
(FPCore (x y z t) :precision binary64 (* (* (- (* x 0.5) y) (sqrt (* z 2.0))) (exp (/ (* t t) 2.0))))
double code(double x, double y, double z, double t) {
return (((x * 0.5) - y) * sqrt((z * 2.0))) * exp(((t * t) / 2.0));
}
real(8) function code(x, y, z, t)
real(8), intent (in) :: x
real(8), intent (in) :: y
real(8), intent (in) :: z
real(8), intent (in) :: t
code = (((x * 0.5d0) - y) * sqrt((z * 2.0d0))) * exp(((t * t) / 2.0d0))
end function
public static double code(double x, double y, double z, double t) {
return (((x * 0.5) - y) * Math.sqrt((z * 2.0))) * Math.exp(((t * t) / 2.0));
}
def code(x, y, z, t): return (((x * 0.5) - y) * math.sqrt((z * 2.0))) * math.exp(((t * t) / 2.0))
function code(x, y, z, t) return Float64(Float64(Float64(Float64(x * 0.5) - y) * sqrt(Float64(z * 2.0))) * exp(Float64(Float64(t * t) / 2.0))) end
function tmp = code(x, y, z, t) tmp = (((x * 0.5) - y) * sqrt((z * 2.0))) * exp(((t * t) / 2.0)); end
code[x_, y_, z_, t_] := N[(N[(N[(N[(x * 0.5), $MachinePrecision] - y), $MachinePrecision] * N[Sqrt[N[(z * 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] * N[Exp[N[(N[(t * t), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\left(\left(x \cdot 0.5 - y\right) \cdot \sqrt{z \cdot 2}\right) \cdot e^{\frac{t \cdot t}{2}}
\end{array}
Sampling outcomes in binary64 precision:
Herbie found 12 alternatives:
| Alternative | Accuracy | Speedup |
|---|
(FPCore (x y z t) :precision binary64 (* (* (- (* x 0.5) y) (sqrt (* z 2.0))) (exp (/ (* t t) 2.0))))
double code(double x, double y, double z, double t) {
return (((x * 0.5) - y) * sqrt((z * 2.0))) * exp(((t * t) / 2.0));
}
real(8) function code(x, y, z, t)
real(8), intent (in) :: x
real(8), intent (in) :: y
real(8), intent (in) :: z
real(8), intent (in) :: t
code = (((x * 0.5d0) - y) * sqrt((z * 2.0d0))) * exp(((t * t) / 2.0d0))
end function
public static double code(double x, double y, double z, double t) {
return (((x * 0.5) - y) * Math.sqrt((z * 2.0))) * Math.exp(((t * t) / 2.0));
}
def code(x, y, z, t): return (((x * 0.5) - y) * math.sqrt((z * 2.0))) * math.exp(((t * t) / 2.0))
function code(x, y, z, t) return Float64(Float64(Float64(Float64(x * 0.5) - y) * sqrt(Float64(z * 2.0))) * exp(Float64(Float64(t * t) / 2.0))) end
function tmp = code(x, y, z, t) tmp = (((x * 0.5) - y) * sqrt((z * 2.0))) * exp(((t * t) / 2.0)); end
code[x_, y_, z_, t_] := N[(N[(N[(N[(x * 0.5), $MachinePrecision] - y), $MachinePrecision] * N[Sqrt[N[(z * 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] * N[Exp[N[(N[(t * t), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\left(\left(x \cdot 0.5 - y\right) \cdot \sqrt{z \cdot 2}\right) \cdot e^{\frac{t \cdot t}{2}}
\end{array}
(FPCore (x y z t) :precision binary64 (* (- (* x 0.5) y) (sqrt (* z (* 2.0 (pow (exp t) t))))))
double code(double x, double y, double z, double t) {
return ((x * 0.5) - y) * sqrt((z * (2.0 * pow(exp(t), t))));
}
real(8) function code(x, y, z, t)
real(8), intent (in) :: x
real(8), intent (in) :: y
real(8), intent (in) :: z
real(8), intent (in) :: t
code = ((x * 0.5d0) - y) * sqrt((z * (2.0d0 * (exp(t) ** t))))
end function
public static double code(double x, double y, double z, double t) {
return ((x * 0.5) - y) * Math.sqrt((z * (2.0 * Math.pow(Math.exp(t), t))));
}
def code(x, y, z, t): return ((x * 0.5) - y) * math.sqrt((z * (2.0 * math.pow(math.exp(t), t))))
