/ Machine Learning

A high performance topological machine learning toolbox in Python

A high performance topological machine learning toolbox in Python

giotto-tda

giotto-tda is a high performance topological machine learning toolbox in Python built on top of scikit-learn and is distributed under the GNU AGPLv3 license. It is part of the Giotto family of open-source projects.

Project genesis

giotto-tda is the result of a collaborative effort between L2F SA, the Laboratory for Topology and Neuroscience at EPFL, and the Institute of Reconfigurable & Embedded Digital Systems (REDS) of HEIG-VD.

Getting started

To get started with giotto-tda, first follow the installations steps below. This blog post, and references therein, offer a friendly introduction to the topic of topological machine learning and to the philosophy behind giotto-tda.

Tutorials and use cases
Simple tutorials can be found in the examples folder. For a wide selection of use cases and application domains, you can visit this page.

Installation

Dependencies


The latest stable version of giotto-tda requires:

- Python (>= 3.6)
- NumPy (>= 1.17.0)
- SciPy (>= 0.17.0)
- joblib (>= 0.11)
- scikit-learn (>= 0.22.0)
- python-igraph (>= 0.7.1.post6)
- matplotlib (>= 3.0.3)
- plotly (>= 4.4.1)
- ipywidgets (>= 7.5.1)

To run the examples, jupyter is required.

User installation

The simplest way to install giotto-tda is using pip ::

pip install -U giotto-tda

If necessary, this will also automatically install all the above dependencies. Note: we recommend
upgrading pip to a recent version as the above may fail on very old versions.

Pre-release, experimental builds containing recently added features, and/or
bug fixes can be installed by running ::

pip install -U giotto-tda-nightly

The main difference between giotto-tda-nightly and the developer installation (see the section
on contributing, below) is that the former is shipped with pre-compiled wheels (similarly to the stable
release) and hence does not require any C++ dependencies. As the main library module is called gtda in
both the stable and nightly versions, giotto-tda and giotto-tda-nightly should not be installed in
the same environment.

Contributing

We welcome new contributors of all experience levels. The Giotto
community goals are to be helpful, welcoming, and effective. To learn more about
making a contribution to giotto-tda, please see the CONTRIBUTING.rst
<https://github.com/giotto-ai/giotto-tda/blob/master/CONTRIBUTING.rst>_ file.

Developer installation

Installing both the PyPI release and source of giotto-tda in the same environment is not recommended since it is
known to cause conflicts with the C++ bindings.

The developer installation requires three important C++ dependencies:

  • A C++14 compatible compiler
  • CMake >= 3.9
  • Boost >= 1.56

Please refer to your system's instructions and to the CMake <https://cmake.org/>_ and
Boost <https://www.boost.org/doc/libs/1_72_0/more/getting_started/index.html>_ websites for definitive guidance on how to install these dependencies. The instructions below are unofficial, please follow them at your own risk.

Linux
'''''
Most Linux systems should come with a suitable compiler pre-installed. For the other two dependencies, you may consider using your distribution's package manager, e.g. by running

.. code-block:: bash

sudo apt-get install cmake libboost-dev

if apt-get is available in your system.

macOS
'''''
On macOS, you may consider using brew (https://brew.sh/) to install the dependencies as follows:

.. code-block:: bash

brew install gcc cmake boost

Windows
'''''''
On Windows, you will likely need to have Visual Studio <https://visualstudio.microsoft.com/>_ installed. At present,
it appears to be important to have a recent version of the VS C++ compiler. One way to check whether this is the case
is as follows: 1) open the VS Installer GUI; 2) under the "Installed" tab, click on "Modify" in the relevant VS
version; 3) in the newly opened window, select "Individual components" and ensure that v14.24 or above of the MSVC
"C++ x64/x86 build tools" is selected. The CMake and Boost dependencies are best installed using the latest binary
executables from the websites of the respective projects.

Source code
'''''''''''

You can obtain the latest state of the source code with the command::

git clone https://github.com/giotto-ai/giotto-tda.git

To install:
'''''''''''

.. code-block:: bash

cd giotto-tda
pip install -e ".[tests, doc]"

This way, you can pull the library's latest changes and make them immediately available on your machine.
Note: we recommend upgrading pip and setuptools to recent versions before installing in this way.

Testing

After installation, you can launch the test suite from outside the
source directory::

pytest gtda

GitHub