One-dimensional spline with explicit internal knots.
Fits a spline y=s(x) of degree k to the provided x,`y` data. t specifies the internal knots of the spline
Parameters : | x : sequence
y : sequence
t: sequence :
w : sequence or None, optional
bbox : sequence or None, optional
k : int, optional
|
---|---|
Raises : | ValueError :
|
See also
Examples
>>> from numpy import linspace,exp
>>> from numpy.random import randn
>>> from scipy.interpolate import LSQUnivariateSpline
>>> x = linspace(-3,3,100)
>>> y = exp(-x**2) + randn(100)/10
>>> t = [-1,0,1]
>>> s = LSQUnivariateSpline(x,y,t)
>>> xs = linspace(-3,3,1000)
>>> ys = s(xs)
xs,ys is now a smoothed, super-sampled version of the noisy gaussian x,y with knots [-3,-1,0,1,3]
Methods
derivatives | |
get_coeffs | |
get_knots | |
get_residual | |
integral | |
roots | |
set_smoothing_factor |