Implemented simple gradient descent method with fixed step size in cartesian space.
Removed debug code.
Updated examples to remove explicit reference to platform, so that best platform is selected automatically.
Removed Context fallback code since this is now incorporated into OpenMM.  Changed gradient descent minimization to be adaptive by default.  Added some temporary debug code.
Removed temporary debug code.
Updated README for correct local repo Travis CI badge.
Fixed problem with README change.
Added check for NaNs in acceptance for CustomIntegrator minimizer.
Updated minimizer to eliminate NaNs in case where gradient norm is zero.
Removed debug output.
Added minimization test for all systems to nose tests.
Added another test to ensure initial energy of all test systems is not NaN.
Fixed error in AMOEBA test systems specification (non-periodic box had been specified for periodic system).
Added doctests to testsystems nose tests.
Fixed up docstring for gradient descent minimizer.
Rolled back use of CustomIntegrator based minimization, since it wasn't much faster than LocalEnergyMinimizer.
Added simulation scripts for villin example.
Fixed a bug.
Some edits to tests to make them run in a timely manner, but I can't track down why the test_mcmc.py test is taking so damn long to run.
More debugging of minimization tests.
Merge pull request #110 from jchodera/faster-minimizer

[WIP] Implemented gradient descent method as CustomIntegrator