ifm_contrib

Description

ifm_contrib is an Open-Source Extension of the IFM, the Python API of the groundwater modellierung software FEFLOW by DHI.

It extents the namespace of the classic IFM to facilitate using FEFLOW in combination with the popular Python datascience libraries pandas, geopandas and matplotlib.

The ifm_contrib namespace is a superset of the classic ifm namespace, thus scripts written for the latter will be back-wards compatible and only one library import statement is required.

Project status

The library has been developed since 2019, and reached maturity around 2021 with most features for (geo-)pandas as matplotlib integration in place.

ifm_contrib is published under the MIT license. It is free to use, share and modify. Users are encouraged to contribute their own code back to the project.

Please note that the maintainer of this project is not associated with DHI.

Development setup

Clone this repo

Inside the repo:

python -m venv .venv
source .venv/bin/activate
pip install -e ".[test]"

Run unit test with pytest

If you want to create the documentation:

source .venv/bin/activate
pip install -e ".[test,doc]"
cd doc/sphinx
make html
# Open doc/sphinx/build/html/index.html in a browser

Installation

The recommended way of installing ifm_contrib is by copying or cloning the repository directly into the FEFLOW program director next to the classic IFM.

Installation via pip should be done by:

pip install https://github.com/red5alex/ifm_contrib/archive/refs/heads/master.zip

An installation of FEFLOW (version 7.2 or higher) is required.

Getting started

For a detailed introduction and installation notes, see ifm_contrib: An Introduction

Its not a pretty one, but you can find an (unregularly updated) help system including API reference here](https://red5alex.github.io/ifm_contrib/ifm_contrib.contrib_lib.html).

Troubleshooting and Contribution

If you run into issues please open an issue. Please note that the maintainer may not dedicate significant time to the project at this time but will try its best to respond.

Gallery

Visualize FEFLOW Results directly in Jupyter

Create inline plots with the look-and-feel of FEFLOWs directly within Jupyter. The plots can be exported as GeoDataFrames and saved to shape-files easily.
ifm_contrib adds light support for coordinate systems to FEFLOW.

Process FEFLOWs Time Series with Pandas

Time Series (aka Power functions) and History charts can be easily exported to pandas DataFrames. Automatic conversion to DateTime based on FEFLOWs Reference Time. In-Built Synchronization to observation point reference data.

Pandas-access to Nodal and Elemntal Data, Multi-Layer Wells, and much more

Read more in ifm_contrib: An Introduction