Diagrams.ThreeD.Shapes:frustum from diagrams-lib-1.3.0.3, A

Average Accuracy: 90.6% → 97.2%

Time: 34.0s

Precision: binary64

Cost: 2504

Math

\[2 \cdot \left(\left(x \cdot y + z \cdot t\right) - \left(\left(a + b \cdot c\right) \cdot c\right) \cdot i\right) \]

↓

\[\begin{array}{l} t_1 := a + b \cdot c\\ t_2 := i \cdot \left(c \cdot t_1\right)\\ \mathbf{if}\;t_2 \leq -5 \cdot 10^{+305}:\\ \;\;\;\;2 \cdot \left(z \cdot t - c \cdot \left(a \cdot i + c \cdot \left(b \cdot i\right)\right)\right)\\ \mathbf{elif}\;t_2 \leq 4 \cdot 10^{+296}:\\ \;\;\;\;2 \cdot \left(\left(z \cdot t + x \cdot y\right) - t_2\right)\\ \mathbf{else}:\\ \;\;\;\;2 \cdot \left(z \cdot t - c \cdot \left(t_1 \cdot i\right)\right)\\ \end{array} \]

FPCore

(FPCore (x y z t a b c i)
 :precision binary64
 (* 2.0 (- (+ (* x y) (* z t)) (* (* (+ a (* b c)) c) i))))

↓

(FPCore (x y z t a b c i)
 :precision binary64
 (let* ((t_1 (+ a (* b c))) (t_2 (* i (* c t_1))))
   (if (<= t_2 -5e+305)
     (* 2.0 (- (* z t) (* c (+ (* a i) (* c (* b i))))))
     (if (<= t_2 4e+296)
       (* 2.0 (- (+ (* z t) (* x y)) t_2))
       (* 2.0 (- (* z t) (* c (* t_1 i))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i) {
	return 2.0 * (((x * y) + (z * t)) - (((a + (b * c)) * c) * i));
}

↓

double code(double x, double y, double z, double t, double a, double b, double c, double i) {
	double t_1 = a + (b * c);
	double t_2 = i * (c * t_1);
	double tmp;
	if (t_2 <= -5e+305) {
		tmp = 2.0 * ((z * t) - (c * ((a * i) + (c * (b * i)))));
	} else if (t_2 <= 4e+296) {
		tmp = 2.0 * (((z * t) + (x * y)) - t_2);
	} else {
		tmp = 2.0 * ((z * t) - (c * (t_1 * i)));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    code = 2.0d0 * (((x * y) + (z * t)) - (((a + (b * c)) * c) * i))
end function

↓

real(8) function code(x, y, z, t, a, b, c, i)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8) :: t_1
    real(8) :: t_2
    real(8) :: tmp
    t_1 = a + (b * c)
    t_2 = i * (c * t_1)
    if (t_2 <= (-5d+305)) then
        tmp = 2.0d0 * ((z * t) - (c * ((a * i) + (c * (b * i)))))
    else if (t_2 <= 4d+296) then
        tmp = 2.0d0 * (((z * t) + (x * y)) - t_2)
    else
        tmp = 2.0d0 * ((z * t) - (c * (t_1 * i)))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i) {
	return 2.0 * (((x * y) + (z * t)) - (((a + (b * c)) * c) * i));
}

↓

public static double code(double x, double y, double z, double t, double a, double b, double c, double i) {
	double t_1 = a + (b * c);
	double t_2 = i * (c * t_1);
	double tmp;
	if (t_2 <= -5e+305) {
		tmp = 2.0 * ((z * t) - (c * ((a * i) + (c * (b * i)))));
	} else if (t_2 <= 4e+296) {
		tmp = 2.0 * (((z * t) + (x * y)) - t_2);
	} else {
		tmp = 2.0 * ((z * t) - (c * (t_1 * i)));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i):
	return 2.0 * (((x * y) + (z * t)) - (((a + (b * c)) * c) * i))

