tan-example (used to crash)

Average Error: 13.5 → 0.2

Time: 34.5s

Precision: binary64

Cost: 39360

\[\left(\left(\left(x = 0 \lor 0.5884142 \leq x \land x \leq 505.5909\right) \land \left(-1.796658 \cdot 10^{+308} \leq y \land y \leq -9.425585 \cdot 10^{-310} \lor 1.284938 \cdot 10^{-309} \leq y \land y \leq 1.751224 \cdot 10^{+308}\right)\right) \land \left(-1.776707 \cdot 10^{+308} \leq z \land z \leq -8.599796 \cdot 10^{-310} \lor 3.293145 \cdot 10^{-311} \leq z \land z \leq 1.725154 \cdot 10^{+308}\right)\right) \land \left(-1.796658 \cdot 10^{+308} \leq a \land a \leq -9.425585 \cdot 10^{-310} \lor 1.284938 \cdot 10^{-309} \leq a \land a \leq 1.751224 \cdot 10^{+308}\right)\]

Math

\[x + \left(\tan \left(y + z\right) - \tan a\right) \]

↓

\[x + \left(\frac{\tan y + \tan z}{1 - \frac{\tan z \cdot \sin y}{\cos y}} - \tan a\right) \]

FPCore

(FPCore (x y z a) :precision binary64 (+ x (- (tan (+ y z)) (tan a))))

↓

(FPCore (x y z a)
 :precision binary64
 (+
  x
  (- (/ (+ (tan y) (tan z)) (- 1.0 (/ (* (tan z) (sin y)) (cos y)))) (tan a))))

C

double code(double x, double y, double z, double a) {
	return x + (tan((y + z)) - tan(a));
}

↓

double code(double x, double y, double z, double a) {
	return x + (((tan(y) + tan(z)) / (1.0 - ((tan(z) * sin(y)) / cos(y)))) - tan(a));
}

Fortran

real(8) function code(x, y, z, a)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: a
    code = x + (tan((y + z)) - tan(a))
end function

↓

real(8) function code(x, y, z, a)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: a
    code = x + (((tan(y) + tan(z)) / (1.0d0 - ((tan(z) * sin(y)) / cos(y)))) - tan(a))
end function

Java

public static double code(double x, double y, double z, double a) {
	return x + (Math.tan((y + z)) - Math.tan(a));
}

↓

public static double code(double x, double y, double z, double a) {
	return x + (((Math.tan(y) + Math.tan(z)) / (1.0 - ((Math.tan(z) * Math.sin(y)) / Math.cos(y)))) - Math.tan(a));
}

Python

def code(x, y, z, a):
	return x + (math.tan((y + z)) - math.tan(a))

↓

def code(x, y, z, a):
	return x + (((math.tan(y) + math.tan(z)) / (1.0 - ((math.tan(z) * math.sin(y)) / math.cos(y)))) - math.tan(a))

Julia

function code(x, y, z, a)
	return Float64(x + Float64(tan(Float64(y + z)) - tan(a)))
end

↓

function code(x, y, z, a)
	return Float64(x + Float64(Float64(Float64(tan(y) + tan(z)) / Float64(1.0 - Float64(Float64(tan(z) * sin(y)) / cos(y)))) - tan(a)))
end

MATLAB

function tmp = code(x, y, z, a)
	tmp = x + (tan((y + z)) - tan(a));
end

↓

function tmp = code(x, y, z, a)
	tmp = x + (((tan(y) + tan(z)) / (1.0 - ((tan(z) * sin(y)) / cos(y)))) - tan(a));
end

Wolfram

code[x_, y_, z_, a_] := N[(x + N[(N[Tan[N[(y + z), $MachinePrecision]], $MachinePrecision] - N[Tan[a], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]

↓

code[x_, y_, z_, a_] := N[(x + N[(N[(N[(N[Tan[y], $MachinePrecision] + N[Tan[z], $MachinePrecision]), $MachinePrecision] / N[(1.0 - N[(N[(N[Tan[z], $MachinePrecision] * N[Sin[y], $MachinePrecision]), $MachinePrecision] / N[Cos[y], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[Tan[a], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]

Derivation

1. Initial program 13.5

   \[x + \left(\tan \left(y + z\right) - \tan a\right) \]

