MIKE IO: input/output of MIKE files in Python
Read, write and manipulate dfs0, dfs1, dfs2, dfs3, dfsu and mesh files.
MIKE IO facilitates common data processing workflows for MIKE files in Python.
Requirements
- Windows or Linux operating system
- Python x64 3.8 - 3.11
- (Windows) VC++ redistributables (already installed if you have MIKE)
Where can I get help?
- Documentation - https://dhi.github.io/mikeio/
- General help, new ideas and feature requests - GitHub Discussions
- Bugs - GitHub Issues
Installation
From PyPI:
pip install mikeio
Or development version:
pip install https://github.com/DHI/mikeio/archive/main.zip
Tested
MIKE IO is tested extensively.
See detailed test coverage report below:
---------- coverage: platform linux, python 3.11.1-final-0 -----------
Name Stmts Miss Cover
-----------------------------------------------------
mikeio/__init__.py 38 2 95%
mikeio/base.py 26 5 81%
mikeio/data_utils.py 111 5 95%
mikeio/dataarray.py 992 152 85%
mikeio/dataset.py 772 100 87%
mikeio/dfs0.py 299 24 92%
mikeio/dfs1.py 67 3 96%
mikeio/dfs2.py 188 8 96%
mikeio/dfs3.py 186 26 86%
mikeio/dfs.py 288 36 88%
mikeio/dfsu/__init__.py 3 0 100%
mikeio/dfsu/dfsu.py 592 56 91%
mikeio/dfsu/factory.py 41 2 95%
mikeio/dfsu/layered.py 180 20 89%
mikeio/dfsu/spectral.py 127 6 95%
mikeio/dfsutil.py 129 15 88%
mikeio/eum.py 1324 12 99%
mikeio/exceptions.py 25 8 68%
mikeio/generic.py 433 16 96%
mikeio/interpolation.py 60 5 92%
mikeio/pfs/__init__.py 4 0 100%
mikeio/pfs/pfsdocument.py 242 16 93%
mikeio/pfs/pfssection.py 220 9 96%
mikeio/spatial/FM_geometry.py 1118 102 91%
mikeio/spatial/FM_utils.py 293 30 90%
mikeio/spatial/__init__.py 0 0 100%
mikeio/spatial/crs.py 50 4 92%
mikeio/spatial/geometry.py 90 33 63%
mikeio/spatial/grid_geometry.py 558 42 92%
mikeio/spatial/utils.py 38 0 100%
mikeio/spectral.py 90 5 94%
mikeio/track.py 100 14 86%
mikeio/xyz.py 12 0 100%
-----------------------------------------------------
TOTAL 8696 756 91%
=========== 697 passed, 3 warnings in 46.01s ========
Cloud enabled
It is possible to run MIKE IO in your favorite cloud notebook environment e.g. Deepnote, Google Colab, etc...
