Installation of Dependencies¶
To run the examples, there are a handful of Python libraries that must be installed. Here we will try to summarize the libraries and how they can be installed. Links and references to more detailed installation instructions from the source libraries themselves will be provided as well.
numpy¶
This is a pretty standard computational library, it can be pip installed if needed:
pip install numpy
For additional information, see the numpy website.
matplotlib¶
For basic visualizations, this is also a commonly used library. If needed, it can be pip installed as well:
pip install matplotlib
For additional information, see the matplotlib website.
landlab¶
Landlab is a modular set of tools for landscape evolution modeling. Installation instructions are provided for both conda and pip installation of this package. These commands are:
conda install landlab -c conda-forge
and
pip install landlab
Refer to their documentation for more information about landlab.
dmsh¶
dmsh is a fully Pythonic mesh generator. It can be pip installed:
pip install dmsh
For more information, visit the project repository.
Anuga¶
Anuga is a Python package developed for simulating the shallow water equations. Installation of Anuga can be a bit challenging as it interfaces with C under the hood. In addition to dependencies created by non-Python programming langauges, Anuga also uses popular geospatial libraries. Geospatial libraries are notorious for causing dependency clashes. To further complicate matters, Anuga is currently (as of Sept, 2020) still in Python 2.7. Fear not, for a Python 3.x branch exists, and that is what the examples shown here will be based on.
Installation of Anuga is described in the project wiki. We suggest installation via Miniconda or Anaconda to help manage the dependencies.
Note
After running git clone to get a local copy of the Anuga repository prior to installation, you should be sure to checkout the anuga_py3 branch to ensure the version of Anuga you install is Python 3.x compatible.
itkwidgets¶
itkwidgets is a nifty package for creating interactive visualizations within Jupyter Notebooks. The package can be both conda and pip installed:
conda install -c conda-forge itkwidgets
and
pip install itkwidgets
Visit the project repository for more information about this library.
PyVista¶
PyVista brings the power of VTK visualizations to Python. It can be pip installed:
pip install pyvista
For more information about the installation process and the project, visit the PyVista documentation.