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-0.1.3.tar.gz (65.7 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-0.1.3-py3-none-any.whl (68.5 kB view details)

Uploaded Python 3

File details

Details for the file Cb_FloodDy-0.1.3.tar.gz.

File metadata

  • Download URL: Cb_FloodDy-0.1.3.tar.gz
  • Upload date:
  • Size: 65.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.10.9

File hashes

Hashes for Cb_FloodDy-0.1.3.tar.gz
Algorithm Hash digest
SHA256 3adf8fa88b277035febcc4d840bc5e8354a194819563f82d11e5ae204498351c
MD5 948af3d84e0414bc10287421f333641b
BLAKE2b-256 775c67a07578f899c4189588ef87b4c2eb3e85d74f679d7f97170ebcd0e03687

See more details on using hashes here.

File details

Details for the file Cb_FloodDy-0.1.3-py3-none-any.whl.

File metadata

  • Download URL: Cb_FloodDy-0.1.3-py3-none-any.whl
  • Upload date:
  • Size: 68.5 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-0.1.3-py3-none-any.whl
Algorithm Hash digest
SHA256 7c28e755bc0f6dbad6d9fc08fcc6aa221b176883300896092b85883bd7002720
MD5 f9d148d307a89649021d3a7ef73a52df
BLAKE2b-256 6ea61bc9f61ccb000e552a5f2c91d726777c65f966bd2182405b0e7faa25b62b

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