function code(x, y, z, t) return Float64(Float64(Float64(x * 0.5) - y) * sqrt(Float64(z * Float64(2.0 * (exp(t) ^ t))))) end
function tmp = code(x, y, z, t) tmp = ((x * 0.5) - y) * sqrt((z * (2.0 * (exp(t) ^ t)))); end
code[x_, y_, z_, t_] := N[(N[(N[(x * 0.5), $MachinePrecision] - y), $MachinePrecision] * N[Sqrt[N[(z * N[(2.0 * N[Power[N[Exp[t], $MachinePrecision], t], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\left(x \cdot 0.5 - y\right) \cdot \sqrt{z \cdot \left(2 \cdot {\left(e^{t}\right)}^{t}\right)}
\end{array}
Initial program 99.8%
associate-*l*N/A
*-lowering-*.f64N/A
--lowering--.f64N/A
*-lowering-*.f64N/A
exp-sqrtN/A
sqrt-unprodN/A
sqrt-lowering-sqrt.f64N/A
associate-*l*N/A
*-lowering-*.f64N/A
*-lowering-*.f64N/A
exp-lowering-exp.f64N/A
*-lowering-*.f6499.8%
Applied egg-rr99.8%
exp-prodN/A
pow-lowering-pow.f64N/A
exp-lowering-exp.f6499.8%
Applied egg-rr99.8%
(FPCore (x y z t) :precision binary64 (* (- (* x 0.5) y) (sqrt (* z (* 2.0 (exp (* t t)))))))
double code(double x, double y, double z, double t) {
return ((x * 0.5) - y) * sqrt((z * (2.0 * exp((t * t)))));
}
real(8) function code(x, y, z, t)
real(8), intent (in) :: x
real(8), intent (in) :: y
real(8), intent (in) :: z
real(8), intent (in) :: t
code = ((x * 0.5d0) - y) * sqrt((z * (2.0d0 * exp((t * t)))))
end function
public static double code(double x, double y, double z, double t) {
return ((x * 0.5) - y) * Math.sqrt((z * (2.0 * Math.exp((t * t)))));
}
def code(x, y, z, t): return ((x * 0.5) - y) * math.sqrt((z * (2.0 * math.exp((t * t)))))
function code(x, y, z, t) return Float64(Float64(Float64(x * 0.5) - y) * sqrt(Float64(z * Float64(2.0 * exp(Float64(t * t)))))) end
function tmp = code(x, y, z, t) tmp = ((x * 0.5) - y) * sqrt((z * (2.0 * exp((t * t))))); end
code[x_, y_, z_, t_] := N[(N[(N[(x * 0.5), $MachinePrecision] - y), $MachinePrecision] * N[Sqrt[N[(z * N[(2.0 * N[Exp[N[(t * t), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\left(x \cdot 0.5 - y\right) \cdot \sqrt{z \cdot \left(2 \cdot e^{t \cdot t}\right)}
\end{array}
Initial program 99.8%
associate-*l*N/A
*-lowering-*.f64N/A
--lowering--.f64N/A
*-lowering-*.f64N/A
exp-sqrtN/A
sqrt-unprodN/A
sqrt-lowering-sqrt.f64N/A
associate-*l*N/A
*-lowering-*.f64N/A
*-lowering-*.f64N/A
exp-lowering-exp.f64N/A
*-lowering-*.f6499.8%
Applied egg-rr99.8%
(FPCore (x y z t)
:precision binary64
(*
(*
(- (* x 0.5) y)
(+
1.0
(*
t
(* t (+ 0.5 (* (* t t) (+ 0.125 (* t (* t 0.020833333333333332)))))))))
(sqrt (* z 2.0))))
double code(double x, double y, double z, double t) {
return (((x * 0.5) - y) * (1.0 + (t * (t * (0.5 + ((t * t) * (0.125 + (t * (t * 0.020833333333333332))))))))) * sqrt((z * 2.0));
}
real(8) function code(x, y, z, t)
real(8), intent (in) :: x
real(8), intent (in) :: y
real(8), intent (in) :: z
real(8), intent (in) :: t
code = (((x * 0.5d0) - y) * (1.0d0 + (t * (t * (0.5d0 + ((t * t) * (0.125d0 + (t * (t * 0.020833333333333332d0))))))))) * sqrt((z * 2.0d0))
end function
public static double code(double x, double y, double z, double t) {
return (((x * 0.5) - y) * (1.0 + (t * (t * (0.5 + ((t * t) * (0.125 + (t * (t * 0.020833333333333332))))))))) * Math.sqrt((z * 2.0));
}
def code(x, y, z, t): return (((x * 0.5) - y) * (1.0 + (t * (t * (0.5 + ((t * t) * (0.125 + (t * (t * 0.020833333333333332))))))))) * math.sqrt((z * 2.0))
function code(x, y, z, t) return Float64(Float64(Float64(Float64(x * 0.5) - y) * Float64(1.0 + Float64(t * Float64(t * Float64(0.5 + Float64(Float64(t * t) * Float64(0.125 + Float64(t * Float64(t * 0.020833333333333332))))))))) * sqrt(Float64(z * 2.0))) end
