Python Geoscience Modelling and Interpretation
PyGMI stands for Python Geoscience Modelling and Interpretation. It is a modelling and interpretation suite aimed at magnetic, gravity and other datasets.
PyGMI is developed at the Council for Geoscience (Geological Survey of South Africa).
- Magnetic and Gravity 3D forward modelling.
- Cluster Analysis, including use of scikit-learn libraries.
- Routines for cutting, reprojecting and doing simple modifications to data.
- Convenient display of data using pseudo-color, ternary and sunshaded representation.
- MT processing and 1D inversion using MTpy.
- Gravity processing.
- Seismological functions for SEISAN data.
- Remote sensing ratios and improved imports.
It is released under the Gnu General Public License version 3.0
The PyGMI Wiki pages, include installation and full usage!
The latest release version can be found here.
You may need to install the Microsoft Visual C++ Redistributable for Visual Studio 2015, 2017 and 2019.
PyGMI will run on both Windows and Linux. It should be noted that the main development is done in Python 3.8 on Windows.
PyGMI is developed and has been tested with the following libraries in order to function:
- python 3.8.3
- fiona 1.8.13
- gdal 3.1.2
- geopandas 0.7.0
- IPython 7.14.0
- llvmlite 0.33.0
- matplotlib 3.2.2
- mtpy 1.1.3
- numba 0.50.1
- numexpr 2.7.1
- numpy 1.19.0+mkl
- pandas 1.0.5
- pillow 7.2.0
- pymatsolver 0.1.2
- pyopengl 3.1.5
- PyQt5 5.12.3
- pytest 5.4.2
- scikit-image 0.17.2
- scikit-learn 0.23.1
- scipy 1.5.1
- segyio 1.9.1
- shapely 1.7.0
General (Not Anaconda)
The easiest way to install pygmi if you are working in a python environment is to use the pip command as follows:
pip install pygmi
This will download pygmi from PyPI and install it within your python repository. Please note the use of pip when installing PyGMI may cause Anaconda installations to break. Anaconda users should follow the instructions below.
Alternatively, if you satisfy the requirements, you can download pygmi either from Github or PyPI, extract it and run the following command from within the extracted directory:
python setup.py install
In either case, running pygmi can be now done at the command prompt as follows:
If you are in python, you can run PyGMI by using the following commands:
If you prefer not to install pygmi as a library, or if there is a problem with running it in that matter, you can simply execute the following command to run it manually:
Installers are available in 64-bit
Alternatively, you can use the instructions above to run PyGMI with your local python installation. You may need to install some dependencies using downloaded binaries, because of compilation requirements. Therefore, if you do get an error, you can try installing precompiled binaries before installing PyGMI.
Examples of binaries you may need to get are:
They can be obtained from the website by Christoph Gohlke.
Linux normally comes with python installed, but the additional libraries will still need to be installed. One convenient option is to install the above libraries through Anaconda Python.
Anaconda users are advised not to use pip since it can break PyQt5. However, two packages are installed only by pip, so a Conda environment should be created. The process to install is as follows:
conda create -n pygmi python=3.7
conda activate pygmi
conda install pyqt
conda install numpy
conda install scipy
conda install numexpr
conda install gdal
conda install pillow
conda install matplotlib
conda install numba
conda install pandas
conda install scikit-learn
conda install scikit-image
conda install geopandas
conda install pyopengl
conda install pyyaml
pip install mtpy
pip install segyio
Once this is done, download pygmi, extract it to a directory, and run it from its root directory with the following command:
Alternatively, if you satisfy the requirements, you can run the following command from within the extracted directory:
python setup_anaconda.py install
Running pygmi can be now done at the command prompt as follows:
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