Examples
// x: finely sampled x = 0:0.2:30; y = CL_rMod(x, 0, 2*%pi); CL_unMod(y, 2*%pi) - x // => 0 // x: loosely sampled x = x(1:20:$); y = y(1:20:$); CL_unMod(y, 2*%pi, x, 1) - x // => 0 |  |  |
Makes data continuous (removes "modulo")
yc = CL_unMod(y, a, [, x, slope])
Makes data continuous by adding an integer number of "a" to data when necessary.
Abscissae and slope(s) may be provided in case the "distance" between consecutive data is too large (more than a/2).
Notes:
- y may contain %nan: %nan values are ignored.
- The slope does not have to be exact. It only has to be precise enough so that the prediction error between consecutive data is small enough.
Vector of real values (ordinates) (1xN)
Positive value (= "modulo") (1x1)
(optional) Vector of real values (abscissae). Default is []. (1xN)
(optional) Approximate value of the slope = dy/dx. Default is []. (1x1 or 1xN)
y made continuous (1xN)
CNES - DCT/SB
// x: finely sampled x = 0:0.2:30; y = CL_rMod(x, 0, 2*%pi); CL_unMod(y, 2*%pi) - x // => 0 // x: loosely sampled x = x(1:20:$); y = y(1:20:$); CL_unMod(y, 2*%pi, x, 1) - x // => 0 | | |