Python package for creation, reading, analysis, and plotting of finite difference fields.
Project description
discretisedfield
Marijan Beg1,2, Ryan A. Pepper2, Thomas Kluyver1, and Hans Fangohr1,2
1 European XFEL GmbH, Holzkoppel 4, 22869 Schenefeld, Germany
2 Faculty of Engineering and the Environment, University of Southampton, Southampton SO17 1BJ, United Kingdom
| Description | Badge |
|---|---|
| Latest release |  |
 |
|
| Build |  |
 |
|
| Coverage |  |
| Documentation |  |
| Binder |  |
| Dependecies |  |
| License |  |
About
discretisedfield is a Python package that provides:
-
Creation of finite difference meshes
-
Creation, analysis, and plotting of finite difference fields
-
Reading and writing of different file types, such as
.ovfand.vtk
It is available on all major operating systems (Windows, MacOS, Linux) and requires Python 3.5 or higher.
Installation
We recommend installing discretisedfield by using either of the pip or conda package managers.
Python requirements
Before installing discretisedfield via pip, please make sure you have Python 3.5 or higher on your system. You can check that by running
python3 --version
If you are on Linux, it is likely that you already have Python installed. However, on MacOS and Windows, this is usually not the case. If you do not have Python 3.5 or higher on your machine, we strongly recommend installing the Anaconda Python distribution. Download Anaconda for your operating system and follow instructions on the download page. Further information about installing Anaconda can be found here.
pip
After installing Anaconda on MacOS or Windows, pip will also be installed. However, on Linux, if you do not already have pip, you can install it with
sudo apt install python3-pip
To install the discretisedfield version currently in the Python Package Index repository PyPI on all operating systems run:
python3 -m pip install discretisedfield
conda
discretisedfield is installed using conda by running
conda install --channel conda-forge discretisedfield
For further information on the conda package, dependency, and environment management, please have a look at its documentation.
Updating
If you used pip to install discretisedfield, you can update to the latest released version in PyPI by running
python3 -m pip install --upgrade discretisedfield
On the other hand, if you used conda for installation, update discretisedfield with
conda upgrade discretisedfield
Development version
The most recent development version of discretisedfield that is not yet released can be installed/updated with
git clone https://github.com/joommf/discretisedfield.git
python3 -m pip install --upgrade discretisedfield
Note: If you do not have git on your system, it can be installed by following the instructions here.
Binder
discretisedfield can be used in the cloud via Binder. This does not require you to have anything installed and no files will be created on your machine. To use discretisedfield in the cloud, follow this link.
Documentation
Documentation for discretisedfield is available here, where APIs and tutorials (in the form of Jupyter notebooks) are available.
Support
If you require support on installation or usage of discretisedfield or if you want to report a problem, you are welcome to raise an issue in our joommf/help repository.
License
Licensed under the BSD 3-Clause "New" or "Revised" License. For details, please refer to the LICENSE file.
How to cite
If you use discretisedfield in your research, please cite it as:
-
M. Beg, R. A. Pepper, and H. Fangohr. User interfaces for computational science: A domain specific language for OOMMF embedded in Python. AIP Advances, 7, 56025 (2017).
-
DOI will be available soon
Acknowledgements
discretisedfield was developed as a part of OpenDreamKit – Horizon 2020 European Research Infrastructure project (676541).
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
Built Distribution
File details
Details for the file discretisedfield-0.8.2.tar.gz.
File metadata
- Download URL: discretisedfield-0.8.2.tar.gz
- Upload date:
- Size: 22.2 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | f52a8eade5fd2cafe8898a59cc533da14369c67fe0a5d1c91d414d2a9ac455e2 |
|
| MD5 | 7b970b88cc91d903148e93bfe98e941d |
|
| BLAKE2b-256 | 549e2c81229a52466dd43ae4032bb051f620dc90ac58339daeb1d41e6c95876d |
File details
Details for the file discretisedfield-0.8.2-py3-none-any.whl.
File metadata
- Download URL: discretisedfield-0.8.2-py3-none-any.whl
- Upload date:
- Size: 21.9 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | 80fbc085fc4f41ab21ddf572ce340a78394f33531eee0e47113a17c2f56eb512 |
|
| MD5 | 163c7a04947d466d1eef8821cc9c2980 |
|
| BLAKE2b-256 | 666f77ce398fd76f9b9c2a15a81a1942b018ddc6abf35ff23126fd165531bdb0 |
