Logistic distribution

Average Error: 0.2 → 0.2

Time: 16.8s

Precision: binary32

Cost: 6944

\[0 \leq s \land s \leq 1.0651631\]

Math

\[\frac{e^{\frac{-\left|x\right|}{s}}}{\left(s \cdot \left(1 + e^{\frac{-\left|x\right|}{s}}\right)\right) \cdot \left(1 + e^{\frac{-\left|x\right|}{s}}\right)} \]

↓

\[\begin{array}{l} t_0 := e^{\frac{x}{s}}\\ \frac{1}{\left(s + \frac{1}{\frac{t_0}{s}}\right) \cdot \left(1 + t_0\right)} \end{array} \]

FPCore

(FPCore (x s)
 :precision binary32
 (/
  (exp (/ (- (fabs x)) s))
  (* (* s (+ 1.0 (exp (/ (- (fabs x)) s)))) (+ 1.0 (exp (/ (- (fabs x)) s))))))

↓

(FPCore (x s)
 :precision binary32
 (let* ((t_0 (exp (/ x s)))) (/ 1.0 (* (+ s (/ 1.0 (/ t_0 s))) (+ 1.0 t_0)))))

C

float code(float x, float s) {
	return expf((-fabsf(x) / s)) / ((s * (1.0f + expf((-fabsf(x) / s)))) * (1.0f + expf((-fabsf(x) / s))));
}

↓

float code(float x, float s) {
	float t_0 = expf((x / s));
	return 1.0f / ((s + (1.0f / (t_0 / s))) * (1.0f + t_0));
}

Fortran

real(4) function code(x, s)
    real(4), intent (in) :: x
    real(4), intent (in) :: s
    code = exp((-abs(x) / s)) / ((s * (1.0e0 + exp((-abs(x) / s)))) * (1.0e0 + exp((-abs(x) / s))))
end function

↓

real(4) function code(x, s)
    real(4), intent (in) :: x
    real(4), intent (in) :: s
    real(4) :: t_0
    t_0 = exp((x / s))
    code = 1.0e0 / ((s + (1.0e0 / (t_0 / s))) * (1.0e0 + t_0))
end function

Julia

function code(x, s)
	return Float32(exp(Float32(Float32(-abs(x)) / s)) / Float32(Float32(s * Float32(Float32(1.0) + exp(Float32(Float32(-abs(x)) / s)))) * Float32(Float32(1.0) + exp(Float32(Float32(-abs(x)) / s)))))
end

↓

function code(x, s)
	t_0 = exp(Float32(x / s))
	return Float32(Float32(1.0) / Float32(Float32(s + Float32(Float32(1.0) / Float32(t_0 / s))) * Float32(Float32(1.0) + t_0)))
end

MATLAB

function tmp = code(x, s)
	tmp = exp((-abs(x) / s)) / ((s * (single(1.0) + exp((-abs(x) / s)))) * (single(1.0) + exp((-abs(x) / s))));
end

↓

function tmp = code(x, s)
	t_0 = exp((x / s));
	tmp = single(1.0) / ((s + (single(1.0) / (t_0 / s))) * (single(1.0) + t_0));
end

Derivation

1. Initial program 0.2

   \[\frac{e^{\frac{-\left|x\right|}{s}}}{\left(s \cdot \left(1 + e^{\frac{-\left|x\right|}{s}}\right)\right) \cdot \left(1 + e^{\frac{-\left|x\right|}{s}}\right)} \]

2. Simplified 0.2

   \[\leadsto \color{blue}{\frac{1}{\left(s + \frac{s}{e^{\frac{\left|x\right|}{s}}}\right) \cdot \left(1 + e^{\frac{\left|x\right|}{s}}\right)}} \]
   Proof