↓

def code(x, y, z, t, a, b, c, i):
	t_1 = a + (b * c)
	t_2 = i * (c * t_1)
	tmp = 0
	if t_2 <= -5e+305:
		tmp = 2.0 * ((z * t) - (c * ((a * i) + (c * (b * i)))))
	elif t_2 <= 4e+296:
		tmp = 2.0 * (((z * t) + (x * y)) - t_2)
	else:
		tmp = 2.0 * ((z * t) - (c * (t_1 * i)))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i)
	return Float64(2.0 * Float64(Float64(Float64(x * y) + Float64(z * t)) - Float64(Float64(Float64(a + Float64(b * c)) * c) * i)))
end

↓

function code(x, y, z, t, a, b, c, i)
	t_1 = Float64(a + Float64(b * c))
	t_2 = Float64(i * Float64(c * t_1))
	tmp = 0.0
	if (t_2 <= -5e+305)
		tmp = Float64(2.0 * Float64(Float64(z * t) - Float64(c * Float64(Float64(a * i) + Float64(c * Float64(b * i))))));
	elseif (t_2 <= 4e+296)
		tmp = Float64(2.0 * Float64(Float64(Float64(z * t) + Float64(x * y)) - t_2));
	else
		tmp = Float64(2.0 * Float64(Float64(z * t) - Float64(c * Float64(t_1 * i))));
	end
	return tmp
end

MATLAB

function tmp = code(x, y, z, t, a, b, c, i)
	tmp = 2.0 * (((x * y) + (z * t)) - (((a + (b * c)) * c) * i));
end

↓

function tmp_2 = code(x, y, z, t, a, b, c, i)
	t_1 = a + (b * c);
	t_2 = i * (c * t_1);
	tmp = 0.0;
	if (t_2 <= -5e+305)
		tmp = 2.0 * ((z * t) - (c * ((a * i) + (c * (b * i)))));
	elseif (t_2 <= 4e+296)
		tmp = 2.0 * (((z * t) + (x * y)) - t_2);
	else
		tmp = 2.0 * ((z * t) - (c * (t_1 * i)));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_] := N[(2.0 * N[(N[(N[(x * y), $MachinePrecision] + N[(z * t), $MachinePrecision]), $MachinePrecision] - N[(N[(N[(a + N[(b * c), $MachinePrecision]), $MachinePrecision] * c), $MachinePrecision] * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]

↓

code[x_, y_, z_, t_, a_, b_, c_, i_] := Block[{t$95$1 = N[(a + N[(b * c), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(i * N[(c * t$95$1), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[t$95$2, -5e+305], N[(2.0 * N[(N[(z * t), $MachinePrecision] - N[(c * N[(N[(a * i), $MachinePrecision] + N[(c * N[(b * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t$95$2, 4e+296], N[(2.0 * N[(N[(N[(z * t), $MachinePrecision] + N[(x * y), $MachinePrecision]), $MachinePrecision] - t$95$2), $MachinePrecision]), $MachinePrecision], N[(2.0 * N[(N[(z * t), $MachinePrecision] - N[(c * N[(t$95$1 * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]

Target

Original	90.6%
Target	97.0%
Herbie	97.2%

\[2 \cdot \left(\left(x \cdot y + z \cdot t\right) - \left(a + b \cdot c\right) \cdot \left(c \cdot i\right)\right) \]

Derivation

1. Split input into 3 regimes

2. if (*.f64 (*.f64 (+.f64 a (*.f64 b c)) c) i) < -5.00000000000000009e305

   1. Initial program 2.7%

      \[2 \cdot \left(\left(x \cdot y + z \cdot t\right) - \left(\left(a + b \cdot c\right) \cdot c\right) \cdot i\right) \]

