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 is developed at the `Council for Geoscience <http://www.geoscience.org.za>`_ (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 <http://www.gnu.org/copyleft/gpl.html>`_
The PyGMI `Wiki <http://patrick-cole.github.io/pygmi/index.html>`_ pages, include installation and full usage!
The latest release version can be found `here <https://github.com/Patrick-Cole/pygmi/releases>`_.
You may need to install the `Microsoft Visual C++ Redistributable for Visual Studio 2015, 2017 and 2019 <https://support.microsoft.com/en-us/help/2977003/the-latest-supported-visual-c-downloads>`_.
If you have any comments or queries, you can contact the author either through `GitHub <https://github.com/Patrick-Cole/pygmi>`_ 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 3.11 on Windows.
PyGMI should still work with Python 3.9 and Python 3.10.
PyGMI is developed and has been tested with the following libraries in order to function:
* python 3.11.6
* discretize 0.10.0
* fiona 1.9.5
* gdal 3.8.2
* geopandas 0.14.2
* matplotlib 3.8.2
* mtpy 1.1.5
* natsort 8.4.0
* numba 0.58.1
* numexpr 2.8.8
* numpy 1.26.3
* openpyxl 3.1.2
* pandas 2.1.4
* psutil 5.9.7
* pyogrio 0.7.2
* pyopengl 3.1.7
* pyproj 3.6.1
* PyQt5 5.15.10
* pytest 7.4.4
* rasterio 1.3.9
* scikit-image 0.22.0
* scikit-learn 1.3.2
* scipy 1.11.3
* shapely 2.0.2
* shapelysmooth 0.1.1
* SimPEG 0.20.0.post2
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. Depending on your operating system, and which libraries you already have installed, you may need to follow instructions in sections below. Please note the use of pip when installing PyGMI may cause Anaconda installations to break. Anaconda users should follow the instructions below.
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:
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
Windows Users
-------------
Installers are available in `64-bit <https://github.com/Patrick-Cole/pygmi/releases>`_
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
* discretize
* fiona
They can be obtained from the `website <https://www.cgohlke.com/>`_ by Christoph Gohlke.
Linux
-----
Linux normally comes with python installed, but the additional libraries will still need to be installed.
Typically, packages can be installed using pip. 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=3.10
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
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
Raw data
{
"_id": null,
"home_page": "",
"name": "pygmi",
"maintainer": "",
"docs_url": null,
"requires_python": ">=3.9",
"maintainer_email": "Patrick Cole <pcole@geoscience.org.za>",
"keywords": "Geoscience,Geophysics,Magnetic,Gravity,Modelling,Interpretation,Remote Sensing",
"author": "",
"author_email": "Patrick Cole <pcole@geoscience.org.za>",
"download_url": "https://files.pythonhosted.org/packages/c5/2d/ced0c4c85e801418af4e256b3eb55f2ba1152617009488d6b9c8f676a1ca/pygmi-3.2.8.0.tar.gz",
"platform": null,
