| Alternative 1 | |
|---|---|
| Error | 1.0 |
| Cost | 19648 |
\[\frac{b}{1 + e^{a}} + \mathsf{log1p}\left(e^{a}\right)
\]
(FPCore (a b) :precision binary64 (log (+ (exp a) (exp b))))
(FPCore (a b)
:precision binary64
(let* ((t_0 (+ 1.0 (exp a))))
(+
(/ b t_0)
(fma (* b b) (+ (/ 0.5 t_0) (/ -0.5 (pow t_0 2.0))) (log1p (exp a))))))double code(double a, double b) {
return log((exp(a) + exp(b)));
}
double code(double a, double b) {
double t_0 = 1.0 + exp(a);
return (b / t_0) + fma((b * b), ((0.5 / t_0) + (-0.5 / pow(t_0, 2.0))), log1p(exp(a)));
}
function code(a, b) return log(Float64(exp(a) + exp(b))) end
function code(a, b) t_0 = Float64(1.0 + exp(a)) return Float64(Float64(b / t_0) + fma(Float64(b * b), Float64(Float64(0.5 / t_0) + Float64(-0.5 / (t_0 ^ 2.0))), log1p(exp(a)))) end
code[a_, b_] := N[Log[N[(N[Exp[a], $MachinePrecision] + N[Exp[b], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]
code[a_, b_] := Block[{t$95$0 = N[(1.0 + N[Exp[a], $MachinePrecision]), $MachinePrecision]}, N[(N[(b / t$95$0), $MachinePrecision] + N[(N[(b * b), $MachinePrecision] * N[(N[(0.5 / t$95$0), $MachinePrecision] + N[(-0.5 / N[Power[t$95$0, 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[Log[1 + N[Exp[a], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\log \left(e^{a} + e^{b}\right)
\begin{array}{l}
t_0 := 1 + e^{a}\\
\frac{b}{t_0} + \mathsf{fma}\left(b \cdot b, \frac{0.5}{t_0} + \frac{-0.5}{{t_0}^{2}}, \mathsf{log1p}\left(e^{a}\right)\right)
\end{array}
Initial program 29.7
Taylor expanded in b around 0 1.0
Simplified0.9
[Start]1.0 | \[ \log \left(1 + e^{a}\right) + \left(0.5 \cdot \left(\left(\frac{1}{1 + e^{a}} - \frac{1}{{\left(1 + e^{a}\right)}^{2}}\right) \cdot {b}^{2}\right) + \frac{b}{1 + e^{a}}\right)
\] |
|---|---|
associate-+r+ [=>]1.0 | \[ \color{blue}{\left(\log \left(1 + e^{a}\right) + 0.5 \cdot \left(\left(\frac{1}{1 + e^{a}} - \frac{1}{{\left(1 + e^{a}\right)}^{2}}\right) \cdot {b}^{2}\right)\right) + \frac{b}{1 + e^{a}}}
\] |
+-commutative [=>]1.0 | \[ \color{blue}{\frac{b}{1 + e^{a}} + \left(\log \left(1 + e^{a}\right) + 0.5 \cdot \left(\left(\frac{1}{1 + e^{a}} - \frac{1}{{\left(1 + e^{a}\right)}^{2}}\right) \cdot {b}^{2}\right)\right)}
\] |
+-commutative [=>]1.0 | \[ \frac{b}{1 + e^{a}} + \color{blue}{\left(0.5 \cdot \left(\left(\frac{1}{1 + e^{a}} - \frac{1}{{\left(1 + e^{a}\right)}^{2}}\right) \cdot {b}^{2}\right) + \log \left(1 + e^{a}\right)\right)}
\] |
associate-*r* [=>]1.0 | \[ \frac{b}{1 + e^{a}} + \left(\color{blue}{\left(0.5 \cdot \left(\frac{1}{1 + e^{a}} - \frac{1}{{\left(1 + e^{a}\right)}^{2}}\right)\right) \cdot {b}^{2}} + \log \left(1 + e^{a}\right)\right)
\] |
*-commutative [=>]1.0 | \[ \frac{b}{1 + e^{a}} + \left(\color{blue}{{b}^{2} \cdot \left(0.5 \cdot \left(\frac{1}{1 + e^{a}} - \frac{1}{{\left(1 + e^{a}\right)}^{2}}\right)\right)} + \log \left(1 + e^{a}\right)\right)
\] |
fma-def [=>]1.0 | \[ \frac{b}{1 + e^{a}} + \color{blue}{\mathsf{fma}\left({b}^{2}, 0.5 \cdot \left(\frac{1}{1 + e^{a}} - \frac{1}{{\left(1 + e^{a}\right)}^{2}}\right), \log \left(1 + e^{a}\right)\right)}
\] |
Final simplification0.9
| Alternative 1 | |
|---|---|
| Error | 1.0 |
| Cost | 19648 |
| Alternative 2 | |
|---|---|
| Error | 1.4 |
| Cost | 19392 |
| Alternative 3 | |
|---|---|
| Error | 2.6 |
| Cost | 12992 |
| Alternative 4 | |
|---|---|
| Error | 31.6 |
| Cost | 12864 |
| Alternative 5 | |
|---|---|
| Error | 32.4 |
| Cost | 6720 |
| Alternative 6 | |
|---|---|
| Error | 32.5 |
| Cost | 6592 |
| Alternative 7 | |
|---|---|
| Error | 32.9 |
| Cost | 6464 |
| Alternative 8 | |
|---|---|
| Error | 62.3 |
| Cost | 192 |
| Alternative 9 | |
|---|---|
| Error | 61.2 |
| Cost | 192 |
herbie shell --seed 2023016
(FPCore (a b)
:name "symmetry log of sum of exp"
:precision binary64
(log (+ (exp a) (exp b))))