Library for constructing variable bandwidth diffusion maps
This is the home of the documentation for pyDiffMap, an open-source project to develop a robust and accessible diffusion map code for public use. Our documentation is currently under construction, please bear with us.
- Free software: MIT License.
Pydiffmap is installable using pip. You can install it using the command
pip install pyDiffMap
You can also install the package directly from the source directly by downloading the package from github and running the command below, optionally with the “-e” flag for an editable install.
pip install [source_directory]
To run the all tests run:
Note, to combine the coverage data from all the tox environments run:
set PYTEST_ADDOPTS=--cov-append tox
If you don’t have tox installed, you can also run the python tests directly with
0.2.0.1 (2019-02-04) New Features ~~~~~~~~~~~~ * Added a more generous epsilon procedure for convenience.
- Added support for user-provided kernel functions.
- Added a utility for building a sparse matrix from a function on the data.
- (Re)added separate TMDmap class wrapping base diffusion map class to allow for easier construction of TMDmaps.
- Added ability to explicitly provide the sampled density for q^alpha normalization.
- Added Variable Bandwidth Diffusion Maps.
- Added a new out-of-sample extension method that should work for variable bandwidth methods.
Tweaks and Modifications
- Changed from exp^(-d^2) to exp^(-d^2/4) convention.
- Moved weight functionality into a function provided on initialization, rather than input values, and added a helper function that allows values to be read from a lookup table.
- Improved the Diffusion Map test suite.
- Moved out-of-sample routines into separate functions.
- Moved matrix symmetrization into newly made utility file.
- Adjusted constructor for the diffusion map to take the kernel object directly.
- Fixed bug where weight matrices were not included for out of sample extension.
- Moved to MIT license.
- Fixed setup.py issues.
- Added base functionality to the code.
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