def check_linear_1d(self):
x = [1,2,3]
y = [0,2,4]
lut = UnivariateSpline(x,y,k=1)
assert_array_almost_equal(lut.get_knots(),[1,3])
assert_array_almost_equal(lut.get_coeffs(),[0,4])
assert_almost_equal(lut.get_residual(),0.0)
assert_array_almost_equal(lut([1,1.5,2]),[0,1,2])
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..')