Skip to main content

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

Project description

logo

MIKE IO: input/output of MIKE files in python

Python version Python package PyPI version Conda Version

https://dhi.github.io/mikeio/

Read, write and manipulate dfs0, dfs1, dfs2, dfs3, dfsu and mesh files.

Facilitates common data processing workflows for MIKE files.

For res1d and xns11 files use the related package MIKE IO 1D

Blue cafe

Requirements

  • Windows or Linux operating system
  • Python x64 3.6, 3.7,3.8 or 3.9
  • (Windows) VC++ redistributables (already installed if you have MIKE)

More info about dependencies

Where can I get help?

Installation

From PyPI:

pip install mikeio

For Anaconda:

conda install -c conda-forge mikeio

Or development version (main is the default branch since 2021-04-23):

pip install https://github.com/DHI/mikeio/archive/main.zip

Examples

Reading data from dfs0, dfs1, dfs2, dfsu

Generic read method to read values, if you need additional features such as coordinates, use specialised classes instead e.g. Dfsu

>>> import mikeio
>>> ds = mikeio.read("random.dfs0")
>>> ds
<mikeio.DataSet>
Dimensions: (1000,)
Time: 2017-01-01 00:00:00 - 2017-07-28 03:00:00
Items:
  0:  VarFun01 <Water Level> (meter)
  1:  NotFun <Water Level> (meter)
>>> ds = mikeio.read("random.dfs1")
>>> ds
<mikeio.DataSet>
Dimensions: (100, 3)
Time: 2012-01-01 00:00:00 - 2012-01-01 00:19:48
Items:
  0:  testing water level <Water Level> (meter)

Reading dfs0 file into Pandas DataFrame

>>>  from mikeio import Dfs0
>>>  dfs = Dfs0('simple.dfs0')
>>>  ts = dfs.to_dataframe()

Write simple timeseries

>>>  from datetime import datetime
>>>  import numpy as np
>>>  from mikeio import Dfs0
>>>  data = [np.random.random([100])]
>>>  dfs = Dfs0()
>>>  dfs.write('simple.dfs0', data, start_time=datetime(2017, 1, 1), dt=60)

Write timeseries from dataframe

import pandas as pd
import mikeio
>>> df = pd.read_csv(
...         "tests/testdata/co2-mm-mlo.csv",
...         parse_dates=True,
...         index_col="Date",
...         na_values=-99.99,
...     )
>>> df.to_dfs0("mauna_loa.dfs0")

For more examples on timeseries data see this notebook

Read dfs2 data

>>>  from mikeio import Dfs2
>>> dfs = Dfs2("random.dfs2")
>>> ds = dfs.read()
>>> ds
<mikeio.DataSet>
Dimensions: (3, 100, 2)
Time: 2012-01-01 00:00:00 - 2012-01-01 00:00:24
Items:
  0:  testing water level <Water Level> (meter)

Create dfs2

For a complete example of conversion from netcdf to dfs2 see this notebook.

Another example of downloading meteorological forecast from the Global Forecasting System and converting it to a dfs2 ready to be used by a MIKE 21 model.

Read dfsu files

>>>  import matplotlib.pyplot as plt
>>>  from mikeio import Dfsu
>>>  dfs = Dfsu("HD.dfsu")
>>>  ds = dfs.read()
>>>  idx = dfs.find_nearest_element(x=608000, y=6907000)
>>>  plt.plot(ds.time, ds.data[0][:,idx])

Timeseries

>>>  from mikeio import Mesh
>>>  msh = Mesh("FakeLake.dfsu")
>>>  msh.plot()

Mesh

For more examples on working with dfsu and mesh see these notebooks:

Pfs

Pfs is the format used for MIKE setup files (.m21fm, .m3fm, .sw etc.).

There is experimental support for reading pfs files, but the API is likely to change.

pfs

Items, units

Useful when creating a new dfs file

>>> from mikeio.eum import EUMType, EUMUnit
>>> EUMType.Temperature
<EUMType.Temperature: 100006>
>>> EUMType.Temperature.units
[degree Celsius, degree Fahrenheit, degree Kelvin]
>>> EUMUnit.degree_Kelvin
degree Kelvin

Tested

MIKE IO is tested extensively. 95% total test coverage.

See detailed test coverage report below:

File                           Covered  Missed  %
-------------------------------------------------
mikeio\__init__.py               40      1    98%
mikeio\aggregator.py            103      9    91%
mikeio\bin\__init__.py            0      0   100%
mikeio\custom_exceptions.py      19      1    95%
mikeio\dataset.py               272      3    99%
mikeio\dfs.py                   206      7    97%
mikeio\dfs0.py                  239     15    94%
mikeio\dfs1.py                   48      2    96%
mikeio\dfs2.py                  100      2    98%
mikeio\dfs3.py                  201     79    61%
mikeio\dfsu.py                 1337     57    96%
mikeio\dfsutil.py                76      4    95%
mikeio\dotnet.py                 63      4    94%
mikeio\eum.py                  1230      3    99%
mikeio\generic.py               228      2    99%
mikeio\helpers.py                13      0   100%
mikeio\interpolation.py          54      1    98%
mikeio\spatial.py               279      4    99%
mikeio\xyz.py                    12      0   100%
-------------------------------------------------
TOTAL                          5082    229    95%

=================== 335 passed ==================



Project details


Release history Release notifications | RSS feed

This version

0.7.0

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

mikeio-0.7.0.tar.gz (1.5 MB view details)

Uploaded Source

File details

Details for the file mikeio-0.7.0.tar.gz.

File metadata

  • Download URL: mikeio-0.7.0.tar.gz
  • Upload date:
  • Size: 1.5 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.1 importlib_metadata/4.6.0 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.61.1 CPython/3.7.9

File hashes

Hashes for mikeio-0.7.0.tar.gz
Algorithm Hash digest
SHA256 3932ef81ce6b4f8b58e0b8e13519e84a574f71157238e072c9b716271a05e9ab
MD5 4d29fc9805eeda609382b262278f1627
BLAKE2b-256 ccc2ce45455a9d43155fbd500aa8e6156951a9263964d617642d8f672142c8ed

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page