Skip to main content

Plugin-based component modeling tool.

Project description

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.readthedocs.org

After installation, tests can be run with:

$ python -c ‘import landlab; landlab.test()’

The most current development version is always available from our git repository:

http://github.com/landlab/landlab

Project Status

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?svg=true https://landscape.io/github/landlab/landlab/master/landscape.svg

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-0.1.27.tar.gz (541.2 kB view details)

Uploaded Source

Built Distributions

landlab-0.1.27-cp34-cp34m-macosx_10_5_x86_64.whl (721.5 kB view details)

Uploaded CPython 3.4m macOS 10.5+ x86-64

landlab-0.1.27-cp33-cp33m-macosx_10_5_x86_64.whl (721.5 kB view details)

Uploaded CPython 3.3m macOS 10.5+ x86-64

landlab-0.1.27-cp27-none-win_amd64.whl (613.8 kB view details)

Uploaded CPython 2.7 Windows x86-64

landlab-0.1.27-cp27-none-win32.whl (607.3 kB view details)

Uploaded CPython 2.7 Windows x86

landlab-0.1.27-cp27-none-macosx_10_5_x86_64.whl (738.5 kB view details)

Uploaded CPython 2.7 macOS 10.5+ x86-64

landlab-0.1.27-cp26-none-win_amd64.whl (614.5 kB view details)

Uploaded CPython 2.6 Windows x86-64

landlab-0.1.27-cp26-none-win32.whl (608.1 kB view details)

Uploaded CPython 2.6 Windows x86

landlab-0.1.27-cp26-none-macosx_10_5_x86_64.whl (738.6 kB view details)

Uploaded CPython 2.6 macOS 10.5+ x86-64

File details

Details for the file landlab-0.1.27.tar.gz.

File metadata

  • Download URL: landlab-0.1.27.tar.gz
  • Upload date:
  • Size: 541.2 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No

File hashes

Hashes for landlab-0.1.27.tar.gz
Algorithm Hash digest
SHA256 f6ae96e1fd36fcea538d461fb5d4e288e5d2abaa6d25c09dcf7da1da459729ce
MD5 d0f39d131099707146b6f99d89a39929
BLAKE2b-256 4fa54247494b5de8d9e499af8f0f5bcf0f68fc31c05b7d013b0ba75622af333b

See more details on using hashes here.

File details

Details for the file landlab-0.1.27-cp34-cp34m-macosx_10_5_x86_64.whl.

File metadata

File hashes

Hashes for landlab-0.1.27-cp34-cp34m-macosx_10_5_x86_64.whl
Algorithm Hash digest
SHA256 bb7bd053909e8b23c4121003d857859964ac29fcf830d8abf69e26ca56c368b4
MD5 d9edafea4aa1b51000e819e8fb0cb1d2
BLAKE2b-256 0214cafa534c897cbe99ad6068bee0ae8cad8ba852e3fc9372256b60698230cc

See more details on using hashes here.

File details

Details for the file landlab-0.1.27-cp33-cp33m-macosx_10_5_x86_64.whl.

File metadata

File hashes

Hashes for landlab-0.1.27-cp33-cp33m-macosx_10_5_x86_64.whl
Algorithm Hash digest
SHA256 d067e31b2f1fefe58ce3ef70ab70d685c60fbc6805688cb6363c852a76ebf881
MD5 30443371c3c21e9727b11c2eff167018
BLAKE2b-256 f1885d4f07b676a1a75bcf0ee37af6de33512164a930d29828374793f5c8607a

See more details on using hashes here.

File details

Details for the file landlab-0.1.27-cp27-none-win_amd64.whl.

File metadata

File hashes

Hashes for landlab-0.1.27-cp27-none-win_amd64.whl
Algorithm Hash digest
SHA256 a4b412f0498ccdb6084af1c017af32c29c836c5e51d8d6e55e22af37cf8d1504
MD5 928176548e2af417960627aa573f24e8
BLAKE2b-256 4fb3f9a677ad12217feb323799b47fc58f532a8284c30255ad14ebaf199cc1b6

See more details on using hashes here.

File details

Details for the file landlab-0.1.27-cp27-none-win32.whl.

File metadata

File hashes

Hashes for landlab-0.1.27-cp27-none-win32.whl
Algorithm Hash digest
SHA256 9107733988d4bb9c94e671e8ec5e87572222b667d2ad42831c08e0b34385fdd9
MD5 eb9a663f0ece29eb6dd8954648a708fc
BLAKE2b-256 12ddfc7af8ebba354b0953960f64762f340cd5afc75ae7d18bb93525c3860036

See more details on using hashes here.

File details

Details for the file landlab-0.1.27-cp27-none-macosx_10_5_x86_64.whl.

File metadata

File hashes

Hashes for landlab-0.1.27-cp27-none-macosx_10_5_x86_64.whl
Algorithm Hash digest
SHA256 36f29b6901ac1c086d5ad290e3c2867c9c4c934afaaff85993223f4b43d486a2
MD5 5b221434170e60e8449f7e875a5d6be8
BLAKE2b-256 d9cc0dbaaf6803f5a21d8d6f9c42817230bac61670134665fc177f5a774157b8

See more details on using hashes here.

File details

Details for the file landlab-0.1.27-cp26-none-win_amd64.whl.

File metadata

File hashes

Hashes for landlab-0.1.27-cp26-none-win_amd64.whl
Algorithm Hash digest
SHA256 51b9786e74d5decc402fcffa6c2a303be13fb3572dc83b03a46a352e1dd30942
MD5 0717f7607e025734632a697094ba2c32
BLAKE2b-256 410c91f984a719e14089d6bfa7fef7550e4aa19bc4daa848209df1c5c8175594

See more details on using hashes here.

File details

Details for the file landlab-0.1.27-cp26-none-win32.whl.

File metadata

File hashes

Hashes for landlab-0.1.27-cp26-none-win32.whl
Algorithm Hash digest
SHA256 cd28b99cd580f87dbb804e8789d02e5c2c0f5324b71e3aeab46488ac386c115e
MD5 5c475d8717a99bd70605f06321910f29
BLAKE2b-256 dd2be6c6eb06809b19613936687a5566c8d716cf1d9ebaeeff56e93c21863cc7

See more details on using hashes here.

File details

Details for the file landlab-0.1.27-cp26-none-macosx_10_5_x86_64.whl.

File metadata

File hashes

Hashes for landlab-0.1.27-cp26-none-macosx_10_5_x86_64.whl
Algorithm Hash digest
SHA256 11b7ad486689ecaa07430319fd4106fedee84ee195f11f2affe5857ca9461db6
MD5 cb17758f76e63ce7eaa10427800719c1
BLAKE2b-256 6eb6de301aaa75079275ad2a2fb6906f8bcd7b41f3e113c7c9df5e35a273721a

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