pygmi 3.2.8.19

Description:

pygmi 3.2.8.19

Overview
PyGMI stands for Python Geoscience Modelling and Interpretation. It is a modelling and interpretation suite aimed at magnetic, gravity, remote sensing and other datasets. PyGMI has a graphical user interface, and is meant to be run as such.
PyGMI is developed at the Council for Geoscience (Geological Survey of South Africa).
It includes:

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! Contributors can check this link for ways to contribute.
The latest release version (including windows installers) can be found here.
You may need to install the Microsoft Visual C++ Redistributable for Visual Studio 2015, 2017 and 2019.
If you have any comments or queries, you can contact the author either through GitHub or via email at [email protected]


Installation
The simplest installation of PyGMI is on Windows, using a pre-built installer at 64-bit.
If you prefer building from source, you can use PyPi or Conda. Note that if you are using PyPi, certain libraries require binaries built. To do so or download binaries manually, please see the Linux or Windows section below.
Once built, running pygmi can be done at the command prompt as follows:

pygmi

If you are in python, you can run PyGMI by using the following commands:

from pygmi.main import main
main()

If you prefer not to install pygmi as a library, download the source code and execute the following command to run it manually:

python quickstart.py


Requirements
PyGMI will run on both Windows and Linux. It should be noted that the main development is done in Python 3.12 on Windows.
PyGMI should still work with Python 3.11.
PyGMI is developed and has been tested with the following libraries in order to function:

python 3.12.4
discretize 0.10.0
fiona 1.9.5
gdal 3.8.4
geopandas 0.14.4
matplotlib 3.9.0
mtpy 1.1.5
natsort 8.4.0
numba 0.60.0
numexpr 2.10.1
numpy 1.26.4
openpyxl 3.1.2
pandas 2.2.2
psutil 6.0.0
pyogrio 0.9.0
pyopengl 3.1.7
pyproj 3.6.1
PyQt5 5.15.10
pytest 8.2.2
rasterio 1.3.9
scikit-image 0.24.0
scikit-learn 1.5.0
scipy 1.13.1
shapely 2.0.3
shapelysmooth 0.2.0
SimPEG 0.21.1
xlrd 2.0.1
xarray 2024.6.0
h5netcdf 1.3.0
rioxarray 0.15.6



PyPi - Windows
Windows users can use the WinPython distribution as an alternative to Anaconda. It comes with most libraries preinstalled, so using pip should be sufficient.
Alternatively, if you are not an Anaconda or WinPython user, you will 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. Visual Studio 2022 can be used to most compile binaries, if it is in the same path as python.
GDAL in particular is non-trivial to compile to binary form, so downloading a binary is recommended. Related binaries can be obtained at the website by Christoph Gohlke.
If you obtain binaries here, you will need to download and install:

fiona
GDAL
pyproj
rasterio
Rtree
shapely

All these binaries should be downloaded since they have internal co-dependencies.
Once this is done, install with the following command.

pip install pygmi



PyPi - Linux
Linux normally comes with python installed, but the additional libraries will still need to be installed.
The process is as follows:

sudo apt-get install pip
sudo apt-get install gdal-bin
sudo apt-get install libgdal-dev
pip install cython
pip install numpy
pip install pygmi



Anaconda
Anaconda users are advised not to use pip since it can break PyQt5. However, one package is installed only by pip, so a Conda environment should be created.
The process to install is as follows:

conda create -n pygmi python=3.12
conda activate pygmi
conda config –add channels conda-forge
conda config –set channel_priority flexible
conda install pyqt
conda install numpy
conda install scipy
conda install matplotlib
conda install psutil
conda install numexpr
conda install pandas
conda install rasterio
conda install geopandas
conda install numba
conda install natsort
conda install scikit-learn
conda install scikit-image
conda install pyopengl
conda install simpeg
conda install shapelysmooth
conda install pyogrio
conda install openpyxl
conda install xlrd
conda install xarray
conda install h5netcdf
conda install rioxarray
pip install mtpy
conda update –all

Once this is done, download pygmi, extract (unzip) it to a directory, and run it from its root directory with the following command:

python quickstart.py




References

Cole, P. 2012, Development of a 3D Potential Field Forward Modelling System in Python, AGU fall meeting, 3-7 December, San Francisco, USA
Cole, P. 2013, PyGMI – The use of Python in geophysical modelling and interpretation. South African Geophysical Association, 13th Biennial Conference, Skukuza Rest Camp, Kruger National Park (7-9 October)
Cole, P. 2014, The history and design behind the Python Geophysical Modelling and Interpretation (PyGMI) package, SciPy 2014, Austin, Texas (6-12 July)
Cole, P. 2016, The continued evolution of the open source PyGMI project. 35th IGC, Cape Town.