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answered 2011-11-14 10:24:59 -0600

DSM gravatar image

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.

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