orbithunter 0.7.0b¶

Major Changes¶

Orbit.__getattr__ now provides more detail regarding errors fetching attributes, specifically those corresponding to parameter labels.
Numerical algorithm wrappers now have separate factory functions which produce the callables required for the various SciPy routines. This allows for more tidiness and separability between requirements for various routines.
Many fixes in SciPy wrappers
Orbit not allow for assignment of workers attribute; determines cores to use for KSe fft transforms. Only useful if dimension approx >= 128.
Orbit.costgrad() now optionally takes Orbit.eqn() to be more general; i.e. allow for costgrad which do not require eqn to be passed.
Jacobian for OrbitKS subclasses now much more efficient, many matrix related helper functions have been deprecated Memory usage cut down by approx 50% and time cut down by factor of 10.

KSE Jacobians are now produced much more efficiently
Inplace computation of differentiation and FFTs now implemented for KSe. Uglier code but makes certain calculations more efficient.
np.reshape calls replaced with usage of None/np.newaxis where possible; as it is typically faster.

When three or more methods were included, orbithunter.optimize.hunt was unable to aggregate runtime statistics due to type errors; was trying to extend lists with numbers instead of lists
Certain keyword arguments that were meant for outer iteration loops (orbithunter routines) and not inner loops (scipy routines) were conflicting, causing unintended performance issues. Most notable was maxiter keyword meant for the number of outer loop iterations was determining the size of the Krylov subspace in scipy.optimize.newton_krylov
The outer-iteration function factories were actually in the completely wrong place; needed to be within while loop but they were not..