
(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 11 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 C) A (* B_m B_m))))
(if (<= B_m 2.15e-51)
(/
(sqrt (* t_0 (* (fma (/ (* B_m B_m) C) -0.5 (+ A A)) (* 2.0 F))))
(- t_0))
(if (<= B_m 1.75e+112)
(-
(sqrt
(*
(*
(/ (- (+ C A) (hypot B_m (- A C))) (fma (* C A) -4.0 (* B_m B_m)))
F)
2.0)))
(* (/ (sqrt 2.0) (- B_m)) (sqrt (* (- A (hypot B_m A)) F)))))))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 * C), A, (B_m * B_m));
double tmp;
if (B_m <= 2.15e-51) {
tmp = sqrt((t_0 * (fma(((B_m * B_m) / C), -0.5, (A + A)) * (2.0 * F)))) / -t_0;
} else if (B_m <= 1.75e+112) {
tmp = -sqrt((((((C + A) - hypot(B_m, (A - C))) / fma((C * A), -4.0, (B_m * B_m))) * F) * 2.0));
} else {
tmp = (sqrt(2.0) / -B_m) * sqrt(((A - hypot(B_m, A)) * F));
}
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 * C), A, Float64(B_m * B_m)) tmp = 0.0 if (B_m <= 2.15e-51) tmp = Float64(sqrt(Float64(t_0 * Float64(fma(Float64(Float64(B_m * B_m) / C), -0.5, Float64(A + A)) * Float64(2.0 * F)))) / Float64(-t_0)); elseif (B_m <= 1.75e+112) tmp = Float64(-sqrt(Float64(Float64(Float64(Float64(Float64(C + A) - hypot(B_m, Float64(A - C))) / fma(Float64(C * A), -4.0, Float64(B_m * B_m))) * F) * 2.0))); else tmp = Float64(Float64(sqrt(2.0) / Float64(-B_m)) * sqrt(Float64(Float64(A - hypot(B_m, A)) * F))); 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 * C), $MachinePrecision] * A + N[(B$95$m * B$95$m), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[B$95$m, 2.15e-51], N[(N[Sqrt[N[(t$95$0 * N[(N[(N[(N[(B$95$m * B$95$m), $MachinePrecision] / C), $MachinePrecision] * -0.5 + N[(A + A), $MachinePrecision]), $MachinePrecision] * N[(2.0 * F), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / (-t$95$0)), $MachinePrecision], If[LessEqual[B$95$m, 1.75e+112], (-N[Sqrt[N[(N[(N[(N[(N[(C + A), $MachinePrecision] - N[Sqrt[B$95$m ^ 2 + N[(A - C), $MachinePrecision] ^ 2], $MachinePrecision]), $MachinePrecision] / N[(N[(C * A), $MachinePrecision] * -4.0 + N[(B$95$m * B$95$m), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] * F), $MachinePrecision] * 2.0), $MachinePrecision]], $MachinePrecision]), N[(N[(N[Sqrt[2.0], $MachinePrecision] / (-B$95$m)), $MachinePrecision] * N[Sqrt[N[(N[(A - N[Sqrt[B$95$m ^ 2 + A ^ 2], $MachinePrecision]), $MachinePrecision] * F), $MachinePrecision]], $MachinePrecision]), $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 C, A, B\_m \cdot B\_m\right)\\
\mathbf{if}\;B\_m \leq 2.15 \cdot 10^{-51}:\\
\;\;\;\;\frac{\sqrt{t\_0 \cdot \left(\mathsf{fma}\left(\frac{B\_m \cdot B\_m}{C}, -0.5, A + A\right) \cdot \left(2 \cdot F\right)\right)}}{-t\_0}\\
\mathbf{elif}\;B\_m \leq 1.75 \cdot 10^{+112}:\\
\;\;\;\;-\sqrt{\left(\frac{\left(C + A\right) - \mathsf{hypot}\left(B\_m, A - C\right)}{\mathsf{fma}\left(C \cdot A, -4, B\_m \cdot B\_m\right)} \cdot F\right) \cdot 2}\\
\mathbf{else}:\\
\;\;\;\;\frac{\sqrt{2}}{-B\_m} \cdot \sqrt{\left(A - \mathsf{hypot}\left(B\_m, A\right)\right) \cdot F}\\
