.0], $MachinePrecision] + N[Power[B, 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]) / t$95$0), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {B}^{2} - \left(4 \cdot A\right) \cdot C\\
\frac{-\sqrt{\left(2 \cdot \left(t\_0 \cdot F\right)\right) \cdot \left(\left(A + C\right) - \sqrt{{\left(A - C\right)}^{2} + {B}^{2}}\right)}}{t\_0}
\end{array}
\end{array}
B_m = (fabs.f64 B)
NOTE: A, B_m, C, and F should be sorted in increasing order before calling this function.
(FPCore (A B_m C F)
:precision binary64
(let* ((t_0 (fma (* -4.0 A) C (* B_m B_m)))
(t_1 (fma -4.0 (* C A) (* B_m B_m)))
(t_2 (* (* 4.0 A) C))
(t_3 (- (pow B_m 2.0) t_2))
(t_4
(/
(sqrt
(*
(* 2.0 (* t_3 F))
(- (+ A C) (sqrt (+ (pow (- A C) 2.0) (pow B_m 2.0))))))
(- t_3))))
(if (<= t_4 (- INFINITY))
(* (- (sqrt 2.0)) (sqrt (* F (/ (- (+ C A) (hypot (- A C) B_m)) t_1))))
(if (<= t_4 -5e-184)
(/
(sqrt (* (- (+ C A) (hypot B_m (- A C))) (* (* 2.0 F) t_1)))
(fma (- B_m) B_m t_2))
(if (<= t_4 INFINITY)
(/
(sqrt (* (fma (* -0.5 B_m) (/ B_m C) (+ A A)) (* (* 2.0 F) t_0)))
(- t_0))
(/ (sqrt (* 2.0 (* (- A (hypot A B_m)) F))) (- B_m)))))))B_m = fabs(B);
assert(A < B_m && B_m < C && C < F);
double code(double A, double B_m, double C, double F) {
double t_0 = fma((-4.0 * A), C, (B_m * B_m));
double t_1 = fma(-4.0, (C * A), (B_m * B_m));
double t_2 = (4.0 * A) * C;
double t_3 = pow(B_m, 2.0) - t_2;
double t_4 = sqrt(((2.0 * (t_3 * F)) * ((A + C) - sqrt((pow((A - C), 2.0) + pow(B_m, 2.0)))))) / -t_3;
double tmp;
if (t_4 <= -((double) INFINITY)) {
tmp = -sqrt(2.0) * sqrt((F * (((C + A) - hypot((A - C), B_m)) / t_1)));
} else if (t_4 <= -5e-184) {
tmp = sqrt((((C + A) - hypot(B_m, (A - C))) * ((2.0 * F) * t_1))) / fma(-B_m, B_m, t_2);
} else if (t_4 <= ((double) INFINITY)) {
tmp = sqrt((fma((-0.5 * B_m), (B_m / C), (A + A)) * ((2.0 * F) * t_0))) / -t_0;
} else {
tmp = sqrt((2.0 * ((A - hypot(A, B_m)) * F))) / -B_m;
}
return tmp;
}
B_m = abs(B) A, B_m, C, F = sort([A, B_m, C, F]) function code(A, B_m, C, F) t_0 = fma(Float64(-4.0 * A), C, Float64(B_m * B_m)) t_1 = fma(-4.0, Float64(C * A), Float64(B_m * B_m)) t_2 = Float64(Float64(4.0 * A) * C) t_3 = Float64((B_m ^ 2.0) - t_2) t_4 = Float64(sqrt(Float64(Float64(2.0 * Float64(t_3 * F)) * Float64(Float64(A + C) - sqrt(Float64((Float64(A - C) ^ 2.0) + (B_m ^ 2.0)))))) / Float64(-t_3)) tmp = 0.0 if (t_4 <= Float64(-Inf)) tmp = Float64(Float64(-sqrt(2.0)) * sqrt(Float64(F * Float64(Float64(Float64(C + A) - hypot(Float64(A - C), B_m)) / t_1)))); elseif (t_4 <= -5e-184) tmp = Float64(sqrt(Float64(Float64(Float64(C + A) - hypot(B_m, Float64(A - C))) * Float64(Float64(2.0 * F) * t_1))) / fma(Float64(-B_m), B_m, t_2)); elseif (t_4 <= Inf) tmp = Float64(sqrt(Float64(fma(Float64(-0.5 * B_m), Float64(B_m / C), Float64(A + A)) * Float64(Float64(2.0 * F) * t_0))) / Float64(-t_0)); else tmp = Float64(sqrt(Float64(2.0 * Float64(Float64(A - hypot(A, B_m)) * F))) / Float64(-B_m)); end return tmp end
B_m = N[Abs[B], $MachinePrecision]
NOTE: A, B_m, C, and F should be sorted in increasing order before calling this function.
code[A_, B$95$m_, C_, F_] := Block[{t$95$0 = N[(N[(-4.0 * A), $MachinePrecision] * C + N[(B$95$m * B$95$m), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[(-4.0 * N[(C * A), $MachinePrecision] + N[(B$95$m * B$95$m), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(N[(4.0 * A), $MachinePrecision] * C), $MachinePrecision]}, Block[{t$95$3 = N[(N[Power[B$95$m, 2.0], $MachinePrecision] - t$95$2), $MachinePrecision]}, Block[{t$95$4 = N[(N[Sqrt[N[(N[(2.0 * N[(t$95$3 * F), $MachinePrecision]), $MachinePrecision] * N[(N[(A + C), $MachinePrecision] - N[Sqrt[N[(N[Power[N[(A - C), $MachinePrecision], 2.0], $MachinePrecision] + N[Power[B$95$m, 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / (-t$95$3)), $MachinePrecision]}, If[LessEqual[t$95$4, (-Infinity)], N[((-N[Sqrt[2.0], $MachinePrecision]) * N[Sqrt[N[(F * N[(N[(N[(C + A), $MachinePrecision] - N[Sqrt[N[(A - C), $MachinePrecision] ^ 2 + B$95$m ^ 2], $MachinePrecision]), $MachinePrecision] / t$95$1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision], If[LessEqual[t$95$4, -5e-184], N[(N[Sqrt[N[(N[(N[(C + A), $MachinePrecision] - N[Sqrt[B$95$m ^ 2 + N[(A - C), $MachinePrecision] ^ 2], $MachinePrecision]), $MachinePrecision] * N[(N[(2.0 * F), $MachinePrecision] * t$95$1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[((-B$95$m) * B$95$m + t$95$2), $MachinePrecision]), $MachinePrecision], If[LessEqual[t$95$4, Infinity], N[(N[Sqrt[N[(N[(N[(-0.5 * B$95$m), $MachinePrecision] * N[(B$95$m / C), $MachinePrecision] + N[(A + A), $MachinePrecision]), $MachinePrecision] * N[(N[(2.0 * F), $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / (-t$95$0)), $MachinePrecision], N[(N[Sqrt[N[(2.0 * N[(N[(A - N[Sqrt[A ^ 2 + B$95$m ^ 2], $MachinePrecision]), $MachinePrecision] * F), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / (-B$95$m)), $MachinePrecision]]]]]]]]]
