Linear.Quaternion:$ccosh from linear-1.19.1.3

Average Accuracy: 77.1% → 99.8%

Time: 10.2s

Precision: binary64

Cost: 13120

Math

\[\frac{\sin x \cdot \sinh y}{x} \]

↓

\[\frac{\sin x}{x} \cdot \sinh y \]

FPCore

(FPCore (x y) :precision binary64 (/ (* (sin x) (sinh y)) x))

↓

(FPCore (x y) :precision binary64 (* (/ (sin x) x) (sinh y)))

C

double code(double x, double y) {
	return (sin(x) * sinh(y)) / x;
}

↓

double code(double x, double y) {
	return (sin(x) / x) * sinh(y);
}

Fortran

real(8) function code(x, y)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    code = (sin(x) * sinh(y)) / x
end function

↓

real(8) function code(x, y)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    code = (sin(x) / x) * sinh(y)
end function

Java

public static double code(double x, double y) {
	return (Math.sin(x) * Math.sinh(y)) / x;
}

↓

public static double code(double x, double y) {
	return (Math.sin(x) / x) * Math.sinh(y);
}

Python

def code(x, y):
	return (math.sin(x) * math.sinh(y)) / x

↓

def code(x, y):
	return (math.sin(x) / x) * math.sinh(y)

Julia

function code(x, y)
	return Float64(Float64(sin(x) * sinh(y)) / x)
end

↓

function code(x, y)
	return Float64(Float64(sin(x) / x) * sinh(y))
end

MATLAB

function tmp = code(x, y)
	tmp = (sin(x) * sinh(y)) / x;
end

↓

function tmp = code(x, y)
	tmp = (sin(x) / x) * sinh(y);
end

Wolfram

code[x_, y_] := N[(N[(N[Sin[x], $MachinePrecision] * N[Sinh[y], $MachinePrecision]), $MachinePrecision] / x), $MachinePrecision]

↓

code[x_, y_] := N[(N[(N[Sin[x], $MachinePrecision] / x), $MachinePrecision] * N[Sinh[y], $MachinePrecision]), $MachinePrecision]

Target

Original	77.1%
Target	99.7%
Herbie	99.8%

\[\sin x \cdot \frac{\sinh y}{x} \]

Derivation

1. Initial program 77.1%

   \[\frac{\sin x \cdot \sinh y}{x} \]

2. Simplified 99.8%

   \[\leadsto \color{blue}{\frac{\sin x}{x} \cdot \sinh y} \]
   Proof

   [Start] 77.1	\[ \frac{\sin x \cdot \sinh y}{x} \]
   associate-*l/ [<=] 99.8	\[ \color{blue}{\frac{\sin x}{x} \cdot \sinh y} \]

3. Final simplification 99.8%

   \[\leadsto \frac{\sin x}{x} \cdot \sinh y \]

Alternatives

Alternative 1
Accuracy	99.7%
Cost	13120

\[\sin x \cdot \frac{\sinh y}{x} \]

Alternative 2
Accuracy	98.0%
Cost	6720

\[\sin x \cdot \frac{y}{x} \]

Alternative 3
Accuracy	98.1%
Cost	6720

\[\frac{\sin x}{x} \cdot y \]

Alternative 4
Accuracy	72.1%
Cost	320

\[x \cdot \frac{y}{x} \]

Alternative 5
Accuracy	52.0%
Cost	64

\[y \]

Reproduce

herbie shell --seed 2023151 
(FPCore (x y)
  :name "Linear.Quaternion:$ccosh from linear-1.19.1.3"
  :precision binary64

  :herbie-target
  (* (sin x) (/ (sinh y) x))

  (/ (* (sin x) (sinh y)) x))