function tmp = code(x, y, z, t) tmp = (((x * 0.5) - y) * (1.0 + (t * (t * (0.5 + ((t * t) * (0.125 + (t * (t * 0.020833333333333332))))))))) * sqrt((z * 2.0)); end
code[x_, y_, z_, t_] := N[(N[(N[(N[(x * 0.5), $MachinePrecision] - y), $MachinePrecision] * N[(1.0 + N[(t * N[(t * N[(0.5 + N[(N[(t * t), $MachinePrecision] * N[(0.125 + N[(t * N[(t * 0.020833333333333332), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] * N[Sqrt[N[(z * 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\left(\left(x \cdot 0.5 - y\right) \cdot \left(1 + t \cdot \left(t \cdot \left(0.5 + \left(t \cdot t\right) \cdot \left(0.125 + t \cdot \left(t \cdot 0.020833333333333332\right)\right)\right)\right)\right)\right) \cdot \sqrt{z \cdot 2}
\end{array}
Initial program 99.8%
Taylor expanded in t around 0
+-lowering-+.f64N/A
*-lowering-*.f64N/A
unpow2N/A
*-lowering-*.f64N/A
+-lowering-+.f64N/A
*-lowering-*.f64N/A
unpow2N/A
*-lowering-*.f64N/A
+-lowering-+.f64N/A
unpow2N/A
associate-*r*N/A
*-commutativeN/A
*-lowering-*.f64N/A
*-commutativeN/A
*-lowering-*.f6496.6%
Simplified96.6%
flip--N/A
difference-of-squaresN/A
flip3-+N/A
div-invN/A
unpow-prod-downN/A
cube-unmultN/A
metadata-evalN/A
cube-unmultN/A
times-fracN/A
*-lowering-*.f64N/A
Applied egg-rr27.4%
Applied egg-rr97.0%
Final simplification97.0%
(FPCore (x y z t) :precision binary64 (* (* (- (* x 0.5) y) (sqrt (* z 2.0))) (+ 1.0 (* (* t t) (+ 0.5 (* t (* t 0.125)))))))
double code(double x, double y, double z, double t) {
return (((x * 0.5) - y) * sqrt((z * 2.0))) * (1.0 + ((t * t) * (0.5 + (t * (t * 0.125)))));
}
real(8) function code(x, y, z, t)
real(8), intent (in) :: x
real(8), intent (in) :: y
real(8), intent (in) :: z
real(8), intent (in) :: t
code = (((x * 0.5d0) - y) * sqrt((z * 2.0d0))) * (1.0d0 + ((t * t) * (0.5d0 + (t * (t * 0.125d0)))))
end function
public static double code(double x, double y, double z, double t) {
return (((x * 0.5) - y) * Math.sqrt((z * 2.0))) * (1.0 + ((t * t) * (0.5 + (t * (t * 0.125)))));
}
def code(x, y, z, t): return (((x * 0.5) - y) * math.sqrt((z * 2.0))) * (1.0 + ((t * t) * (0.5 + (t * (t * 0.125)))))
function code(x, y, z, t) return Float64(Float64(Float64(Float64(x * 0.5) - y) * sqrt(Float64(z * 2.0))) * Float64(1.0 + Float64(Float64(t * t) * Float64(0.5 + Float64(t * Float64(t * 0.125)))))) end
function tmp = code(x, y, z, t) tmp = (((x * 0.5) - y) * sqrt((z * 2.0))) * (1.0 + ((t * t) * (0.5 + (t * (t * 0.125))))); end
code[x_, y_, z_, t_] := N[(N[(N[(N[(x * 0.5), $MachinePrecision] - y), $MachinePrecision] * N[Sqrt[N[(z * 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] * N[(1.0 + N[(N[(t * t), $MachinePrecision] * N[(0.5 + N[(t * N[(t * 0.125), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\left(\left(x \cdot 0.5 - y\right) \cdot \sqrt{z \cdot 2}\right) \cdot \left(1 + \left(t \cdot t\right) \cdot \left(0.5 + t \cdot \left(t \cdot 0.125\right)\right)\right)
\end{array}
Initial program 99.8%
Taylor expanded in t around 0
+-lowering-+.f64N/A
*-lowering-*.f64N/A
unpow2N/A
*-lowering-*.f64N/A
+-lowering-+.f64N/A
*-commutativeN/A
unpow2N/A
associate-*l*N/A
*-lowering-*.f64N/A
*-lowering-*.f6494.4%
Simplified94.4%
(FPCore (x y z t) :precision binary64 (* (- (* x 0.5) y) (sqrt (+ (* z 2.0) (* (* t t) (* z (+ 2.0 (* t t))))))))