\begin{array}{l}
B_m = \left|B\right|
\\
[A, B_m, C, F] = \mathsf{sort}([A, B_m, C, F])\\
\\
\begin{array}{l}
t_0 := \mathsf{fma}\left(-4 \cdot A, C, B\_m \cdot B\_m\right)\\
t_1 := \mathsf{fma}\left(-4, C \cdot A, B\_m \cdot B\_m\right)\\
t_2 := \left(4 \cdot A\right) \cdot C\\
t_3 := {B\_m}^{2} - t\_2\\
t_4 := \frac{\sqrt{\left(2 \cdot \left(t\_3 \cdot F\right)\right) \cdot \left(\left(A + C\right) - \sqrt{{\left(A - C\right)}^{2} + {B\_m}^{2}}\right)}}{-t\_3}\\
\mathbf{if}\;t\_4 \leq -\infty:\\
\;\;\;\;\left(-\sqrt{2}\right) \cdot \sqrt{F \cdot \frac{\left(C + A\right) - \mathsf{hypot}\left(A - C, B\_m\right)}{t\_1}}\\
\mathbf{elif}\;t\_4 \leq -5 \cdot 10^{-184}:\\
\;\;\;\;\frac{\sqrt{\left(\left(C + A\right) - \mathsf{hypot}\left(B\_m, A - C\right)\right) \cdot \left(\left(2 \cdot F\right) \cdot t\_1\right)}}{\mathsf{fma}\left(-B\_m, B\_m, t\_2\right)}\\
\mathbf{elif}\;t\_4 \leq \infty:\\
\;\;\;\;\frac{\sqrt{\mathsf{fma}\left(-0.5 \cdot B\_m, \frac{B\_m}{C}, A + A\right) \cdot \left(\left(2 \cdot F\right) \cdot t\_0\right)}}{-t\_0}\\
\mathbf{else}:\\
\;\;\;\;\frac{\sqrt{2 \cdot \left(\left(A - \mathsf{hypot}\left(A, B\_m\right)\right) \cdot F\right)}}{-B\_m}\\
\end{array}
\end{array}
if (/.f64 (neg.f64 (sqrt.f64 (*.f64 (*.f64 #s(literal 2 binary64) (*.f64 (-.f64 (pow.f64 B #s(literal 2 binary64)) (*.f64 (*.f64 #s(literal 4 binary64) A) C)) F)) (-.f64 (+.f64 A C) (sqrt.f64 (+.f64 (pow.f64 (-.f64 A C) #s(literal 2 binary64)) (pow.f64 B #s(literal 2 binary64)))))))) (-.f64 (pow.f64 B #s(literal 2 binary64)) (*.f64 (*.f64 #s(literal 4 binary64) A) C))) < -inf.0Initial program 3.2%
Taylor expanded in F around 0
mul-1-negN/A
*-commutativeN/A
distribute-lft-neg-inN/A
lower-*.f64N/A
lower-neg.f64N/A
lower-sqrt.f64N/A
lower-sqrt.f64N/A
associate-/l*N/A
lower-*.f64N/A
Applied rewrites57.2%
if -inf.0 < (/.f64 (neg.f64 (sqrt.f64 (*.f64 (*.f64 #s(literal 2 binary64) (*.f64 (-.f64 (pow.f64 B #s(literal 2 binary64)) (*.f64 (*.f64 #s(literal 4 binary64) A) C)) F)) (-.f64 (+.f64 A C) (sqrt.f64 (+.f64 (pow.f64 (-.f64 A C) #s(literal 2 binary64)) (pow.f64 B #s(literal 2 binary64)))))))) (-.f64 (pow.f64 B #s(literal 2 binary64)) (*.f64 (*.f64 #s(literal 4 binary64) A) C))) < -5.00000000000000003e-184Initial program 99.4%
Applied rewrites99.4%
if -5.00000000000000003e-184 < (/.f64 (neg.f64 (sqrt.f64 (*.f64 (*.f64 #s(literal 2 binary64) (*.f64 (-.f64 (pow.f64 B #s(literal 2 binary64)) (*.f64 (*.f64 #s(literal 4 binary64) A) C)) F)) (-.f64 (+.f64 A C) (sqrt.f64 (+.f64 (pow.f64 (-.f64 A C) #s(literal 2 binary64)) (pow.f64 B #s(literal 2 binary64)))))))) (-.f64 (pow.f64 B #s(literal 2 binary64)) (*.f64 (*.f64 #s(literal 4 binary64) A) C))) < +inf.0Initial program 10.0%
Taylor expanded in C around inf
mul-1-negN/A
lower--.f64N/A
+-commutativeN/A
*-commutativeN/A
lower-fma.f64N/A
lower-/.f64N/A
unpow2N/A
lower-*.f64N/A
lower-neg.f6422.2
Applied rewrites22.2%
Applied rewrites22.2%
if +inf.0 < (/.f64 (neg.f64 (sqrt.f64 (*.f64 (*.f64 #s(literal 2 binary64) (*.f64 (-.f64 (pow.f64 B #s(literal 2 binary64)) (*.f64 (*.f64 #s(literal 4 binary64) A) C)) F)) (-.f64 (+.f64 A C) (sqrt.f64 (+.f64 (pow.f64 (-.f64 A C) #s(literal 2 binary64)) (pow.f64 B #s(literal 2 binary64)))))))) (-.f64 (pow.f64 B #s(literal 2 binary64)) (*.f64 (*.f64 #s(literal 4 binary64) A) C))) Initial program 0.0%
Taylor expanded in C around 0
mul-1-negN/A
distribute-lft-neg-inN/A
lower-*.f64N/A
lower-neg.f64N/A
lower-/.f64N/A
lower-sqrt.f64N/A
lower-sqrt.f64N/A
*-commutativeN/A
lower-*.f64N/A
lower--.f64N/A
+-commutativeN/A
unpow2N/A
unpow2N/A
lower-hypot.f6421.1
Applied rewrites21.1%
Applied rewrites21.1%
Final simplification40.3%
B_m = (fabs.f64 B)
NOTE: A, B_m, C, and F should be sorted in increasing order before calling this function.
