ENA, Section 1.4, Mentioned, A

Average Error: 29.9 → 0.0

Time: 6.3s

Precision: binary64

Cost: 13120

\[-0.01 \leq x \land x \leq 0.01\]

Math

\[1 - \cos x \]

↓

\[\sin x \cdot \tan \left(\frac{x}{2}\right) \]

FPCore

(FPCore (x) :precision binary64 (- 1.0 (cos x)))

↓

(FPCore (x) :precision binary64 (* (sin x) (tan (/ x 2.0))))

C

double code(double x) {
	return 1.0 - cos(x);
}

↓

double code(double x) {
	return sin(x) * tan((x / 2.0));
}

Fortran

real(8) function code(x)
    real(8), intent (in) :: x
    code = 1.0d0 - cos(x)
end function

↓

real(8) function code(x)
    real(8), intent (in) :: x
    code = sin(x) * tan((x / 2.0d0))
end function

Java

public static double code(double x) {
	return 1.0 - Math.cos(x);
}

↓

public static double code(double x) {
	return Math.sin(x) * Math.tan((x / 2.0));
}

Python

def code(x):
	return 1.0 - math.cos(x)

↓

def code(x):
	return math.sin(x) * math.tan((x / 2.0))

Julia

function code(x)
	return Float64(1.0 - cos(x))
end

↓

function code(x)
	return Float64(sin(x) * tan(Float64(x / 2.0)))
end

MATLAB

function tmp = code(x)
	tmp = 1.0 - cos(x);
end

↓

function tmp = code(x)
	tmp = sin(x) * tan((x / 2.0));
end

Wolfram

code[x_] := N[(1.0 - N[Cos[x], $MachinePrecision]), $MachinePrecision]

↓

code[x_] := N[(N[Sin[x], $MachinePrecision] * N[Tan[N[(x / 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]

Target

Original	29.9
Target	0.0
Herbie	0.0

\[\frac{\sin x \cdot \sin x}{1 + \cos x} \]

Derivation

1. Initial program 29.9

   \[1 - \cos x \]

2. Applied egg-rr 0.0

   \[\leadsto \color{blue}{\frac{\sin x \cdot \sin x}{1 + \cos x}} \]

3. Taylor expanded in x around inf 0.0

   \[\leadsto \color{blue}{\frac{{\sin x}^{2}}{1 + \cos x}} \]

4. Simplified 0.0

   \[\leadsto \color{blue}{\sin x \cdot \tan \left(\frac{x}{2}\right)} \]

5. Final simplification 0.0

   \[\leadsto \sin x \cdot \tan \left(\frac{x}{2}\right) \]

Alternatives

Alternative 1
Error	0.0
Cost	960

\[\left(x \cdot x\right) \cdot \left(x \cdot \left(x \cdot -0.041666666666666664\right)\right) + \left(x \cdot x\right) \cdot 0.5 \]

Alternative 2
Error	0.2
Cost	320

\[x \cdot \left(x \cdot 0.5\right) \]

Reproduce

herbie shell --seed 2022228 
(FPCore (x)
  :name "ENA, Section 1.4, Mentioned, A"
  :precision binary64
  :pre (and (<= -0.01 x) (<= x 0.01))

  :herbie-target
  (/ (* (sin x) (sin x)) (+ 1.0 (cos x)))

  (- 1.0 (cos x)))