iisignature 0.23

Iterated integral signature calculations

This package provides tools for calculating the signature and log signature of a data stream. These are summary statistics of piecewise linear paths, consisting of iterated integrals, inspired by rough path theory. See <http://www2.warwick.ac.uk/jreizenstein/iisignature.pdf> for documentation, the page <http://www2.warwick.ac.uk/jreizenstein> for more information about the calculations, and <https://github.com/bottler/iisignature> for source code.

It is work in progress.

Python

Install with:

pip install iisignature

Don’t install this package if you don’t have numpy > 1.7 installed. On Windows, this package is not usable with Python 2.x. For Python 3.5, 3.6 and 3.7 on Windows, there are precompiled wheels available, you may need to do pip install wheel to use them. On other platforms, you will need to be able to compile C++ extensions. On a Mac, you will need to have installed Xcode and the Xcode command line tools before doing the installation. The fastest, on-the-fly compiled versions of the log signature calculations are for Windows, Mac and Linux, on both 32 and 64 bit.

Sometimes there are compile errors on a Mac, if this happens try:

MACOSX_DEPLOYMENT_TARGET=10.9 pip install iisignature

Use without installing a released version

To install the current “master” development version straight from github you can type:

pip install git+git://github.com/bottler/iisignature

From a checkout of this repository, you can build the extension and run the tests using:

python setup.py test

From a checkout of this repository, you can build the extension into this directory itself using:

python setup.py build_ext --inplace

after which you can use the package in Python in this directory, use the examples in the examples directory, or add this directory to your PYTHONPATH and then use the package in Python anywhere.

Authors

• Dr Benjamin Graham

• Jeremy Reizenstein

Thanks

This package includes BCH coefficients from Fernando Casas and Ander Murua. <http://arxiv.org/abs/0810.2656>