Initialized with the contents of nef_theano.
Created the Connection API class.

- first commit of the connection API class
- connection is responsible for storing connections between nodes
- class currently has basic functionality and docs
Make setup.py develop work
Changed Network to conform to API

- Removed run(), make_theano_tick(), write_to_hdf5
- Changed make to make_ensemble
- Removed theano references
- Added lists for different network objects
- Updated probe, removed compute_tranform
- Updated "func" to "function" in Network.connect.
- Renamed the "func" parameter to "function" for clairity.
- Moved the pre-node get routine before it is used
- Wrote Network.connect_neurons function.
- Fixed up the documentation for this function
- Made Network.connect and Network.connect_neurons return connection
- Added metadata and properties properties
- Added remove function to network
- Alias added to network, network.probe stripped
First pass at LearningRule and HPES rule.
Created initial version of Node
Implementing ensemble and neuron

- pulling theano out of ensemble and neuron
- removed theano references from Filter
- ensemble passing
- added sanity check on SpikingEnsemble neuron count
- ensemble separates neuron_model, population
Created nengo_testing branch.

Created nengo_testing branch and added updated test_array.py class. New testing class will be based of python unittests.
Refactored test code.

Removed old nef-py test code. Created new test code for Model, Network, Ensemble, Node, Connection, Filter, LearningRate, NeuronModel objects.
Updated ensemble test.

Added advanced test framework and possible unittest framework.
Added one advanced test example.

Updated ensemble test code to include framework for adding advanced tests to the testcase framework.
first commit of model
Moved the contents of nef to the top-level
Updated example scripts to the new API.

Also added new example network_array_2d.py.
network_array_2d.py is similar to the 2drepresentation.py example
except it uses a Network Array in place of an ensemble. Supposed to
demonstrate the most basic use of Network Arrays.

Note:
- All network/ensemble/node names need to be capitalized
- Comments are aligned to each other
- Uses model.build()
- Currently assuming that functions passed to make_node take time as an
  input, but this is subject to change over to Terry's generator scheme

Todo:
- Add header, and maybe get rid of big transform comment
Updated examples to conform with rest of repo

- Updated example scripts to use dictionary for filter parameter.
- Updated matrix_multiplication.py and network_array_2d.py to use
  array.connect instead of model.connect.
- Updated integrator.py to use proposed shorted method of specifying
  transform and filter parameters.
fix setup.py after nengo_sprint
Removing all nengo python files

Clearing them for rewrite based on code from nengo_ocl
Continuing removals: neuron/ subdir
Partial init of reference from nengo_ocl

A basic test of making an ensemble using the old_api.py works,
but probes are not implemented, so I can't even verify the output yet.
Things are at a very early stage.
More initial work on reference from nengo_ocl

- Fixed many bugs since last commit
- added decoder calculations.
- next is working on connect fn