API for FDEM inversion and data manipulation
Project description
EMagPy
Python API for inversion/modelling of frequency domain electromagnetic data (FDEM).
EMagPy is divided into a python API and a standalone graphical user interface (GUI). It aims to be a powerfull but simple tool for inverting EMI data obtain from conductimeter.
Getting started
Clone the repository:
git clone https://gitlab.com/hkex/emagpy
Change to the src
directory and run ui.py
to start the GUI.
cd emgapy/src
python ui.py # this will start the GUI
The python API is available by simply importing the emagpy
module from the python shell:
import emagpy
k = Problem()
k.createSurvey('./test/coverCrop.csv')
k.invert(forwardModel='CS') # specify the forward model (here the Cumulative Sensitivty of McNeil1980)
k.showResults() # display the section
k.showMisfit() # display predicted and observed apparent EC
k.showOne2one() # 1:1 line of misfit of apparent EC
Check out the jupyter notebook examples in emagpy/examples/
.
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
emagpy-1.0.0.tar.gz
(44.0 kB
view details)
Built Distribution
emagpy-1.0.0-py3-none-any.whl
(57.8 kB
view details)
File details
Details for the file emagpy-1.0.0.tar.gz
.
File metadata
- Download URL: emagpy-1.0.0.tar.gz
- Upload date:
- Size: 44.0 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/1.13.0 pkginfo/1.5.0.1 requests/2.21.0 setuptools/46.0.0 requests-toolbelt/0.9.1 tqdm/4.28.1 CPython/3.7.3
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 17bf454dac5065b12f5fe2cb83d530cf35f057f9bc42e77322c3a4b9d3987666 |
|
MD5 | ea2f34ae35dc21680851a2ef4cc60253 |
|
BLAKE2b-256 | 2dc244f1e996aa979ae8d5c928ec70bd23f819cca64351de5cf9a3a23874d7b1 |
File details
Details for the file emagpy-1.0.0-py3-none-any.whl
.
File metadata
- Download URL: emagpy-1.0.0-py3-none-any.whl
- Upload date:
- Size: 57.8 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/1.13.0 pkginfo/1.5.0.1 requests/2.21.0 setuptools/46.0.0 requests-toolbelt/0.9.1 tqdm/4.28.1 CPython/3.7.3
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 0cd6436d0e7fd3267b4057e1094598286d8fcc0f91f0ab6611d7b3ec2ed0f18f |
|
MD5 | 99653fb49f33f140960560e09e3f3535 |
|
BLAKE2b-256 | 58c12d66d9e921e53265edfcdab5fff8b654ff43fef36b5a05cd828848dfa749 |