"description": "Overview\r\n========\r\n\r\nPyGMI stands for Python Geoscience Modelling and Interpretation. It is a modelling and interpretation suite aimed at magnetic, gravity, remote sensing and other datasets.\r\n\r\nPyGMI is developed at the `Council for Geoscience <http://www.geoscience.org.za>`_ (Geological Survey of South Africa).\r\n\r\nIt includes:\r\n\r\n* Magnetic and Gravity 3D forward modelling.\r\n* Cluster Analysis, including use of scikit-learn libraries.\r\n* Routines for cutting, reprojecting and doing simple modifications to data.\r\n* Convenient display of data using pseudo-color, ternary and sunshaded representation.\r\n* MT processing and 1D inversion using MTpy.\r\n* Gravity processing.\r\n* Seismological functions for SEISAN data.\r\n* Remote sensing ratios and improved imports.\r\n\r\nIt is released under the `Gnu General Public License version 3.0 <http://www.gnu.org/copyleft/gpl.html>`_\r\n\r\nThe PyGMI `Wiki <http://patrick-cole.github.io/pygmi/index.html>`_ pages, include installation and full usage!\r\n\r\nThe latest release version can be found `here <https://github.com/Patrick-Cole/pygmi/releases>`_.\r\n\r\nYou may need to install the `Microsoft Visual C++ Redistributable for Visual Studio 2015, 2017 and 2019 <https://support.microsoft.com/en-us/help/2977003/the-latest-supported-visual-c-downloads>`_.\r\n\r\nIf you have any comments or queries, you can contact the author either through `GitHub <https://github.com/Patrick-Cole/pygmi>`_ or via email at pcole@geoscience.org.za\r\n\r\nRequirements\r\n------------\r\nPyGMI will run on both Windows and Linux. It should be noted that the main development is done in Python 3.11 on Windows.\r\n\r\nPyGMI should still work with Python 3.9 and Python 3.10.\r\n\r\nPyGMI is developed and has been tested with the following libraries in order to function:\r\n\r\n* python 3.11.6\r\n* discretize 0.10.0\r\n* fiona 1.9.5\r\n* gdal 3.8.2\r\n* geopandas 0.14.2\r\n* matplotlib 3.8.2\r\n* mtpy 1.1.5\r\n* natsort 8.4.0\r\n* numba 0.58.1\r\n* numexpr 2.8.8\r\n* numpy 1.26.3\r\n* openpyxl 3.1.2\r\n* pandas 2.1.4\r\n* psutil 5.9.7\r\n* pyogrio 0.7.2\r\n* pyopengl 3.1.7\r\n* pyproj 3.6.1\r\n* PyQt5 5.15.10\r\n* pytest 7.4.4\r\n* rasterio 1.3.9\r\n* scikit-image 0.22.0\r\n* scikit-learn 1.3.2\r\n* scipy 1.11.3\r\n* shapely 2.0.2\r\n* shapelysmooth 0.1.1\r\n* SimPEG 0.20.0.post2\r\n\r\nInstallation\r\n------------\r\nGeneral (Not Anaconda)\r\n----------------------\r\nThe easiest way to install pygmi if you are working in a python environment is to use the pip command as follows:\r\n\r\n pip install pygmi\r\n\r\nThis will download pygmi from PyPI and install it within your python repository. Depending on your operating system, and which libraries you already have installed, you may need to follow instructions in sections below. Please note the use of pip when installing PyGMI may cause Anaconda installations to break. Anaconda users should follow the instructions below.\r\n\r\nRunning pygmi can be now done at the command prompt as follows:\r\n\r\n pygmi\r\n\r\nIf you are in python, you can run PyGMI by using the following commands:\r\n\r\n from pygmi.main import main\r\n\r\n main()\r\n\r\nIf you prefer not to install pygmi as a library, download the source code and execute the following command to run it manually:\r\n\r\n python quickstart.py\r\n\r\nWindows Users\r\n-------------\r\nInstallers are available in `64-bit <https://github.com/Patrick-Cole/pygmi/releases>`_\r\n\r\nAlternatively, 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.\r\n\r\nExamples of binaries you may need to get are:\r\n\r\n* numexpr\r\n* numba\r\n* llvmlite\r\n* GDAL\r\n* discretize\r\n* fiona\r\n\r\nThey can be obtained from the `website <https://www.cgohlke.com/>`_ by Christoph Gohlke.\r\n\r\nLinux\r\n-----\r\nLinux normally comes with python installed, but the additional libraries will still need to be installed.