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#!/usr/bin/env python
# Created by Pearu Peterson, Aug 2003
""" Test xplt based demos for interpolate.fitpack2 module
"""
__usage__ = """
Build interpolate:
python setup_interpolate.py build
Run demos (assumes that scipy is installed):
python -i tests/demos_xplt.py
"""
import sys
from numpy.test.testing import set_package_path
set_package_path()
from interpolate.fitpack2 import UnivariateSpline,LSQUnivariateSpline,\
InterpolatedUnivariateSpline
from interpolate.fitpack2 import LSQBivariateSpline, SmoothBivariateSpline
del sys.path[0]
from scipy import *
def demo1():
x = arange(0,2*pi+pi/4,2*pi/8)
xnew = arange(-pi/10,2*pi+pi/4+pi/10,pi/50)
y = sin(x)
def make_plot():
xplt.plot(x,y,'x',xnew,spline(xnew),x,y,'b',xnew,sin(xnew),
spline.get_knots(),spline(spline.get_knots()),'o')
spline = UnivariateSpline(x,y,k=1)
assert isinstance(spline,LSQUnivariateSpline)
print 'Linear LSQ approximation of sin(x):',spline.__class__.__name__
make_plot()
print 'Residual=',spline.get_residual()
raw_input('Press any key to continue..')
spline.set_smoothing_factor(0)
assert isinstance(spline,InterpolatedUnivariateSpline)
print 'Linear interpolation of sin(x):',spline.__class__.__name__
make_plot()
print 'Residual=',spline.get_residual()
raw_input('Press any key to continue..')
spline = UnivariateSpline(x,y,k=1,s=0.1)
print 'Linear smooth approximation of sin(x):',spline.__class__.__name__
assert isinstance(spline,UnivariateSpline)
make_plot()
print 'Residual=',spline.get_residual()
raw_input('Press any key to continue..')
if __name__ == "__main__":
demo1()
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