(FPCore (A B_m C F)
:precision binary64
(let* ((t_0 (fma (* -4.0 A) C (* B_m B_m))))
(if (<= B_m 1.4e-13)
(/
(sqrt (* (fma (* -0.5 B_m) (/ B_m C) (+ A A)) (* (* 2.0 F) t_0)))
(- t_0))
(if (<= B_m 1.15e+79)
(*
(- (sqrt 2.0))
(sqrt
(*
F
(/ (- (+ C A) (hypot (- A C) B_m)) (fma -4.0 (* C A) (* B_m B_m))))))
(/ (sqrt (* (- A (hypot A B_m)) (+ F F))) (- B_m))))))B_m = fabs(B);
assert(A < B_m && B_m < C && C < F);
double code(double A, double B_m, double C, double F) {
double t_0 = fma((-4.0 * A), C, (B_m * B_m));
double tmp;
if (B_m <= 1.4e-13) {
tmp = sqrt((fma((-0.5 * B_m), (B_m / C), (A + A)) * ((2.0 * F) * t_0))) / -t_0;
} else if (B_m <= 1.15e+79) {
tmp = -sqrt(2.0) * sqrt((F * (((C + A) - hypot((A - C), B_m)) / fma(-4.0, (C * A), (B_m * B_m)))));
} else {
tmp = sqrt(((A - hypot(A, B_m)) * (F + F))) / -B_m;
}
return tmp;
}
B_m = abs(B) A, B_m, C, F = sort([A, B_m, C, F]) function code(A, B_m, C, F) t_0 = fma(Float64(-4.0 * A), C, Float64(B_m * B_m)) tmp = 0.0 if (B_m <= 1.4e-13) tmp = Float64(sqrt(Float64(fma(Float64(-0.5 * B_m), Float64(B_m / C), Float64(A + A)) * Float64(Float64(2.0 * F) * t_0))) / Float64(-t_0)); elseif (B_m <= 1.15e+79) tmp = Float64(Float64(-sqrt(2.0)) * sqrt(Float64(F * Float64(Float64(Float64(C + A) - hypot(Float64(A - C), B_m)) / fma(-4.0, Float64(C * A), Float64(B_m * B_m)))))); else tmp = Float64(sqrt(Float64(Float64(A - hypot(A, B_m)) * Float64(F + F))) / Float64(-B_m)); end return tmp end
B_m = N[Abs[B], $MachinePrecision]
NOTE: A, B_m, C, and F should be sorted in increasing order before calling this function.
code[A_, B$95$m_, C_, F_] := Block[{t$95$0 = N[(N[(-4.0 * A), $MachinePrecision] * C + N[(B$95$m * B$95$m), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[B$95$m, 1.4e-13], N[(N[Sqrt[N[(N[(N[(-0.5 * B$95$m), $MachinePrecision] * N[(B$95$m / C), $MachinePrecision] + N[(A + A), $MachinePrecision]), $MachinePrecision] * N[(N[(2.0 * F), $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / (-t$95$0)), $MachinePrecision], If[LessEqual[B$95$m, 1.15e+79], N[((-N[Sqrt[2.0], $MachinePrecision]) * N[Sqrt[N[(F * N[(N[(N[(C + A), $MachinePrecision] - N[Sqrt[N[(A - C), $MachinePrecision] ^ 2 + B$95$m ^ 2], $MachinePrecision]), $MachinePrecision] / N[(-4.0 * N[(C * A), $MachinePrecision] + N[(B$95$m * B$95$m), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision], N[(N[Sqrt[N[(N[(A - N[Sqrt[A ^ 2 + B$95$m ^ 2], $MachinePrecision]), $MachinePrecision] * N[(F + F), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / (-B$95$m)), $MachinePrecision]]]]
\begin{array}{l}
B_m = \left|B\right|
\\
[A, B_m, C, F] = \mathsf{sort}([A, B_m, C, F])\\
\\
\begin{array}{l}
t_0 := \mathsf{fma}\left(-4 \cdot A, C, B\_m \cdot B\_m\right)\\
\mathbf{if}\;B\_m \leq 1.4 \cdot 10^{-13}:\\
\;\;\;\;\frac{\sqrt{\mathsf{fma}\left(-0.5 \cdot B\_m, \frac{B\_m}{C}, A + A\right) \cdot \left(\left(2 \cdot F\right) \cdot t\_0\right)}}{-t\_0}\\
\mathbf{elif}\;B\_m \leq 1.15 \cdot 10^{+79}:\\
\;\;\;\;\left(-\sqrt{2}\right) \cdot \sqrt{F \cdot \frac{\left(C + A\right) - \mathsf{hypot}\left(A - C, B\_m\right)}{\mathsf{fma}\left(-4, C \cdot A, B\_m \cdot B\_m\right)}}\\
\mathbf{else}:\\
\;\;\;\;\frac{\sqrt{\left(A - \mathsf{hypot}\left(A, B\_m\right)\right) \cdot \left(F + F\right)}}{-B\_m}\\
\end{array}
\end{array}
if B < 1.4000000000000001e-13Initial program 20.4%
Taylor expanded in C around inf
mul-1-negN/A
lower--.f64N/A
+-commutativeN/A
*-commutativeN/A
lower-fma.f64N/A
lower-/.f64N/A
unpow2N/A
lower-*.f64N/A
lower-neg.f6417.6
Applied rewrites17.6%
Applied rewrites17.6%
if 1.4000000000000001e-13 < B < 1.15e79Initial program 32.6%
Taylor expanded in F around 0
mul-1-negN/A
*-commutativeN/A
distribute-lft-neg-inN/A
lower-*.f64N/A
lower-neg.f64N/A
lower-sqrt.f64N/A
lower-sqrt.f64N/A
associate-/l*N/A
lower-*.f64N/A
Applied rewrites57.4%
if 1.15e79 < B Initial program 10.1%
Taylor expanded in C around 0
mul-1-negN/A
distribute-lft-neg-inN/A
lower-*.f64N/A
lower-neg.f64N/A
lower-/.f64N/A
lower-sqrt.f64N/A
lower-sqrt.f64N/A
*-commutativeN/A
lower-*.f64N/A
lower--.f64N/A
+-commutativeN/A
unpow2N/A
unpow2N/A
lower-hypot.f6458.0
Applied rewrites58.0%
Applied rewrites58.4%
Applied rewrites58.4%
Final simplification28.2%
B_m = (fabs.f64 B)
NOTE: A, B_m, C, and F should be sorted in increasing order before calling this function.
