Skip to main content

Plugin-based component modeling tool.

Project description

https://zenodo.org/badge/DOI/10.5281/zenodo.154179.svg https://readthedocs.org/projects/landlab/badge/?version=latest https://travis-ci.org/landlab/landlab.svg?branch=master https://coveralls.io/repos/landlab/landlab/badge.png https://ci.appveyor.com/api/projects/status/6u0bj0pggxrmf7s1/branch/master?svg=true https://landscape.io/github/landlab/landlab/master/landscape.svg

landlab

The Landlab project creates an environment in which scientists can build a numerical landscape model without having to code all of the individual components. Landscape models compute flows of mass, such as water, sediment, glacial ice, volcanic material, or landslide debris, across a gridded terrain surface. Landscape models have a number of commonalities, such as operating on a grid of points and routing material across the grid. Scientists who want to use a landscape model often build their own unique model from the ground up, re-coding the basic building blocks of their landscape model rather than taking advantage of codes that have already been written.

More information can be found at the website:

http://landlab.github.io

This open-source manuscript is a gateway for entering the Landlab world:

http://www.earth-surf-dynam.net/5/21/2017/

Two main installation options exist for Landlab. Most people will likely want to install the conda package. Individuals interested in modifying the Landlab source code should follow the developer installation instructions.

The most current source code is always available from our git repository:

http://github.com/landlab/landlab

Project details


Release history Release notifications | RSS feed

Download files

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

Source Distribution

landlab-1.9.0b1.tar.gz (825.8 kB view details)

Uploaded Source

Built Distributions

landlab-1.9.0b1-cp37-cp37m-win_amd64.whl (1.9 MB view details)

Uploaded CPython 3.7m Windows x86-64

landlab-1.9.0b1-cp36-cp36m-win_amd64.whl (1.9 MB view details)

Uploaded CPython 3.6m Windows x86-64

landlab-1.9.0b1-cp27-cp27m-win_amd64.whl (2.0 MB view details)

Uploaded CPython 2.7m Windows x86-64

File details

Details for the file landlab-1.9.0b1.tar.gz.

File metadata

  • Download URL: landlab-1.9.0b1.tar.gz
  • Upload date:
  • Size: 825.8 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.13.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.0.1 requests-toolbelt/0.9.1 tqdm/4.32.1 CPython/3.7.3

File hashes

Hashes for landlab-1.9.0b1.tar.gz
Algorithm Hash digest
SHA256 169a85d8d9a5d5b73db97bd5fa699dacb43a120f48bc5b9e0c608ff38c30e0b5
MD5 ed738599c86273731097d1bc06fa2324
BLAKE2b-256 5a1059e9b022701dc59cd0ce8591eb2952813e101b004b868e65ebb40db5f115

See more details on using hashes here.

File details

Details for the file landlab-1.9.0b1-cp37-cp37m-win_amd64.whl.

File metadata

  • Download URL: landlab-1.9.0b1-cp37-cp37m-win_amd64.whl
  • Upload date:
  • Size: 1.9 MB
  • Tags: CPython 3.7m, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.13.0 pkginfo/1.5.0.1 requests/2.21.0 setuptools/40.6.3 requests-toolbelt/0.9.1 tqdm/4.32.1 CPython/3.7.1

File hashes

Hashes for landlab-1.9.0b1-cp37-cp37m-win_amd64.whl
Algorithm Hash digest
SHA256 fb506e64147dd3f94f50b8991821376caedeefedd32cabdae42585a012f69971
MD5 b0711b0e2414867278c8ffe016b01940
BLAKE2b-256 2ee4ec9d175776305180c838f6845f9d51d8582dcbd05ad908d456505f9b51cd

See more details on using hashes here.

File details

Details for the file landlab-1.9.0b1-cp36-cp36m-win_amd64.whl.

File metadata

  • Download URL: landlab-1.9.0b1-cp36-cp36m-win_amd64.whl
  • Upload date:
  • Size: 1.9 MB
  • Tags: CPython 3.6m, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.13.0 pkginfo/1.5.0.1 requests/2.21.0 setuptools/39.2.0 requests-toolbelt/0.9.1 tqdm/4.32.1 CPython/3.6.5

File hashes

Hashes for landlab-1.9.0b1-cp36-cp36m-win_amd64.whl
Algorithm Hash digest
SHA256 eee47f60a7b1179fd1b834593063bed875aecea2a0986501e454db3eb52688be
MD5 7483674acf7efeacfd9cdb70884755bb
BLAKE2b-256 0fbdf06a573913871468e65c2c567e88cad509654fb7a2e5d8663dcbc9dad869

See more details on using hashes here.

File details

Details for the file landlab-1.9.0b1-cp27-cp27m-win_amd64.whl.

File metadata

  • Download URL: landlab-1.9.0b1-cp27-cp27m-win_amd64.whl
  • Upload date:
  • Size: 2.0 MB
  • Tags: CPython 2.7m, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.13.0 pkginfo/1.5.0.1 requests/2.21.0 setuptools/40.6.3 requests-toolbelt/0.9.1 tqdm/4.32.1 CPython/2.7.15

File hashes

Hashes for landlab-1.9.0b1-cp27-cp27m-win_amd64.whl
Algorithm Hash digest
SHA256 f42ff760b015759a4177934e4afff4edc8c8959f40510116439032cd38d48238
MD5 2da626d07feae6edf7a99546ac3681b9
BLAKE2b-256 edca1061b040970753fa21c233e9713f01bb1cbbf27e7c5f11e9923856f0b1ce

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