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

Project description

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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

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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 ==================



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