\r\n\r\nTypically, packages can be installed using pip. The process is as follows:\r\n\r\n sudo apt-get install pip\r\n\r\n sudo apt-get install gdal-bin\r\n\r\n sudo apt-get install libgdal-dev\r\n\r\n pip install cython\r\n\r\n pip install numpy\r\n\r\n pip install pygmi\r\n\r\nAnaconda\r\n--------\r\nAnaconda 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.\r\n\r\nThe process to install is as follows:\r\n\r\n conda create -n pygmi python=3.10\r\n\r\n conda activate pygmi\r\n\r\n conda config --add channels conda-forge\r\n\r\n conda config --set channel_priority flexible\r\n\r\n conda install pyqt\r\n\r\n conda install numpy\r\n\r\n conda install scipy\r\n\r\n conda install matplotlib\r\n\r\n conda install psutil\r\n\r\n conda install numexpr\r\n\r\n conda install pandas\r\n\r\n conda install rasterio\r\n\r\n conda install geopandas\r\n\r\n conda install numba\r\n \r\n conda install natsort\r\n\r\n conda install scikit-learn\r\n\r\n conda install scikit-image\r\n\r\n conda install pyopengl\r\n\r\n conda install simpeg\r\n\r\n conda install shapelysmooth\r\n \r\n conda install pyogrio\r\n \r\n conda install openpyxl\r\n\r\n pip install mtpy\r\n\r\n conda update --all\r\n\r\nOnce this is done, download pygmi, extract (unzip) it to a directory, and run it from its root directory with the following command:\r\n\r\n python quickstart.py\r\n",
"bugtrack_url": null,
"license": "GNU General Public License v3 (GPLv3)",
"summary": "Python Geoscience Modelling and Interpretation",
"version": "3.2.8.0",
"project_urls": {
"changelog": "https://github.com/Patrick-Cole/pygmi/blob/pygmi3/CHANGES.rst",
"documentation": "https://patrick-cole.github.io/pygmi/wiki.html",
"homepage": "http://patrick-cole.github.io/pygmi/",
"repository": "https://github.com/Patrick-Cole/pygmi.git"
},
"split_keywords": [
"geoscience",
"geophysics",
"magnetic",
"gravity",
"modelling",
"interpretation",
"remote sensing"
],
"urls": [
{
"comment_text": "",
"digests": {
"blake2b_256": "84d5ff59467a4ebc8340d67f802b2b926c023bc04d8a44d8c9592674ff178c6f",
"md5": "2b4a9a433bbc4d75ecec4662702266ea",
"sha256": "a88108381e9ab208a2fae742784eb3bfb60ccf17e9ba5d5cfa78110ec1762141"
},
"downloads": -1,
"filename": "pygmi-3.2.8.0-py3-none-any.whl",
"has_sig": false,
"md5_digest": "2b4a9a433bbc4d75ecec4662702266ea",
"packagetype": "bdist_wheel",
"python_version": "py3",
"requires_python": ">=3.9",
"size": 684193,
"upload_time": "2024-01-18T11:44:14",
"upload_time_iso_8601": "2024-01-18T11:44:14.267743Z",
"url": "https://files.pythonhosted.org/packages/84/d5/ff59467a4ebc8340d67f802b2b926c023bc04d8a44d8c9592674ff178c6f/pygmi-3.2.8.0-py3-none-any.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"blake2b_256": "c52dced0c4c85e801418af4e256b3eb55f2ba1152617009488d6b9c8f676a1ca",
"md5": "055b9b446a026a66d0e634d4c19aecb1",
"sha256": "f3bc54d3b3634b33ab3c2c8fd644bf3247344042f1e7a866c1339d9a81b63e6c"
},
"downloads": -1,
"filename": "pygmi-3.2.8.0.tar.gz",
"has_sig": false,
"md5_digest": "055b9b446a026a66d0e634d4c19aecb1",
"packagetype": "sdist",
"python_version": "source",
"requires_python": ">=3.9",
"size": 590072,
"upload_time": "2024-01-18T11:44:15",
"upload_time_iso_8601": "2024-01-18T11:44:15.949799Z",
"url": "https://files.pythonhosted.org/packages/c5/2d/ced0c4c85e801418af4e256b3eb55f2ba1152617009488d6b9c8f676a1ca/pygmi-3.2.8.0.tar.gz",
"yanked": false,
"yanked_reason": null
}
],
"upload_time": "2024-01-18 11:44:15",
"github": true,
"gitlab": false,
"bitbucket": false,
"codeberg": false,
"github_user": "Patrick-Cole",
"github_project": "pygmi",
"travis_ci": false,
"coveralls": false,
"github_actions": false,
"lcname": "pygmi"
}
JSON
