mikeio 1.1.0

A package that uses the DHI dfs libraries to create, write and read dfs and mesh files.

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.

MIKE IO Course | October 2022

:loudspeaker: Sign up for the online instructor-led course here!

MIKE IO 1.0

MIKE IO 1.0 is now available and it has a lot of benefits to working with dfs files even easier than before.

Important changes

• New class mikeio.DataArray which will be the main class to interact with, having these properties and methods
  • item info
  • geometry (grid coordinates)
  • methods for plotting
  • methods for aggreation in time and space
• Indexing into a dataset e.g. ds.Surface_elevation to get a specific item, will not return a numpy array, but a mikeio.DataArray

Requirements

• Windows or Linux operating system
• Python x64 3.7 - 3.10
• (Windows) VC++ redistributables (already installed if you have MIKE)

More info about dependencies

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

:warning: Don't use conda to install MIKE IO!, the version on conda is outdated.

Tested

MIKE IO is tested extensively.

See detailed test coverage report below:

---------- coverage: platform linux, python 3.10.4-final-0 -----------
Name                              Stmts   Miss  Cover
-----------------------------------------------------
mikeio/__init__.py                   39      2    95%
mikeio/base.py                       26      5    81%
mikeio/custom_exceptions.py          25      8    68%
mikeio/data_utils.py                127     22    83%
mikeio/dataarray.py                 927    145    84%
mikeio/dataset.py                   722     92    87%
mikeio/dfs0.py                      284     33    88%
mikeio/dfs1.py                       62      6    90%
mikeio/dfs2.py                      244     42    83%
mikeio/dfs3.py                      201     15    93%
mikeio/dfs.py                       275     30    89%
mikeio/dfsu.py                      699     63    91%
mikeio/dfsu_factory.py               41      2    95%
mikeio/dfsu_layered.py              186     23    88%
mikeio/dfsu_spectral.py             128      7    95%
mikeio/dfsutil.py                   104      8    92%
mikeio/eum.py                      1297      3    99%
mikeio/generic.py                   396      9    98%
mikeio/helpers.py                    16      5    69%
mikeio/interpolation.py              63      1    98%
mikeio/pfs.py                        93      0   100%
mikeio/spatial/FM_geometry.py      1123    116    90%
mikeio/spatial/FM_utils.py          293     30    90%
mikeio/spatial/__init__.py            0      0   100%
mikeio/spatial/crs.py                50     25    50%
mikeio/spatial/geometry.py           88     33    62%
mikeio/spatial/grid_geometry.py     497     33    93%
mikeio/spatial/utils.py              38      0   100%
mikeio/spectral_utils.py             89      5    94%
mikeio/xyz.py                        12      0   100%
-----------------------------------------------------
TOTAL                              8145    763    91%


============ 561 passed in 74.58s (0:01:14) ============

Cloud enabled

It is possible to run MIKE IO in your favorite cloud notebook environment e.g. Deepnote, Google Colab, etc...