   2. Taylor expanded in x around 0 73.2%

      \[\leadsto 2 \cdot \color{blue}{\left(t \cdot z - c \cdot \left(i \cdot \left(c \cdot b + a\right)\right)\right)} \]

   3. Taylor expanded in a around 0 80.1%

      \[\leadsto 2 \cdot \left(t \cdot z - c \cdot \color{blue}{\left(i \cdot a + c \cdot \left(i \cdot b\right)\right)}\right) \]

   if -5.00000000000000009e305 < (*.f64 (*.f64 (+.f64 a (*.f64 b c)) c) i) < 3.99999999999999993e296

   1. Initial program 99.5%

      \[2 \cdot \left(\left(x \cdot y + z \cdot t\right) - \left(\left(a + b \cdot c\right) \cdot c\right) \cdot i\right) \]

   if 3.99999999999999993e296 < (*.f64 (*.f64 (+.f64 a (*.f64 b c)) c) i)

   1. Initial program 11.9%

      \[2 \cdot \left(\left(x \cdot y + z \cdot t\right) - \left(\left(a + b \cdot c\right) \cdot c\right) \cdot i\right) \]

   2. Taylor expanded in x around 0 71.6%

      \[\leadsto 2 \cdot \color{blue}{\left(t \cdot z - c \cdot \left(i \cdot \left(c \cdot b + a\right)\right)\right)} \]
3. Recombined 3 regimes into one program.

4. Final simplification 97.2%

   \[\leadsto \begin{array}{l} \mathbf{if}\;i \cdot \left(c \cdot \left(a + b \cdot c\right)\right) \leq -5 \cdot 10^{+305}:\\ \;\;\;\;2 \cdot \left(z \cdot t - c \cdot \left(a \cdot i + c \cdot \left(b \cdot i\right)\right)\right)\\ \mathbf{elif}\;i \cdot \left(c \cdot \left(a + b \cdot c\right)\right) \leq 4 \cdot 10^{+296}:\\ \;\;\;\;2 \cdot \left(\left(z \cdot t + x \cdot y\right) - i \cdot \left(c \cdot \left(a + b \cdot c\right)\right)\right)\\ \mathbf{else}:\\ \;\;\;\;2 \cdot \left(z \cdot t - c \cdot \left(\left(a + b \cdot c\right) \cdot i\right)\right)\\ \end{array} \]

Alternatives

Alternative 1
Accuracy	71.3%
Cost	2017

\[\begin{array}{l} t_1 := c \cdot \left(\left(a + b \cdot c\right) \cdot i\right)\\ t_2 := 2 \cdot \left(z \cdot t - t_1\right)\\ t_3 := 2 \cdot \left(x \cdot y - t_1\right)\\ t_4 := 2 \cdot \left(z \cdot t + x \cdot y\right)\\ \mathbf{if}\;x \leq -7.8 \cdot 10^{+114}:\\ \;\;\;\;t_3\\ \mathbf{elif}\;x \leq -5.6 \cdot 10^{+60}:\\ \;\;\;\;t_4\\ \mathbf{elif}\;x \leq -7.5 \cdot 10^{+25}:\\ \;\;\;\;t_3\\ \mathbf{elif}\;x \leq -1.2 \cdot 10^{-39}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;x \leq -2.7 \cdot 10^{-55}:\\ \;\;\;\;2 \cdot \left(x \cdot y - c \cdot \left(b \cdot \left(c \cdot i\right)\right)\right)\\ \mathbf{elif}\;x \leq -8 \cdot 10^{-56}:\\ \;\;\;\;\left(a \cdot c\right) \cdot \left(i \cdot -2\right)\\ \mathbf{elif}\;x \leq -1.45 \cdot 10^{-161} \lor \neg \left(x \leq 9 \cdot 10^{-121}\right):\\ \;\;\;\;t_4\\ \mathbf{else}:\\ \;\;\;\;t_2\\ \end{array} \]

