Math FPCore C Java Python Julia MATLAB Wolfram TeX \[\frac{x \cdot \left(y - z\right)}{y}
\]
↓
\[\begin{array}{l}
t_0 := \frac{x \cdot \left(y - z\right)}{y}\\
t_1 := \left(1 - \frac{z}{y}\right) \cdot x\\
\mathbf{if}\;t_0 \leq -\infty:\\
\;\;\;\;t_1\\
\mathbf{elif}\;t_0 \leq -20:\\
\;\;\;\;x + \left(-\frac{z \cdot x}{y}\right)\\
\mathbf{else}:\\
\;\;\;\;t_1\\
\end{array}
\]
(FPCore (x y z) :precision binary64 (/ (* x (- y z)) y)) ↓
(FPCore (x y z)
:precision binary64
(let* ((t_0 (/ (* x (- y z)) y)) (t_1 (* (- 1.0 (/ z y)) x)))
(if (<= t_0 (- INFINITY))
t_1
(if (<= t_0 -20.0) (+ x (- (/ (* z x) y))) t_1)))) double code(double x, double y, double z) {
return (x * (y - z)) / y;
}
↓
double code(double x, double y, double z) {
double t_0 = (x * (y - z)) / y;
double t_1 = (1.0 - (z / y)) * x;
double tmp;
if (t_0 <= -((double) INFINITY)) {
tmp = t_1;
} else if (t_0 <= -20.0) {
tmp = x + -((z * x) / y);
} else {
tmp = t_1;
}
return tmp;
}
public static double code(double x, double y, double z) {
return (x * (y - z)) / y;
}
↓
public static double code(double x, double y, double z) {
double t_0 = (x * (y - z)) / y;
double t_1 = (1.0 - (z / y)) * x;
double tmp;
if (t_0 <= -Double.POSITIVE_INFINITY) {
tmp = t_1;
} else if (t_0 <= -20.0) {
tmp = x + -((z * x) / y);
} else {
tmp = t_1;
}
return tmp;
}
def code(x, y, z):
return (x * (y - z)) / y
↓
def code(x, y, z):
t_0 = (x * (y - z)) / y
t_1 = (1.0 - (z / y)) * x
tmp = 0
if t_0 <= -math.inf:
tmp = t_1
elif t_0 <= -20.0:
tmp = x + -((z * x) / y)
else:
tmp = t_1
return tmp
function code(x, y, z)
return Float64(Float64(x * Float64(y - z)) / y)
end
↓
function code(x, y, z)
t_0 = Float64(Float64(x * Float64(y - z)) / y)
t_1 = Float64(Float64(1.0 - Float64(z / y)) * x)
tmp = 0.0
if (t_0 <= Float64(-Inf))
tmp = t_1;
elseif (t_0 <= -20.0)
tmp = Float64(x + Float64(-Float64(Float64(z * x) / y)));
else
tmp = t_1;
end
return tmp
end
function tmp = code(x, y, z)
tmp = (x * (y - z)) / y;
end
↓
function tmp_2 = code(x, y, z)
t_0 = (x * (y - z)) / y;
t_1 = (1.0 - (z / y)) * x;
tmp = 0.0;
if (t_0 <= -Inf)
tmp = t_1;
elseif (t_0 <= -20.0)
tmp = x + -((z * x) / y);
else
tmp = t_1;
end
tmp_2 = tmp;
end
code[x_, y_, z_] := N[(N[(x * N[(y - z), $MachinePrecision]), $MachinePrecision] / y), $MachinePrecision]
↓
code[x_, y_, z_] := Block[{t$95$0 = N[(N[(x * N[(y - z), $MachinePrecision]), $MachinePrecision] / y), $MachinePrecision]}, Block[{t$95$1 = N[(N[(1.0 - N[(z / y), $MachinePrecision]), $MachinePrecision] * x), $MachinePrecision]}, If[LessEqual[t$95$0, (-Infinity)], t$95$1, If[LessEqual[t$95$0, -20.0], N[(x + (-N[(N[(z * x), $MachinePrecision] / y), $MachinePrecision])), $MachinePrecision], t$95$1]]]]
\frac{x \cdot \left(y - z\right)}{y}
↓
\begin{array}{l}
t_0 := \frac{x \cdot \left(y - z\right)}{y}\\
t_1 := \left(1 - \frac{z}{y}\right) \cdot x\\
\mathbf{if}\;t_0 \leq -\infty:\\
\;\;\;\;t_1\\
\mathbf{elif}\;t_0 \leq -20:\\
\;\;\;\;x + \left(-\frac{z \cdot x}{y}\right)\\
\mathbf{else}:\\
\;\;\;\;t_1\\
\end{array}