Files in this directory demonstrate basic use of mystic.  The most common
case demonstrated is fitting a standard test function from mystic.models,
however the use of constraints, the use of ensemble solvers, and the use
of parallel computing is also demonstrated.


== Notes on mystic examples ==
Dependencies:
 - Several of the examples require matplotlib to be installed.
 - For the examples that use matplotlib, see trac ticket #36 for more details.

Other dependencies:
 - Examples with prefix "example" are part of the tutorial (TRY THESE FIRST).
 - All examples with prefix "example" should run without new dependencies.
 - All examples with prefix "test_" should run without new dependencies.
 - All examples with prefix "gplot_" requre gnuplot-py for visualization.

Exceptions to the rule:
 - The following examples also require scipy to be installed:
   . test_lorentzian.py
   . test_mogi_anneal.py,

Special examples:
 - All examples with prefix "rosetta_" require park to be installed. (tests on version park-1.2).  Run with "--park" to execute with park. See "--help" for more options.


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Notes on the "ffit" tests/examples:
 - test_ffit: The fitting problem whose exact solution is 8th order Chebyshev polynomial of the first kind.  This example uses a Ctrl-C signal handler. Try ctrl-c as the differential_evolution strategy is running.
 - test_ffit2: The fitting problem whose exact solution is 16th order Chebyshev polynomial of the first kind.  Also uses the signal_handler. 
 - test_ffitB: Same as test_ffit.py, but uses DifferentialEvolutionSolver2 instead of DifferentialEvolutionSolver. 
 - test_ffitC: Same as test_ffit.py, but uses scipy_optimize.fmin.
 - test_ffitD: Same as test_ffit.py, but uses scipy_optimize.diffev.


Notes on the "mogi" tests/examples:
 - test_mogi.py: One mogi source with noise, comparison between DE and Conjugate Gradient, Simplex, and least squares (Levenberg Marquardt). CG / lsq don't work very well. lsq should work when bounds on the parameters are given, but minpack (wrapped by scipy) version doesn't seem to support bounds.
 - test_mogi_anneal.py: tests with scipy simulated annealing, but hasn't been tuned, so again, doesn't work at all.
 - test_mogi2.py: two mogi sources
 - test_mogi3.py: reimplements test_mogi 


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