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Tools to read in CryoGrid MATLAB data to Python and create forcing data

Project description

CryoGrid-pyTools

Tools to read in CryoGrid MATLAB data to Python, includes forcing, outputs, DEMs, etc.

Feel free to use, modify, and distribute as you see fit.

Installation

pip install cryogrid_pytools

Usage

This package can read in

  • CryoGrid output (from OUT_regridded_FCI2)
  • simple MATLAB struct files (not run_info.mat)
  • ERA5 forcing
  • excel run configuration files (experimental)

Basic examples are shown below for the first two items, but see demo.ipynb for more comprehensive examples.

Reading single CryoGrid output files

Currently, only output files from the calss OUT_regridded_FCI2 are supported. However, the majority of files you'll use follow this format.

import cryogrid_pytools as cgt

# a single file that should look something like this
fname = "results_from_RUN_SIMPLE/<project_name>_<YYYYMMDD>.mat"

# currently the only output from OUT_regridded_FCI2 is supported
dataset = cgt.read_OUT_regridded_FCI2_file(fname)

Reading multiple CryoGrid output files

If you're working with RUN_SPATIAL_SPINUP_CLUSTERING, you can read in multiple files at once. The data are returned as an xarray.Dataset with the dimensions: [gridcell, depth, time]

# path contains wildcards where cluster ID and date are respectively
fname = "results_from_RUN_SPATIAL_SPINUP_CLUSTERING/project_name_*_*.mat"

# deepest_point is the deepest point in the saved files
dataset = cgt.read_OUT_regridded_FCI2_clusters(fname, deepest_point=-5)

Reading struct files from MATLAB

TIP: In MATLAB, You need to add the `CryoGrid/source` directory to the MATLAB path before the file can be loaded properly.

Note that run_info.mat cannot be read as it contains special classes that are not supported by scipy.io.loadmat. To save parts of run_info, use the following code in MATLAB:

run_info_spatial = run_info.SPATIAL.STATVAR
save "run_info_spatial.mat" run_info_spatial

Then, in Python:

fname = 'path_to_file/run_spatial_statvar.mat'
spatial = cgt.read_mat_struct_as_dataset(fname, index=['Y', 'X'])

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