# ?

Average Error: 0.0 → 0.0
Time: 1.9s
Precision: binary64
Cost: 320

# ?

$0 \leq p \land p \leq 1$
$\frac{1 - p}{p}$
$\frac{1 - p}{p}$
(FPCore (p) :precision binary64 (/ (- 1.0 p) p))
(FPCore (p) :precision binary64 (/ (- 1.0 p) p))
double code(double p) {
return (1.0 - p) / p;
}

double code(double p) {
return (1.0 - p) / p;
}

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

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

public static double code(double p) {
return (1.0 - p) / p;
}

public static double code(double p) {
return (1.0 - p) / p;
}

def code(p):
return (1.0 - p) / p

def code(p):
return (1.0 - p) / p

function code(p)
return Float64(Float64(1.0 - p) / p)
end

function code(p)
return Float64(Float64(1.0 - p) / p)
end

function tmp = code(p)
tmp = (1.0 - p) / p;
end

function tmp = code(p)
tmp = (1.0 - p) / p;
end

code[p_] := N[(N[(1.0 - p), $MachinePrecision] / p),$MachinePrecision]

code[p_] := N[(N[(1.0 - p), $MachinePrecision] / p),$MachinePrecision]

\frac{1 - p}{p}

\frac{1 - p}{p}


# Try it out?

Results

 In Out
Enter valid numbers for all inputs

# Derivation?

1. Initial program 0.0

$\frac{1 - p}{p}$
2. Final simplification0.0

$\leadsto \frac{1 - p}{p}$

# Reproduce?

herbie shell --seed 1
(FPCore (p)
:name "(1-p)/p"
:precision binary64
:pre (and (<= 0.0 p) (<= p 1.0))
(/ (- 1.0 p) p))