def splint(a,b,tck,full_output=False):
"""Evaluate the definite integral of a B-spline.
Description:
Given the knots and coefficients of a B-spline, evaluate the definite
integral of the smoothing polynomial between two given points.
Inputs:
a, b -- The end-points of the integration interval.
tck -- A length 3 sequence describing the given spline (See splev).
full_output -- True to return optional output.
Outputs: (integral, {wrk})
integral -- The resulting integral.
wrk -- An array containing the integrals of the normalized B-splines
defined on the set of knots.
See also:
splprep, splrep, sproot, spalde, splev - evaluation, roots, integral
bisplrep, bisplev - bivariate splines
UnivariateSpline, BivariateSpline - an alternative wrapping
of the FITPACK functions
"""
t,c,k=tck
try:
c[0][0] # check if c is >1-d
parametric = True # it is
except TypeError: parametric = False # c is 1-d
if parametric:
return map(lambda c,a=a,b=b,t=t,k=k:splint(a,b,[t,c,k]),c)
else:
c = c.copy()
c.resize(len(t))
aint,wrk = dfitpack.splint(t,c,k,a,b)
if full_output: return aint,wrk
else: return aint
def integral(self, a, b):
""" Return definite integral of the spline between two given points.
"""
return dfitpack.splint(*(self._eval_args + (a, b)))
def integral(self, a, b):
""" Return definite integral of the spline between two
given points.
"""
iy, wrk = dfitpack.splint(*(self._eval_args + (a, b)))
return iy