double code(double x, double y, double z, double t) {
return ((x * 0.5) - y) * sqrt(((z * 2.0) + ((t * t) * (z * (2.0 + (t * t))))));
}
real(8) function code(x, y, z, t)
real(8), intent (in) :: x
real(8), intent (in) :: y
real(8), intent (in) :: z
real(8), intent (in) :: t
code = ((x * 0.5d0) - y) * sqrt(((z * 2.0d0) + ((t * t) * (z * (2.0d0 + (t * t))))))
end function
public static double code(double x, double y, double z, double t) {
return ((x * 0.5) - y) * Math.sqrt(((z * 2.0) + ((t * t) * (z * (2.0 + (t * t))))));
}
def code(x, y, z, t): return ((x * 0.5) - y) * math.sqrt(((z * 2.0) + ((t * t) * (z * (2.0 + (t * t))))))
function code(x, y, z, t) return Float64(Float64(Float64(x * 0.5) - y) * sqrt(Float64(Float64(z * 2.0) + Float64(Float64(t * t) * Float64(z * Float64(2.0 + Float64(t * t))))))) end
function tmp = code(x, y, z, t) tmp = ((x * 0.5) - y) * sqrt(((z * 2.0) + ((t * t) * (z * (2.0 + (t * t)))))); end
code[x_, y_, z_, t_] := N[(N[(N[(x * 0.5), $MachinePrecision] - y), $MachinePrecision] * N[Sqrt[N[(N[(z * 2.0), $MachinePrecision] + N[(N[(t * t), $MachinePrecision] * N[(z * N[(2.0 + N[(t * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\left(x \cdot 0.5 - y\right) \cdot \sqrt{z \cdot 2 + \left(t \cdot t\right) \cdot \left(z \cdot \left(2 + t \cdot t\right)\right)}
\end{array}
Initial program 99.8%
associate-*l*N/A
*-lowering-*.f64N/A
--lowering--.f64N/A
*-lowering-*.f64N/A
exp-sqrtN/A
sqrt-unprodN/A
sqrt-lowering-sqrt.f64N/A
associate-*l*N/A
*-lowering-*.f64N/A
*-lowering-*.f64N/A
exp-lowering-exp.f64N/A
*-lowering-*.f6499.8%
Applied egg-rr99.8%
Taylor expanded in t around 0
+-lowering-+.f64N/A
*-lowering-*.f64N/A
*-lowering-*.f64N/A
unpow2N/A
*-lowering-*.f64N/A
distribute-rgt-outN/A
*-lowering-*.f64N/A
+-lowering-+.f64N/A
unpow2N/A
*-lowering-*.f6491.4%
Simplified91.4%
Final simplification91.4%
(FPCore (x y z t) :precision binary64 (* (sqrt (* z 2.0)) (- (* 0.5 (+ x (* (- (* x 0.5) y) (* t t)))) y)))
double code(double x, double y, double z, double t) {
return sqrt((z * 2.0)) * ((0.5 * (x + (((x * 0.5) - y) * (t * t)))) - y);
}
real(8) function code(x, y, z, t)
real(8), intent (in) :: x
real(8), intent (in) :: y
real(8), intent (in) :: z
real(8), intent (in) :: t
code = sqrt((z * 2.0d0)) * ((0.5d0 * (x + (((x * 0.5d0) - y) * (t * t)))) - y)
end function
public static double code(double x, double y, double z, double t) {
return Math.sqrt((z * 2.0)) * ((0.5 * (x + (((x * 0.5) - y) * (t * t)))) - y);
}
def code(x, y, z, t): return math.sqrt((z * 2.0)) * ((0.5 * (x + (((x * 0.5) - y) * (t * t)))) - y)
function code(x, y, z, t) return Float64(sqrt(Float64(z * 2.0)) * Float64(Float64(0.5 * Float64(x + Float64(Float64(Float64(x * 0.5) - y) * Float64(t * t)))) - y)) end
function tmp = code(x, y, z, t) tmp = sqrt((z * 2.0)) * ((0.5 * (x + (((x * 0.5) - y) * (t * t)))) - y); end
code[x_, y_, z_, t_] := N[(N[Sqrt[N[(z * 2.0), $MachinePrecision]], $MachinePrecision] * N[(N[(0.5 * N[(x + N[(N[(N[(x * 0.5), $MachinePrecision] - y), $MachinePrecision] * N[(t * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - y), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\sqrt{z \cdot 2} \cdot \left(0.5 \cdot \left(x + \left(x \cdot 0.5 - y\right) \cdot \left(t \cdot t\right)\right) - y\right)
\end{array}
Initial program 99.8%
Taylor expanded in t around 0
+-lowering-+.f64N/A
*-lowering-*.f64N/A
unpow2N/A
*-lowering-*.f64N/A
+-lowering-+.f64N/A
*-lowering-*.f64N/A
