Skip to main content

Python Geoscience Modelling and Interpretation

Project description

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).

It includes:

  • Magnetic and Gravity 3D forward modelling

  • Cluster Analysis

  • Routines for cutting, reprojecting and doing simple modifications to data

  • Convenient display of data using pseudo-color, ternary and sunshaded representation.

  • 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.

If you have any comments or queries, you can contact the author either through GitHub or via email at pcole@geoscience.org.za

Requirements

PyGMI will run on both Windows and Linux. It should be noted that the main development is done in Python 3.7 on Windows.

PyGMI is developed and has been tested with the following libraries in order to function:

  • python 3.7.4

  • GDAL 3.0.2

  • llvmlite 0.29.0

  • matplotlib 3.1.1

  • numba 0.45.1

  • numexpr 2.7.0

  • numpy 1.16.5

  • pillow 6.2.1

  • pandas 0.25.1

  • pyopengl 3.1.3b2

  • pyqt5 5.13.1

  • scipy 1.3.1

  • scikit_learn 0.21.3

  • scikit_image 0.16.2

  • setuptools 41.0.1

  • segyio 1.8.8

  • geopandas 0.6.1

  • pytest 5.1.2

  • mtpy 1.1.3

Installation

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:

pygmi

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

import pygmi pygmi.main()

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:

python quickstart.py

Windows Users

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:

  • numexpr

  • numba

  • llvmlite

  • GDAL

They can be obtained from the website by Christoph Gohlke.

You may also need to install the Microsoft Visual C++ 2015 Redistributable.

Linux

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

Anaconda users are advised not to use pip since it can break PyQt5. Instead, you can install anaconda3 using the regular method, and then:

conda update –all conda install numba conda install scipy conda install pyopengl conda install gdal conda install scikit-learn conda install pandas conda install matplotlib conda install numexpr conda install numpy conda install pillow conda install setuptools conda install segyio conda install geopandas conda install mtpy conda install pytest

Alternatively if you use environments you can simply use the following command:

conda create -n pygmi2 scipy numba gdal pandas matplotlib numexpr numpy setuptools pillow pyopengl scikit-learn segyio geopandas mtpy pytest

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

python quickstart.py

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:

pygmi

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

pygmi-3.0.1.tar.gz (1.6 MB view details)

Uploaded Source

Built Distribution

pygmi-3.0.1-py3-none-any.whl (667.4 kB view details)

Uploaded Python 3

File details

Details for the file pygmi-3.0.1.tar.gz.

File metadata

  • Download URL: pygmi-3.0.1.tar.gz
  • Upload date:
  • Size: 1.6 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.15.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.2.0 requests-toolbelt/0.9.1 tqdm/4.36.1 CPython/3.7.4

File hashes

Hashes for pygmi-3.0.1.tar.gz
Algorithm Hash digest
SHA256 03b5bd3487f0ae674320cc546c002dc5a4a04fa3b223fc6e5b16a034928ce1d4
MD5 fb5b2932cb4c1f025d1429f77b7bf102
BLAKE2b-256 6886f2a6baed8d1ec3f7a24613b3648ac8cdec56392a7b91123fa77c7196f828

See more details on using hashes here.

File details

Details for the file pygmi-3.0.1-py3-none-any.whl.

File metadata

  • Download URL: pygmi-3.0.1-py3-none-any.whl
  • Upload date:
  • Size: 667.4 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.15.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.2.0 requests-toolbelt/0.9.1 tqdm/4.36.1 CPython/3.7.4

File hashes

Hashes for pygmi-3.0.1-py3-none-any.whl
Algorithm Hash digest
SHA256 5d74f7551fd1b7df39cc4dba3c3d4e827a99c204a595b1fa45307473626ce6b3
MD5 20e87be9ba0d0263d047877b4ea70220
BLAKE2b-256 1dfb7e6380dbef50d12319f35327eea6579927118f751b85f407acd220fbb09b

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page