Skip to main content

Sequential Monte Carlo modeling for linear Gaussian systems

Project description

# smc_kalman

Sequential Monte Carlo modeling for linear Gaussian systems

## Installation

  • Clone this repo to any convenient location on your local drive

  • From within your Python development environment (base environment or a virtual environment), run pip install -e LOCAL_PATH_TO_REPO

  • pip will install the smc_kalman package in your Python development environment (along with all dependencies)

  • You can then import the modules like any other Python package (e.g., import smc_kalman)

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

wf-smc-kalman-0.1.0.tar.gz (3.8 kB view details)

Uploaded Source

Built Distribution

wf_smc_kalman-0.1.0-py3-none-any.whl (4.7 kB view details)

Uploaded Python 3

File details

Details for the file wf-smc-kalman-0.1.0.tar.gz.

File metadata

  • Download URL: wf-smc-kalman-0.1.0.tar.gz
  • Upload date:
  • Size: 3.8 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/2.0.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/39.0.1 requests-toolbelt/0.9.1 tqdm/4.36.1 CPython/3.6.5

File hashes

Hashes for wf-smc-kalman-0.1.0.tar.gz
Algorithm Hash digest
SHA256 f6f35c0c4f729a177e5971eaf971d742ff7997251c239edcfefb1e52ec6db5b8
MD5 9c11066a704dda6006d2d07bb008c1ce
BLAKE2b-256 e2296ff892d89f05ba6f7396f9cbd340d6abb7b47b16b3a02f454fb041afdf24

See more details on using hashes here.

File details

Details for the file wf_smc_kalman-0.1.0-py3-none-any.whl.

File metadata

  • Download URL: wf_smc_kalman-0.1.0-py3-none-any.whl
  • Upload date:
  • Size: 4.7 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/2.0.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/39.0.1 requests-toolbelt/0.9.1 tqdm/4.36.1 CPython/3.6.5

File hashes

Hashes for wf_smc_kalman-0.1.0-py3-none-any.whl
Algorithm Hash digest
SHA256 4018749e20da14fdebe1c8f2d80162d8f00064f7860f7553ec3d8e7de7f749ad
MD5 05cba6f6899e4b4b6bd9f0837d614379
BLAKE2b-256 b367c9f409948c2700a86e76890b1b6f88880315977208ef0b4a096dc3c0e62a

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page