Custom DataAdapter#

DataAdapterBase is the base class for all HydroMT data adapters. It defines the core structure and transformation utilities used to standardize and convert data after it has been read by a Driver.

Overview#

A DataAdapter is responsible for transforming raw data from a Driver into a consistent HydroMT representation. This may include renaming variables, applying unit conversions, or adjusting time ranges.

DataAdapterBase provides the foundational fields and helper methods for such transformations.

Attributes#

  • unit_add: dict[str, Any] Dictionary of additive adjustments for variables. Commonly used for unit conversions or temporal offsets.

  • unit_mult: dict[str, Any] Dictionary of multiplicative adjustments for variables. Used for unit conversions.

  • rename: dict[str, str] Mapping from source variable names to standardized HydroMT variable names.

Methods#

_to_source_timerange(time_range: Optional[TimeRange]) → Optional[TimeRange]

Transforms a HydroMT TimeRange into the source-native time range. If unit_add contains a time offset, it is subtracted from the start and end times.

Parameters:

  • time_range: Optional[TimeRange]

    Start and end datetime of the requested HydroMT time range.

Returns:

  • Optional[TimeRange] — the transformed time range in source-native units, or None if no range was provided.

_to_source_variables(variables: Optional[List[str]]) → Optional[List[str]]

Transforms HydroMT variable names into source-native variable names based on the rename mapping.

Parameters:

  • variables: Optional[List[str]] List of variable names in HydroMT format.

Returns:

  • Optional[List[str]] — List of corresponding source-native variable names.

Usage Notes#

  • Subclasses should extend DataAdapterBase to implement specific variable transformations, unit conversions, or other dataset-specific logic.

  • The adapter works automatically when a DataSource passes loaded data through it.

  • unit_add and unit_mult provide a simple mechanism for adjusting numeric values or temporal offsets consistently across datasets.

  • The rename dictionary allows standardizing variable names from heterogeneous sources.

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