Rosa's DopplerBench

Average Error: 18.5 → 1.4

Time: 7.3s

Precision: binary64

Cost: 704

Math

\[\frac{\left(-t1\right) \cdot v}{\left(t1 + u\right) \cdot \left(t1 + u\right)} \]

↓

\[\frac{\frac{v}{t1 + u}}{-1 - \frac{u}{t1}} \]

FPCore

(FPCore (u v t1) :precision binary64 (/ (* (- t1) v) (* (+ t1 u) (+ t1 u))))

↓

(FPCore (u v t1) :precision binary64 (/ (/ v (+ t1 u)) (- -1.0 (/ u t1))))

C

double code(double u, double v, double t1) {
	return (-t1 * v) / ((t1 + u) * (t1 + u));
}

↓

double code(double u, double v, double t1) {
	return (v / (t1 + u)) / (-1.0 - (u / t1));
}

Fortran

real(8) function code(u, v, t1)
    real(8), intent (in) :: u
    real(8), intent (in) :: v
    real(8), intent (in) :: t1
    code = (-t1 * v) / ((t1 + u) * (t1 + u))
end function

↓

real(8) function code(u, v, t1)
    real(8), intent (in) :: u
    real(8), intent (in) :: v
    real(8), intent (in) :: t1
    code = (v / (t1 + u)) / ((-1.0d0) - (u / t1))
end function

Java

public static double code(double u, double v, double t1) {
	return (-t1 * v) / ((t1 + u) * (t1 + u));
}

↓

public static double code(double u, double v, double t1) {
	return (v / (t1 + u)) / (-1.0 - (u / t1));
}

Python

def code(u, v, t1):
	return (-t1 * v) / ((t1 + u) * (t1 + u))

↓

def code(u, v, t1):
	return (v / (t1 + u)) / (-1.0 - (u / t1))

Julia

function code(u, v, t1)
	return Float64(Float64(Float64(-t1) * v) / Float64(Float64(t1 + u) * Float64(t1 + u)))
end

↓

function code(u, v, t1)
	return Float64(Float64(v / Float64(t1 + u)) / Float64(-1.0 - Float64(u / t1)))
end

MATLAB

function tmp = code(u, v, t1)
	tmp = (-t1 * v) / ((t1 + u) * (t1 + u));
end

↓

function tmp = code(u, v, t1)
	tmp = (v / (t1 + u)) / (-1.0 - (u / t1));
end

Wolfram

code[u_, v_, t1_] := N[(N[((-t1) * v), $MachinePrecision] / N[(N[(t1 + u), $MachinePrecision] * N[(t1 + u), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]

↓

code[u_, v_, t1_] := N[(N[(v / N[(t1 + u), $MachinePrecision]), $MachinePrecision] / N[(-1.0 - N[(u / t1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]

Derivation

1. Initial program 18.5

   \[\frac{\left(-t1\right) \cdot v}{\left(t1 + u\right) \cdot \left(t1 + u\right)} \]

