fit_curve
fit a smooth cubic spline curve to a set of points
fit_curve input_lines.tag output_lines.obj n_controls n_intervals [smoothness_weight] [disjoint_distance]
DESCRIPTION
fit_curve creates a cubic spline curve that approximates the set of points in a tag file. The n_controls parameter sets the number of control vertices, effectively controlling the smoothness of the spline — fewer controls produce a smoother curve. The n_intervals parameter specifies the number of intervals between each control vertex in the discretized line that is finally output. An optional smoothness weight and disjoint distance may be specified.
OPTIONS
This tool uses positional arguments only. There are no named options.
input_lines.tag- The input tag file containing the points to fit.
output_lines.obj- The output line object file containing the fitted curve.
n_controls- The number of control vertices for the spline. Fewer controls yield a smoother curve.
n_intervals- The number of intervals between each control vertex in the output line.
smoothness_weight- Optional weight controlling the smoothness of the fit.
disjoint_distance- Optional distance threshold for treating points as belonging to disjoint segments.
EXAMPLES
Fit a spline with 10 control points and 5 intervals:
fit_curve points.tag curve.obj 10 5
Fit with a smoothness weight of 0.1:
fit_curve points.tag curve.obj 10 5 0.1
AUTHOR
David MacDonald - McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University.
COPYRIGHTS
Copyright © by David MacDonald