Metadata-Version: 2.1
Name: simdkalman
Version: 1.0.1
Summary: Kalman filters vectorized as Single Instruction, Multiple Data
Home-page: https://github.com/oseiskar/simdkalman
Author: Otto Seiskari
Author-email: UNKNOWN
License: MIT
Keywords: kalman filter smoothing em timeseries
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3
Requires-Dist: numpy (>=1.9.0)
Provides-Extra: dev
Requires-Dist: check-manifest ; extra == 'dev'
Provides-Extra: docs
Requires-Dist: sphinx ; extra == 'docs'
Provides-Extra: test
Requires-Dist: nose ; extra == 'test'

Fast Kalman filters in Python leveraging single-instruction multiple-data
vectorization. That is, running *n* similar Kalman filters on *n* independent
series of observations. Not to be confused with SIMD processor instructions.

See `full documentation <https://simdkalman.readthedocs.io/>`_.


