PAMI - An Open Source PAttern MIning Python Library

PAMI is a Python library containing 100+ algorithms to discover useful patterns in various databases across multiple computing platforms. (Active)

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Location to place an algorithm in PAMI

Hierarchical structure of algorithms

The algorithm in PAMI follow an hierarchical structure as shown below.

  1. PAMI
    • theoreticalModel1
      • basic
        • Algo1
        • Algo2 …
        • AlgoM
      • closed
        • cAlgo1
        • cAlgo2 …
        • cAlgoM
      • maximal
        • mAlgo1
        • mAlgo2 …
        • mAlgoM
      • top-k
        • kAlgo1
        • kAlgo2 …
        • kAlgoM
    • extras
      • graphs

Steps to place an algorithm for a new pattern model

If the user is writing the code for new theoretical pattern model that does not exist in PAMI, then please perform the following steps:

  1. Create a directory with name of the pattern and enter into the corresponding directory.
  2. Generate an empty file, titled __init__.py
  3. Create another directory, say basic, closed, or maximal, depending on the type of pattern.
  4. Enter into this subdirectory and generate another empty file, titled __init__.py
  5. Place your abstract.py file in this subdirectory.
  6. Place your algorithm inheriting the abstract.py file also in this subdirectory. If your algorithm does not inherit the abstract.py file, no problem. Simply place your algorithm here.

Steps to place an algorithm for the already existing pattern model

If the user has written an algorithm for a pattern model that already exists in the PAMI repository, then perform the following steps:

  1. Enter into the directory of the corresponding theoretical pattern model.
  2. Enter into the subdirectory, say basic, of the corresponding model. If the subdirectory for your algorithm does not exist, then create a subdirectory, and create a __init__.py file.
  3. Place your algorithm in the subdirectory.