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Reading CryoGrid Output

CryoGrid-pyTools provides functionality to read CryoGrid output files into Python. Currently, it supports reading regridded FCI2 output files.

Reading FCI2 Output Files

Use the read_OUT_regridded_FCI2_file function to read a regridded FCI2 output file:

import cryogrid_pytools as cg

# Read a single output file
ds = cg.read_OUT_regridded_FCI2_file(
    'path/to/your/output_file.mat',
    deepest_point=-5  # Set the deepest point in meters
)

The function returns an xarray Dataset with the following variables: - time: Time coordinate (datetime64) - depth: Depth coordinate in meters - T: Temperature - water: Water content - ice: Ice content - class_number: Class number - FCI: Frozen/Thawed state - elevation: Surface elevation

Reading Multiple Files

For spatial runs with multiple output files, use read_OUT_regridded_FCI2_clusters:

# Read multiple output files
ds = cg.read_OUT_regridded_FCI2_clusters(
    'path/to/output/directory/*.mat',  # Glob pattern for output files
    deepest_point=-5
)

The resulting Dataset will have an additional gridcell dimension for the spatial component.

Data Structure

The output is an xarray Dataset with:

  • Dimensions:
  • time: Timesteps in the simulation
  • depth: Vertical grid points

  • gridcell: (Only for cluster runs) Spatial grid points

  • Variables:

  • All variables are stored as dask arrays for efficient memory usage
  • Temperature and other fields are stored with dimensions (time, depth) or (gridcell, depth, time)

Working with the Data

Being an xarray Dataset, you can use all standard xarray operations:

```python

Select a specific time

ds.sel(time='2000-01-01')

Get mean temperature over time

ds.T.mean(dim='time')

Plot temperature profile

ds.T.plot()