(FPCore (A B_m C F)
:precision binary64
(let* ((t_0 (fma (* -4.0 A) C (* B_m B_m))))
(if (<= B_m 1.8e-13)
(/
(sqrt (* (fma (* -0.5 B_m) (/ B_m C) (+ A A)) (* (* 2.0 F) t_0)))
(- t_0))
(/ (sqrt (* (- A (hypot A B_m)) (+ F F))) (- B_m)))))B_m = fabs(B);
assert(A < B_m && B_m < C && C < F);
double code(double A, double B_m, double C, double F) {
double t_0 = fma((-4.0 * A), C, (B_m * B_m));
double tmp;
if (B_m <= 1.8e-13) {
tmp = sqrt((fma((-0.5 * B_m), (B_m / C), (A + A)) * ((2.0 * F) * t_0))) / -t_0;
} else {
tmp = sqrt(((A - hypot(A, B_m)) * (F + F))) / -B_m;
}
return tmp;
}
B_m = abs(B) A, B_m, C, F = sort([A, B_m, C, F]) function code(A, B_m, C, F) t_0 = fma(Float64(-4.0 * A), C, Float64(B_m * B_m)) tmp = 0.0 if (B_m <= 1.8e-13) tmp = Float64(sqrt(Float64(fma(Float64(-0.5 * B_m), Float64(B_m / C), Float64(A + A)) * Float64(Float64(2.0 * F) * t_0))) / Float64(-t_0)); else tmp = Float64(sqrt(Float64(Float64(A - hypot(A, B_m)) * Float64(F + F))) / Float64(-B_m)); end return tmp end
B_m = N[Abs[B], $MachinePrecision]
NOTE: A, B_m, C, and F should be sorted in increasing order before calling this function.
code[A_, B$95$m_, C_, F_] := Block[{t$95$0 = N[(N[(-4.0 * A), $MachinePrecision] * C + N[(B$95$m * B$95$m), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[B$95$m, 1.8e-13], N[(N[Sqrt[N[(N[(N[(-0.5 * B$95$m), $MachinePrecision] * N[(B$95$m / C), $MachinePrecision] + N[(A + A), $MachinePrecision]), $MachinePrecision] * N[(N[(2.0 * F), $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / (-t$95$0)), $MachinePrecision], N[(N[Sqrt[N[(N[(A - N[Sqrt[A ^ 2 + B$95$m ^ 2], $MachinePrecision]), $MachinePrecision] * N[(F + F), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / (-B$95$m)), $MachinePrecision]]]
\begin{array}{l}
B_m = \left|B\right|
\\
[A, B_m, C, F] = \mathsf{sort}([A, B_m, C, F])\\
\\
\begin{array}{l}
t_0 := \mathsf{fma}\left(-4 \cdot A, C, B\_m \cdot B\_m\right)\\
\mathbf{if}\;B\_m \leq 1.8 \cdot 10^{-13}:\\
\;\;\;\;\frac{\sqrt{\mathsf{fma}\left(-0.5 \cdot B\_m, \frac{B\_m}{C}, A + A\right) \cdot \left(\left(2 \cdot F\right) \cdot t\_0\right)}}{-t\_0}\\
\mathbf{else}:\\
\;\;\;\;\frac{\sqrt{\left(A - \mathsf{hypot}\left(A, B\_m\right)\right) \cdot \left(F + F\right)}}{-B\_m}\\
\end{array}
\end{array}
if B < 1.7999999999999999e-13Initial program 20.4%
Taylor expanded in C around inf
mul-1-negN/A
lower--.f64N/A
+-commutativeN/A
*-commutativeN/A
lower-fma.f64N/A
lower-/.f64N/A
unpow2N/A
lower-*.f64N/A
lower-neg.f6417.6
Applied rewrites17.6%
Applied rewrites17.6%
if 1.7999999999999999e-13 < B Initial program 15.5%
Taylor expanded in C around 0
mul-1-negN/A
distribute-lft-neg-inN/A
lower-*.f64N/A
lower-neg.f64N/A
lower-/.f64N/A
lower-sqrt.f64N/A
lower-sqrt.f64N/A
*-commutativeN/A
lower-*.f64N/A
lower--.f64N/A
+-commutativeN/A
unpow2N/A
unpow2N/A
lower-hypot.f6454.7
Applied rewrites54.7%
Applied rewrites55.1%
Applied rewrites55.1%
Final simplification27.4%
B_m = (fabs.f64 B)
NOTE: A, B_m, C, and F should be sorted in increasing order before calling this function.
(FPCore (A B_m C F)
:precision binary64
(let* ((t_0 (fma (* -4.0 A) C (* B_m B_m))))
(if (<= B_m 1.48e+82)
(/
(sqrt (* (fma (* -0.5 B_m) (/ B_m C) (+ A A)) (* (* 2.0 F) t_0)))
(- t_0))
(/ (sqrt (* B_m (fma -2.0 F (* 2.0 (/ (* A F) B_m))))) (- B_m)))))B_m = fabs(B);
assert(A < B_m && B_m < C && C < F);
double code(double A, double B_m, double C, double F) {
double t_0 = fma((-4.0 * A), C, (B_m * B_m));
double tmp;
if (B_m <= 1.48e+82) {
tmp = sqrt((fma((-0.5 * B_m), (B_m / C), (A + A)) * ((2.0 * F) * t_0))) / -t_0;
} else {
tmp = sqrt((B_m * fma(-2.0, F, (2.0 * ((A * F) / B_m))))) / -B_m;
}
return tmp;
}
B_m = abs(B) A, B_m, C, F = sort([A, B_m, C, F]) function code(A, B_m, C, F) t_0 = fma(Float64(-4.0 * A), C, Float64(B_m * B_m)) tmp = 0.0 if (B_m <= 1.48e+82) tmp = Float64(sqrt(Float64(fma(Float64(-0.5 * B_m), Float64(B_m / C), Float64(A + A)) * Float64(Float64(2.0 * F) * t_0))) / Float64(-t_0)); else tmp = Float64(sqrt(Float64(B_m * fma(-2.0, F, Float64(2.0 * Float64(Float64(A * F) / B_m))))) / Float64(-B_m)); end return tmp end
B_m = N[Abs[B], $MachinePrecision]
NOTE: A, B_m, C, and F should be sorted in increasing order before calling this function.
code[A_, B$95$m_, C_, F_] := Block[{t$95$0 = N[(N[(-4.0 * A), $MachinePrecision] * C + N[(B$95$m * B$95$m), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[B$95$m, 1.48e+82], N[(N[Sqrt[N[(N[(N[(-0.5 * B$95$m), $MachinePrecision] * N[(B$95$m / C), $MachinePrecision] + N[(A + A), $MachinePrecision]), $MachinePrecision] * N[(N[(2.0 * F), $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / (-t$95$0)), $MachinePrecision], N[(N[Sqrt[N[(B$95$m * N[(-2.0 * F + N[(2.0 * N[(N[(A * F), $MachinePrecision] / B$95$m), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / (-B$95$m)), $MachinePrecision]]]
\begin{array}{l}
B_m = \left|B\right|
\\
[A, B_m, C, F] = \mathsf{sort}([A, B_m, C, F])\\
\\
\begin{array}{l}
t_0 := \mathsf{fma}\left(-4 \cdot A, C, B\_m \cdot B\_m\right)\\
\mathbf{if}\;B\_m \leq 1.48 \cdot 10^{+82}:\\
\;\;\;\;\frac{\sqrt{\mathsf{fma}\left(-0.5 \cdot B\_m, \frac{B\_m}{C}, A + A\right) \cdot \left(\left(2 \cdot F\right) \cdot t\_0\right)}}{-t\_0}\\
\mathbf{else}:\\
\;\;\;\;\frac{\sqrt{B\_m \cdot \mathsf{fma}\left(-2, F, 2 \cdot \frac{A \cdot F}{B\_m}\right)}}{-B\_m}\\
\end{array}
\end{array}
if B < 1.48e82Initial program 21.4%
Taylor expanded in C around inf
mul-1-negN/A
lower--.f64N/A
+-commutativeN/A
*-commutativeN/A
lower-fma.f64N/A
lower-/.f64N/A
unpow2N/A
lower-*.f64N/A
lower-neg.f6417.0
Applied rewrites17.0%
Applied rewrites17.0%
if 1.48e82 < B Initial program 10.1%
Taylor expanded in C around 0
mul-1-negN/A
distribute-lft-neg-inN/A
lower-*.f64N/A
lower-neg.f64N/A
lower-/.f64N/A
lower-sqrt.f64N/A
lower-sqrt.f64N/A
*-commutativeN/A
lower-*.f64N/A
lower--.f64N/A
+-commutativeN/A
unpow2N/A
unpow2N/A
lower-hypot.f6458.0
Applied rewrites58.0%
Applied rewrites58.4%
Applied rewrites58.4%
Taylor expanded in B around inf
Applied rewrites52.7%
Final simplification24.1%
B_m = (fabs.f64 B)
NOTE: A, B_m, C, and F should be sorted in increasing order before calling this function.