2. Simplified 1.4

   \[\leadsto \color{blue}{\frac{\frac{v}{t1 + u}}{-1 - \frac{u}{t1}}} \]
   Proof
   (/.f64 (/.f64 v (+.f64 t1 u)) (-.f64 -1 (/.f64 u t1))): 0 points increase in error, 0 points decrease in error
   (/.f64 (/.f64 v (+.f64 t1 u)) (-.f64 (Rewrite<= metadata-eval (neg.f64 1)) (/.f64 u t1))): 0 points increase in error, 0 points decrease in error
   (/.f64 (/.f64 v (+.f64 t1 u)) (-.f64 (neg.f64 (Rewrite<= *-inverses_binary64 (/.f64 t1 t1))) (/.f64 u t1))): 0 points increase in error, 0 points decrease in error
   (/.f64 (/.f64 v (+.f64 t1 u)) (-.f64 (Rewrite<= distribute-frac-neg_binary64 (/.f64 (neg.f64 t1) t1)) (/.f64 u t1))): 0 points increase in error, 0 points decrease in error
   (/.f64 (/.f64 v (+.f64 t1 u)) (Rewrite<= div-sub_binary64 (/.f64 (-.f64 (neg.f64 t1) u) t1))): 5 points increase in error, 1 points decrease in error
   (/.f64 (/.f64 v (+.f64 t1 u)) (/.f64 (Rewrite<= unsub-neg_binary64 (+.f64 (neg.f64 t1) (neg.f64 u))) t1)): 0 points increase in error, 0 points decrease in error
   (/.f64 (/.f64 v (+.f64 t1 u)) (/.f64 (Rewrite=> distribute-neg-out_binary64 (neg.f64 (+.f64 t1 u))) t1)): 0 points increase in error, 0 points decrease in error
   (/.f64 (/.f64 v (+.f64 t1 u)) (/.f64 (Rewrite=> neg-mul-1_binary64 (*.f64 -1 (+.f64 t1 u))) t1)): 0 points increase in error, 0 points decrease in error
   (/.f64 (/.f64 v (+.f64 t1 u)) (/.f64 (*.f64 -1 (+.f64 t1 u)) (Rewrite<= remove-double-neg_binary64 (neg.f64 (neg.f64 t1))))): 0 points increase in error, 0 points decrease in error
   (/.f64 (/.f64 v (+.f64 t1 u)) (/.f64 (*.f64 -1 (+.f64 t1 u)) (Rewrite=> neg-mul-1_binary64 (*.f64 -1 (neg.f64 t1))))): 0 points increase in error, 0 points decrease in error
   (/.f64 (/.f64 v (+.f64 t1 u)) (Rewrite=> times-frac_binary64 (*.f64 (/.f64 -1 -1) (/.f64 (+.f64 t1 u) (neg.f64 t1))))): 0 points increase in error, 0 points decrease in error
   (/.f64 (/.f64 v (+.f64 t1 u)) (*.f64 (Rewrite=> metadata-eval 1) (/.f64 (+.f64 t1 u) (neg.f64 t1)))): 0 points increase in error, 0 points decrease in error
   (/.f64 (/.f64 v (+.f64 t1 u)) (Rewrite=> *-lft-identity_binary64 (/.f64 (+.f64 t1 u) (neg.f64 t1)))): 0 points increase in error, 0 points decrease in error
   (/.f64 (/.f64 v (+.f64 t1 u)) (/.f64 (+.f64 t1 u) (Rewrite=> neg-mul-1_binary64 (*.f64 -1 t1)))): 0 points increase in error, 0 points decrease in error
   (/.f64 (/.f64 v (+.f64 t1 u)) (Rewrite<= associate-/l/_binary64 (/.f64 (/.f64 (+.f64 t1 u) t1) -1))): 0 points increase in error, 0 points decrease in error
   (Rewrite<= associate-/l*_binary64 (/.f64 (*.f64 (/.f64 v (+.f64 t1 u)) -1) (/.f64 (+.f64 t1 u) t1))): 0 points increase in error, 0 points decrease in error
   (Rewrite<= associate-*r/_binary64 (*.f64 (/.f64 v (+.f64 t1 u)) (/.f64 -1 (/.f64 (+.f64 t1 u) t1)))): 9 points increase in error, 10 points decrease in error
   (*.f64 (/.f64 v (+.f64 t1 u)) (Rewrite<= associate-/l*_binary64 (/.f64 (*.f64 -1 t1) (+.f64 t1 u)))): 5 points increase in error, 7 points decrease in error
   (*.f64 (/.f64 v (+.f64 t1 u)) (/.f64 (Rewrite<= neg-mul-1_binary64 (neg.f64 t1)) (+.f64 t1 u))): 0 points increase in error, 0 points decrease in error
   (Rewrite<= times-frac_binary64 (/.f64 (*.f64 v (neg.f64 t1)) (*.f64 (+.f64 t1 u) (+.f64 t1 u)))): 89 points increase in error, 11 points decrease in error
   (/.f64 (Rewrite<= *-commutative_binary64 (*.f64 (neg.f64 t1) v)) (*.f64 (+.f64 t1 u) (+.f64 t1 u))): 0 points increase in error, 0 points decrease in error

3. Final simplification 1.4

   \[\leadsto \frac{\frac{v}{t1 + u}}{-1 - \frac{u}{t1}} \]

Alternatives

Alternative 1
Error	13.9
Cost	1300

\[\begin{array}{l} t_1 := \frac{-v}{t1 + u \cdot 2}\\ t_2 := \frac{v}{t1 + u}\\ t_3 := \frac{-u}{t1}\\ \mathbf{if}\;u \leq -1.554068598124104 \cdot 10^{-53}:\\ \;\;\;\;t_2 \cdot \frac{-t1}{u}\\ \mathbf{elif}\;u \leq 2.028575570830355 \cdot 10^{-51}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;u \leq 4.0473127352540444 \cdot 10^{+30}:\\ \;\;\;\;\frac{t_2}{t_3}\\ \mathbf{elif}\;u \leq 8.0912493323973425 \cdot 10^{+62}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;u \leq 7.4111261144358745 \cdot 10^{+137}:\\ \;\;\;\;\frac{v}{u \cdot u} \cdot \left(-t1\right)\\ \mathbf{else}:\\ \;\;\;\;\frac{v \cdot \frac{1}{u}}{t_3}\\ \end{array} \]

Alternative 2
Error	31.5
Cost	784

\[\begin{array}{l} t_1 := \frac{-v}{t1}\\ \mathbf{if}\;t1 \leq -2.382174026442836 \cdot 10^{+49}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;t1 \leq -7.372444439511483 \cdot 10^{-53}:\\ \;\;\;\;\frac{v}{u}\\ \mathbf{elif}\;t1 \leq -5.103629354947841 \cdot 10^{-119}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;t1 \leq 1.407503942584769 \cdot 10^{-167}:\\ \;\;\;\;\frac{-v}{u}\\ \mathbf{else}:\\ \;\;\;\;t_1\\ \end{array} \]

Alternative 3
Error	20.2
Cost	712

\[\begin{array}{l} t_1 := \frac{t1}{\frac{u \cdot u}{v}}\\ \mathbf{if}\;u \leq -2.784332895547422 \cdot 10^{+105}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;u \leq 8.0912493323973425 \cdot 10^{+62}:\\ \;\;\;\;\frac{\frac{v}{t1 + u}}{-1}\\ \mathbf{else}:\\ \;\;\;\;t_1\\ \end{array} \]

Alternative 4
Error	24.8
Cost	384

\[\frac{-v}{t1 + u} \]

Reproduce

herbie shell --seed 2022289 
(FPCore (u v t1)
  :name "Rosa's DopplerBench"
  :precision binary64
  (/ (* (- t1) v) (* (+ t1 u) (+ t1 u))))