\end{array}
\end{array}
if B < 2.1499999999999999e-51Initial program 19.8%
Taylor expanded in C around inf
mul-1-negN/A
lower--.f64N/A
lower-neg.f6416.6
Applied rewrites16.6%
lift-/.f64N/A
lift-neg.f64N/A
distribute-frac-negN/A
distribute-neg-frac2N/A
lower-/.f64N/A
Applied rewrites16.6%
Taylor expanded in C around inf
mul-1-negN/A
lower--.f64N/A
+-commutativeN/A
lower-fma.f64N/A
lower-/.f64N/A
unpow2N/A
lower-*.f64N/A
lower-neg.f6416.8
Applied rewrites16.8%
lift-*.f64N/A
lift-*.f64N/A
associate-*r*N/A
*-commutativeN/A
lower-*.f64N/A
lower-*.f6416.9
Applied rewrites16.9%
if 2.1499999999999999e-51 < B < 1.74999999999999998e112Initial program 30.9%
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 rewrites51.5%
Applied rewrites51.8%
if 1.74999999999999998e112 < B Initial program 6.1%
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.f6444.1
Applied rewrites44.1%
Final simplification26.2%
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 C) A (* B_m B_m))))
(if (<= (pow B_m 2.0) 5e+68)
(/ (sqrt (* (+ A A) (* (* F 2.0) t_0))) (- t_0))
(* (- (sqrt 2.0)) (sqrt (* F (/ (- (/ (+ C A) B_m) 1.0) 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) {
double t_0 = fma((-4.0 * C), A, (B_m * B_m));
double tmp;
if (pow(B_m, 2.0) <= 5e+68) {
tmp = sqrt(((A + A) * ((F * 2.0) * t_0))) / -t_0;
} else {
tmp = -sqrt(2.0) * sqrt((F * ((((C + A) / B_m) - 1.0) / 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 * C), A, Float64(B_m * B_m)) tmp = 0.0 if ((B_m ^ 2.0) <= 5e+68) tmp = Float64(sqrt(Float64(Float64(A + A) * Float64(Float64(F * 2.0) * t_0))) / Float64(-t_0)); else tmp = Float64(Float64(-sqrt(2.0)) * sqrt(Float64(F * Float64(Float64(Float64(Float64(C + A) / B_m) - 1.0) / 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 * C), $MachinePrecision] * A + N[(B$95$m * B$95$m), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[N[Power[B$95$m, 2.0], $MachinePrecision], 5e+68], N[(N[Sqrt[N[(N[(A + A), $MachinePrecision] * N[(N[(F * 2.0), $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / (-t$95$0)), $MachinePrecision], N[((-N[Sqrt[2.0], $MachinePrecision]) * N[Sqrt[N[(F * N[(N[(N[(N[(C + A), $MachinePrecision] / B$95$m), $MachinePrecision] - 1.0), $MachinePrecision] / B$95$m), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $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 C, A, B\_m \cdot B\_m\right)\\
\mathbf{if}\;{B\_m}^{2} \leq 5 \cdot 10^{+68}:\\
\;\;\;\;\frac{\sqrt{\left(A + A\right) \cdot \left(\left(F \cdot 2\right) \cdot t\_0\right)}}{-t\_0}\\
\mathbf{else}:\\
\;\;\;\;\left(-\sqrt{2}\right) \cdot \sqrt{F \cdot \frac{\frac{C + A}{B\_m} - 1}{B\_m}}\\
\end{array}
\end{array}
if (pow.f64 B #s(literal 2 binary64)) < 5.0000000000000004e68Initial program 23.0%
Taylor expanded in C around inf
mul-1-negN/A
lower--.f64N/A
lower-neg.f6419.4
Applied rewrites19.4%
lift-/.f64N/A
lift-neg.f64N/A
distribute-frac-negN/A
distribute-neg-frac2N/A
