python-fastpip 1.2

Segmentation Based On Turning Points

The “Perceptually Important Points” algorithm gives a method for dimensionality reduction and a mechanism to automatically extract the most important points from a human observer perspective, favouring compression and a good visualization of time series with high dimensionality.

Example

>>> from fastpip import pip
>>> pip([(0, 0), (1, 1), (2, 2), (3, 1), (4, 0), (5, 1), (6, 2), (7, 1), (8, 0)], 5)
[(0, 0), (2, 2), (4, 0), (6, 2), (8, 0)]

References

• https://github.com/intelie/fastpip-js

• http://www.academia.edu/1578716/Aplica%C3%A7%C3%A3o_do_algoritmo_Perceptually_Important_Points_em_s%C3%A9ries_temporais_de_datacenters

• http://thescipub.com/PDF/jcssp.2010.1389.1395.pdf