   [Start] 0.2	\[ \frac{e^{\frac{-\left|x\right|}{s}}}{\left(s \cdot \left(1 + e^{\frac{-\left|x\right|}{s}}\right)\right) \cdot \left(1 + e^{\frac{-\left|x\right|}{s}}\right)} \]
   associate-/l/ [<=] 0.2	\[ \color{blue}{\frac{\frac{e^{\frac{-\left|x\right|}{s}}}{1 + e^{\frac{-\left|x\right|}{s}}}}{s \cdot \left(1 + e^{\frac{-\left|x\right|}{s}}\right)}} \]
   *-lft-identity [<=] 0.2	\[ \frac{\color{blue}{1 \cdot \frac{e^{\frac{-\left|x\right|}{s}}}{1 + e^{\frac{-\left|x\right|}{s}}}}}{s \cdot \left(1 + e^{\frac{-\left|x\right|}{s}}\right)} \]
   *-lft-identity [<=] 0.2	\[ \frac{1 \cdot \frac{e^{\frac{-\left|x\right|}{s}}}{\color{blue}{1 \cdot \left(1 + e^{\frac{-\left|x\right|}{s}}\right)}}}{s \cdot \left(1 + e^{\frac{-\left|x\right|}{s}}\right)} \]
   *-commutative [<=] 0.2	\[ \frac{1 \cdot \frac{e^{\frac{-\left|x\right|}{s}}}{\color{blue}{\left(1 + e^{\frac{-\left|x\right|}{s}}\right) \cdot 1}}}{s \cdot \left(1 + e^{\frac{-\left|x\right|}{s}}\right)} \]
   associate-*r/ [=>] 0.2	\[ \frac{\color{blue}{\frac{1 \cdot e^{\frac{-\left|x\right|}{s}}}{\left(1 + e^{\frac{-\left|x\right|}{s}}\right) \cdot 1}}}{s \cdot \left(1 + e^{\frac{-\left|x\right|}{s}}\right)} \]
   associate-/l* [=>] 0.2	\[ \frac{\color{blue}{\frac{1}{\frac{\left(1 + e^{\frac{-\left|x\right|}{s}}\right) \cdot 1}{e^{\frac{-\left|x\right|}{s}}}}}}{s \cdot \left(1 + e^{\frac{-\left|x\right|}{s}}\right)} \]
   associate-/l/ [=>] 0.2	\[ \color{blue}{\frac{1}{\left(s \cdot \left(1 + e^{\frac{-\left|x\right|}{s}}\right)\right) \cdot \frac{\left(1 + e^{\frac{-\left|x\right|}{s}}\right) \cdot 1}{e^{\frac{-\left|x\right|}{s}}}}} \]

3. Applied egg-rr 11.7

   \[\leadsto \frac{1}{\color{blue}{s + \left(\frac{s}{e^{\frac{x}{s}}} + e^{\frac{x}{s}} \cdot \left(s + \frac{s}{e^{\frac{x}{s}}}\right)\right)}} \]

4. Simplified 0.2

   \[\leadsto \frac{1}{\color{blue}{\left(s + \frac{s}{e^{\frac{x}{s}}}\right) \cdot \left(1 + e^{\frac{x}{s}}\right)}} \]
   Proof

   [Start] 11.7	\[ \frac{1}{s + \left(\frac{s}{e^{\frac{x}{s}}} + e^{\frac{x}{s}} \cdot \left(s + \frac{s}{e^{\frac{x}{s}}}\right)\right)} \]
   associate-+r+ [=>] 11.7	\[ \frac{1}{\color{blue}{\left(s + \frac{s}{e^{\frac{x}{s}}}\right) + e^{\frac{x}{s}} \cdot \left(s + \frac{s}{e^{\frac{x}{s}}}\right)}} \]
   distribute-rgt1-in [=>] 0.2	\[ \frac{1}{\color{blue}{\left(e^{\frac{x}{s}} + 1\right) \cdot \left(s + \frac{s}{e^{\frac{x}{s}}}\right)}} \]
   *-commutative [<=] 0.2	\[ \frac{1}{\color{blue}{\left(s + \frac{s}{e^{\frac{x}{s}}}\right) \cdot \left(e^{\frac{x}{s}} + 1\right)}} \]
   +-commutative [=>] 0.2	\[ \frac{1}{\left(s + \frac{s}{e^{\frac{x}{s}}}\right) \cdot \color{blue}{\left(1 + e^{\frac{x}{s}}\right)}} \]

5. Applied egg-rr 0.6

   \[\leadsto \frac{1}{\left(s + \color{blue}{e^{\log s - \frac{x}{s}}}\right) \cdot \left(1 + e^{\frac{x}{s}}\right)} \]

6. Applied egg-rr 0.2

   \[\leadsto \frac{1}{\left(s + \color{blue}{\frac{1}{\frac{e^{\frac{x}{s}}}{s}}}\right) \cdot \left(1 + e^{\frac{x}{s}}\right)} \]

7. Final simplification 0.2

   \[\leadsto \frac{1}{\left(s + \frac{1}{\frac{e^{\frac{x}{s}}}{s}}\right) \cdot \left(1 + e^{\frac{x}{s}}\right)} \]

