Average Error: 0.0 → 0.0
Time: 1.5s
Precision: binary64
\[e^{-\left(1 - x \cdot x\right)} \]
↓
\[e^{-1} \cdot {\left(e^{x}\right)}^{x} \]
(FPCore (x) :precision binary64 (exp (- (- 1.0 (* x x)))))
↓
(FPCore (x) :precision binary64 (* (exp -1.0) (pow (exp x) x)))
double code(double x) {
	return exp(-(1.0 - (x * x)));
}
↓
double code(double x) {
	return exp(-1.0) * pow(exp(x), x);
}

real(8) function code(x)
    real(8), intent (in) :: x
    code = exp(-(1.0d0 - (x * x)))
end function
↓
real(8) function code(x)
    real(8), intent (in) :: x
    code = exp((-1.0d0)) * (exp(x) ** x)
end function

public static double code(double x) {
	return Math.exp(-(1.0 - (x * x)));
}
↓
public static double code(double x) {
	return Math.exp(-1.0) * Math.pow(Math.exp(x), x);
}

def code(x):
	return math.exp(-(1.0 - (x * x)))
↓
def code(x):
	return math.exp(-1.0) * math.pow(math.exp(x), x)

function code(x)
	return exp(Float64(-Float64(1.0 - Float64(x * x))))
end
↓
function code(x)
	return Float64(exp(-1.0) * (exp(x) ^ x))
end

function tmp = code(x)
	tmp = exp(-(1.0 - (x * x)));
end
↓
function tmp = code(x)
	tmp = exp(-1.0) * (exp(x) ^ x);
end

code[x_] := N[Exp[(-N[(1.0 - N[(x * x), $MachinePrecision]), $MachinePrecision])], $MachinePrecision]
↓
code[x_] := N[(N[Exp[-1.0], $MachinePrecision] * N[Power[N[Exp[x], $MachinePrecision], x], $MachinePrecision]), $MachinePrecision]

e^{-\left(1 - x \cdot x\right)}
↓
e^{-1} \cdot {\left(e^{x}\right)}^{x}

Error

Bits error versus x

Try it out

Your Program's Arguments

Results

Enter valid numbers for all inputs

Derivation

  1. Initial program 0.0

    \[e^{-\left(1 - x \cdot x\right)} \]

  2. Simplified0.0

    \[\leadsto \color{blue}{e^{\mathsf{fma}\left(x, x, -1\right)}} \]

  3. Applied egg-rr0.0

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

  4. Final simplification0.0

    \[\leadsto e^{-1} \cdot {\left(e^{x}\right)}^{x} \]

Reproduce

herbie shell --seed 2022150 
(FPCore (x)
  :name "exp neg sub"
  :precision binary64
  (exp (- (- 1.0 (* x x)))))