.. currentmodule:: geocat.comp
This installation guide includes only the GeoCAT-comp installation and build instructions. Please refer to GeoCAT Contributor's Guide for installation of the whole GeoCAT project.
The easiest way to install GeoCAT-comp is using Conda:
conda create -n geocat -c conda-forge geocat-comp
where "geocat" is the name of a new conda environment, which can then be activated using:
conda activate geocat
If you somewhat need to make use of other software packages, such as Matplotlib,
Cartopy, Jupyter, etc. with GeoCAT-comp, you may wish to install into your geocat
environment. The following conda create
command can be used to create a new
conda
environment that includes some of these additional commonly used Python
packages pre-installed:
conda create -n geocat -c conda-forge geocat-comp matplotlib cartopy jupyter
Alternatively, if you already created a conda environment using the first command (without the extra packages), you can activate and install the packages in an existing environment with the following commands:
conda activate geocat # or whatever your environment is called conda install -c conda-forge matplotlib cartopy jupyter
Please note that the use of the conda-forge
channel is essential to guarantee
compatibility between dependency packages.
Also, note that the Conda package manager automatically installs all required dependencies of GeoCAT-comp, meaning it is not necessary to explicitly install Python, NumPy, Xarray, or Dask when creating an envionment and installing GeoCAT-comp. Although packages like Matplotlib are often used with GeoCAT-comp, they are considered optional dependencies and must be explicitly installed.
If you are interested in learning more about how Conda environments work, please visit the managing environments page of the Conda documentation.
If you started a project and later decided to use GeoCAT-comp, you will need to install it in your pre-existing environment.
Make sure your conda is up to date by running this command from the terminal:
conda update conda
Activate the conda environment you want to add GeoCAT to. In this example, the environment is called
foo
:conda activate foo
Install geocat-comp:
conda install -c conda-forge geocat-comp
It is important to keep your version of geocat-comp
up to date. This can be done as follows:
Make sure your Conda is up to date by running this command from the terminal:
conda update conda
Activate the conda environment you want to update. In this example, the environment is called
geocat
:conda activate geocat
Update
geocat-comp
:conda update geocat-comp
GeoCAT-comp is distributed also in PyPI; therefore, the above Conda installation instructions should, in theory,
apply to PyPI installation through using pip install
commands instead of conda install
wherever they occur.
Building GeoCAT-comp from source code is a fairly straightforward task, but doing so should not be necessary for most users. If you are interested in building GeoCAT-comp from source, you will need the following packages to be installed.
- Python 3.8+
- GeoCAT-datafiles (For tests only)
- GeoCAT-f2py
- cf_xarray
- cftime
- eofs
- dask
- distributed
- netcdf4 (For tests only)
- numpy
- pytest (For tests only)
- xarray
Note: GeoCAT-f2py dependency will automatically install further dependencies for compiled language implementation.
The GeoCAT-comp source code includes a conda environment definition file in
the build_envs
folder under the root directory that can be used to create a
development environment containing all of the packages required to build GeoCAT-comp.
The file environment.yml
is intended to be used on Linux systems and macOS.
The following commands should work on both Linux and macOS:
conda env create -f build_envs/environment.yml conda activate geocat_comp_build
Once the dependencies listed above are installed, you can install GeoCAT-comp with running the following command from the root-directory:
pip install .
For compatibility purposes, we strongly recommend using Conda to configure your build environment as described above.
A GeoCAT-comp build can be tested from the root directory of the source code repository using the following command (Explicit installation of the pytest package may be required, please see above):
pytest test