Table of contents Index

Module PySplines.CubicSplines

Declared in module PySplines

class COND
class COND_A(COND)
class COND_B(COND)
class CubicSpline(CheckArgs) # General Cubic Spline class.
class CubicSplineError(Exception)
class CubicSplineWithGivenFirstDerivation(CubicSpline)
class CubicSplineWithGivenThirdDerivation(CubicSpline)
class FirstDerivA(COND_A) # Boundary condition.
class FirstDerivB(COND_B) # Boundary condition.
class GeneralNaturalCubicSpline(CubicSpline)
class NaturalA(COND_A) # Boundary condition.
class NaturalB(COND_B) # Boundary condition.
class NaturalCubicSpline(CubicSpline)
class NotANodeA(COND_A) # Boundary condition.
class NotANodeB(COND_B) # Boundary condition.
class NotANodeCubicSpline(CubicSpline)
class Periodic(COND_A) # Boundary condition.
class PeriodicCubicSpline(CubicSpline)
class SecondDerivA(COND_A) # Boundary condition.
class SecondDerivB(COND_B) # Boundary condition.
class ThirdDerivA(COND_A) # Boundary condition.
class ThirdDerivB(COND_B) # Boundary condition.
def _normalize(p)
def _polynom(val, coe)
float EPS = 1e-10
string __author__ = 'Berthold H\366llmann, bhoel@starship.python.net'
string __file__ = '../PySplines/CubicSplines.pyc'
string __version__ = '1.7'

Description

Classes for calculating cubic spline curves for given nodes.

Requires NumPy and, for the exampes, Michael Haggerty's Gnuplot module.

A note to the Examples: It seems that my Linux box is too fast. Some of the Examples don't get written to the PostScript file. The data files disappear before gnuplot sees them.

References:

Gisela Engeln-Müllges and Fritz Reutter, Numerik-Algorithmen: Entscheidungshilfe zur Auswahl und Nutzung, 8. neubearb. und erw. Aufl. -- Düsseldorf: VDI-Verlag, 1996, Kapitel 10, ISBN 3-18-401539-4 (engl. Version might be: `Numerical Algorithms with Fortran' by Gisela Engeln-Mullges and Frank Uhlig, published by Springer 1996. ISBN 3-540-60529-0)

_normalize(p)

Strip unnecessary zero coefficients

_polynom(val, coe)

Evaluate the value polynom defined by coe for val.

The value is: coe[0] + coe[1]*val + ... + coe[n]*val^n + ... + coe[len(coe)]*val^len(coe)