Average Error: 0.0 → 0.0
Time: 7.9s
Precision: 64
\[x \cdot \left(1 - x \cdot 0.5\right)\]
↓
\[x \cdot 1 + \left(-0.5 \cdot {x}^{2}\right)\]
x \cdot \left(1 - x \cdot 0.5\right)
↓
x \cdot 1 + \left(-0.5 \cdot {x}^{2}\right)
double f(double x) {
        double r36559 = x;
        double r36560 = 1.0;
        double r36561 = 0.5;
        double r36562 = r36559 * r36561;
        double r36563 = r36560 - r36562;
        double r36564 = r36559 * r36563;
        return r36564;
}
↓
double f(double x) {
        double r36565 = x;
        double r36566 = 1.0;
        double r36567 = r36565 * r36566;
        double r36568 = 0.5;
        double r36569 = 2.0;
        double r36570 = pow(r36565, r36569);
        double r36571 = r36568 * r36570;
        double r36572 = -r36571;
        double r36573 = r36567 + r36572;
        return r36573;
}

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

    \[x \cdot \left(1 - x \cdot 0.5\right)\]
  2. Using strategy rm

  3. Applied sub-neg0.0

    \[\leadsto x \cdot \color{blue}{\left(1 + \left(-x \cdot 0.5\right)\right)}\]

  4. Applied distribute-lft-in0.0

    \[\leadsto \color{blue}{x \cdot 1 + x \cdot \left(-x \cdot 0.5\right)}\]

  5. Simplified0.0

    \[\leadsto x \cdot 1 + \color{blue}{\left(-0.5 \cdot {x}^{2}\right)}\]

  6. Final simplification0.0

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

Reproduce

herbie shell --seed 2019304 
(FPCore (x)
  :name "Numeric.SpecFunctions:log1p from math-functions-0.1.5.2, B"
  :precision binary64
  (* x (- 1 (* x 0.5))))