2. Simplified 13.5

   \[\leadsto \color{blue}{x - \left(\tan a - \tan \left(y + z\right)\right)} \]
   Proof
   (-.f64 x (-.f64 (tan.f64 a) (tan.f64 (+.f64 y z)))): 0 points increase in error, 0 points decrease in error
   (Rewrite=> associate--r-_binary64 (+.f64 (-.f64 x (tan.f64 a)) (tan.f64 (+.f64 y z)))): 28 points increase in error, 7 points decrease in error
   (+.f64 (Rewrite<= unsub-neg_binary64 (+.f64 x (neg.f64 (tan.f64 a)))) (tan.f64 (+.f64 y z))): 0 points increase in error, 0 points decrease in error
   (Rewrite<= associate-+r+_binary64 (+.f64 x (+.f64 (neg.f64 (tan.f64 a)) (tan.f64 (+.f64 y z))))): 7 points increase in error, 28 points decrease in error
   (+.f64 x (Rewrite<= +-commutative_binary64 (+.f64 (tan.f64 (+.f64 y z)) (neg.f64 (tan.f64 a))))): 0 points increase in error, 0 points decrease in error
   (+.f64 x (Rewrite<= sub-neg_binary64 (-.f64 (tan.f64 (+.f64 y z)) (tan.f64 a)))): 0 points increase in error, 0 points decrease in error

3. Applied egg-rr 0.2

   \[\leadsto x - \left(\tan a - \color{blue}{\left(\tan y + \tan z\right) \cdot \frac{1}{1 - \tan y \cdot \tan z}}\right) \]

4. Simplified 0.2

   \[\leadsto x - \left(\tan a - \color{blue}{\frac{\tan y + \tan z}{1 - \tan y \cdot \tan z}}\right) \]
   Proof
   (/.f64 (+.f64 (tan.f64 y) (tan.f64 z)) (-.f64 1 (*.f64 (tan.f64 y) (tan.f64 z)))): 0 points increase in error, 0 points decrease in error
   (/.f64 (Rewrite<= *-rgt-identity_binary64 (*.f64 (+.f64 (tan.f64 y) (tan.f64 z)) 1)) (-.f64 1 (*.f64 (tan.f64 y) (tan.f64 z)))): 0 points increase in error, 0 points decrease in error
   (Rewrite<= associate-*r/_binary64 (*.f64 (+.f64 (tan.f64 y) (tan.f64 z)) (/.f64 1 (-.f64 1 (*.f64 (tan.f64 y) (tan.f64 z)))))): 10 points increase in error, 6 points decrease in error

5. Applied egg-rr 0.2

   \[\leadsto x - \left(\tan a - \frac{\tan y + \tan z}{1 - \color{blue}{\frac{\tan z \cdot \sin y}{\cos y}}}\right) \]

6. Final simplification 0.2

   \[\leadsto x + \left(\frac{\tan y + \tan z}{1 - \frac{\tan z \cdot \sin y}{\cos y}} - \tan a\right) \]

Alternatives

Alternative 1
Error	7.0
Cost	45768

\[\begin{array}{l} t_0 := \tan \left(y + z\right)\\ \mathbf{if}\;\tan a \leq -0.0015:\\ \;\;\;\;x + \left(t_0 + \frac{-1}{\frac{\cos a}{\sin a}}\right)\\ \mathbf{elif}\;\tan a \leq 5 \cdot 10^{-17}:\\ \;\;\;\;\mathsf{fma}\left(\tan y + \tan z, \frac{1}{1 - \tan y \cdot \tan z}, x\right)\\ \mathbf{else}:\\ \;\;\;\;x + \left(t_0 + \frac{-1}{\frac{1}{\tan a}}\right)\\ \end{array} \]

Alternative 2
Error	7.0
Cost	45704

\[\begin{array}{l} t_0 := \tan \left(y + z\right)\\ \mathbf{if}\;\tan a \leq -0.0015:\\ \;\;\;\;x + \left(t_0 + \frac{-1}{\frac{\cos a}{\sin a}}\right)\\ \mathbf{elif}\;\tan a \leq 5 \cdot 10^{-17}:\\ \;\;\;\;x + \frac{\tan y + \tan z}{\mathsf{fma}\left(\tan y, -\tan z, 1\right)}\\ \mathbf{else}:\\ \;\;\;\;x + \left(t_0 + \frac{-1}{\frac{1}{\tan a}}\right)\\ \end{array} \]

Alternative 3
Error	7.0
Cost	39496

\[\begin{array}{l} t_0 := \tan \left(y + z\right)\\ \mathbf{if}\;\tan a \leq -0.0015:\\ \;\;\;\;x + \left(t_0 + \frac{-1}{\frac{\cos a}{\sin a}}\right)\\ \mathbf{elif}\;\tan a \leq 5 \cdot 10^{-17}:\\ \;\;\;\;x + \frac{1}{\frac{1 - \tan y \cdot \tan z}{\tan y + \tan z}}\\ \mathbf{else}:\\ \;\;\;\;x + \left(t_0 + \frac{-1}{\frac{1}{\tan a}}\right)\\ \end{array} \]