Alternative 2
Accuracy	66.8%
Cost	1884

\[\begin{array}{l} t_1 := 2 \cdot \left(z \cdot t - c \cdot \left(\left(a + b \cdot c\right) \cdot i\right)\right)\\ t_2 := 2 \cdot \left(z \cdot t + x \cdot y\right)\\ t_3 := 2 \cdot \left(z \cdot t - a \cdot \left(c \cdot i\right)\right)\\ \mathbf{if}\;a \leq -3 \cdot 10^{+188}:\\ \;\;\;\;t_3\\ \mathbf{elif}\;a \leq -7.8 \cdot 10^{+95}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;a \leq -1850:\\ \;\;\;\;t_1\\ \mathbf{elif}\;a \leq -3.7 \cdot 10^{-255}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;a \leq -1.9 \cdot 10^{-301}:\\ \;\;\;\;2 \cdot \left(x \cdot y - c \cdot \left(b \cdot \left(c \cdot i\right)\right)\right)\\ \mathbf{elif}\;a \leq 6.1 \cdot 10^{-58}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;a \leq 1.1 \cdot 10^{+87}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;a \leq 1.05 \cdot 10^{+278}:\\ \;\;\;\;t_3\\ \mathbf{else}:\\ \;\;\;\;2 \cdot \left(x \cdot y - c \cdot \left(a \cdot i\right)\right)\\ \end{array} \]

Alternative 3
Accuracy	62.9%
Cost	1628

\[\begin{array}{l} t_1 := \left(c \cdot \left(\left(a + b \cdot c\right) \cdot i\right)\right) \cdot -2\\ t_2 := 2 \cdot \left(z \cdot t + x \cdot y\right)\\ t_3 := 2 \cdot \left(z \cdot t - a \cdot \left(c \cdot i\right)\right)\\ \mathbf{if}\;a \leq -3 \cdot 10^{+188}:\\ \;\;\;\;t_3\\ \mathbf{elif}\;a \leq -1.7 \cdot 10^{+87}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;a \leq -3000000:\\ \;\;\;\;t_1\\ \mathbf{elif}\;a \leq -4.1 \cdot 10^{-255}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;a \leq -1.85 \cdot 10^{-301}:\\ \;\;\;\;2 \cdot \left(x \cdot y - c \cdot \left(b \cdot \left(c \cdot i\right)\right)\right)\\ \mathbf{elif}\;a \leq 2.7 \cdot 10^{-30}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;a \leq 1.15 \cdot 10^{+49}:\\ \;\;\;\;t_1\\ \mathbf{else}:\\ \;\;\;\;t_3\\ \end{array} \]

Alternative 4
Accuracy	63.2%
Cost	1628

\[\begin{array}{l} t_1 := a \cdot \left(c \cdot i\right)\\ t_2 := 2 \cdot \left(z \cdot t + x \cdot y\right)\\ t_3 := 2 \cdot \left(z \cdot t - t_1\right)\\ \mathbf{if}\;a \leq -3.6 \cdot 10^{+188}:\\ \;\;\;\;t_3\\ \mathbf{elif}\;a \leq -6.5 \cdot 10^{+86}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;a \leq -3000000:\\ \;\;\;\;-2 \cdot \left(t_1 + \left(c \cdot i\right) \cdot \left(b \cdot c\right)\right)\\ \mathbf{elif}\;a \leq -3.6 \cdot 10^{-255}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;a \leq -1.62 \cdot 10^{-301}:\\ \;\;\;\;2 \cdot \left(x \cdot y - c \cdot \left(b \cdot \left(c \cdot i\right)\right)\right)\\ \mathbf{elif}\;a \leq 2.75 \cdot 10^{-30}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;a \leq 1.15 \cdot 10^{+49}:\\ \;\;\;\;\left(c \cdot \left(\left(a + b \cdot c\right) \cdot i\right)\right) \cdot -2\\ \mathbf{else}:\\ \;\;\;\;t_3\\ \end{array} \]

