source: fact/tools/pyscripts/simulation/old_and_tests/interpolate_textfile_tests_and_so.py

#!/usr/bin/python -itt

import struct
import sys
import numpy as np

import rlcompleter
import readline
readline.parse_and_bind('tab: complete')

import matplotlib.pyplot as plt
import scipy.interpolate

print "start"

f = open(sys.argv[1])
lines = []
print "file open"

for index, line in enumerate(f):
    line = line.split()
    if '#' in line[0]:
        continue
    line = map(float, line)
    
    print index, line
    if len(line) == 0:
        continue
    
    lines.append(line)

data = np.array(lines)

x = data[:,0]
y = data[:,1]
w = None

plt.ion()
fig = plt.figure()

#plt.plot(x,y, '.')


#scipy.interpolate.UnivariateSpline
#(self, x, y, w=None, bbox=[None, None], k=3, s=None)
#spline = scipy.interpolate.UnivariateSpline( x=x ,y=y ,w=w )

#PiecewisePolynomial
# __init__(self, xi, yi, orders=None, direction=None)
#spline = scipy.interpolate.PiecewisePolynomial(x,y)
# did not work

# ringing like hell!
#spline = scipy.interpolate.BarycentricInterpolator(x,y)

spline = scipy.interpolate.InterpolatedUnivariateSpline(x,y)
#spline2 = scipy.interpolate.UnivariateSpline(x,y)

# generate y-x-data from spline just for plotting.
xx = np.linspace( x[0], x[-1], len(x)*10)
xx = x

#plt.plot(xx,spline(xx), ':')
plt.plot(xx,spline(xx)-y, ':')
#plt.plot(xx,spline2(xx), ':')