Note: Presentation is simpler than that in textbook
Interval subpartitions
Piecewise Lagrange basis
Analysis: rate of convergence
Two levels of partitioning for f:[a,b]→ℝ. The idea is to use low-degree polynomials over subintervals.
Overall partition [a,b]=⋃j=1n[aj,bj], a=a1<a2<⋯<an=b-l. Options:
If function does not exhibit regions of large variability: uniform partition
If function varies rapidly in subregions: adaptive partition
Interval subpartition, almost always uniform, m chosen small, (m⩽5)
Function sample points are chosen as:
For piecewise constant: x0j=(aj+bj)/2 (midpoint)
For m>0, xi⁡j=aj+i⁡hj, hj=(bj-aj)/m
Idea: m sample points over each of n partition intervals:
Interpolation can be discontinous at subinterval edges a2,…,an
Discontinuity in function or derivatives is often required (corners, jumps)
Over interval [aj,bj], barycentric Lagrange interpolation is
Weights are easily precomputed for uniform subpartitions xi⁡j=aj+i⁡hj
On interval [aj,bj] Lagrange basis is: {l0j(t),…,lm⁡j(t)}, j=1,…,n.
Outside interval [aj,bj] set li⁡j(t)=0, i=0,1,…,m.
Gather into single basis set
Figure 1. Two members of a piecewise Lagrange basis of degree 5 over two subintervals