Average Error: 2.3 → 2.3
Time: 4.5s
Precision: binary64
\[\frac{x - y}{z - y} \cdot t \]
↓
\[\frac{t}{\frac{z - y}{x - y}} \]
(FPCore (x y z t) :precision binary64 (* (/ (- x y) (- z y)) t))
↓
(FPCore (x y z t) :precision binary64 (/ t (/ (- z y) (- x y))))
double code(double x, double y, double z, double t) {
	return ((x - y) / (z - y)) * t;
}
↓
double code(double x, double y, double z, double t) {
	return t / ((z - y) / (x - y));
}

real(8) function code(x, y, z, t)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    code = ((x - y) / (z - y)) * t
end function
↓
real(8) function code(x, y, z, t)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    code = t / ((z - y) / (x - y))
end function

public static double code(double x, double y, double z, double t) {
	return ((x - y) / (z - y)) * t;
}
↓
public static double code(double x, double y, double z, double t) {
	return t / ((z - y) / (x - y));
}

def code(x, y, z, t):
	return ((x - y) / (z - y)) * t
↓
def code(x, y, z, t):
	return t / ((z - y) / (x - y))

function code(x, y, z, t)
	return Float64(Float64(Float64(x - y) / Float64(z - y)) * t)
end
↓
function code(x, y, z, t)
	return Float64(t / Float64(Float64(z - y) / Float64(x - y)))
end

function tmp = code(x, y, z, t)
	tmp = ((x - y) / (z - y)) * t;
end
↓
function tmp = code(x, y, z, t)
	tmp = t / ((z - y) / (x - y));
end

code[x_, y_, z_, t_] := N[(N[(N[(x - y), $MachinePrecision] / N[(z - y), $MachinePrecision]), $MachinePrecision] * t), $MachinePrecision]
↓
code[x_, y_, z_, t_] := N[(t / N[(N[(z - y), $MachinePrecision] / N[(x - y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]

\frac{x - y}{z - y} \cdot t
↓
\frac{t}{\frac{z - y}{x - y}}

Error

Bits error versus x

Bits error versus y

Bits error versus z

Bits error versus t

Try it out

Your Program's Arguments

Results

Enter valid numbers for all inputs

Target

Original2.3
Target2.3
Herbie2.3
\[\frac{t}{\frac{z - y}{x - y}} \]

Derivation

  1. Initial program 2.3

    \[\frac{x - y}{z - y} \cdot t \]

  2. Applied egg-rr2.3

    \[\leadsto \color{blue}{\frac{t}{\frac{z - y}{x - y}}} \]

  3. Final simplification2.3

    \[\leadsto \frac{t}{\frac{z - y}{x - y}} \]

Reproduce

herbie shell --seed 2022133 
(FPCore (x y z t)
  :name "Numeric.Signal.Multichannel:$cput from hsignal-0.2.7.1"
  :precision binary64

  :herbie-target
  (/ t (/ (- z y) (- x y)))

  (* (/ (- x y) (- z y)) t))