v0.5.0

Runge Kutta Nyström methods added.

v0.4.0

Added sensitivity analysis and Me4 method.
Updated and extended documentation (examples).

improvements

simplifications
step size control settings modified for some methods
revert to original weight vector in SSV2stab

specific methods

Include two methods for specific problems:

• CFMR7osc for oscillatory problems
• SSV2stab: for large mildly stiff problems

update and enable stepsize control for standard RK methods.

stepsize control

Add second order stepsize control for Runge Kutta methods. (Not enabled by default yet)
Fix bugs stiffness detection.

fix bugs

v0.2.2

version number

Stiffness detection

Stiffness detection for Runge Kutta methods is added, and the methods are given an simpler name.

Other changes to the Runge Kutta base class:

• The stepsize near the end of the integration is different:
  - look ahead to prevent too small step sizes
  - linear extrapolation if the last step is too small despite it.
• the min_step accounts for the distance between C-values
• the scale (weight) is smoothed differently
• a different tolerance validation is used.

Most of these changes originate from the RKSuite code.

Shampine Gordon Watts ABM method added

The Fortran code DDEABM is translated to Python and impemented as an OdeSolver class for solve_ivp.

Other updates:

• The error estimator order (instead of method order) is used for the initial step size estimation of the Runge Kutta methods.
• minor changes

Internal updates

Updates:

• Add more elaborate intial step estimator (by H.A. Watts)
• Add linear and cubic dense output classes
• Custom RungeKutta class that differs from Scipy's class in:
  • intial step size method
  • handling of end of the integration range (t_span[1])
  • the dense output classes
  • includes failed step counter

Release v0.1.0: Prince methods added

Changelog:

• High order Prince methods added
• Jupyter notebook for Prince methods
• Created a base class for conventional RK methods
• Created a base class for dense output with Horner's rule
• Some minor simplifications and modifications