I'm trying to generate a basis spline function by defining the order of b-splines, number of basis functions, knots and range of evaluation. Please refer me to a suitable function in Python that can help me.
My current implementation is using the johntfoster/bspline method. It doesn't allow me to define the number of basis functions and the results are not similar to that of MATLAB. https://github.com/johntfoster/bspline
The scipy.interpolate.BSpline.basis_element function doesn't allow me to define the order of spline, number of basis functions,knots
Matlab Implementation:
nbreaks = 20;
nbasis = nbreaks + norder - 2;
breaks = linspace(0,taufmax,nbreaks)';
%Create a smooth function that passes through the break point / knots
wtaubasis = create_bspline_basis([0,max(breaks)], nbasis, norder, breaks);
% Create a matrix of basis functions at each break points for the entire Tau
basisValueMat_f = full(eval_basis(wtaubasis, tauf));
Python Implementation (johntfoster/bspline method)
import numpy as np
import bspline
import bspline.splinelab as splinelab
norder = 4
nbreaks = 20
#This defines the number of basis function
nbasis = nbreaks + norder - 2
#For the spline, it has to pass thorough the corresponding break points
breaks = np.linspace(0,tauf_max,nbreaks)
k = splinelab.augknt(breaks, norder)
# create spline basis of order p on knots k
B = bspline.Bspline(k, norder)
A0 = B.collmat(np.squeeze(tau_f), deriv_order=0)
I would like to get the B Spline basis functions evaluated at specified points. Results similar to MATLAB would be highly encouraging.
There's evaluate_all_bspl,
https://github.com/scipy/scipy/blob/v1.3.0/scipy/interpolate/_bspl.pyx#L163
which computes all non-zero b-splines given knots at a given evaluation point. It is not a public function though, so if you end up using it, you're on your own.