Added docs. Build using Sphinx.
Some fixes for building docs on RTD.
One last fix for buildling docs on RTD.
Update to ensure docs generate.

Since theano is tough to get running on readthedocs,
it's easier to just mock out theano stuff that we use.
Added some mocks for the new theano random number generator.
Copied Nengo examples for compatibility testing.

These also serve as good examples of how to use the nef API.
Examples import from Theano now.

Also ranamed non-importable files with '-' in the name.
Modified examples to run

- removed net.add_to_nengo()
- added net.run(1)
- made changes to ensemble.make_encoders to run properly
- added lines for comments to be added in several files
Learning examples work

From the examples added in #24, removed make_fourier_input, gating,
and direct mode references.
Updated the learning code to accept rate as a parameter, and use kwargs
instead of repeating parameter lists in ensemble and network.
Input now handles 'time:value' dict as value input

- controlledintegrator examples from #24 now work
Integrator example for #24 runs
Removed accumulator, set up terminations

- Terminations in ensemble implement Filters
- dt is now specified in network.run instead of in ensemble constructor
- only place dt is used now is update functions and
- in compute_decoders, timestep is explicitly given as .001 for A matrix calc
- names added to terminations, implementation a little clumsy
- streamlined ensemble update function
- All tests work
ENH: python setup.py develop (via setuptools)
Fix #7, direct mode functionality added

- Ensembles handle two modes: spiking (default), and direct
- Direct mode ensembles use origin, instead of ensemble_origin
- test_direct added
- basal ganglia template modified to use direct mode input / output
- network class formatting cleaned up in connect function
- TODO: add update function to origin, change input and simplenode,
  and ensemble.update to interact through this function for consistency
- TODO: add rate mode
Fix - direct mode: funcs on connections

Function output with both lists and scalar output
for connections now work with the network arrays.
- updated direct mode test
Fix - direct mode: radius
Updated test_enc file
Formatted make_alpha_bias to match Nengo code
Fix #30 - added noise to A matrix elements

- added Gaussian noise with std=max_rate * .1 to A in compute_encoders
- added self.max_rate to ensemble
- also renamed some internal variables in neuron
Added exception if eval_points is of wrong form
Updated eval_points test