{
  "context": "This criteria evaluates how well the engineer uses h5netcdf's invalid_netcdf mode to enable advanced HDF5 features beyond the standard netCDF4 specification, specifically boolean data types and scale-offset compression filters.",
  "type": "weighted_checklist",
  "checklist": [
    {
      "name": "File with invalid_netcdf",
      "description": "Opens or creates the h5netcdf.File with invalid_netcdf=True parameter to enable non-standard netCDF4 features",
      "max_score": 25
    },
    {
      "name": "Boolean variable creation",
      "description": "Creates the valid_flags variable using create_variable() with dtype=np.bool_ or dtype=bool, which requires invalid_netcdf mode",
      "max_score": 20
    },
    {
      "name": "Scale-offset filter",
      "description": "Applies scale-offset compression to the temperature variable using the scaleoffset parameter in create_variable(), which requires invalid_netcdf mode",
      "max_score": 20
    },
    {
      "name": "Group creation",
      "description": "Creates the 'sensors' group using create_group() method to organize data hierarchically",
      "max_score": 10
    },
    {
      "name": "Dimension management",
      "description": "Creates the 'time' dimension with size 100 using the dimensions dictionary assignment (e.g., group.dimensions['time'] = 100)",
      "max_score": 10
    },
    {
      "name": "Variable creation",
      "description": "Creates both temperature and valid_flags variables using create_variable() with appropriate dimensions and dtypes",
      "max_score": 10
    },
    {
      "name": "Data writing",
      "description": "Writes data to variables using NumPy-style indexing (e.g., variable[:] = data)",
      "max_score": 5
    }
  ]
}