Alternative 4
Error	7.0
Cost	39368

\[\begin{array}{l} t_0 := \tan \left(y + z\right)\\ \mathbf{if}\;\tan a \leq -0.0015:\\ \;\;\;\;x + \left(t_0 + \frac{-1}{\frac{\cos a}{\sin a}}\right)\\ \mathbf{elif}\;\tan a \leq 5 \cdot 10^{-17}:\\ \;\;\;\;x + \frac{\tan y + \tan z}{1 - \tan y \cdot \tan z}\\ \mathbf{else}:\\ \;\;\;\;x + \left(t_0 + \frac{-1}{\frac{1}{\tan a}}\right)\\ \end{array} \]

Alternative 5
Error	0.2
Cost	32832

\[x + \left(\frac{\tan y + \tan z}{1 - \tan y \cdot \tan z} - \tan a\right) \]

Alternative 6
Error	26.1
Cost	19784

\[\begin{array}{l} t_0 := x - \tan a\\ \mathbf{if}\;\tan a \leq -0.065:\\ \;\;\;\;t_0\\ \mathbf{elif}\;\tan a \leq 4 \cdot 10^{-23}:\\ \;\;\;\;x + \tan \left(y + z\right)\\ \mathbf{else}:\\ \;\;\;\;t_0\\ \end{array} \]

Alternative 7
Error	13.5
Cost	13504

\[x + \left(\tan \left(y + z\right) + \frac{-1}{\frac{1}{\tan a}}\right) \]

Alternative 8
Error	19.9
Cost	13384

\[\begin{array}{l} t_0 := \tan z + \left(x - \tan a\right)\\ \mathbf{if}\;a \leq -1.25 \cdot 10^{-14}:\\ \;\;\;\;t_0\\ \mathbf{elif}\;a \leq 880:\\ \;\;\;\;x + \left(\tan \left(y + z\right) + \frac{-1}{a \cdot -0.3333333333333333 + \frac{1}{a}}\right)\\ \mathbf{else}:\\ \;\;\;\;t_0\\ \end{array} \]

Alternative 9
Error	19.9
Cost	13384

\[\begin{array}{l} t_0 := x + \left(\tan z - \tan a\right)\\ \mathbf{if}\;a \leq -1.25 \cdot 10^{-14}:\\ \;\;\;\;t_0\\ \mathbf{elif}\;a \leq 880:\\ \;\;\;\;x + \left(\tan \left(y + z\right) + \frac{-1}{a \cdot -0.3333333333333333 + \frac{1}{a}}\right)\\ \mathbf{else}:\\ \;\;\;\;t_0\\ \end{array} \]

Alternative 10
Error	19.9
Cost	13384

\[\begin{array}{l} \mathbf{if}\;a \leq -1.25 \cdot 10^{-14}:\\ \;\;\;\;\left(x + \tan z\right) - \tan a\\ \mathbf{elif}\;a \leq 880:\\ \;\;\;\;x + \left(\tan \left(y + z\right) + \frac{-1}{a \cdot -0.3333333333333333 + \frac{1}{a}}\right)\\ \mathbf{else}:\\ \;\;\;\;x + \left(\tan z - \tan a\right)\\ \end{array} \]

Alternative 11
Error	13.5
Cost	13248

\[x + \left(\tan \left(y + z\right) - \tan a\right) \]

Alternative 12
Error	37.2
Cost	6592

\[x - \tan a \]

Alternative 13
Error	43.8
Cost	64

\[x \]

Reproduce

herbie shell --seed 2022332 
(FPCore (x y z a)
  :name "tan-example (used to crash)"
  :precision binary64
  :pre (and (and (and (or (== x 0.0) (and (<= 0.5884142 x) (<= x 505.5909))) (or (and (<= -1.796658e+308 y) (<= y -9.425585e-310)) (and (<= 1.284938e-309 y) (<= y 1.751224e+308)))) (or (and (<= -1.776707e+308 z) (<= z -8.599796e-310)) (and (<= 3.293145e-311 z) (<= z 1.725154e+308)))) (or (and (<= -1.796658e+308 a) (<= a -9.425585e-310)) (and (<= 1.284938e-309 a) (<= a 1.751224e+308))))
  (+ x (- (tan (+ y z)) (tan a))))