(FPCore (A B_m C F)
:precision binary64
(let* ((t_0 (fma (* C -4.0) A (* B_m B_m))))
(if (<= B_m 1.35e+50)
(* (sqrt (* t_0 2.0)) (/ (sqrt (* F (+ A A))) (- t_0)))
(/ (sqrt (fma -2.0 (* B_m F) (* 2.0 (* A F)))) (- B_m)))))B_m = fabs(B);
assert(A < B_m && B_m < C && C < F);
double code(double A, double B_m, double C, double F) {
double t_0 = fma((C * -4.0), A, (B_m * B_m));
double tmp;
if (B_m <= 1.35e+50) {
tmp = sqrt((t_0 * 2.0)) * (sqrt((F * (A + A))) / -t_0);
} else {
tmp = sqrt(fma(-2.0, (B_m * F), (2.0 * (A * F)))) / -B_m;
}
return tmp;
}
B_m = abs(B) A, B_m, C, F = sort([A, B_m, C, F]) function code(A, B_m, C, F) t_0 = fma(Float64(C * -4.0), A, Float64(B_m * B_m)) tmp = 0.0 if (B_m <= 1.35e+50) tmp = Float64(sqrt(Float64(t_0 * 2.0)) * Float64(sqrt(Float64(F * Float64(A + A))) / Float64(-t_0))); else tmp = Float64(sqrt(fma(-2.0, Float64(B_m * F), Float64(2.0 * Float64(A * F)))) / Float64(-B_m)); end return tmp end
B_m = N[Abs[B], $MachinePrecision]
NOTE: A, B_m, C, and F should be sorted in increasing order before calling this function.
code[A_, B$95$m_, C_, F_] := Block[{t$95$0 = N[(N[(C * -4.0), $MachinePrecision] * A + N[(B$95$m * B$95$m), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[B$95$m, 1.35e+50], N[(N[Sqrt[N[(t$95$0 * 2.0), $MachinePrecision]], $MachinePrecision] * N[(N[Sqrt[N[(F * N[(A + A), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / (-t$95$0)), $MachinePrecision]), $MachinePrecision], N[(N[Sqrt[N[(-2.0 * N[(B$95$m * F), $MachinePrecision] + N[(2.0 * N[(A * F), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / (-B$95$m)), $MachinePrecision]]]
\begin{array}{l}
B_m = \left|B\right|
\\
[A, B_m, C, F] = \mathsf{sort}([A, B_m, C, F])\\
\\
\begin{array}{l}
t_0 := \mathsf{fma}\left(C \cdot -4, A, B\_m \cdot B\_m\right)\\
\mathbf{if}\;B\_m \leq 1.35 \cdot 10^{+50}:\\
\;\;\;\;\sqrt{t\_0 \cdot 2} \cdot \frac{\sqrt{F \cdot \left(A + A\right)}}{-t\_0}\\
\mathbf{else}:\\
\;\;\;\;\frac{\sqrt{\mathsf{fma}\left(-2, B\_m \cdot F, 2 \cdot \left(A \cdot F\right)\right)}}{-B\_m}\\
\end{array}
\end{array}
if B < 1.35e50Initial program 21.5%
Taylor expanded in A around -inf
mul-1-negN/A
lower-neg.f6412.9
Applied rewrites12.9%
lift-sqrt.f64N/A
lift-*.f64N/A
lift-*.f64N/A
lift-*.f64N/A
associate-*r*N/A
associate-*l*N/A
sqrt-prodN/A
pow1/2N/A
Applied rewrites9.7%
lift-/.f64N/A
lift-neg.f64N/A
lift-*.f64N/A
distribute-rgt-neg-inN/A
associate-/l*N/A
lower-*.f64N/A
Applied rewrites9.6%
Taylor expanded in C around inf
lower-sqrt.f64N/A
lower-*.f64N/A
mul-1-negN/A
lower--.f64N/A
lower-neg.f6411.2
Applied rewrites11.2%
if 1.35e50 < B Initial program 10.9%
Taylor expanded in C around 0
mul-1-negN/A
distribute-lft-neg-inN/A
lower-*.f64N/A
lower-neg.f64N/A
lower-/.f64N/A
lower-sqrt.f64N/A
lower-sqrt.f64N/A
*-commutativeN/A
lower-*.f64N/A
lower--.f64N/A
+-commutativeN/A
unpow2N/A
unpow2N/A
lower-hypot.f6456.4
Applied rewrites56.4%
Applied rewrites56.8%
Taylor expanded in A around 0
Applied rewrites50.3%
Final simplification20.0%
B_m = (fabs.f64 B)
NOTE: A, B_m, C, and F should be sorted in increasing order before calling this function.