lower-/.f64N/A
Applied rewrites19.4%
if 5.0000000000000004e68 < (pow.f64 B #s(literal 2 binary64)) Initial program 14.9%
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 rewrites30.0%
Taylor expanded in B around inf
Applied rewrites28.8%
Final simplification23.3%
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 (<= (pow B_m 2.0) 4e-102)
(/
(sqrt (* (* -4.0 (* A C)) (* (* F 2.0) (+ A A))))
(- (fma (* -4.0 C) A (* B_m B_m))))
(* (- (sqrt 2.0)) (sqrt (* F (/ (- (/ (+ C A) B_m) 1.0) 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) {
double tmp;
if (pow(B_m, 2.0) <= 4e-102) {
tmp = sqrt(((-4.0 * (A * C)) * ((F * 2.0) * (A + A)))) / -fma((-4.0 * C), A, (B_m * B_m));
} else {
tmp = -sqrt(2.0) * sqrt((F * ((((C + A) / B_m) - 1.0) / 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 ^ 2.0) <= 4e-102) tmp = Float64(sqrt(Float64(Float64(-4.0 * Float64(A * C)) * Float64(Float64(F * 2.0) * Float64(A + A)))) / Float64(-fma(Float64(-4.0 * C), A, Float64(B_m * B_m)))); else tmp = Float64(Float64(-sqrt(2.0)) * sqrt(Float64(F * Float64(Float64(Float64(Float64(C + A) / B_m) - 1.0) / 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[N[Power[B$95$m, 2.0], $MachinePrecision], 4e-102], N[(N[Sqrt[N[(N[(-4.0 * N[(A * C), $MachinePrecision]), $MachinePrecision] * N[(N[(F * 2.0), $MachinePrecision] * N[(A + A), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / (-N[(N[(-4.0 * C), $MachinePrecision] * A + N[(B$95$m * B$95$m), $MachinePrecision]), $MachinePrecision])), $MachinePrecision], N[((-N[Sqrt[2.0], $MachinePrecision]) * N[Sqrt[N[(F * N[(N[(N[(N[(C + A), $MachinePrecision] / B$95$m), $MachinePrecision] - 1.0), $MachinePrecision] / B$95$m), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $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}^{2} \leq 4 \cdot 10^{-102}:\\
\;\;\;\;\frac{\sqrt{\left(-4 \cdot \left(A \cdot C\right)\right) \cdot \left(\left(F \cdot 2\right) \cdot \left(A + A\right)\right)}}{-\mathsf{fma}\left(-4 \cdot C, A, B\_m \cdot B\_m\right)}\\
\mathbf{else}:\\
\;\;\;\;\left(-\sqrt{2}\right) \cdot \sqrt{F \cdot \frac{\frac{C + A}{B\_m} - 1}{B\_m}}\\
\end{array}
\end{array}
if (pow.f64 B #s(literal 2 binary64)) < 3.99999999999999973e-102Initial program 20.9%
Taylor expanded in C around inf
mul-1-negN/A
lower--.f64N/A
lower-neg.f6424.1
Applied rewrites24.1%
lift-/.f64N/A
lift-neg.f64N/A
distribute-frac-negN/A
distribute-neg-frac2N/A
lower-/.f64N/A
Applied rewrites24.1%
lift-*.f64N/A
lift-*.f64N/A
associate-*r*N/A
lift-fma.f64N/A
lift-*.f64N/A
associate-*r*N/A
lift-*.f64N/A
lift-fma.f64N/A
*-commutativeN/A
lower-*.f64N/A
Applied rewrites24.2%
Taylor expanded in A around inf
lower-*.f64N/A
lower-*.f6423.5
Applied rewrites23.5%
if 3.99999999999999973e-102 < (pow.f64 B #s(literal 2 binary64)) Initial program 18.6%
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 rewrites32.9%
Taylor expanded in B around inf
Applied rewrites24.5%
Final simplification24.0%
