Metadata-Version: 2.0
Name: simdkalman
Version: 0.9.2
Summary: Kalman filters vectorized as Single Instruction, Multiple Data
Home-page: https://simdkalman.readthedocs.io/
Author: Otto Seiskari
Author-email: UNKNOWN
License: MIT
Description-Content-Type: UNKNOWN
Keywords: kalman filter smoothing em timeseries
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
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 (>=1.10.0)
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.


