NuPIC

Numenta Platform for Intelligent Computing

NuPIC is a library that provides the building blocks for online prediction and anomaly detection systems. The library contains the Cortical Learning Algorithm (CLA), but also the [Online Prediction Framework (OPF)] (https://github.com/numenta/nupic/wiki/Online-Prediction-Framework) that allows clients to build prediction systems out of encoders, models, and metrics.

For more information, see numenta.org or the NuPIC wiki.

Installation

For all installation options, see the Installing and Building NuPIC wiki page.

Currently supported platforms:

• Linux (32/64bit)
• Mac OSX
• Raspberry Pi (ARMv6)
• Chromebook (Ubuntu ARM, Crouton) (ARMv7)
• VM images

Dependencies:

• Python (2.6-2.7) (with development headers)
• GCC (4.6-4.8), or Clang
• Make or any IDE supported by CMake (Visual Studio, Eclipse, XCode, KDevelop, etc)

The dependencies are included in platform-specific repositories for convenience:

• nupic-linux64 for 64-bit Linux systems
• nupic-darwin64 for 64-bit OS X systems

Complete set of python requirements are documented in requirements.txt, compatible with pip:

pip install -r external/common/requirements.txt

Note: If using pip 1.5 or later:

pip install --allow-all-external --allow-unverified PIL --allow-unverified psutil -r external/common/requirements.txt

Note: If you get a "permission denied" error when using pip, you may add the --user flag to install to a location in your home directory, which should resolve any permissions issues. Doing this, you may need to add this location to your PATH and PYTHONPATH. Alternatively, you can run pip with 'sudo'.

Build and test NuPIC:

NuPIC needs the following environment variables to build:

# `$NUPIC` is the path to your NuPIC repository.
# Remember to replace <NuPIC path> with the real path:
export NUPIC=<NuPIC path>

# `$NTA` is the installation path for NuPIC. 
export NTA=$NUPIC/build/release

NuPIC needs to be added to $PYTHONPATH to run and test:

# You may choose one of the following based on your version of Python:
# For Python 2.6:
export PYTHONPATH=$PYTHONPATH:$NTA/lib/python2.6/site-packages
# For Python 2.7:
export PYTHONPATH=$PYTHONPATH:$NTA/lib/python2.7/site-packages

Tips:

• You may set these environment variables in your dotfiles(e.g. ~/.bashrc under Bash) to avoid repeated typing.
• You may set a different path for $NTA or specify the location with CMake with the command line option -DPROJECT_BUILD_RELEASE_DIR:STRING=/my/custom/path.
• For more tips, please see Development-Tips

Using command line

Configure and generate build files:

mkdir -p $NUPIC/build/scripts
cd $NUPIC/build/scripts
cmake $NUPIC

Build:

cd $NUPIC/build/scripts
make -j3

Note: -j3 option specify '3' as the maximum number of parallel jobs/threads that Make will use during the build in order to gain speed. However, you can increase this number depending your CPU.

Run the tests:

cd $NUPIC/build/scripts
# all C++ unit tests
make cpp_unit_tests
# C++ HTM Network API tests
make tests_cpphtm
# Python HTM Network API tests
make tests_pyhtm
# Python OPF unit tests
make python_unit_tests
# Python OPF integration tests (requires mysql)
make python_integration_tests
# Run all tests!
make tests_all

Using graphical interface

Generate the IDE solution:

• Open CMake executable.
• Specify the source folder ($NUPIC).
• Specify the build system folder ($NUPIC/build/scripts), i.e. where IDE solution will be created.
• Click Generate.
• Choose the IDE that interest you (remember that IDE choice is limited to your OS, i.e. Visual Studio is available only on CMake for Windows).

Build:

• Open nupic.*proj solution file generated on $NUPIC/build/scripts.
• Run ALL_BUILD project from your IDE.

Run the tests:

• Run any test project from your IDE (check output panel to see the results).

Examples

For examples, tutorials, and screencasts about using NuPIC, see the Using NuPIC wiki page.