{
  "context": "This criteria evaluates how effectively the engineer uses h5netcdf for creating, organizing, and accessing multidimensional scientific data. It focuses specifically on proper usage of h5netcdf's variable creation, storage configuration, indexing operations, and metadata management features.",
  "type": "weighted_checklist",
  "checklist": [
    {
      "name": "File Creation",
      "description": "Uses h5netcdf.File() to create the netCDF4 file with appropriate mode ('w' or 'a'). Should use context manager (with statement) or explicit close() for proper resource management.",
      "max_score": 10
    },
    {
      "name": "Group Hierarchy",
      "description": "Uses create_group() method to establish hierarchical organization for regions. Groups should be properly nested to represent the regional structure.",
      "max_score": 15
    },
    {
      "name": "Dimension Creation",
      "description": "Creates dimensions using the dictionary-style assignment (e.g., group.dimensions['time'] = 10) for both time and station dimensions in appropriate groups.",
      "max_score": 10
    },
    {
      "name": "Variable Creation",
      "description": "Uses create_variable() method to create temperature and precipitation variables with correct dimension tuples (e.g., ('time', 'station')) and appropriate dtype (float).",
      "max_score": 15
    },
    {
      "name": "Compression Configuration",
      "description": "Passes compression parameter (e.g., compression='gzip') to create_variable() for both temperature and precipitation variables to enable data compression.",
      "max_score": 15
    },
    {
      "name": "Fill Value",
      "description": "Sets fillvalue parameter in create_variable() to -999.9 for handling missing data, or sets the _FillValue attribute after variable creation.",
      "max_score": 10
    },
    {
      "name": "Data Writing",
      "description": "Writes data to variables using NumPy-style indexing (e.g., var[:] = data or var[start:end] = data) with appropriate array shapes.",
      "max_score": 10
    },
    {
      "name": "Array Slicing",
      "description": "Reads data using array slicing operations (e.g., var[2:6] or var[:, station_idx]) to extract specific time ranges or station data.",
      "max_score": 10
    },
    {
      "name": "Metadata Attributes",
      "description": "Uses the .attrs dictionary interface to set attributes on variables (e.g., var.attrs['units'] = 'celsius') and file/group level (e.g., file.attrs['created'] = timestamp).",
      "max_score": 5
    }
  ]
}