(FPCore (A B_m C F)
:precision binary64
(let* ((t_0 (fma (* -4.0 A) C (* B_m B_m))))
(if (<= B_m 9e+47)
(/ (sqrt (* (- (+ C A) (- A)) (* (* 2.0 F) t_0))) (- t_0))
(/ (sqrt (fma -2.0 (* B_m F) (* 2.0 (* A F)))) (- B_m)))))B_m = fabs(B);
assert(A < B_m && B_m < C && C < F);
double code(double A, double B_m, double C, double F) {
double t_0 = fma((-4.0 * A), C, (B_m * B_m));
double tmp;
if (B_m <= 9e+47) {
tmp = sqrt((((C + A) - -A) * ((2.0 * F) * t_0))) / -t_0;
} else {
tmp = sqrt(fma(-2.0, (B_m * F), (2.0 * (A * F)))) / -B_m;
}
return tmp;
}
B_m = abs(B) A, B_m, C, F = sort([A, B_m, C, F]) function code(A, B_m, C, F) t_0 = fma(Float64(-4.0 * A), C, Float64(B_m * B_m)) tmp = 0.0 if (B_m <= 9e+47) tmp = Float64(sqrt(Float64(Float64(Float64(C + A) - Float64(-A)) * Float64(Float64(2.0 * F) * t_0))) / Float64(-t_0)); else tmp = Float64(sqrt(fma(-2.0, Float64(B_m * F), Float64(2.0 * Float64(A * F)))) / Float64(-B_m)); end return tmp end
B_m = N[Abs[B], $MachinePrecision]
NOTE: A, B_m, C, and F should be sorted in increasing order before calling this function.
code[A_, B$95$m_, C_, F_] := Block[{t$95$0 = N[(N[(-4.0 * A), $MachinePrecision] * C + N[(B$95$m * B$95$m), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[B$95$m, 9e+47], N[(N[Sqrt[N[(N[(N[(C + A), $MachinePrecision] - (-A)), $MachinePrecision] * N[(N[(2.0 * F), $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / (-t$95$0)), $MachinePrecision], N[(N[Sqrt[N[(-2.0 * N[(B$95$m * F), $MachinePrecision] + N[(2.0 * N[(A * F), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / (-B$95$m)), $MachinePrecision]]]
\begin{array}{l}
B_m = \left|B\right|
\\
[A, B_m, C, F] = \mathsf{sort}([A, B_m, C, F])\\
\\
\begin{array}{l}
t_0 := \mathsf{fma}\left(-4 \cdot A, C, B\_m \cdot B\_m\right)\\
\mathbf{if}\;B\_m \leq 9 \cdot 10^{+47}:\\
\;\;\;\;\frac{\sqrt{\left(\left(C + A\right) - \left(-A\right)\right) \cdot \left(\left(2 \cdot F\right) \cdot t\_0\right)}}{-t\_0}\\
\mathbf{else}:\\
\;\;\;\;\frac{\sqrt{\mathsf{fma}\left(-2, B\_m \cdot F, 2 \cdot \left(A \cdot F\right)\right)}}{-B\_m}\\
\end{array}
\end{array}
if B < 8.99999999999999958e47Initial program 21.5%
Taylor expanded in A around -inf
mul-1-negN/A
lower-neg.f6412.9
Applied rewrites12.9%
lift-/.f64N/A
lift-neg.f64N/A
distribute-frac-negN/A
distribute-neg-frac2N/A
lower-/.f64N/A
Applied rewrites12.9%
if 8.99999999999999958e47 < B Initial program 10.9%
Taylor expanded in C around 0
mul-1-negN/A
distribute-lft-neg-inN/A
lower-*.f64N/A
lower-neg.f64N/A
lower-/.f64N/A
lower-sqrt.f64N/A
lower-sqrt.f64N/A
*-commutativeN/A
lower-*.f64N/A
lower--.f64N/A
+-commutativeN/A
unpow2N/A
unpow2N/A
lower-hypot.f6456.4
Applied rewrites56.4%
Applied rewrites56.8%
Taylor expanded in A around 0
Applied rewrites50.3%
B_m = (fabs.f64 B)
NOTE: A, B_m, C, and F should be sorted in increasing order before calling this function.
(FPCore (A B_m C F)
:precision binary64
(if (<= B_m 1.65e-50)
(*
(- (sqrt (* -8.0 (* A C))))
(/ (sqrt (* (- (+ C A) (- A)) F)) (fma (* C -4.0) A (* B_m B_m))))
(/ (sqrt (fma -2.0 (* B_m F) (* 2.0 (* A F)))) (- B_m))))B_m = fabs(B);
assert(A < B_m && B_m < C && C < F);
double code(double A, double B_m, double C, double F) {
double tmp;
if (B_m <= 1.65e-50) {
tmp = -sqrt((-8.0 * (A * C))) * (sqrt((((C + A) - -A) * F)) / fma((C * -4.0), A, (B_m * B_m)));
} else {
tmp = sqrt(fma(-2.0, (B_m * F), (2.0 * (A * F)))) / -B_m;
}
return tmp;
}
B_m = abs(B) A, B_m, C, F = sort([A, B_m, C, F]) function code(A, B_m, C, F) tmp = 0.0 if (B_m <= 1.65e-50) tmp = Float64(Float64(-sqrt(Float64(-8.0 * Float64(A * C)))) * Float64(sqrt(Float64(Float64(Float64(C + A) - Float64(-A)) * F)) / fma(Float64(C * -4.0), A, Float64(B_m * B_m)))); else tmp = Float64(sqrt(fma(-2.0, Float64(B_m * F), Float64(2.0 * Float64(A * F)))) / Float64(-B_m)); end return tmp end
B_m = N[Abs[B], $MachinePrecision] NOTE: A, B_m, C, and F should be sorted in increasing order before calling this function. code[A_, B$95$m_, C_, F_] := If[LessEqual[B$95$m, 1.65e-50], N[((-N[Sqrt[N[(-8.0 * N[(A * C), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]) * N[(N[Sqrt[N[(N[(N[(C + A), $MachinePrecision] - (-A)), $MachinePrecision] * F), $MachinePrecision]], $MachinePrecision] / N[(N[(C * -4.0), $MachinePrecision] * A + N[(B$95$m * B$95$m), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[Sqrt[N[(-2.0 * N[(B$95$m * F), $MachinePrecision] + N[(2.0 * N[(A * F), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / (-B$95$m)), $MachinePrecision]]
\begin{array}{l}
B_m = \left|B\right|
\\
[A, B_m, C, F] = \mathsf{sort}([A, B_m, C, F])\\
\\
\begin{array}{l}
\mathbf{if}\;B\_m \leq 1.65 \cdot 10^{-50}:\\
\;\;\;\;\left(-\sqrt{-8 \cdot \left(A \cdot C\right)}\right) \cdot \frac{\sqrt{\left(\left(C + A\right) - \left(-A\right)\right) \cdot F}}{\mathsf{fma}\left(C \cdot -4, A, B\_m \cdot B\_m\right)}\\
\mathbf{else}:\\
\;\;\;\;\frac{\sqrt{\mathsf{fma}\left(-2, B\_m \cdot F, 2 \cdot \left(A \cdot F\right)\right)}}{-B\_m}\\
