b parameter of renormalized beta distribution

Average Error: 0.1 → 0.1

Time: 5.9s

Precision: binary64

Cost: 832

\[\left(0 < m \land 0 < v\right) \land v < 0.25\]

Math

\[\left(\frac{m \cdot \left(1 - m\right)}{v} - 1\right) \cdot \left(1 - m\right) \]

↓

\[\left(1 - m\right) \cdot \left(\frac{m}{v} \cdot \left(1 - m\right) + -1\right) \]

FPCore

(FPCore (m v) :precision binary64 (* (- (/ (* m (- 1.0 m)) v) 1.0) (- 1.0 m)))

↓

(FPCore (m v) :precision binary64 (* (- 1.0 m) (+ (* (/ m v) (- 1.0 m)) -1.0)))

C

double code(double m, double v) {
	return (((m * (1.0 - m)) / v) - 1.0) * (1.0 - m);
}

↓

double code(double m, double v) {
	return (1.0 - m) * (((m / v) * (1.0 - m)) + -1.0);
}

Fortran

real(8) function code(m, v)
    real(8), intent (in) :: m
    real(8), intent (in) :: v
    code = (((m * (1.0d0 - m)) / v) - 1.0d0) * (1.0d0 - m)
end function

↓

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

Java

public static double code(double m, double v) {
	return (((m * (1.0 - m)) / v) - 1.0) * (1.0 - m);
}

↓

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

Python

def code(m, v):
	return (((m * (1.0 - m)) / v) - 1.0) * (1.0 - m)

↓

def code(m, v):
	return (1.0 - m) * (((m / v) * (1.0 - m)) + -1.0)

Julia

function code(m, v)
	return Float64(Float64(Float64(Float64(m * Float64(1.0 - m)) / v) - 1.0) * Float64(1.0 - m))
end

↓

function code(m, v)
	return Float64(Float64(1.0 - m) * Float64(Float64(Float64(m / v) * Float64(1.0 - m)) + -1.0))
end

MATLAB

function tmp = code(m, v)
	tmp = (((m * (1.0 - m)) / v) - 1.0) * (1.0 - m);
end

↓

function tmp = code(m, v)
	tmp = (1.0 - m) * (((m / v) * (1.0 - m)) + -1.0);
end

Wolfram

code[m_, v_] := N[(N[(N[(N[(m * N[(1.0 - m), $MachinePrecision]), $MachinePrecision] / v), $MachinePrecision] - 1.0), $MachinePrecision] * N[(1.0 - m), $MachinePrecision]), $MachinePrecision]

↓

code[m_, v_] := N[(N[(1.0 - m), $MachinePrecision] * N[(N[(N[(m / v), $MachinePrecision] * N[(1.0 - m), $MachinePrecision]), $MachinePrecision] + -1.0), $MachinePrecision]), $MachinePrecision]

Derivation

1. Initial program 0.1

   \[\left(\frac{m \cdot \left(1 - m\right)}{v} - 1\right) \cdot \left(1 - m\right) \]

2. Applied egg-rr 0.1

   \[\leadsto \left(\color{blue}{\frac{m}{v} \cdot \left(1 - m\right)} - 1\right) \cdot \left(1 - m\right) \]

3. Final simplification 0.1

   \[\leadsto \left(1 - m\right) \cdot \left(\frac{m}{v} \cdot \left(1 - m\right) + -1\right) \]

Alternatives

Alternative 1
Error	0.3
Cost	836

\[\begin{array}{l} \mathbf{if}\;m \leq 6.994743418164479 \cdot 10^{-20}:\\ \;\;\;\;\frac{m}{v} - \left(1 - m\right)\\ \mathbf{else}:\\ \;\;\;\;\frac{1 - m}{\frac{v}{m \cdot \left(1 - m\right)}}\\ \end{array} \]

Alternative 2
Error	0.3
Cost	836

\[\begin{array}{l} \mathbf{if}\;m \leq 3.3384560737346664 \cdot 10^{-22}:\\ \;\;\;\;\frac{m}{v} - \left(1 - m\right)\\ \mathbf{else}:\\ \;\;\;\;\frac{m \cdot \left(1 - m\right)}{\frac{v}{1 - m}}\\ \end{array} \]

Alternative 3
Error	2.4
Cost	708

\[\begin{array}{l} \mathbf{if}\;m \leq 2.1035662616266904:\\ \;\;\;\;\frac{m}{v} - \left(1 - m\right)\\ \mathbf{else}:\\ \;\;\;\;\frac{m + -1}{\frac{v}{m \cdot m}}\\ \end{array} \]

Alternative 4
Error	1.9
Cost	708

\[\begin{array}{l} \mathbf{if}\;m \leq 2.1035662616266904:\\ \;\;\;\;\frac{m}{v} - \left(1 - m\right)\\ \mathbf{else}:\\ \;\;\;\;\left(m \cdot \frac{m}{v}\right) \cdot \left(m + -2\right)\\ \end{array} \]

Alternative 5
Error	2.3
Cost	708

\[\begin{array}{l} \mathbf{if}\;m \leq 6.282490693267588 \cdot 10^{-7}:\\ \;\;\;\;\left(1 - m\right) \cdot \left(\frac{m}{v} + -1\right)\\ \mathbf{else}:\\ \;\;\;\;\left(m \cdot \frac{m}{v}\right) \cdot \left(m + -2\right)\\ \end{array} \]

Alternative 6
Error	9.9
Cost	448

\[\frac{m}{v} - \left(1 - m\right) \]

Alternative 7
Error	24.3
Cost	324

\[\begin{array}{l} \mathbf{if}\;v \leq 9.875192348832731 \cdot 10^{-145}:\\ \;\;\;\;\frac{m}{v}\\ \mathbf{else}:\\ \;\;\;\;-1\\ \end{array} \]

Alternative 8
Error	24.1
Cost	324

\[\begin{array}{l} \mathbf{if}\;v \leq 9.875192348832731 \cdot 10^{-145}:\\ \;\;\;\;\frac{m}{v}\\ \mathbf{else}:\\ \;\;\;\;m + -1\\ \end{array} \]

Alternative 9
Error	37.4
Cost	64

\[-1 \]

Reproduce

herbie shell --seed 2022298 
(FPCore (m v)
  :name "b parameter of renormalized beta distribution"
  :precision binary64
  :pre (and (and (< 0.0 m) (< 0.0 v)) (< v 0.25))
  (* (- (/ (* m (- 1.0 m)) v) 1.0) (- 1.0 m)))