Work with iMOD MODFLOW models
Work with iMOD MODFLOW models in Python.
Source code: https://gitlab.com/deltares/imod-python
import imod # read and write IPF files to pandas DataFrame df = imod.ipf.load('wells.ipf') imod.ipf.save('wells-out.ipf', df) # get all calculated heads in a xarray DataArray # with dimensions time, layer, y, x da = imod.idf.load('path/to/results/head_*.idf')
The imod Python package is an addition to iMOD and iMODFLOW, intended to facilitate working with groundwater models from Python. It does this by supporting reading and writing of the different iMOD file formats to existing objects often used in Python data processing.
IDF - iMOD Data Format
IDF is the binary raster format of iMOD. One file contains a X and Y 2 dimensional grid. Using a set of file name conventions more dimensions such as time and layer are added, for example: head_20181113_l3.idf for layer 3 and timestamp 2018-11-13. This package maps IDF files to and from the N dimensional labeled arrays of xarray.DataArray, using imod.idf.load and imod.idf.save, or, to read multiple parameters at the same time, imod.idf.loadset.
For more information on how to work with xarray.DataArray objects, we refer to the xarray documentation. Note that converting GIS raster formats to IDF is supported through xarray.open_rasterio, followed by imod.idf.save.
IPF - iMOD Point File
IPF files are text files used for storing tabular point data such as timeseries and borehole measurements. In the imod Python package these files are read in as pandas.DataFrame. Pandas is a popular package that makes analysis and processing of tabular data easy, and provides many input and output options, which in turn enables us to convert for instance existing CSV or Excel files to IPF files. The primary functions for reading and writing IPF files are imod.ipf.load and imod.ipf.save.
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