Internals

Spline Representation

The computed splines are represented by classes SplinePPForm (inherited from scipy.interpolate.PPoly) for univariate/multivariate and NdGridSplinePPForm (inherited from scipy.interpolate.NdPPoly) for n-d gridded data. This representation can be named as “PP-form” (piecewise-polynomial form).

Here is an example of SplinePPForm object:

>>> from csaps import CubicSmoothingSpline

>>> x = [0, 1, 2, 3]
>>> y = [(1, 3, 4, 4), (5, 6, 7, 8)]

>>> s = CubicSmoothingSpline(x, y)
>>> print(s.spline)

SplinePPForm
  breaks: [0. 1. 2. 3.]
  coeffs shape: (4, 3, 2)
  data shape: (2, 4)
  axis: 1
  pieces: 3
  order: 4
  ndim: 2

The coefficients array in this case has the shape (4, 3, 2) where:

• 4 – spline order (4 for cubic)

• 3 – the number of spline pieces (3 pieces for 4 X-points)

• 2 – the number of 1-d Y-data vectors