Skip to main content

A cluster-based temporal attention approach for predicting cyclone-induced compound flood dynamics

Project description

Cb_FloodDy

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

Cb_FloodDy-0.1.9.tar.gz (60.7 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

Cb_FloodDy-0.1.9-py3-none-any.whl (64.0 kB view details)

Uploaded Python 3

File details

Details for the file Cb_FloodDy-0.1.9.tar.gz.

File metadata

  • Download URL: Cb_FloodDy-0.1.9.tar.gz
  • Upload date:
  • Size: 60.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.10.9

File hashes

Hashes for Cb_FloodDy-0.1.9.tar.gz
Algorithm Hash digest
SHA256 195ba27c5a3bc15ef9db6c9c7a0ca21ecbb9c52159a17324f21758d2f70215a5
MD5 4b2618d78c412b716e25dcd600313538
BLAKE2b-256 1582cfb617e15c319cdbe220bd9045cdc0978f3892bd8c76e08871b896480ae6

See more details on using hashes here.

File details

Details for the file Cb_FloodDy-0.1.9-py3-none-any.whl.

File metadata

  • Download URL: Cb_FloodDy-0.1.9-py3-none-any.whl
  • Upload date:
  • Size: 64.0 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.10.9

File hashes

Hashes for Cb_FloodDy-0.1.9-py3-none-any.whl
Algorithm Hash digest
SHA256 1b285a179618b61750f77390d0690eff0bc41dfc8e0f96fdaa49e85b091748b9
MD5 0c85a3aa2d6ab86d70181c69b896d411
BLAKE2b-256 dd6d6353b61053698ea788f3003cb49733337be9c82f24159f04b5e0a746e386

See more details on using hashes here.

Supported by

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