./wip/py-mystic, Constrained non-convex optimization and uncertainty quantification

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Branch: CURRENT, Version: 0.3.6, Package name: py312-mystic-0.3.6, Maintainer: jihbed.research

The mystic framework provides a collection of optimization algorithms
and tools that allows the user to more robustly (and easily) solve hard
optimization problems. All optimization algorithms included in mystic
provide workflow at the fitting layer, not just access to the algorithms
as function calls. mystic gives the user fine-grained power to both
monitor and steer optimizations as the fit processes are running.
Optimizers can advance one iteration with Step, or run to completion
with ``Solve``. Users can customize optimizer stop conditions, where both
compound and user-provided conditions may be used. Optimizers can save
state, can be reconfigured dynamically, and can be restarted from a
saved solver or from a results file. All solvers can also leverage
parallel computing, either within each iteration or as an ensemble of
solvers.


Required to run:
[devel/py-setuptools] [math/py-numpy] [lang/python37]

Required to build:
[pkgtools/cwrappers]

Master sites:

RMD160: cdc1171f91ae519a1fa38dc69e4fe48da3caabea
Filesize: 984.048 KB

Version history: (Expand)

CVS history: (Expand)


   2013-09-06 23:24:11 by Kamel Derouiche | Files touched by this commit (4) 
Log message:
Import py27-mystic-0.2a1 as wip/py-mystic.

Mystic is written in python, and relies on numpy for several of it's
data structures. The plotting package matplotlib is not required by mystic,
however several of mystic's tutorial examples do require it to be installed.
Note that although the tutorial examples are bundled with the distribution, they
are not installed as a package.