Data Assimilation with Python: a Package for Experimental Research.

Navigation

Verified details

These details have been verified by PyPI
Maintainers
Avatar for patricknraanes from gravatar.com patricknraanes

Unverified details

These details have not been verified by PyPI
Project links
Meta
  • License: MIT License
  • Author: Patrick N. Raanes
  • Tags data-assimilation, enkf, kalman-filtering, state-estimation, particle-filter, kalman, bayesian-methods, bayesian-filter, chaos
  • Requires: Python >=3.7
Classifiers

Project description

DAPPER is a set of templates for benchmarking the performance of data assimilation (DA). See full README at github.com/nansencenter/DAPPER.

Project details

Verified details

These details have been verified by PyPI
Maintainers
Avatar for patricknraanes from gravatar.com patricknraanes

Unverified details

These details have not been verified by PyPI
Project links
Meta
  • License: MIT License
  • Author: Patrick N. Raanes
  • Tags data-assimilation, enkf, kalman-filtering, state-estimation, particle-filter, kalman, bayesian-methods, bayesian-filter, chaos
  • Requires: Python >=3.7
Classifiers

Release history Release notifications | RSS feed

1.2.2

1.2.1

1.2.0

1.1.0

1.0.8

This version

1.0.0

0.9.9

0.9.8

0.9.6

0.9.5

0.9.4

0.9.3

0.9.2

0.9.1

0.9.0

Download files

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

Source Distribution

DA-DAPPER-1.0.0.tar.gz (256.2 kB view hashes)

Uploaded Source

Built Distribution

DA_DAPPER-1.0.0-py3-none-any.whl (291.4 kB view hashes)

Uploaded Python 3

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