unpow2N/A
*-lowering-*.f64N/A
+-lowering-+.f64N/A
unpow2N/A
associate-*r*N/A
*-commutativeN/A
*-lowering-*.f64N/A
*-commutativeN/A
*-lowering-*.f6496.6%
Simplified96.6%
flip--N/A
difference-of-squaresN/A
flip3-+N/A
div-invN/A
unpow-prod-downN/A
cube-unmultN/A
metadata-evalN/A
cube-unmultN/A
times-fracN/A
*-lowering-*.f64N/A
Applied egg-rr27.4%
Applied egg-rr97.0%
Taylor expanded in t around 0
--lowering--.f64N/A
distribute-lft-outN/A
*-lowering-*.f64N/A
+-lowering-+.f64N/A
*-commutativeN/A
*-lowering-*.f64N/A
--lowering--.f64N/A
*-lowering-*.f64N/A
unpow2N/A
*-lowering-*.f6489.5%
Simplified89.5%
Final simplification89.5%
(FPCore (x y z t) :precision binary64 (let* ((t_1 (sqrt (* z 2.0))) (t_2 (* t_1 (- 0.0 y)))) (if (<= y -1.2e-65) t_2 (if (<= y 17500000000.0) (* x (* 0.5 t_1)) t_2))))
double code(double x, double y, double z, double t) {
double t_1 = sqrt((z * 2.0));
double t_2 = t_1 * (0.0 - y);
double tmp;
if (y <= -1.2e-65) {
tmp = t_2;
} else if (y <= 17500000000.0) {
tmp = x * (0.5 * t_1);
} else {
tmp = t_2;
}
return tmp;
}
real(8) function code(x, y, z, t)
real(8), intent (in) :: x
real(8), intent (in) :: y
real(8), intent (in) :: z
real(8), intent (in) :: t
real(8) :: t_1
real(8) :: t_2
real(8) :: tmp
t_1 = sqrt((z * 2.0d0))
t_2 = t_1 * (0.0d0 - y)
if (y <= (-1.2d-65)) then
tmp = t_2
else if (y <= 17500000000.0d0) then
tmp = x * (0.5d0 * t_1)
else
tmp = t_2
end if
code = tmp
end function
public static double code(double x, double y, double z, double t) {
double t_1 = Math.sqrt((z * 2.0));
double t_2 = t_1 * (0.0 - y);
double tmp;
if (y <= -1.2e-65) {
tmp = t_2;
} else if (y <= 17500000000.0) {
tmp = x * (0.5 * t_1);
} else {
tmp = t_2;
}
return tmp;
}
def code(x, y, z, t): t_1 = math.sqrt((z * 2.0)) t_2 = t_1 * (0.0 - y) tmp = 0 if y <= -1.2e-65: tmp = t_2 elif y <= 17500000000.0: tmp = x * (0.5 * t_1) else: tmp = t_2 return tmp
function code(x, y, z, t) t_1 = sqrt(Float64(z * 2.0)) t_2 = Float64(t_1 * Float64(0.0 - y)) tmp = 0.0 if (y <= -1.2e-65) tmp = t_2; elseif (y <= 17500000000.0) tmp = Float64(x * Float64(0.5 * t_1)); else tmp = t_2; end return tmp end
function tmp_2 = code(x, y, z, t) t_1 = sqrt((z * 2.0)); t_2 = t_1 * (0.0 - y); tmp = 0.0; if (y <= -1.2e-65) tmp = t_2; elseif (y <= 17500000000.0) tmp = x * (0.5 * t_1); else tmp = t_2; end tmp_2 = tmp; end
code[x_, y_, z_, t_] := Block[{t$95$1 = N[Sqrt[N[(z * 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[(t$95$1 * N[(0.0 - y), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[y, -1.2e-65], t$95$2, If[LessEqual[y, 17500000000.0], N[(x * N[(0.5 * t$95$1), $MachinePrecision]), $MachinePrecision], t$95$2]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_1 := \sqrt{z \cdot 2}\\
t_2 := t\_1 \cdot \left(0 - y\right)\\
\mathbf{if}\;y \leq -1.2 \cdot 10^{-65}:\\
\;\;\;\;t\_2\\
\mathbf{elif}\;y \leq 17500000000:\\
\;\;\;\;x \cdot \left(0.5 \cdot t\_1\right)\\
\mathbf{else}:\\
\;\;\;\;t\_2\\
\end{array}
\end{array}
if y < -1.2000000000000001e-65 or 1.75e10 < y Initial program 99.8%
Taylor expanded in t around 0
Simplified63.5%
Taylor expanded in x around 0
mul-1-negN/A
neg-sub0N/A
--lowering--.f6453.8%
Simplified53.8%
if -1.2000000000000001e-65 < y < 1.75e10Initial program 99.8%
Taylor expanded in t around 0
Simplified50.0%
Taylor expanded in x around inf
*-lowering-*.f6441.8%
Simplified41.8%
*-rgt-identityN/A
*-commutativeN/A
associate-*r*N/A
*-lowering-*.f64N/A
*-lowering-*.f64N/A