\end{array}
\end{array}
if B < 1.6499999999999999e-50Initial program 20.1%
Taylor expanded in A around -inf
mul-1-negN/A
lower-neg.f6412.0
Applied rewrites12.0%
lift-sqrt.f64N/A
lift-*.f64N/A
lift-*.f64N/A
lift-*.f64N/A
associate-*r*N/A
associate-*l*N/A
sqrt-prodN/A
pow1/2N/A
Applied rewrites8.5%
lift-/.f64N/A
lift-neg.f64N/A
lift-*.f64N/A
distribute-rgt-neg-inN/A
associate-/l*N/A
lower-*.f64N/A
Applied rewrites8.4%
Taylor expanded in A around inf
lower-*.f64N/A
lower-*.f646.9
Applied rewrites6.9%
if 1.6499999999999999e-50 < B Initial program 17.0%
Taylor expanded in C around 0
mul-1-negN/A
distribute-lft-neg-inN/A
lower-*.f64N/A
lower-neg.f64N/A
lower-/.f64N/A
lower-sqrt.f64N/A
lower-sqrt.f64N/A
*-commutativeN/A
lower-*.f64N/A
lower--.f64N/A
+-commutativeN/A
unpow2N/A
unpow2N/A
lower-hypot.f6450.0
Applied rewrites50.0%
Applied rewrites50.3%
Taylor expanded in A around 0
Applied rewrites41.3%
Final simplification17.6%
B_m = (fabs.f64 B) NOTE: A, B_m, C, and F should be sorted in increasing order before calling this function. (FPCore (A B_m C F) :precision binary64 (/ (sqrt (fma -2.0 (* B_m F) (* 2.0 (* A F)))) (- B_m)))
B_m = fabs(B);
assert(A < B_m && B_m < C && C < F);
double code(double A, double B_m, double C, double F) {
return sqrt(fma(-2.0, (B_m * F), (2.0 * (A * F)))) / -B_m;
}
B_m = abs(B) A, B_m, C, F = sort([A, B_m, C, F]) function code(A, B_m, C, F) return Float64(sqrt(fma(-2.0, Float64(B_m * F), Float64(2.0 * Float64(A * F)))) / Float64(-B_m)) end
B_m = N[Abs[B], $MachinePrecision] NOTE: A, B_m, C, and F should be sorted in increasing order before calling this function. code[A_, B$95$m_, C_, F_] := N[(N[Sqrt[N[(-2.0 * N[(B$95$m * F), $MachinePrecision] + N[(2.0 * N[(A * F), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / (-B$95$m)), $MachinePrecision]
\begin{array}{l}
B_m = \left|B\right|
\\
[A, B_m, C, F] = \mathsf{sort}([A, B_m, C, F])\\
\\
\frac{\sqrt{\mathsf{fma}\left(-2, B\_m \cdot F, 2 \cdot \left(A \cdot F\right)\right)}}{-B\_m}
\end{array}
Initial program 19.1%
Taylor expanded in C around 0
mul-1-negN/A
distribute-lft-neg-inN/A
lower-*.f64N/A
lower-neg.f64N/A
lower-/.f64N/A
lower-sqrt.f64N/A
lower-sqrt.f64N/A
*-commutativeN/A
lower-*.f64N/A
lower--.f64N/A
+-commutativeN/A
unpow2N/A
unpow2N/A
lower-hypot.f6417.7
Applied rewrites17.7%
Applied rewrites17.8%
Taylor expanded in A around 0
Applied rewrites13.7%
B_m = (fabs.f64 B) NOTE: A, B_m, C, and F should be sorted in increasing order before calling this function. (FPCore (A B_m C F) :precision binary64 (/ (sqrt (* -2.0 (* B_m F))) (- B_m)))
B_m = fabs(B);
assert(A < B_m && B_m < C && C < F);
double code(double A, double B_m, double C, double F) {
return sqrt((-2.0 * (B_m * F))) / -B_m;
}
B_m = abs(b)
NOTE: A, B_m, C, and F should be sorted in increasing order before calling this function.
real(8) function code(a, b_m, c, f)
real(8), intent (in) :: a
real(8), intent (in) :: b_m
real(8), intent (in) :: c
real(8), intent (in) :: f
code = sqrt(((-2.0d0) * (b_m * f))) / -b_m
end function
B_m = Math.abs(B);
assert A < B_m && B_m < C && C < F;
public static double code(double A, double B_m, double C, double F) {
return Math.sqrt((-2.0 * (B_m * F))) / -B_m;
}
B_m = math.fabs(B) [A, B_m, C, F] = sort([A, B_m, C, F]) def code(A, B_m, C, F): return math.sqrt((-2.0 * (B_m * F))) / -B_m
B_m = abs(B) A, B_m, C, F = sort([A, B_m, C, F]) function code(A, B_m, C, F) return Float64(sqrt(Float64(-2.0 * Float64(B_m * F))) / Float64(-B_m)) end
B_m = abs(B);
A, B_m, C, F = num2cell(sort([A, B_m, C, F])){:}
function tmp = code(A, B_m, C, F)
tmp = sqrt((-2.0 * (B_m * F))) / -B_m;
end
B_m = N[Abs[B], $MachinePrecision] NOTE: A, B_m, C, and F should be sorted in increasing order before calling this function. code[A_, B$95$m_, C_, F_] := N[(N[Sqrt[N[(-2.0 * N[(B$95$m * F), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / (-B$95$m)), $MachinePrecision]
\begin{array}{l}
B_m = \left|B\right|
\\
[A, B_m, C, F] = \mathsf{sort}([A, B_m, C, F])\\
\\
\frac{\sqrt{-2 \cdot \left(B\_m \cdot F\right)}}{-B\_m}
\end{array}
Initial program 19.1%
Taylor expanded in C around 0
mul-1-negN/A
distribute-lft-neg-inN/A
lower-*.f64N/A
lower-neg.f64N/A
lower-/.f64N/A
lower-sqrt.f64N/A
lower-sqrt.f64N/A
*-commutativeN/A
lower-*.f64N/A
lower--.f64N/A
+-commutativeN/A
unpow2N/A
unpow2N/A
lower-hypot.f6417.7
Applied rewrites17.7%
Applied rewrites17.8%
Taylor expanded in A around 0
Applied rewrites14.1%
B_m = (fabs.f64 B) NOTE: A, B_m, C, and F should be sorted in increasing order before calling this function. (FPCore (A B_m C F) :precision binary64 (* (/ -2.0 B_m) (sqrt (* F A))))
B_m = fabs(B);
assert(A < B_m && B_m < C && C < F);
double code(double A, double B_m, double C, double F) {
return (-2.0 / B_m) * sqrt((F * A));
}
B_m = abs(b)
NOTE: A, B_m, C, and F should be sorted in increasing order before calling this function.
