landlab 2.6.0

Open-source Python package for numerical modeling of Earth surface dynamics.

Landlab

What does Landlab do?

Landlab is an open-source Python-language package for numerical modeling of Earth surface dynamics. It contains

• A gridding engine which represents the model domain. Regular and irregular grids are supported.

• A library of process components, each of which represents a physical process (e.g., generation of rain, erosion by flowing water). These components have a common interface and can be combined based on a user’s needs.

• Utilities that support general numerical methods, file input/output, and visualization.

In addition Landlab contains a set of Jupyter notebook tutorials providing an introduction to core concepts and examples of use.

Landlab was designed for disciplines that quantify Earth surface dynamics such as geomorphology, hydrology, glaciology, and stratigraphy. It can also be used in related fields. Scientists who use this type of 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. Landlab saves practitioners from the need for this kind of re-invention by providing standardized components that they can re-use.

Watch the webinar Landlab Toolkit Overview at CSDMS to learn more.

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Installation

To install the latest release of landlab using pip, simply run the following in your terminal of choice:

$ pip install landlab

For a full description of how to install Landlab, including using mamba/conda, please see the documentation for our installation instructions.

Source code

If you would like to modify or contribute code to Landlab or use the very latest development version, please see the documentation that describes how to install landlab from source.

Are there any examples of using Landlab I can look at?

The Landlab package contains a directory, landlab/notebooks, with Jupyter Notebooks describing core concepts and giving examples of using components. The file landlab/notebooks/welcome.ipynb provides a table of contents to the notebooks and is the recommended starting place. Additionally, there are a set of notebooks curated to teach physical processes located in the directory landlab/notebooks/teaching.

Run on Binder

To launch an instance of Binder and explore the notebooks click here.

To launch a Binder instance that goes straight to the teaching notebooks click here.

Run on the CSDMS JupyterHub

The Landlab notebooks can also be run on the CSDMS JupyterHub. To sign up for a free account, visit the CSDMS wiki and follow the instructions there. Then, click to explore the example notebooks, or to go straight to the teaching notebooks.

License

landlab is licensed under the MIT License.

Citing Landlab

If you use any portion of Landlab, please see the documentation for our citation guidelines.

Contact

The recommended way to contact the Landlab team is with a GitHub Issue.

• Bug reports: Please make an Issue describing the bug so we can address it, or work with you to address it. Please try to provide a minimal, reproducible example.

• Documentation: If something in our documentation is not clear to you, please make an issue describing the what isn’t clear. Someone will tag the most appropriate member of the core Landlab team. We will work to clarify your question and revise the documentation so that it is clear for the next user.

Keep in touch with the latest landlab news by following us on Twitter.

During workshops and clinics, we sometimes use the Landlab Slack channel.

Credits

Development Leads

• Greg Tucker

• Nicole Gasparini

• Erkan Istanbulluoglu

• Daniel Hobley

• Sai S. Nudurupati

• Jordan Adams

• Eric Hutton

• Jenny Knuth

• Katy Barnhart

• Margaux Mouchene

• Christina Bandaragoda

• Nathan Lyons

Contributors

• Charlie Shobe

• Ronda Strauch

• David Litwin

• Rachel Glade

• Giuseppecipolla95

• Amanda Manaster

• elbeejay

• Allison Pfeiffer

• alangston

• Kristen Thyng

• Dylan Ward

• Benjamin Campforts

• Sebastien Lenard

• Shelby Ahrendt

• Josh Wolpert

• Christopher Sheehan

• slundell123