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 (- (sqrt 2.0))))
(if (<= (pow B_m 2.0) 2e+57)
(* t_0 (sqrt (* F (/ -0.5 C))))
(* t_0 (sqrt (* F (/ (- (/ (+ C A) B_m) 1.0) 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) {
double t_0 = -sqrt(2.0);
double tmp;
if (pow(B_m, 2.0) <= 2e+57) {
tmp = t_0 * sqrt((F * (-0.5 / C)));
} else {
tmp = t_0 * sqrt((F * ((((C + A) / B_m) - 1.0) / B_m)));
}
return tmp;
}
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
real(8) :: t_0
real(8) :: tmp
t_0 = -sqrt(2.0d0)
if ((b_m ** 2.0d0) <= 2d+57) then
tmp = t_0 * sqrt((f * ((-0.5d0) / c)))
else
tmp = t_0 * sqrt((f * ((((c + a) / b_m) - 1.0d0) / b_m)))
end if
code = tmp
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) {
double t_0 = -Math.sqrt(2.0);
double tmp;
if (Math.pow(B_m, 2.0) <= 2e+57) {
tmp = t_0 * Math.sqrt((F * (-0.5 / C)));
} else {
tmp = t_0 * Math.sqrt((F * ((((C + A) / B_m) - 1.0) / B_m)));
}
return tmp;
}
B_m = math.fabs(B) [A, B_m, C, F] = sort([A, B_m, C, F]) def code(A, B_m, C, F): t_0 = -math.sqrt(2.0) tmp = 0 if math.pow(B_m, 2.0) <= 2e+57: tmp = t_0 * math.sqrt((F * (-0.5 / C))) else: tmp = t_0 * math.sqrt((F * ((((C + A) / B_m) - 1.0) / 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 = Float64(-sqrt(2.0)) tmp = 0.0 if ((B_m ^ 2.0) <= 2e+57) tmp = Float64(t_0 * sqrt(Float64(F * Float64(-0.5 / C)))); else tmp = Float64(t_0 * sqrt(Float64(F * Float64(Float64(Float64(Float64(C + A) / B_m) - 1.0) / B_m)))); end return tmp end
B_m = abs(B);
A, B_m, C, F = num2cell(sort([A, B_m, C, F])){:}
function tmp_2 = code(A, B_m, C, F)
t_0 = -sqrt(2.0);
tmp = 0.0;
if ((B_m ^ 2.0) <= 2e+57)
tmp = t_0 * sqrt((F * (-0.5 / C)));
else
tmp = t_0 * sqrt((F * ((((C + A) / B_m) - 1.0) / B_m)));
end
tmp_2 = 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[Sqrt[2.0], $MachinePrecision])}, If[LessEqual[N[Power[B$95$m, 2.0], $MachinePrecision], 2e+57], N[(t$95$0 * N[Sqrt[N[(F * N[(-0.5 / C), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision], N[(t$95$0 * N[Sqrt[N[(F * N[(N[(N[(N[(C + A), $MachinePrecision] / B$95$m), $MachinePrecision] - 1.0), $MachinePrecision] / B$95$m), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $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 := -\sqrt{2}\\
\mathbf{if}\;{B\_m}^{2} \leq 2 \cdot 10^{+57}:\\
\;\;\;\;t\_0 \cdot \sqrt{F \cdot \frac{-0.5}{C}}\\
\mathbf{else}:\\
\;\;\;\;t\_0 \cdot \sqrt{F \cdot \frac{\frac{C + A}{B\_m} - 1}{B\_m}}\\
\end{array}
\end{array}
if (pow.f64 B #s(literal 2 binary64)) < 2.0000000000000001e57Initial program 22.6%
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 rewrites30.3%
Taylor expanded in A around -inf
Applied rewrites16.7%
if 2.0000000000000001e57 < (pow.f64 B #s(literal 2 binary64)) Initial program 15.5%
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 rewrites30.4%
Taylor expanded in B around inf
Applied rewrites28.5%
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 (- A (hypot B_m A))) (t_1 (fma (* -4.0 C) A (* B_m B_m))))
