See the thorough documentation at https://geomdata.github.io/gda-public/
This contains several fundamental tools by Geometric Data Analytics Inc. [http://www.geomdata.com] See LICENSE for copyright information.
The code is written in Python and Cython. It is written for Python 3.5, but it should work in Python 2.7 (albeit with some performance penalty). For stability and consistency, Anaconda is preferred.
See requirements.txt
for requirements.
If you want to work in an air-gapped system, you can pre-download all of the
required packages from http://repo.continuum.io/pkgs/ This is automated in
download.py
and download-viz.py
, and is described below.
Please submit any BUGS to https://github.com/geomdata/gda-public/issues
Here are minimal instructions with no detail. First, unpack or clone the code to /path/to/gda-public
. Then
bash$ cd ~ # Change directory to anywhere *except* /path/to/gda-public ! bash$ conda create --name gda_env --file /path/to/gda-public/requirements.txt python=3 bash$ source activate gda_env (gda_env) bash$ pip install file:///path/to/gda-public (gda_env) bash$ jupyter notebook --notebook-dir /path/to/gda-public/examples
In a worksheet, try
>>> import multidim, homology, timeseries
The package comes with thorough documentation in docstrings, accessible from
within python via the help( )
command:
(gda_env) bash$ python >>> import timeseries >>> help(timeseries) >>> s = timeseries.Signal([1,2,3,4,5]) >>> help(s)
You can build a nice HTML guide, but you need to get a copy of the SciPy Sphinx theme:
(gda_env) bash$ cd /path/to/gda-public (gda_env) bash$ git clone https://github.com/scipy/scipy-sphinx-theme (gda_env) bash$ cd doc_src (gda_env) bash$ ln -sf ../scipy-sphinx-theme/_theme ./ (gda_env) bash$ cd - (gda_env) bash$ python setup.py build_doc_html
which can be viewed in a web browser at file:////path/to/gda-public/docs/build/html/index.html
You can also produce a static PDF documentation with
(gda_env) bash$ python setup.py build_doc_latex (gda_env) bash$ cd /path/to/gda-public/doc_build/latex/latex (gda_env) bash$ make
Or, just build the .tex file using your favorite TeX suite.
This will be filled in later versions, with suggestions.
Take a look at examples_README and the jupyter notebooks in examples/
The docstrings, accessible via help( )
, are always a good reference for
low-level operations.
Note! The code contains a lot of "assert" statements, so you can speed it up
by using python -O
.