Alternative 5
Accuracy	85.7%
Cost	1489

\[\begin{array}{l} t_1 := c \cdot \left(\left(a + b \cdot c\right) \cdot i\right)\\ \mathbf{if}\;c \leq -1.6 \cdot 10^{-20}:\\ \;\;\;\;2 \cdot \left(z \cdot t - t_1\right)\\ \mathbf{elif}\;c \leq 3.4 \cdot 10^{+26}:\\ \;\;\;\;2 \cdot \left(\left(z \cdot t + x \cdot y\right) - i \cdot \left(a \cdot c\right)\right)\\ \mathbf{elif}\;c \leq 2.9 \cdot 10^{+88} \lor \neg \left(c \leq 1.72 \cdot 10^{+162}\right):\\ \;\;\;\;2 \cdot \left(x \cdot y - t_1\right)\\ \mathbf{else}:\\ \;\;\;\;2 \cdot \left(z \cdot t - c \cdot \left(c \cdot \left(b \cdot i\right)\right)\right)\\ \end{array} \]

Alternative 6
Accuracy	86.7%
Cost	1484

\[\begin{array}{l} t_1 := c \cdot \left(\left(a + b \cdot c\right) \cdot i\right)\\ \mathbf{if}\;c \leq -2.4 \cdot 10^{-22}:\\ \;\;\;\;2 \cdot \left(z \cdot t - t_1\right)\\ \mathbf{elif}\;c \leq 3.6 \cdot 10^{+27}:\\ \;\;\;\;2 \cdot \left(\left(z \cdot t + x \cdot y\right) - i \cdot \left(a \cdot c\right)\right)\\ \mathbf{elif}\;c \leq 4.5 \cdot 10^{+134}:\\ \;\;\;\;2 \cdot \left(z \cdot t - c \cdot \left(a \cdot i + c \cdot \left(b \cdot i\right)\right)\right)\\ \mathbf{else}:\\ \;\;\;\;2 \cdot \left(x \cdot y - t_1\right)\\ \end{array} \]

Alternative 7
Accuracy	63.3%
Cost	1364

\[\begin{array}{l} t_1 := \left(c \cdot \left(\left(a + b \cdot c\right) \cdot i\right)\right) \cdot -2\\ t_2 := 2 \cdot \left(z \cdot t + x \cdot y\right)\\ t_3 := 2 \cdot \left(z \cdot t - a \cdot \left(c \cdot i\right)\right)\\ \mathbf{if}\;a \leq -1 \cdot 10^{+190}:\\ \;\;\;\;t_3\\ \mathbf{elif}\;a \leq -5.5 \cdot 10^{+86}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;a \leq -3000000:\\ \;\;\;\;t_1\\ \mathbf{elif}\;a \leq 2.75 \cdot 10^{-30}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;a \leq 1.15 \cdot 10^{+49}:\\ \;\;\;\;t_1\\ \mathbf{else}:\\ \;\;\;\;t_3\\ \end{array} \]

Alternative 8
Accuracy	85.8%
Cost	1356

\[\begin{array}{l} t_1 := z \cdot t + x \cdot y\\ t_2 := 2 \cdot \left(t_1 - i \cdot \left(a \cdot c\right)\right)\\ \mathbf{if}\;a \leq -1.7 \cdot 10^{-43}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;a \leq 1.45 \cdot 10^{-105}:\\ \;\;\;\;2 \cdot \left(t_1 - i \cdot \left(c \cdot \left(b \cdot c\right)\right)\right)\\ \mathbf{elif}\;a \leq 1.25 \cdot 10^{+244}:\\ \;\;\;\;t_2\\ \mathbf{else}:\\ \;\;\;\;2 \cdot \left(t_1 - c \cdot \left(a \cdot i\right)\right)\\ \end{array} \]

