1 | initial version |
Sure, there are a couple of ways. Here are two:
import numpy
from scipy import interpolate
data = [(x, sin(x)**2+(x % 2.7)**3) for x in numpy.linspace(0, 5, 20)]
# separate data into x and y components
xx,yy = zip(*data)
# build spline in two ways..
scipy_spline = interpolate.InterpolatedUnivariateSpline(xx, yy)
gsl_spline = spline(data)
p = list_plot(data, color="green")
p += plot(scipy_spline, (0, 5), color="red")
p += plot(gsl_spline, (0, 5), linestyle='--', color="blue")
show(p)
Note that if you build the spaces yourself and use the built-in spline object you wouldn't need to import anything.