Alternatives

Alternative 1
Error	0.2
Cost	6880

\[\begin{array}{l} t_0 := e^{\frac{x}{s}}\\ \frac{1}{\left(1 + t_0\right) \cdot \left(s + \frac{s}{t_0}\right)} \end{array} \]

Alternative 2
Error	1.2
Cost	6688

\[\frac{1}{s \cdot \left(3 + e^{\frac{\left|x\right|}{s}}\right)} \]

Alternative 3
Error	1.7
Cost	6656

\[\frac{e^{\frac{-\left|x\right|}{s}}}{s \cdot 4} \]

Alternative 4
Error	1.4
Cost	3620

\[\begin{array}{l} t_0 := e^{\frac{x}{s}}\\ \mathbf{if}\;x \leq -9.99999991097579 \cdot 10^{-38}:\\ \;\;\;\;\frac{0.5}{s + \frac{s}{t_0}}\\ \mathbf{else}:\\ \;\;\;\;\frac{1}{-3 - t_0} \cdot \frac{-1}{s}\\ \end{array} \]

Alternative 5
Error	6.6
Cost	3556

\[\begin{array}{l} \mathbf{if}\;x \leq -9.99999991097579 \cdot 10^{-38}:\\ \;\;\;\;\frac{0.5}{s + \frac{s}{e^{\frac{x}{s}}}}\\ \mathbf{else}:\\ \;\;\;\;\frac{1}{2 \cdot \left(s \cdot 2 + \left(0.5 \cdot \left(x \cdot \frac{x}{s}\right) - x\right)\right)}\\ \end{array} \]

Alternative 6
Error	6.3
Cost	3556

\[\begin{array}{l} \mathbf{if}\;x \leq -5.000000015855384 \cdot 10^{-29}:\\ \;\;\;\;\frac{0.5}{s + \frac{s}{e^{\frac{x}{s}}}}\\ \mathbf{else}:\\ \;\;\;\;\frac{1}{\mathsf{fma}\left(4, s, \frac{x}{\frac{s}{x}}\right)}\\ \end{array} \]

Alternative 7
Error	1.4
Cost	3556

\[\begin{array}{l} t_0 := e^{\frac{x}{s}}\\ \mathbf{if}\;x \leq -9.99999991097579 \cdot 10^{-38}:\\ \;\;\;\;\frac{0.5}{s + \frac{s}{t_0}}\\ \mathbf{else}:\\ \;\;\;\;\frac{\frac{1}{s}}{t_0 + 3}\\ \end{array} \]

Alternative 8
Error	6.8
Cost	3492

\[\begin{array}{l} \mathbf{if}\;x \leq -5.000000015855384 \cdot 10^{-29}:\\ \;\;\;\;\frac{\frac{e^{\frac{x}{s}}}{4}}{s}\\ \mathbf{else}:\\ \;\;\;\;\frac{1}{2 \cdot \left(s \cdot 2 + \left(0.5 \cdot \left(x \cdot \frac{x}{s}\right) - x\right)\right)}\\ \end{array} \]

Alternative 9
Error	8.1
Cost	3364

\[\begin{array}{l} \mathbf{if}\;x \leq -4.00000018325482 \cdot 10^{-18}:\\ \;\;\;\;e^{\frac{x}{s}}\\ \mathbf{else}:\\ \;\;\;\;\frac{1}{2 \cdot \left(s \cdot 2 + \left(0.5 \cdot \left(x \cdot \frac{x}{s}\right) - x\right)\right)}\\ \end{array} \]

Alternative 10
Error	11.9
Cost	544

\[\frac{1}{2 \cdot \left(s \cdot 2 + \left(0.5 \cdot \left(x \cdot \frac{x}{s}\right) - x\right)\right)} \]

Alternative 11
Error	22.7
Cost	288

\[\frac{1}{2 \cdot \left(s + \left(s - x\right)\right)} \]

Alternative 12
Error	22.7
Cost	224

\[\frac{0.5}{s \cdot 2 - x} \]

Alternative 13
Error	29.2
Cost	96

\[\frac{-0.5}{x} \]

Alternative 14
Error	23.3
Cost	96

\[\frac{0.25}{s} \]

Alternative 15
Error	29.3
Cost	32

\[1 \]

Reproduce

herbie shell --seed 2023067 
(FPCore (x s)
  :name "Logistic distribution"
  :precision binary32
  :pre (and (<= 0.0 s) (<= s 1.0651631))
  (/ (exp (/ (- (fabs x)) s)) (* (* s (+ 1.0 (exp (/ (- (fabs x)) s)))) (+ 1.0 (exp (/ (- (fabs x)) s))))))