Installing
Quickstart
The fastest way to install PyGMT is with the conda or mamba package manager which takes care of setting up a virtual environment, as well as the installation of GMT and all the dependencies PyGMT depends on:
conda create --name pygmt --channel conda-forge pygmt
mamba create --name pygmt --channel conda-forge pygmt
To activate the virtual environment, you can do:
conda activate pygmt
mamba activate pygmt
After this, check that everything works by running the following in a Python interpreter (e.g., in a Jupyter notebook):
import pygmt
pygmt.show_versions()
You are now ready to make you first figure! Start by looking at the tutorials on our sidebar, good luck!
Note
The sections below provide more detailed, step by step instructions to install and test PyGMT for those who may have a slightly different setup or want to install the latest development version.
Which Python?
PyGMT is tested to run on Python 3.8 or greater.
We recommend using the Anaconda Python distribution to ensure you have all dependencies installed and the conda package manager is available. Installing Anaconda does not require administrative rights to your computer and doesn’t interfere with any other Python installations on your system.
Which GMT?
PyGMT requires Generic Mapping Tools (GMT) version 6 as a minimum, which is the latest released version that can be found at the GMT official site. We need the latest GMT (>=6.3.0) since there are many changes being made to GMT itself in response to the development of PyGMT, mainly the new modern execution mode.
Compiled conda packages of GMT for Linux, macOS and Windows are provided through conda-forge. Advanced users can also build GMT from source instead.
We recommend following the instructions further on to install GMT 6.
Dependencies
PyGMT requires the following libraries to be installed:
The following are optional dependencies:
Installing GMT and other dependencies
Before installing PyGMT, we must install GMT itself along with the other
dependencies. The easiest way to do this is via the conda
package manager.
We recommend working in an isolated
conda environment
to avoid issues with conflicting versions of dependencies.
First, we must configure conda to get packages from the conda-forge channel:
conda config --prepend channels conda-forge
Now we can create a new conda environment with Python and all our dependencies
installed (we’ll call it pygmt
but feel free to change it to whatever you
want):
conda create --name pygmt python=3.9 numpy pandas xarray netcdf4 packaging gmt
mamba create --name pygmt python=3.9 numpy pandas xarray netcdf4 packaging gmt
Activate the environment by running the following (do not forget this step!):
conda activate pygmt
mamba activate pygmt
From now on, all commands will take place inside the conda virtual environment
called pygmt
and won’t affect your default base
installation.
Installing PyGMT
Now that you have GMT installed and your conda virtual environment activated, you can install PyGMT using any of the following methods:
Using conda/mamba (recommended)
This installs the latest stable release of PyGMT from conda-forge:
conda install pygmt
mamba install pygmt
This upgrades the installed PyGMT version to be the latest stable release:
conda update pygmt
mamba update pygmt
Using pip
This installs the latest stable release from PyPI:
pip install pygmt
Tip
You can also run pip install pygmt[all]
to install pygmt with
all of its optional dependencies.
Alternatively, you can install the latest development version from TestPyPI:
pip install --pre --extra-index-url https://test.pypi.org/simple/ pygmt
To upgrade the installed stable release or development version to be the latest
one, just add --upgrade
to the corresponding command above.
Any of the above methods (conda/pip) should allow you to use the PyGMT package from Python.
Testing your install
To ensure that PyGMT and its dependencies are installed correctly, run the following in your Python interpreter:
import pygmt
pygmt.show_versions()
fig = pygmt.Figure()
fig.coast(region="g", frame=True, shorelines=1)
fig.show()
If you see a global map with shorelines, then you’re all set.
Notes for Jupyter users
If you can successfully import pygmt in a Python interpreter or IPython, but
get a ModuleNotFoundError
when importing pygmt in Jupyter, you may need to
install a pygmt
kernel following the commands below:
conda activate pygmt
python -m ipykernel install --user --name pygmt # install conda environment properly
jupyter kernelspec list --json
After that, you need to restart Jupyter, open your notebook, select the
pygmt
kernel and then import pygmt.