\[\frac{\sin x \cdot \sinh y}{x}
\]
↓
\[\sin x \cdot \frac{\sinh y}{x}
\]
(FPCore (x y) :precision binary64 (/ (* (sin x) (sinh y)) x))
↓
(FPCore (x y) :precision binary64 (* (sin x) (/ (sinh y) x)))
double code(double x, double y) {
return (sin(x) * sinh(y)) / x;
}
↓
double code(double x, double y) {
return sin(x) * (sinh(y) / x);
}
real(8) function code(x, y)
real(8), intent (in) :: x
real(8), intent (in) :: y
code = (sin(x) * sinh(y)) / x
end function
↓
real(8) function code(x, y)
real(8), intent (in) :: x
real(8), intent (in) :: y
code = sin(x) * (sinh(y) / x)
end function
public static double code(double x, double y) {
return (Math.sin(x) * Math.sinh(y)) / x;
}
↓
public static double code(double x, double y) {
return Math.sin(x) * (Math.sinh(y) / x);
}
def code(x, y):
return (math.sin(x) * math.sinh(y)) / x
↓
def code(x, y):
return math.sin(x) * (math.sinh(y) / x)
function code(x, y)
return Float64(Float64(sin(x) * sinh(y)) / x)
end
↓
function code(x, y)
return Float64(sin(x) * Float64(sinh(y) / x))
end
function tmp = code(x, y)
tmp = (sin(x) * sinh(y)) / x;
end
↓
function tmp = code(x, y)
tmp = sin(x) * (sinh(y) / x);
end
code[x_, y_] := N[(N[(N[Sin[x], $MachinePrecision] * N[Sinh[y], $MachinePrecision]), $MachinePrecision] / x), $MachinePrecision]
↓
code[x_, y_] := N[(N[Sin[x], $MachinePrecision] * N[(N[Sinh[y], $MachinePrecision] / x), $MachinePrecision]), $MachinePrecision]
\frac{\sin x \cdot \sinh y}{x}
↓
\sin x \cdot \frac{\sinh y}{x}
Alternatives
| Alternative 1 |
|---|
| Error | 1.1 |
|---|
| Cost | 7232 |
|---|
\[\sin x \cdot \left(\frac{y}{x} \cdot \left(1 + \left(y \cdot y\right) \cdot 0.16666666666666666\right)\right)
\]
| Alternative 2 |
|---|
| Error | 1.4 |
|---|
| Cost | 6720 |
|---|
\[\sin x \cdot \frac{y}{x}
\]
| Alternative 3 |
|---|
| Error | 1.3 |
|---|
| Cost | 6720 |
|---|
\[\frac{y}{\frac{x}{\sin x}}
\]
| Alternative 4 |
|---|
| Error | 1.3 |
|---|
| Cost | 6720 |
|---|
\[y \cdot \frac{\sin x}{x}
\]
| Alternative 5 |
|---|
| Error | 16.9 |
|---|
| Cost | 1224 |
|---|
\[\begin{array}{l}
t_0 := \frac{1 + \left(y + -1\right) \cdot \left(1 - y\right)}{1 + \left(1 - y\right)}\\
\mathbf{if}\;x \leq -1621850700.7656224:\\
\;\;\;\;t_0\\
\mathbf{elif}\;x \leq 7.505613740542045 \cdot 10^{+19}:\\
\;\;\;\;y + x \cdot \left(-0.16666666666666666 \cdot \left(x \cdot y\right)\right)\\
\mathbf{else}:\\
\;\;\;\;t_0\\
\end{array}
\]
| Alternative 6 |
|---|
| Error | 16.9 |
|---|
| Cost | 840 |
|---|
\[\begin{array}{l}
t_0 := 1 + \left(y + -1\right)\\
\mathbf{if}\;x \leq -1621850700.7656224:\\
\;\;\;\;t_0\\
\mathbf{elif}\;x \leq 7.505613740542045 \cdot 10^{+19}:\\
\;\;\;\;y + x \cdot \left(-0.16666666666666666 \cdot \left(x \cdot y\right)\right)\\
\mathbf{else}:\\
\;\;\;\;t_0\\
\end{array}
\]
| Alternative 7 |
|---|
| Error | 17.1 |
|---|
| Cost | 584 |
|---|
\[\begin{array}{l}
t_0 := 1 + \left(y + -1\right)\\
\mathbf{if}\;x \leq -19848046.03469217:\\
\;\;\;\;t_0\\
\mathbf{elif}\;x \leq 1.666598580482247:\\
\;\;\;\;y\\
\mathbf{else}:\\
\;\;\;\;t_0\\
\end{array}
\]
| Alternative 8 |
|---|
| Error | 18.3 |
|---|
| Cost | 448 |
|---|
\[x \cdot \left(y \cdot \frac{1}{x}\right)
\]
| Alternative 9 |
|---|
| Error | 31.3 |
|---|
| Cost | 64 |
|---|
\[y
\]