(if (<= B_m 2.15e-51)
(/
(sqrt (* t_1 (* (fma (/ (* B_m B_m) C) -0.5 (+ A A)) (* 2.0 F))))
(- t_1))
(if (<= B_m 1.75e+112)
(* (- (sqrt 2.0)) (sqrt (* F (/ t_0 (* B_m B_m)))))
(* (/ (sqrt 2.0) (- B_m)) (sqrt (* t_0 F)))))))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 = A - hypot(B_m, A);
double t_1 = fma((-4.0 * C), A, (B_m * B_m));
double tmp;
if (B_m <= 2.15e-51) {
tmp = sqrt((t_1 * (fma(((B_m * B_m) / C), -0.5, (A + A)) * (2.0 * F)))) / -t_1;
} else if (B_m <= 1.75e+112) {
tmp = -sqrt(2.0) * sqrt((F * (t_0 / (B_m * B_m))));
} else {
tmp = (sqrt(2.0) / -B_m) * sqrt((t_0 * F));
}
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 = Float64(A - hypot(B_m, A)) t_1 = fma(Float64(-4.0 * C), A, Float64(B_m * B_m)) tmp = 0.0 if (B_m <= 2.15e-51) tmp = Float64(sqrt(Float64(t_1 * Float64(fma(Float64(Float64(B_m * B_m) / C), -0.5, Float64(A + A)) * Float64(2.0 * F)))) / Float64(-t_1)); elseif (B_m <= 1.75e+112) tmp = Float64(Float64(-sqrt(2.0)) * sqrt(Float64(F * Float64(t_0 / Float64(B_m * B_m))))); else tmp = Float64(Float64(sqrt(2.0) / Float64(-B_m)) * sqrt(Float64(t_0 * F))); 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[(A - N[Sqrt[B$95$m ^ 2 + A ^ 2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[(N[(-4.0 * C), $MachinePrecision] * A + N[(B$95$m * B$95$m), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[B$95$m, 2.15e-51], N[(N[Sqrt[N[(t$95$1 * N[(N[(N[(N[(B$95$m * B$95$m), $MachinePrecision] / C), $MachinePrecision] * -0.5 + N[(A + A), $MachinePrecision]), $MachinePrecision] * N[(2.0 * F), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / (-t$95$1)), $MachinePrecision], If[LessEqual[B$95$m, 1.75e+112], N[((-N[Sqrt[2.0], $MachinePrecision]) * N[Sqrt[N[(F * N[(t$95$0 / N[(B$95$m * B$95$m), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision], N[(N[(N[Sqrt[2.0], $MachinePrecision] / (-B$95$m)), $MachinePrecision] * N[Sqrt[N[(t$95$0 * F), $MachinePrecision]], $MachinePrecision]), $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 := A - \mathsf{hypot}\left(B\_m, A\right)\\
t_1 := \mathsf{fma}\left(-4 \cdot C, A, B\_m \cdot B\_m\right)\\
\mathbf{if}\;B\_m \leq 2.15 \cdot 10^{-51}:\\
\;\;\;\;\frac{\sqrt{t\_1 \cdot \left(\mathsf{fma}\left(\frac{B\_m \cdot B\_m}{C}, -0.5, A + A\right) \cdot \left(2 \cdot F\right)\right)}}{-t\_1}\\
\mathbf{elif}\;B\_m \leq 1.75 \cdot 10^{+112}:\\
\;\;\;\;\left(-\sqrt{2}\right) \cdot \sqrt{F \cdot \frac{t\_0}{B\_m \cdot B\_m}}\\
\mathbf{else}:\\
\;\;\;\;\frac{\sqrt{2}}{-B\_m} \cdot \sqrt{t\_0 \cdot F}\\
\end{array}
\end{array}
if B < 2.1499999999999999e-51Initial program 19.8%
Taylor expanded in C around inf
mul-1-negN/A
lower--.f64N/A
lower-neg.f6416.6
Applied rewrites16.6%
lift-/.f64N/A
lift-neg.f64N/A
distribute-frac-negN/A
distribute-neg-frac2N/A
lower-/.f64N/A
Applied rewrites16.6%
Taylor expanded in C around inf
mul-1-negN/A
lower--.f64N/A
+-commutativeN/A
lower-fma.f64N/A
lower-/.f64N/A
unpow2N/A