Alternative 9
Accuracy	66.0%
Cost	1234

\[\begin{array}{l} \mathbf{if}\;c \leq -5.4 \cdot 10^{-44} \lor \neg \left(c \leq 1.85 \cdot 10^{+29}\right) \land \left(c \leq 3.5 \cdot 10^{+87} \lor \neg \left(c \leq 7.2 \cdot 10^{+182}\right)\right):\\ \;\;\;\;\left(c \cdot \left(\left(a + b \cdot c\right) \cdot i\right)\right) \cdot -2\\ \mathbf{else}:\\ \;\;\;\;2 \cdot \left(z \cdot t + x \cdot y\right)\\ \end{array} \]

Alternative 10
Accuracy	97.0%
Cost	1216

\[2 \cdot \left(\left(z \cdot t + x \cdot y\right) - \left(a + b \cdot c\right) \cdot \left(c \cdot i\right)\right) \]

Alternative 11
Accuracy	63.1%
Cost	973

\[\begin{array}{l} \mathbf{if}\;a \leq -6 \cdot 10^{+86} \lor \neg \left(a \leq -1.25 \cdot 10^{+62}\right) \land a \leq 3.8 \cdot 10^{+140}:\\ \;\;\;\;2 \cdot \left(z \cdot t + x \cdot y\right)\\ \mathbf{else}:\\ \;\;\;\;\left(c \cdot i\right) \cdot \left(a \cdot -2\right)\\ \end{array} \]

Alternative 12
Accuracy	43.3%
Cost	848

\[\begin{array}{l} t_1 := 2 \cdot \left(x \cdot y\right)\\ t_2 := 2 \cdot \left(z \cdot t\right)\\ \mathbf{if}\;z \leq -1.02 \cdot 10^{-46}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;z \leq -4 \cdot 10^{-190}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;z \leq -3.7 \cdot 10^{-208}:\\ \;\;\;\;\left(a \cdot c\right) \cdot \left(i \cdot -2\right)\\ \mathbf{elif}\;z \leq 9.5 \cdot 10^{-80}:\\ \;\;\;\;t_1\\ \mathbf{else}:\\ \;\;\;\;t_2\\ \end{array} \]

Alternative 13
Accuracy	43.3%
Cost	848

\[\begin{array}{l} t_1 := 2 \cdot \left(x \cdot y\right)\\ t_2 := 2 \cdot \left(z \cdot t\right)\\ \mathbf{if}\;z \leq -5.5 \cdot 10^{-41}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;z \leq -3.3 \cdot 10^{-190}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;z \leq -4.7 \cdot 10^{-209}:\\ \;\;\;\;\left(c \cdot i\right) \cdot \left(a \cdot -2\right)\\ \mathbf{elif}\;z \leq 7.8 \cdot 10^{-81}:\\ \;\;\;\;t_1\\ \mathbf{else}:\\ \;\;\;\;t_2\\ \end{array} \]

Alternative 14
Accuracy	44.1%
Cost	585

\[\begin{array}{l} \mathbf{if}\;t \leq -4.2 \cdot 10^{-149} \lor \neg \left(t \leq 0.00108\right):\\ \;\;\;\;2 \cdot \left(z \cdot t\right)\\ \mathbf{else}:\\ \;\;\;\;2 \cdot \left(x \cdot y\right)\\ \end{array} \]

Alternative 15
Accuracy	33.6%
Cost	320

\[2 \cdot \left(z \cdot t\right) \]

Reproduce

herbie shell --seed 2023143 
(FPCore (x y z t a b c i)
  :name "Diagrams.ThreeD.Shapes:frustum from diagrams-lib-1.3.0.3, A"
  :precision binary64

  :herbie-target
  (* 2.0 (- (+ (* x y) (* z t)) (* (+ a (* b c)) (* c i))))

  (* 2.0 (- (+ (* x y) (* z t)) (* (* (+ a (* b c)) c) i))))