Skip to main content

DAG tools to process numerical topography and landscape evolution models

Project description

DAGGER

DAG tools to process numerical topography and landscape evolution models

Features

  • TODO

References

TODO add and format the references

Credits

Main developer: Boris Gailleton (boris.gailleton@univ-rennes.fr)

Project partly funded byt projects within the SUBITOP ITN, University of Edinburgh, GFZ Postdam, ERC Feasible, Université de Rennes

This package formatting was created with Cookiecutter and the audreyr/cookiecutter-pypackage project template.

Some I/O operations are using libnpy (MIT), a header-only c++ library to write/load simple numpy arrays.

History

0.0.6 (01/08/2023)

  • Adding quick river and drainage divide extraction tools

0.0.4 (20/07/2023)

  • Hot fix (still developping the CI/CD toolchain)

0.0.3 (20/07/2023)

  • Fixing compilation for conda-forge on MacOS and Windows

  • Adding a quick topo function as quick test

0 (2023-07-20)

  • First release on PyPI.

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

daggerpy-0.0.6.tar.gz (218.5 kB view details)

Uploaded Source

File details

Details for the file daggerpy-0.0.6.tar.gz.

File metadata

  • Download URL: daggerpy-0.0.6.tar.gz
  • Upload date:
  • Size: 218.5 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.10.10

File hashes

Hashes for daggerpy-0.0.6.tar.gz
Algorithm Hash digest
SHA256 10c50c18bae7b69221ebf7f4862a2a475b06896e4b9447beacdc8632002895bd
MD5 fb8ca16284c90963d10c2ce1f6f55a32
BLAKE2b-256 2e8e28a026fcbd4d7bbf5b1a549d8c320ee3231c6dae1a5518f130c52b3b3d32

See more details on using hashes here.

Supported by

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