sqrt-lowering-sqrt.f64N/A
*-lowering-*.f6441.8%
Applied egg-rr41.8%
Final simplification48.9%
(FPCore (x y z t) :precision binary64 (* (sqrt (* z 2.0)) (* (- (* x 0.5) y) (+ 1.0 (* 0.5 (* t t))))))
double code(double x, double y, double z, double t) {
return sqrt((z * 2.0)) * (((x * 0.5) - y) * (1.0 + (0.5 * (t * t))));
}
real(8) function code(x, y, z, t)
real(8), intent (in) :: x
real(8), intent (in) :: y
real(8), intent (in) :: z
real(8), intent (in) :: t
code = sqrt((z * 2.0d0)) * (((x * 0.5d0) - y) * (1.0d0 + (0.5d0 * (t * t))))
end function
public static double code(double x, double y, double z, double t) {
return Math.sqrt((z * 2.0)) * (((x * 0.5) - y) * (1.0 + (0.5 * (t * t))));
}
def code(x, y, z, t): return math.sqrt((z * 2.0)) * (((x * 0.5) - y) * (1.0 + (0.5 * (t * t))))
function code(x, y, z, t) return Float64(sqrt(Float64(z * 2.0)) * Float64(Float64(Float64(x * 0.5) - y) * Float64(1.0 + Float64(0.5 * Float64(t * t))))) end
function tmp = code(x, y, z, t) tmp = sqrt((z * 2.0)) * (((x * 0.5) - y) * (1.0 + (0.5 * (t * t)))); end
code[x_, y_, z_, t_] := N[(N[Sqrt[N[(z * 2.0), $MachinePrecision]], $MachinePrecision] * N[(N[(N[(x * 0.5), $MachinePrecision] - y), $MachinePrecision] * N[(1.0 + N[(0.5 * N[(t * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\sqrt{z \cdot 2} \cdot \left(\left(x \cdot 0.5 - y\right) \cdot \left(1 + 0.5 \cdot \left(t \cdot t\right)\right)\right)
\end{array}
Initial program 99.8%
Taylor expanded in t around 0
+-lowering-+.f64N/A
*-lowering-*.f64N/A
unpow2N/A
*-lowering-*.f64N/A
+-lowering-+.f64N/A
*-lowering-*.f64N/A
unpow2N/A
*-lowering-*.f64N/A
+-lowering-+.f64N/A
unpow2N/A
associate-*r*N/A
*-commutativeN/A
*-lowering-*.f64N/A
*-commutativeN/A
*-lowering-*.f6496.6%
Simplified96.6%
flip--N/A
difference-of-squaresN/A
flip3-+N/A
div-invN/A
unpow-prod-downN/A
cube-unmultN/A
metadata-evalN/A
cube-unmultN/A
times-fracN/A
*-lowering-*.f64N/A
Applied egg-rr27.4%
Applied egg-rr97.0%
Taylor expanded in t around 0
+-lowering-+.f64N/A
*-lowering-*.f64N/A
unpow2N/A
*-lowering-*.f6489.5%
Simplified89.5%
Final simplification89.5%
(FPCore (x y z t) :precision binary64 (let* ((t_1 (sqrt (* z 2.0)))) (if (<= t 0.005) (* (- (* x 0.5) y) t_1) (* t_1 (* x (- 0.5 (/ y x)))))))
double code(double x, double y, double z, double t) {
double t_1 = sqrt((z * 2.0));
double tmp;
if (t <= 0.005) {
tmp = ((x * 0.5) - y) * t_1;
} else {
tmp = t_1 * (x * (0.5 - (y / x)));
}
return tmp;
}
real(8) function code(x, y, z, t)
real(8), intent (in) :: x
real(8), intent (in) :: y
real(8), intent (in) :: z
real(8), intent (in) :: t
real(8) :: t_1
real(8) :: tmp
t_1 = sqrt((z * 2.0d0))
if (t <= 0.005d0) then
tmp = ((x * 0.5d0) - y) * t_1
else
tmp = t_1 * (x * (0.5d0 - (y / x)))
end if
code = tmp
end function
public static double code(double x, double y, double z, double t) {
double t_1 = Math.sqrt((z * 2.0));
double tmp;
if (t <= 0.005) {
tmp = ((x * 0.5) - y) * t_1;
} else {
tmp = t_1 * (x * (0.5 - (y / x)));
}
return tmp;
}
def code(x, y, z, t): t_1 = math.sqrt((z * 2.0)) tmp = 0 if t <= 0.005: tmp = ((x * 0.5) - y) * t_1 else: tmp = t_1 * (x * (0.5 - (y / x))) return tmp
function code(x, y, z, t) t_1 = sqrt(Float64(z * 2.0)) tmp = 0.0 if (t <= 0.005) tmp = Float64(Float64(Float64(x * 0.5) - y) * t_1); else tmp = Float64(t_1 * Float64(x * Float64(0.5 - Float64(y / x)))); end return tmp end
