Installation Instructions¶
Obtaining the Latest Software¶
The latest version of the Time Encoding and Decoding Toolkit can be downloaded from the Bionet Group’s code repository page.
Prerequisites¶
The Python implementation of the Time Encoding and Decoding Toolkit requires that several software packages be present in order to be built and installed (older versions of these packages may work, but have not been tested):
To run the CUDA-dependent implementations, you will also need
- NVIDIA CUDA Toolkit 3.2 or later.
- PyCUDA 0.94.2 or later.
- scikit.cuda 0.04 or later.
To run the demo code and generate plots, the following package is also required:
- Matplotlib 0.98 or later.
Some of the utility functions may require the following packages:
To build the documentation, the following packages are also required:
- Docutils 0.5 or later.
- Jinja2 2.2 or later
- Pygments 0.8 or later
- Sphinx 1.0.1 or later.
- Sphinx ReadTheDocs Theme 0.1.6 or later.
This software has been tested on Linux; it should also work on other platforms supported by the above packages.
Building and Installation¶
To build and install the toolkit, download and unpack the source release and run:
python setup.py install
from within the main directory in the release. Sample code demonstrating how to use the toolkit is located in the demos/ subdirectory. If you have pip installed, you can install the latest package code directly from Github as follows:
pip install git+git://github.com/bionet/ted.python.git
To rebuild the documentation, run:
make
from within the docs/ subdirectory and follow the directions.