Skip to main content

Localized probabilistic data integration

Project description

INTEGRATE Python Module

Build Status PyPI Test PyPI Documentation License: MIT Python 3.10+

This repository contains the INTEGRATE Python module for localized probabilistic data integration in geophysics.

Installation

Assuming you already have Python 3.10+ installed:

pip install integrate_module

On Windows, this will also install the Python wrapper for GA-AEM (1D EM forward modeling - GPL v2 code): ga-aem-forward-win

On Linux/macOS, you will need to install GA-AEM manually.

Using pip (from PyPI, on Ubuntu)

# Install python3 venv
sudo apt install python3-venv

# Create virtual environment
python3 -m venv ~/integrate
source ~/integrate/bin/activate
pip install --upgrade pip

# Install integrate module
pip install integrate_module

Using pip (from source, on Ubuntu)

# Install python3 venv
sudo apt install python3-venv

# Create virtual environment
python3 -m venv ~/integrate
source ~/integrate/bin/activate
pip install --upgrade pip

# Install integrate module
cd path/to/integrate_module
pip install -r requirements.txt -e .

Using Conda + pip (from PyPI)

Create a Conda environment (called integrate) and install the required modules:

conda create --name integrate python=3.10 numpy pandas matplotlib scipy tqdm requests h5py psutil
conda activate integrate
pip install integrate_module

Using Conda + pip (from source)

Create a Conda environment (called integrate) and install the required modules:

conda create --name integrate python=3.10 numpy pandas matplotlib scipy tqdm requests h5py psutil
conda activate integrate
pip install -e .

GA-AEM

In order to use GA-AEM for forward EM modeling, the 'gatdaem1d' Python module must be installed. Follow instructions at https://github.com/GeoscienceAustralia/ga-aem or use the information below.

PyPI package for Windows

On Windows, the ga-aem-forward-win package will be automatically installed, providing access to the GA-AEM forward code. It can be installed manually using:

pip install ga-aem-forward-win

Pre-compiled Python module for Windows

  1. Download the pre-compiled version of GA-AEM for Windows from the latest release: https://github.com/GeoscienceAustralia/ga-aem/releases (GA-AEM.zip)

  2. Download precompiled FFTW3 Windows DLLs from https://www.fftw.org/install/windows.html (fftw-3.3.5-dll64.zip)

  3. Extract both archives:

    • unzip GA-AEM.zip to get GA-AEM
    • unzip fftw-3.3.5-dll64.zip to get fftw-3.3.5-dll64
  4. Copy FFTW3 DLLs to GA-AEM Python directory:

    cp fftw-3.3.5-dll64/*.dll GA-AEM/python/gatdaem1d/

  5. Install the Python gatdaem1d module:

cd GA-AEM/python/
pip install -e .

# Test the installation
cd examples
python integrate_skytem.py

Compile GA-AEM Python module on Debian/Ubuntu/Linux

A script that downloads and installs GA-AEM is located in scripts/cmake_build_script_DebianUbuntu_gatdaem1d.sh. This script has been tested and confirmed to work on both Debian and Ubuntu distributions. Be sure to use the appropriate Python environment and then run:

sh scripts/cmake_build_script_DebianUbuntu_gatdaem1d.sh
cd ga-aem/install-ubuntu/python
pip install .

Compile GA-AEM Python module on macOS/Homebrew

First install Homebrew, then run:

sh ./scripts/cmake_build_script_homebrew_gatdaem1d.sh
cd ga-aem/install-homebrew/python
pip install .

Development

The main branch is the most stable, with less frequent updates but larger changes.

The develop branch contains the current development code and may be updated frequently. Some functions and examples may be broken.

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

integrate_module-0.31.tar.gz (139.3 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

integrate_module-0.31-py3-none-any.whl (140.7 kB view details)

Uploaded Python 3

File details

Details for the file integrate_module-0.31.tar.gz.

File metadata

  • Download URL: integrate_module-0.31.tar.gz
  • Upload date:
  • Size: 139.3 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.10.12

File hashes

Hashes for integrate_module-0.31.tar.gz
Algorithm Hash digest
SHA256 0e3acf4d038ada33d0502e731e1ad5a99e49dd83a55a8a498c50d4c3911e6cb1
MD5 908407a7a1f1441d1b1fb15f52b1af84
BLAKE2b-256 23e242e6562f8635cb4f2189bb3e2f8658b20a452a2216c34c6fd533820aac17

See more details on using hashes here.

File details

Details for the file integrate_module-0.31-py3-none-any.whl.

File metadata

  • Download URL: integrate_module-0.31-py3-none-any.whl
  • Upload date:
  • Size: 140.7 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.10.12

File hashes

Hashes for integrate_module-0.31-py3-none-any.whl
Algorithm Hash digest
SHA256 193c159f0495b532ea545f2dc3cd355e4fcf796888d1b05b3917845674ad1445
MD5 28c2b3b4a38820e28e78554d2f97ca70
BLAKE2b-256 f8e306184ff21de51aa014f3303aa25b568e61dbfb4baf6637c35c5ef43eb05e

See more details on using hashes here.

Supported by

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