dgcnn

This is the documentation of dgcnn.

Contents

License

The MIT License (MIT)

Copyright (c) 2020 Levi Borodenko

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the “Software”), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

Contributors

Changelog

Version 0.1

  • Baseline working implementation of DGCNN
  • pushing to GitHub

Version 0.2

  • Proper Docstrings.
  • Trying it on financial data.

Version 0.3

  • Finished documentation
  • Wrote README.md
  • added flatten_signals option to DeepGraphConvolution
  • publish to pypi and github.
  • publish docs.

dgcnn

dgcnn package

Submodules
dgcnn.attention module
dgcnn.components module
dgcnn.layers module
dgcnn.utils module

Some helpful utility functions.

dgcnn.utils.is_positive_integer(obj, name: str) → None[source]

Checks if obj is a positive integer and raises appropriate errors if it isn’t.

Parameters:
  • obj – object to be checked.
  • name (str) – name of object for error messages.
Module contents

Indices and tables