intervalic

Count and visualize interval relationships across large datasets.

• multiprocessing and numba support for faster computation.
• Visualization with matplotlib.
• Custom numpy.ndarray subclasses for more efficient storage.

Notes

• To run interval counting across dataset, see run.py.
• There exists counting methods for MIDI level as well as token level for interval and duration tokens. One may refer to src/calculations.py for more.
• Houses conversion and preparation functions for Arbitrary Learning Engine (ALE).