lower-*.f64N/A
lower-neg.f6416.8
Applied rewrites16.8%
lift-*.f64N/A
lift-*.f64N/A
associate-*r*N/A
*-commutativeN/A
lower-*.f64N/A
lower-*.f6416.9
Applied rewrites16.9%
if 2.1499999999999999e-51 < B < 1.74999999999999998e112Initial program 30.9%
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 rewrites51.5%
Taylor expanded in C around 0
Applied rewrites42.8%
if 1.74999999999999998e112 < B Initial program 6.1%
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.f6444.1
Applied rewrites44.1%
Final simplification24.7%
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
(let* ((t_0 (fma (* -4.0 C) A (* B_m B_m))))
(if (<= B_m 2.15e-51)
(/
(sqrt (* t_0 (* (fma (/ (* B_m B_m) C) -0.5 (+ A A)) (* 2.0 F))))
(- t_0))
(* (/ (sqrt 2.0) (- B_m)) (sqrt (* (- A (hypot B_m A)) F))))))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 * C), A, (B_m * B_m));
double tmp;
if (B_m <= 2.15e-51) {
tmp = sqrt((t_0 * (fma(((B_m * B_m) / C), -0.5, (A + A)) * (2.0 * F)))) / -t_0;
} else {
tmp = (sqrt(2.0) / -B_m) * sqrt(((A - hypot(B_m, A)) * F));
}
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 * C), A, Float64(B_m * B_m)) tmp = 0.0 if (B_m <= 2.15e-51) tmp = Float64(sqrt(Float64(t_0 * Float64(fma(Float64(Float64(B_m * B_m) / C), -0.5, Float64(A + A)) * Float64(2.0 * F)))) / Float64(-t_0)); else tmp = Float64(Float64(sqrt(2.0) / Float64(-B_m)) * sqrt(Float64(Float64(A - hypot(B_m, A)) * F))); 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 * C), $MachinePrecision] * A + N[(B$95$m * B$95$m), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[B$95$m, 2.15e-51], N[(N[Sqrt[N[(t$95$0 * N[(N[(N[(N[(B$95$m * B$95$m), $MachinePrecision] / C), $MachinePrecision] * -0.5 + N[(A + A), $MachinePrecision]), $MachinePrecision] * N[(2.0 * F), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / (-t$95$0)), $MachinePrecision], N[(N[(N[Sqrt[2.0], $MachinePrecision] / (-B$95$m)), $MachinePrecision] * N[Sqrt[N[(N[(A - N[Sqrt[B$95$m ^ 2 + A ^ 2], $MachinePrecision]), $MachinePrecision] * F), $MachinePrecision]], $MachinePrecision]), $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 C, A, B\_m \cdot B\_m\right)\\
\mathbf{if}\;B\_m \leq 2.15 \cdot 10^{-51}:\\
\;\;\;\;\frac{\sqrt{t\_0 \cdot \left(\mathsf{fma}\left(\frac{B\_m \cdot B\_m}{C}, -0.5, A + A\right) \cdot \left(2 \cdot F\right)\right)}}{-t\_0}\\
\mathbf{else}:\\
\;\;\;\;\frac{\sqrt{2}}{-B\_m} \cdot \sqrt{\left(A - \mathsf{hypot}\left(B\_m, A\right)\right) \cdot F}\\
\end{array}
\end{array}
if B < 2.1499999999999999e-51Initial program 19.8%
Taylor expanded in C around inf
mul-1-negN/A
lower--.f64N/A
lower-neg.f6416.6
Applied rewrites16.6%
lift-/.f64N/A
lift-neg.f64N/A
distribute-frac-negN/A
distribute-neg-frac2N/A
lower-/.f64N/A
Applied rewrites16.6%
Taylor expanded in C around inf
mul-1-negN/A
lower--.f64N/A
+-commutativeN/A
lower-fma.f64N/A
lower-/.f64N/A
unpow2N/A
lower-*.f64N/A
lower-neg.f6416.8
Applied rewrites16.8%
lift-*.f64N/A
lift-*.f64N/A