function tmp_2 = code(x, y, z, t) t_1 = sqrt((z * 2.0)); tmp = 0.0; if (t <= 0.005) tmp = ((x * 0.5) - y) * t_1; else tmp = t_1 * (x * (0.5 - (y / x))); end tmp_2 = tmp; end
code[x_, y_, z_, t_] := Block[{t$95$1 = N[Sqrt[N[(z * 2.0), $MachinePrecision]], $MachinePrecision]}, If[LessEqual[t, 0.005], N[(N[(N[(x * 0.5), $MachinePrecision] - y), $MachinePrecision] * t$95$1), $MachinePrecision], N[(t$95$1 * N[(x * N[(0.5 - N[(y / x), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_1 := \sqrt{z \cdot 2}\\
\mathbf{if}\;t \leq 0.005:\\
\;\;\;\;\left(x \cdot 0.5 - y\right) \cdot t\_1\\
\mathbf{else}:\\
\;\;\;\;t\_1 \cdot \left(x \cdot \left(0.5 - \frac{y}{x}\right)\right)\\
\end{array}
\end{array}
if t < 0.0050000000000000001Initial program 99.7%
Taylor expanded in t around 0
Simplified70.5%
*-rgt-identityN/A
*-lowering-*.f64N/A
--lowering--.f64N/A
*-lowering-*.f64N/A
sqrt-lowering-sqrt.f64N/A
*-lowering-*.f6470.5%
Applied egg-rr70.5%
if 0.0050000000000000001 < t Initial program 100.0%
Taylor expanded in t around 0
Simplified23.9%
Taylor expanded in x around inf
*-lowering-*.f64N/A
mul-1-negN/A
unsub-negN/A
--lowering--.f64N/A
/-lowering-/.f6433.5%
Simplified33.5%
Final simplification60.5%
(FPCore (x y z t) :precision binary64 (* (- (* x 0.5) y) (sqrt (* z (* 2.0 (+ (* t t) 1.0))))))
double code(double x, double y, double z, double t) {
return ((x * 0.5) - y) * sqrt((z * (2.0 * ((t * t) + 1.0))));
}
real(8) function code(x, y, z, t)
real(8), intent (in) :: x
real(8), intent (in) :: y
real(8), intent (in) :: z
real(8), intent (in) :: t
code = ((x * 0.5d0) - y) * sqrt((z * (2.0d0 * ((t * t) + 1.0d0))))
end function
public static double code(double x, double y, double z, double t) {
return ((x * 0.5) - y) * Math.sqrt((z * (2.0 * ((t * t) + 1.0))));
}
def code(x, y, z, t): return ((x * 0.5) - y) * math.sqrt((z * (2.0 * ((t * t) + 1.0))))
function code(x, y, z, t) return Float64(Float64(Float64(x * 0.5) - y) * sqrt(Float64(z * Float64(2.0 * Float64(Float64(t * t) + 1.0))))) end
function tmp = code(x, y, z, t) tmp = ((x * 0.5) - y) * sqrt((z * (2.0 * ((t * t) + 1.0)))); end
code[x_, y_, z_, t_] := N[(N[(N[(x * 0.5), $MachinePrecision] - y), $MachinePrecision] * N[Sqrt[N[(z * N[(2.0 * N[(N[(t * t), $MachinePrecision] + 1.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\left(x \cdot 0.5 - y\right) \cdot \sqrt{z \cdot \left(2 \cdot \left(t \cdot t + 1\right)\right)}
\end{array}
Initial program 99.8%
associate-*l*N/A
*-lowering-*.f64N/A
--lowering--.f64N/A
*-lowering-*.f64N/A
exp-sqrtN/A
sqrt-unprodN/A
sqrt-lowering-sqrt.f64N/A
associate-*l*N/A
*-lowering-*.f64N/A
*-lowering-*.f64N/A
exp-lowering-exp.f64N/A
*-lowering-*.f6499.8%
Applied egg-rr99.8%
Taylor expanded in t around 0
+-commutativeN/A
+-lowering-+.f64N/A
unpow2N/A
*-lowering-*.f6484.7%
Simplified84.7%
(FPCore (x y z t) :precision binary64 (* (- (* x 0.5) y) (sqrt (* z 2.0))))
double code(double x, double y, double z, double t) {
return ((x * 0.5) - y) * sqrt((z * 2.0));
}
real(8) function code(x, y, z, t)
real(8), intent (in) :: x
real(8), intent (in) :: y
real(8), intent (in) :: z
real(8), intent (in) :: t
code = ((x * 0.5d0) - y) * sqrt((z * 2.0d0))
end function
public static double code(double x, double y, double z, double t) {
return ((x * 0.5) - y) * Math.sqrt((z * 2.0));
}
def code(x, y, z, t): return ((x * 0.5) - y) * math.sqrt((z * 2.0))
function code(x, y, z, t) return Float64(Float64(Float64(x * 0.5) - y) * sqrt(Float64(z * 2.0))) end
