Editing CORDIC (section)

== Implementation ==

In Java the Math class has a <code>scalb(double x,int scale)</code> method to perform such a shift,<ref name="Java_Math"/> C has the [[ldexp]] function,<ref name="ldexp"/> and the x86 class of processors have the <code>fscale</code> floating point operation.<ref name="Intel_2016"/>

=== Software example (Python) ===
<syntaxhighlight lang="python3" line="1" start="1">
from math import atan2, sqrt, sin, cos, radians

ITERS = 16
theta_table = [atan2(1, 2**i) for i in range(ITERS)]

def compute_K(n):
    """
    Compute K(n) for n = ITERS. This could also be
    stored as an explicit constant if ITERS above is fixed.
    """
    k = 1.0
    for i in range(n):
        k *= 1 / sqrt(1 + 2 ** (-2 * i))
    return k

def CORDIC(alpha, n):
    assert n <= ITERS
    K_n = compute_K(n)
    theta = 0.0
    x = 1.0
    y = 0.0
    P2i = 1  # This will be 2**(-i) in the loop below
    for arc_tangent in theta_table[:n]:
        sigma = +1 if theta < alpha else -1
        theta += sigma * arc_tangent
        x, y = x - sigma * y * P2i, sigma * P2i * x + y
        P2i /= 2
    return x * K_n, y * K_n

if __name__ == "__main__":
    # Print a table of computed sines and cosines, from -90° to +90°, in steps of 15°,
    # comparing against the available math routines.
    print("  x       sin(x)     diff. sine     cos(x)    diff. cosine ")
    for x in range(-90, 91, 15):
        cos_x, sin_x = CORDIC(radians(x), ITERS)
        print(
            f"{x:+05.1f}°  {sin_x:+.8f} ({sin_x-sin(radians(x)):+.8f}) {cos_x:+.8f} ({cos_x-cos(radians(x)):+.8f})"
        )

</syntaxhighlight>

==== Output ====
<syntaxhighlight lang="console">
$ python cordic.py
  x       sin(x)     diff. sine     cos(x)    diff. cosine
-90.0°  -1.00000000 (+0.00000000) -0.00001759 (-0.00001759)
-75.0°  -0.96592181 (+0.00000402) +0.25883404 (+0.00001499)
-60.0°  -0.86601812 (+0.00000729) +0.50001262 (+0.00001262)
-45.0°  -0.70711776 (-0.00001098) +0.70709580 (-0.00001098)
-30.0°  -0.50001262 (-0.00001262) +0.86601812 (-0.00000729)
-15.0°  -0.25883404 (-0.00001499) +0.96592181 (-0.00000402)
+00.0°  +0.00001759 (+0.00001759) +1.00000000 (-0.00000000)
+15.0°  +0.25883404 (+0.00001499) +0.96592181 (-0.00000402)
+30.0°  +0.50001262 (+0.00001262) +0.86601812 (-0.00000729)
+45.0°  +0.70709580 (-0.00001098) +0.70711776 (+0.00001098)
+60.0°  +0.86601812 (-0.00000729) +0.50001262 (+0.00001262)
+75.0°  +0.96592181 (-0.00000402) +0.25883404 (+0.00001499)
+90.0°  +1.00000000 (-0.00000000) -0.00001759 (-0.00001759)
</syntaxhighlight>

=== Hardware example ===
The number of [[logic gate]]s for the implementation of a CORDIC is roughly comparable to the number required for a multiplier as both require combinations of shifts and additions. The choice for a multiplier-based or CORDIC-based implementation will depend on the context. The multiplication of two [[complex number]]s represented by their real and imaginary components (rectangular coordinates), for example, requires 4 multiplications, but could be realized by a single CORDIC operating on complex numbers represented by their polar coordinates, especially if the magnitude of the numbers is not relevant (multiplying a complex vector with a vector on the unit circle actually amounts to a rotation). CORDICs are often used in circuits for telecommunications such as [[digital down converter]]s.