splinePol.py

import numpy as np
import scipy.interpolate as si


def bspline(cv, n=100, degree=3, periodic=False):
    """
    Calculate n samples on a bspline

    Author: Eric Vignola (https://stackoverflow.com/questions/34803197/fast-b-spline-algorithm-with-numpy-scipy)

    Args:
        cv: (Required) Array ov control vertices
        n  : (Optional, defaults to 100) Number of samples to return
        degree: (Optional, defaults to 3) Curve degree
        periodic:  (Optional, defaults to False) True/False to indicate if the curve is open or closed
    """

    # If periodic, extend the point array by count+degree+1
    cv = np.asarray(cv)
    count = len(cv)

    if periodic:
        factor, fraction = divmod(count+degree+1, count)
        cv = np.concatenate((cv,) * factor + (cv[:fraction],))
        count = len(cv)
        degree = np.clip(degree,1,degree)

    # If opened, prevent degree from exceeding count-1
    else:
        degree = np.clip(degree,1,count-1)


    # Calculate knot vector
    kv = None
    if periodic:
        kv = np.arange(0-degree,count+degree+degree-1)
    else:
        kv = np.clip(np.arange(count+degree+1)-degree,0,count-degree)

    # Calculate query range
    u = np.linspace(periodic,(count-degree),n)


    # Calculate result
    return np.array(si.splev(u, (kv,cv.T,degree))).T