function tmp = code(x, y, z, t) tmp = ((x * 0.5) - y) * sqrt((z * 2.0)); end
code[x_, y_, z_, t_] := N[(N[(N[(x * 0.5), $MachinePrecision] - y), $MachinePrecision] * N[Sqrt[N[(z * 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\left(x \cdot 0.5 - y\right) \cdot \sqrt{z \cdot 2}
\end{array}
Initial program 99.8%
Taylor expanded in t around 0
Simplified57.9%
*-rgt-identityN/A
*-lowering-*.f64N/A
--lowering--.f64N/A
*-lowering-*.f64N/A
sqrt-lowering-sqrt.f64N/A
*-lowering-*.f6457.9%
Applied egg-rr57.9%
(FPCore (x y z t) :precision binary64 (* x (* 0.5 (sqrt (* z 2.0)))))
double code(double x, double y, double z, double t) {
return x * (0.5 * sqrt((z * 2.0)));
}
real(8) function code(x, y, z, t)
real(8), intent (in) :: x
real(8), intent (in) :: y
real(8), intent (in) :: z
real(8), intent (in) :: t
code = x * (0.5d0 * sqrt((z * 2.0d0)))
end function
public static double code(double x, double y, double z, double t) {
return x * (0.5 * Math.sqrt((z * 2.0)));
}
def code(x, y, z, t): return x * (0.5 * math.sqrt((z * 2.0)))
function code(x, y, z, t) return Float64(x * Float64(0.5 * sqrt(Float64(z * 2.0)))) end
function tmp = code(x, y, z, t) tmp = x * (0.5 * sqrt((z * 2.0))); end
code[x_, y_, z_, t_] := N[(x * N[(0.5 * N[Sqrt[N[(z * 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
x \cdot \left(0.5 \cdot \sqrt{z \cdot 2}\right)
\end{array}
Initial program 99.8%
Taylor expanded in t around 0
Simplified57.9%
Taylor expanded in x around inf
*-lowering-*.f6424.9%
Simplified24.9%
*-rgt-identityN/A
*-commutativeN/A
associate-*r*N/A
*-lowering-*.f64N/A
*-lowering-*.f64N/A
sqrt-lowering-sqrt.f64N/A
*-lowering-*.f6424.9%
Applied egg-rr24.9%
Final simplification24.9%
(FPCore (x y z t) :precision binary64 (* (* (- (* x 0.5) y) (sqrt (* z 2.0))) (pow (exp 1.0) (/ (* t t) 2.0))))
double code(double x, double y, double z, double t) {
return (((x * 0.5) - y) * sqrt((z * 2.0))) * pow(exp(1.0), ((t * t) / 2.0));
}
real(8) function code(x, y, z, t)
real(8), intent (in) :: x
real(8), intent (in) :: y
real(8), intent (in) :: z
real(8), intent (in) :: t
code = (((x * 0.5d0) - y) * sqrt((z * 2.0d0))) * (exp(1.0d0) ** ((t * t) / 2.0d0))
end function
public static double code(double x, double y, double z, double t) {
return (((x * 0.5) - y) * Math.sqrt((z * 2.0))) * Math.pow(Math.exp(1.0), ((t * t) / 2.0));
}
def code(x, y, z, t): return (((x * 0.5) - y) * math.sqrt((z * 2.0))) * math.pow(math.exp(1.0), ((t * t) / 2.0))
function code(x, y, z, t) return Float64(Float64(Float64(Float64(x * 0.5) - y) * sqrt(Float64(z * 2.0))) * (exp(1.0) ^ Float64(Float64(t * t) / 2.0))) end
function tmp = code(x, y, z, t) tmp = (((x * 0.5) - y) * sqrt((z * 2.0))) * (exp(1.0) ^ ((t * t) / 2.0)); end
code[x_, y_, z_, t_] := N[(N[(N[(N[(x * 0.5), $MachinePrecision] - y), $MachinePrecision] * N[Sqrt[N[(z * 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] * N[Power[N[Exp[1.0], $MachinePrecision], N[(N[(t * t), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\left(\left(x \cdot 0.5 - y\right) \cdot \sqrt{z \cdot 2}\right) \cdot {\left(e^{1}\right)}^{\left(\frac{t \cdot t}{2}\right)}
\end{array}
herbie shell --seed 2024138
(FPCore (x y z t)
:name "Data.Number.Erf:$cinvnormcdf from erf-2.0.0.0, A"
:precision binary64
:alt
(! :herbie-platform default (* (* (- (* x 1/2) y) (sqrt (* z 2))) (pow (exp 1) (/ (* t t) 2))))
(* (* (- (* x 0.5) y) (sqrt (* z 2.0))) (exp (/ (* t t) 2.0))))