associate-*r*N/A
*-commutativeN/A
lower-*.f64N/A
lower-*.f6416.9
Applied rewrites16.9%
if 2.1499999999999999e-51 < B Initial program 19.2%
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.f6439.6
Applied rewrites39.6%
Final simplification23.6%
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
(let* ((t_0 (- (sqrt 2.0))))
(if (<= (pow B_m 2.0) 2e+57)
(* t_0 (sqrt (* F (/ -0.5 C))))
(* t_0 (sqrt (* F (/ -1.0 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) {
double t_0 = -sqrt(2.0);
double tmp;
if (pow(B_m, 2.0) <= 2e+57) {
tmp = t_0 * sqrt((F * (-0.5 / C)));
} else {
tmp = t_0 * sqrt((F * (-1.0 / B_m)));
}
return tmp;
}
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
real(8) :: t_0
real(8) :: tmp
t_0 = -sqrt(2.0d0)
if ((b_m ** 2.0d0) <= 2d+57) then
tmp = t_0 * sqrt((f * ((-0.5d0) / c)))
else
tmp = t_0 * sqrt((f * ((-1.0d0) / b_m)))
end if
code = tmp
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) {
double t_0 = -Math.sqrt(2.0);
double tmp;
if (Math.pow(B_m, 2.0) <= 2e+57) {
tmp = t_0 * Math.sqrt((F * (-0.5 / C)));
} else {
tmp = t_0 * Math.sqrt((F * (-1.0 / B_m)));
}
return tmp;
}
B_m = math.fabs(B) [A, B_m, C, F] = sort([A, B_m, C, F]) def code(A, B_m, C, F): t_0 = -math.sqrt(2.0) tmp = 0 if math.pow(B_m, 2.0) <= 2e+57: tmp = t_0 * math.sqrt((F * (-0.5 / C))) else: tmp = t_0 * math.sqrt((F * (-1.0 / 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 = Float64(-sqrt(2.0)) tmp = 0.0 if ((B_m ^ 2.0) <= 2e+57) tmp = Float64(t_0 * sqrt(Float64(F * Float64(-0.5 / C)))); else tmp = Float64(t_0 * sqrt(Float64(F * Float64(-1.0 / B_m)))); end return tmp end
B_m = abs(B);
A, B_m, C, F = num2cell(sort([A, B_m, C, F])){:}
function tmp_2 = code(A, B_m, C, F)
t_0 = -sqrt(2.0);
tmp = 0.0;
if ((B_m ^ 2.0) <= 2e+57)
tmp = t_0 * sqrt((F * (-0.5 / C)));
else
tmp = t_0 * sqrt((F * (-1.0 / B_m)));
end
tmp_2 = 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[Sqrt[2.0], $MachinePrecision])}, If[LessEqual[N[Power[B$95$m, 2.0], $MachinePrecision], 2e+57], N[(t$95$0 * N[Sqrt[N[(F * N[(-0.5 / C), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision], N[(t$95$0 * N[Sqrt[N[(F * N[(-1.0 / B$95$m), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $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 := -\sqrt{2}\\
\mathbf{if}\;{B\_m}^{2} \leq 2 \cdot 10^{+57}:\\
\;\;\;\;t\_0 \cdot \sqrt{F \cdot \frac{-0.5}{C}}\\
\mathbf{else}:\\
\;\;\;\;t\_0 \cdot \sqrt{F \cdot \frac{-1}{B\_m}}\\
\end{array}
\end{array}
if (pow.f64 B #s(literal 2 binary64)) < 2.0000000000000001e57Initial program 22.6%
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 rewrites30.3%
Taylor expanded in A around -inf
Applied rewrites16.7%
if 2.0000000000000001e57 < (pow.f64 B #s(literal 2 binary64)) Initial program 15.5%
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 rewrites30.4%
Taylor expanded in B around inf
Applied rewrites26.6%
