\[\left(x \cdot \log y + z \cdot \log \left(1 - y\right)\right) - t
\]
↓
\[\left(z \cdot \mathsf{log1p}\left(-y\right) + x \cdot \log y\right) - t
\]
(FPCore (x y z t)
:precision binary64
(- (+ (* x (log y)) (* z (log (- 1.0 y)))) t))
↓
(FPCore (x y z t)
:precision binary64
(- (+ (* z (log1p (- y))) (* x (log y))) t))
double code(double x, double y, double z, double t) {
return ((x * log(y)) + (z * log((1.0 - y)))) - t;
}
↓
double code(double x, double y, double z, double t) {
return ((z * log1p(-y)) + (x * log(y))) - t;
}
public static double code(double x, double y, double z, double t) {
return ((x * Math.log(y)) + (z * Math.log((1.0 - y)))) - t;
}
↓
public static double code(double x, double y, double z, double t) {
return ((z * Math.log1p(-y)) + (x * Math.log(y))) - t;
}
def code(x, y, z, t):
return ((x * math.log(y)) + (z * math.log((1.0 - y)))) - t
↓
def code(x, y, z, t):
return ((z * math.log1p(-y)) + (x * math.log(y))) - t
function code(x, y, z, t)
return Float64(Float64(Float64(x * log(y)) + Float64(z * log(Float64(1.0 - y)))) - t)
end
↓
function code(x, y, z, t)
return Float64(Float64(Float64(z * log1p(Float64(-y))) + Float64(x * log(y))) - t)
end
code[x_, y_, z_, t_] := N[(N[(N[(x * N[Log[y], $MachinePrecision]), $MachinePrecision] + N[(z * N[Log[N[(1.0 - y), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - t), $MachinePrecision]
↓
code[x_, y_, z_, t_] := N[(N[(N[(z * N[Log[1 + (-y)], $MachinePrecision]), $MachinePrecision] + N[(x * N[Log[y], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - t), $MachinePrecision]
\left(x \cdot \log y + z \cdot \log \left(1 - y\right)\right) - t
↓
\left(z \cdot \mathsf{log1p}\left(-y\right) + x \cdot \log y\right) - t
Alternatives
| Alternative 1 |
|---|
| Error | 0.3 |
|---|
| Cost | 7360 |
|---|
\[\left(z \cdot \left(y \cdot \left(y \cdot -0.5\right) - y\right) + x \cdot \log y\right) - t
\]
| Alternative 2 |
|---|
| Error | 0.5 |
|---|
| Cost | 7168 |
|---|
\[\left(\log \left(\frac{1}{y}\right) \cdot \left(-x\right) - y \cdot z\right) - t
\]
| Alternative 3 |
|---|
| Error | 7.0 |
|---|
| Cost | 7044 |
|---|
\[\begin{array}{l}
\mathbf{if}\;x \leq -8 \cdot 10^{+19}:\\
\;\;\;\;\log \left(\frac{1}{y}\right) \cdot \left(-x\right) - t\\
\mathbf{elif}\;x \leq 5.1 \cdot 10^{-82}:\\
\;\;\;\;z \cdot \left(-0.5 \cdot \left(y \cdot y\right) - y\right) - t\\
\mathbf{else}:\\
\;\;\;\;x \cdot \log y - t\\
\end{array}
\]
| Alternative 4 |
|---|
| Error | 7.0 |
|---|
| Cost | 6984 |
|---|
\[\begin{array}{l}
t_1 := x \cdot \log y - t\\
\mathbf{if}\;x \leq -8 \cdot 10^{+19}:\\
\;\;\;\;t_1\\
\mathbf{elif}\;x \leq 9.6 \cdot 10^{-84}:\\
\;\;\;\;z \cdot \left(-0.5 \cdot \left(y \cdot y\right) - y\right) - t\\
\mathbf{else}:\\
\;\;\;\;t_1\\
\end{array}
\]
| Alternative 5 |
|---|
| Error | 0.5 |
|---|
| Cost | 6976 |
|---|
\[\left(x \cdot \log y - y \cdot z\right) - t
\]
| Alternative 6 |
|---|
| Error | 14.4 |
|---|
| Cost | 6856 |
|---|
\[\begin{array}{l}
t_1 := x \cdot \log y\\
\mathbf{if}\;x \leq -1.45 \cdot 10^{+53}:\\
\;\;\;\;t_1\\
\mathbf{elif}\;x \leq 1.1 \cdot 10^{+54}:\\
\;\;\;\;z \cdot \left(-0.5 \cdot \left(y \cdot y\right) - y\right) - t\\
\mathbf{else}:\\
\;\;\;\;t_1\\
\end{array}
\]
| Alternative 7 |
|---|
| Error | 27.0 |
|---|
| Cost | 704 |
|---|
\[z \cdot \left(-0.5 \cdot \left(y \cdot y\right) - y\right) - t
\]
| Alternative 8 |
|---|
| Error | 32.6 |
|---|
| Cost | 520 |
|---|
\[\begin{array}{l}
\mathbf{if}\;t \leq -7.4 \cdot 10^{-81}:\\
\;\;\;\;-t\\
\mathbf{elif}\;t \leq 3.1 \cdot 10^{-133}:\\
\;\;\;\;y \cdot \left(-z\right)\\
\mathbf{else}:\\
\;\;\;\;-t\\
\end{array}
\]
| Alternative 9 |
|---|
| Error | 27.2 |
|---|
| Cost | 384 |
|---|
\[y \cdot \left(-z\right) - t
\]
| Alternative 10 |
|---|
| Error | 36.4 |
|---|
| Cost | 128 |
|---|
\[-t
\]