What’s new

v0.1.2 (1 Aug 2022)

This release includes better masks and a dependency on cf_xarray.

Breaking changes


New features

  • Plot methods now look land_ice_area_fraction (instead of land_ice_thickness) to determine which grid cells are glacierized.

  • Add accessor method xarray.Dataset.hyoga.assign() to assign new variables by CF-compliant standard names.

  • Add accessor method xarray.Dataset.hyoga.assign_icemask() to assign an ice mask variable with standard name land_ice_area_fraction.

  • Add accessor method xarray.Dataset.hyoga.where_icemask() to filter glacier variable according to land_ice_area_fraction.

  • Add hyoga.config with a glacier_masking_point config parameter, an ice thickness threshold used as a fallback if land_ice_area_fraction is missing in the dataset.

Internal changes

  • Method xarray.Dataset.hyoga.getvar() now uses cf_xarray to retrieve data variables by their standard name. Thus cf_xarray is now a required dependency (#12).

  • Add module hyoga.conf implementing a config object to store additional parameters in the future.


  • A new documentation page shortly explains Masking and interpolation features.

  • A new example has been added to show that interpolation also works when surface topography is provided instead of bedrock topography.

v0.1.1 (8 Mar 2021)

This release includes bug fixes and several documentation improvements.


  • Functions demo.pism_gridded() and demo.pism_series() are deprecated. Use demo.get('pism.alps.out.2d') and demo.get('pism.alps.out.1d') instead.

Bug fixes


  • Examples in the documentation use smaller files currently hosted in a separate Github repository hyoga-data (#11). You may want to delete the previous, 400 MB file in ~/.cache/hyoga.

  • New examples have been added to demonstrate plotting bedrock isostasy and interpolated model output (Examples gallery, #11).

v0.1.0 Akaishi (1 Mar 2021)

Nothing is old, everything is new. This is the first version!