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 2.0)) (sqrt (* F (/ -1.0 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(2.0) * sqrt((F * (-1.0 / 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(2.0d0) * sqrt((f * ((-1.0d0) / 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(2.0) * Math.sqrt((F * (-1.0 / 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(2.0) * math.sqrt((F * (-1.0 / 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 Float64(Float64(-sqrt(2.0)) * sqrt(Float64(F * Float64(-1.0 / 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(2.0) * sqrt((F * (-1.0 / 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[((-N[Sqrt[2.0], $MachinePrecision]) * N[Sqrt[N[(F * N[(-1.0 / B$95$m), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
B_m = \left|B\right|
\\
[A, B_m, C, F] = \mathsf{sort}([A, B_m, C, F])\\
\\
\left(-\sqrt{2}\right) \cdot \sqrt{F \cdot \frac{-1}{B\_m}}
\end{array}
Initial program 19.6%
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 rewrites30.3%
Taylor expanded in B around inf
Applied rewrites14.2%
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 (sqrt (/ (fma F B_m (* B_m 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) {
return sqrt((fma(F, B_m, (B_m * F)) / (B_m * 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(fma(F, B_m, Float64(B_m * F)) / Float64(B_m * 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[(N[(F * B$95$m + N[(B$95$m * F), $MachinePrecision]), $MachinePrecision] / N[(B$95$m * 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{\frac{\mathsf{fma}\left(F, B\_m, B\_m \cdot F\right)}{B\_m \cdot B\_m}}
\end{array}
Initial program 19.6%
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-/.f642.0
Applied rewrites2.0%
Applied rewrites2.0%
Applied rewrites1.9%
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 B_m) 2.0)))
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 / B_m) * 2.0));
}
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 / b_m) * 2.0d0))
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 / B_m) * 2.0));
}
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 / B_m) * 2.0))
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(Float64(F / B_m) * 2.0)) 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 / B_m) * 2.0));
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[(N[(F / B$95$m), $MachinePrecision] * 2.0), $MachinePrecision]], $MachinePrecision]
\begin{array}{l}
B_m = \left|B\right|
\\
[A, B_m, C, F] = \mathsf{sort}([A, B_m, C, F])\\
\\
\sqrt{\frac{F}{B\_m} \cdot 2}
\end{array}
Initial program 19.6%
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-/.f642.0
Applied rewrites2.0%
Applied rewrites2.0%
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 (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 19.6%
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-/.f642.0
Applied rewrites2.0%
Applied rewrites2.0%
Applied rewrites2.0%
herbie shell --seed 2024337
(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))))