real(8) function code(a, b_m, c, f)
real(8), intent (in) :: a
real(8), intent (in) :: b_m
real(8), intent (in) :: c
real(8), intent (in) :: f
code = ((-2.0d0) / b_m) * sqrt((f * a))
end function
B_m = Math.abs(B);
assert A < B_m && B_m < C && C < F;
public static double code(double A, double B_m, double C, double F) {
return (-2.0 / B_m) * Math.sqrt((F * A));
}
B_m = math.fabs(B) [A, B_m, C, F] = sort([A, B_m, C, F]) def code(A, B_m, C, F): return (-2.0 / B_m) * math.sqrt((F * A))
B_m = abs(B) A, B_m, C, F = sort([A, B_m, C, F]) function code(A, B_m, C, F) return Float64(Float64(-2.0 / B_m) * sqrt(Float64(F * A))) end
B_m = abs(B);
A, B_m, C, F = num2cell(sort([A, B_m, C, F])){:}
function tmp = code(A, B_m, C, F)
tmp = (-2.0 / B_m) * sqrt((F * A));
end
B_m = N[Abs[B], $MachinePrecision] NOTE: A, B_m, C, and F should be sorted in increasing order before calling this function. code[A_, B$95$m_, C_, F_] := N[(N[(-2.0 / B$95$m), $MachinePrecision] * N[Sqrt[N[(F * A), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
B_m = \left|B\right|
\\
[A, B_m, C, F] = \mathsf{sort}([A, B_m, C, F])\\
\\
\frac{-2}{B\_m} \cdot \sqrt{F \cdot A}
\end{array}
Initial program 19.1%
Taylor expanded in C around 0
mul-1-negN/A
distribute-lft-neg-inN/A
lower-*.f64N/A
lower-neg.f64N/A
lower-/.f64N/A
lower-sqrt.f64N/A
lower-sqrt.f64N/A
*-commutativeN/A
lower-*.f64N/A
lower--.f64N/A
+-commutativeN/A
unpow2N/A
unpow2N/A
lower-hypot.f6417.7
Applied rewrites17.7%
Taylor expanded in A around -inf
Applied rewrites4.2%
B_m = (fabs.f64 B) NOTE: A, B_m, C, and F should be sorted in increasing order before calling this function. (FPCore (A B_m C F) :precision binary64 (/ (* F 2.0) (sqrt B_m)))
B_m = fabs(B);
assert(A < B_m && B_m < C && C < F);
double code(double A, double B_m, double C, double F) {
return (F * 2.0) / sqrt(B_m);
}
B_m = abs(b)
NOTE: A, B_m, C, and F should be sorted in increasing order before calling this function.
real(8) function code(a, b_m, c, f)
real(8), intent (in) :: a
real(8), intent (in) :: b_m
real(8), intent (in) :: c
real(8), intent (in) :: f
code = (f * 2.0d0) / sqrt(b_m)
end function
B_m = Math.abs(B);
assert A < B_m && B_m < C && C < F;
public static double code(double A, double B_m, double C, double F) {
return (F * 2.0) / Math.sqrt(B_m);
}
B_m = math.fabs(B) [A, B_m, C, F] = sort([A, B_m, C, F]) def code(A, B_m, C, F): return (F * 2.0) / math.sqrt(B_m)
B_m = abs(B) A, B_m, C, F = sort([A, B_m, C, F]) function code(A, B_m, C, F) return Float64(Float64(F * 2.0) / sqrt(B_m)) end
B_m = abs(B);
A, B_m, C, F = num2cell(sort([A, B_m, C, F])){:}
function tmp = code(A, B_m, C, F)
tmp = (F * 2.0) / sqrt(B_m);
end
B_m = N[Abs[B], $MachinePrecision] NOTE: A, B_m, C, and F should be sorted in increasing order before calling this function. code[A_, B$95$m_, C_, F_] := N[(N[(F * 2.0), $MachinePrecision] / N[Sqrt[B$95$m], $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
B_m = \left|B\right|
\\
[A, B_m, C, F] = \mathsf{sort}([A, B_m, C, F])\\
\\
\frac{F \cdot 2}{\sqrt{B\_m}}
\end{array}
Initial program 19.1%
Taylor expanded in B around -inf
mul-1-negN/A
*-commutativeN/A
distribute-lft-neg-inN/A
lower-*.f64N/A
lower-neg.f64N/A
*-commutativeN/A
unpow2N/A
rem-square-sqrtN/A
lower-*.f64N/A
lower-sqrt.f64N/A
lower-sqrt.f64N/A
lower-/.f642.1
Applied rewrites2.1%
Applied rewrites2.1%
Applied rewrites2.1%
Applied rewrites3.1%
B_m = (fabs.f64 B) NOTE: A, B_m, C, and F should be sorted in increasing order before calling this function. (FPCore (A B_m C F) :precision binary64 (sqrt (* F (/ 2.0 B_m))))
B_m = fabs(B);
assert(A < B_m && B_m < C && C < F);
double code(double A, double B_m, double C, double F) {
return sqrt((F * (2.0 / B_m)));
}
B_m = abs(b)
NOTE: A, B_m, C, and F should be sorted in increasing order before calling this function.
real(8) function code(a, b_m, c, f)
real(8), intent (in) :: a
real(8), intent (in) :: b_m
real(8), intent (in) :: c
real(8), intent (in) :: f
code = sqrt((f * (2.0d0 / b_m)))
end function
B_m = Math.abs(B);
assert A < B_m && B_m < C && C < F;
public static double code(double A, double B_m, double C, double F) {
return Math.sqrt((F * (2.0 / B_m)));
}
B_m = math.fabs(B) [A, B_m, C, F] = sort([A, B_m, C, F]) def code(A, B_m, C, F): return math.sqrt((F * (2.0 / B_m)))
B_m = abs(B) A, B_m, C, F = sort([A, B_m, C, F]) function code(A, B_m, C, F) return sqrt(Float64(F * Float64(2.0 / B_m))) end
B_m = abs(B);
A, B_m, C, F = num2cell(sort([A, B_m, C, F])){:}
function tmp = code(A, B_m, C, F)
tmp = sqrt((F * (2.0 / B_m)));
end
B_m = N[Abs[B], $MachinePrecision] NOTE: A, B_m, C, and F should be sorted in increasing order before calling this function. code[A_, B$95$m_, C_, F_] := N[Sqrt[N[(F * N[(2.0 / B$95$m), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]
\begin{array}{l}
B_m = \left|B\right|
\\
[A, B_m, C, F] = \mathsf{sort}([A, B_m, C, F])\\
\\
\sqrt{F \cdot \frac{2}{B\_m}}
\end{array}
Initial program 19.1%
Taylor expanded in B around -inf
mul-1-negN/A
*-commutativeN/A
distribute-lft-neg-inN/A
lower-*.f64N/A
lower-neg.f64N/A
*-commutativeN/A
unpow2N/A
rem-square-sqrtN/A
lower-*.f64N/A
lower-sqrt.f64N/A
lower-sqrt.f64N/A
lower-/.f642.1
Applied rewrites2.1%
Applied rewrites2.1%
Applied rewrites2.1%
herbie shell --seed 2024340
(FPCore (A B C F)
:name "ABCF->ab-angle b"
:precision binary64
(/ (- (sqrt (* (* 2.0 (* (- (pow B 2.0) (* (* 4.0 A) C)) F)) (- (+ A C) (sqrt (+ (pow (- A C) 2.0) (pow B 2.0))))))) (- (pow B 2.0) (* (* 4.0 A) C))))