\[x - \frac{\log \left(\left(1 - y\right) + y \cdot e^{z}\right)}{t}
\]
↓
\[x - \frac{\mathsf{log1p}\left(y \cdot \mathsf{expm1}\left(z\right)\right)}{t}
\]
(FPCore (x y z t)
:precision binary64
(- x (/ (log (+ (- 1.0 y) (* y (exp z)))) t)))
↓
(FPCore (x y z t) :precision binary64 (- x (/ (log1p (* y (expm1 z))) t)))
double code(double x, double y, double z, double t) {
return x - (log(((1.0 - y) + (y * exp(z)))) / t);
}
↓
double code(double x, double y, double z, double t) {
return x - (log1p((y * expm1(z))) / t);
}
public static double code(double x, double y, double z, double t) {
return x - (Math.log(((1.0 - y) + (y * Math.exp(z)))) / t);
}
↓
public static double code(double x, double y, double z, double t) {
return x - (Math.log1p((y * Math.expm1(z))) / t);
}
def code(x, y, z, t):
return x - (math.log(((1.0 - y) + (y * math.exp(z)))) / t)
↓
def code(x, y, z, t):
return x - (math.log1p((y * math.expm1(z))) / t)
function code(x, y, z, t)
return Float64(x - Float64(log(Float64(Float64(1.0 - y) + Float64(y * exp(z)))) / t))
end
↓
function code(x, y, z, t)
return Float64(x - Float64(log1p(Float64(y * expm1(z))) / t))
end
code[x_, y_, z_, t_] := N[(x - N[(N[Log[N[(N[(1.0 - y), $MachinePrecision] + N[(y * N[Exp[z], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / t), $MachinePrecision]), $MachinePrecision]
↓
code[x_, y_, z_, t_] := N[(x - N[(N[Log[1 + N[(y * N[(Exp[z] - 1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / t), $MachinePrecision]), $MachinePrecision]
x - \frac{\log \left(\left(1 - y\right) + y \cdot e^{z}\right)}{t}
↓
x - \frac{\mathsf{log1p}\left(y \cdot \mathsf{expm1}\left(z\right)\right)}{t}
Alternatives
| Alternative 1 |
|---|
| Error | 9.1 |
|---|
| Cost | 13580 |
|---|
\[\begin{array}{l}
t_1 := y \cdot \mathsf{expm1}\left(z\right)\\
t_2 := \frac{-\mathsf{log1p}\left(t_1\right)}{t}\\
\mathbf{if}\;y \leq -5.4 \cdot 10^{+216}:\\
\;\;\;\;t_2\\
\mathbf{elif}\;y \leq -3 \cdot 10^{+174}:\\
\;\;\;\;x\\
\mathbf{elif}\;y \leq -1.1 \cdot 10^{+152}:\\
\;\;\;\;t_2\\
\mathbf{else}:\\
\;\;\;\;x - \frac{t_1}{t}\\
\end{array}
\]
| Alternative 2 |
|---|
| Error | 8.6 |
|---|
| Cost | 6980 |
|---|
\[\begin{array}{l}
\mathbf{if}\;y \leq -1.9 \cdot 10^{+73}:\\
\;\;\;\;x\\
\mathbf{else}:\\
\;\;\;\;x - y \cdot \frac{\mathsf{expm1}\left(z\right)}{t}\\
\end{array}
\]
| Alternative 3 |
|---|
| Error | 9.0 |
|---|
| Cost | 6980 |
|---|
\[\begin{array}{l}
\mathbf{if}\;y \leq -3.4 \cdot 10^{+112}:\\
\;\;\;\;x\\
\mathbf{else}:\\
\;\;\;\;x - \frac{y \cdot \mathsf{expm1}\left(z\right)}{t}\\
\end{array}
\]
| Alternative 4 |
|---|
| Error | 11.8 |
|---|
| Cost | 964 |
|---|
\[\begin{array}{l}
\mathbf{if}\;z \leq -4.7 \cdot 10^{-20}:\\
\;\;\;\;x\\
\mathbf{else}:\\
\;\;\;\;x + \frac{y \cdot \left(-0.5 \cdot \left(z \cdot z\right) - z\right)}{t}\\
\end{array}
\]
| Alternative 5 |
|---|
| Error | 14.7 |
|---|
| Cost | 712 |
|---|
\[\begin{array}{l}
\mathbf{if}\;x \leq -8.5 \cdot 10^{-115}:\\
\;\;\;\;x\\
\mathbf{elif}\;x \leq 1.9 \cdot 10^{-203}:\\
\;\;\;\;x - z \cdot \frac{y}{t}\\
\mathbf{else}:\\
\;\;\;\;x\\
\end{array}
\]
| Alternative 6 |
|---|
| Error | 11.8 |
|---|
| Cost | 708 |
|---|
\[\begin{array}{l}
\mathbf{if}\;z \leq -3.1 \cdot 10^{-20}:\\
\;\;\;\;x\\
\mathbf{else}:\\
\;\;\;\;x + \left(y \cdot z\right) \cdot \frac{-1}{t}\\
\end{array}
\]
| Alternative 7 |
|---|
| Error | 17.7 |
|---|
| Cost | 648 |
|---|
\[\begin{array}{l}
\mathbf{if}\;t \leq -1.92 \cdot 10^{-243}:\\
\;\;\;\;x\\
\mathbf{elif}\;t \leq -3.35 \cdot 10^{-296}:\\
\;\;\;\;y \cdot \frac{-z}{t}\\
\mathbf{else}:\\
\;\;\;\;x\\
\end{array}
\]
| Alternative 8 |
|---|
| Error | 11.3 |
|---|
| Cost | 580 |
|---|
\[\begin{array}{l}
\mathbf{if}\;z \leq -4.7 \cdot 10^{-20}:\\
\;\;\;\;x\\
\mathbf{else}:\\
\;\;\;\;x - \frac{y}{\frac{t}{z}}\\
\end{array}
\]
| Alternative 9 |
|---|
| Error | 11.8 |
|---|
| Cost | 580 |
|---|
\[\begin{array}{l}
\mathbf{if}\;z \leq -2 \cdot 10^{-22}:\\
\;\;\;\;x\\
\mathbf{else}:\\
\;\;\;\;x - \frac{y \cdot z}{t}\\
\end{array}
\]
| Alternative 10 |
|---|
| Error | 17.6 |
|---|
| Cost | 64 |
|---|
\[x
\]