zensvi.metadata.KVMetadata
==========================

.. py:class:: zensvi.metadata.KVMetadata(path_input: Union[str, pathlib.Path], log_path: Optional[Union[str, pathlib.Path]] = None)

   Bases: :py:obj:`zensvi.metadata.base_metadata.BaseMetadata`


   Compute metadata for a KartaView (KV) dataset.

   Normalizes the columns of a KartaView ``kv_pids.csv`` (produced by ``KVDownloader``)
   to the schema expected by :class:`BaseMetadata`:

   - ``shotDate`` (``"%Y-%m-%d %H:%M:%S%.f"``, UTC) -> ``captured_at`` (ms since Unix epoch)
   - ``heading`` -> ``compass_angle``
   - ``sequenceId`` -> ``sequence_id``
   - ``userId`` -> ``creator_id``
   - ``orgCode`` -> ``organization_id``
   - ``id``, ``lat``, ``lon``, ``is_pano`` are used as-is.

   :param path_input: path to the input CSV file (e.g. ``kv_pids.csv``).
   :type path_input: Union[str, Path]
   :param log_path: Path to the log file. Defaults to None.
   :type log_path: Union[str, Path], optional


   .. py:method:: compute_metadata(unit: str = 'image', grid_resolution: int = 7, coverage_buffer: int = 50, indicator_list: str = 'all', path_output: Optional[Union[str, pathlib.Path]] = None, max_distance: int = 50) -> pandas.DataFrame

      Compute metadata for the dataset.

      :param unit: The unit of analysis. Defaults to "image".
      :type unit: str
      :param grid_resolution: The resolution of the H3 grid.
                              Defaults to 7.
      :type grid_resolution: int
      :param indicator_list: List of indicators to compute metadata
                             for. Use space- separated string of indicators or "all".
                             Options for image-level metadata: "year", "month",
                             "day", "hour", "day_of_week", "relative_angle", "h3_id",
                             "speed_kmh". Options for grid-level metadata:
                             "coverage", "count", "days_elapsed", "most_recent_date",
                             "oldest_date", "number_of_years", "number_of_months",
                             "number_of_days", "number_of_hours",
                             "number_of_days_of_week", "number_of_daytime",
                             "number_of_nighttime", "number_of_spring",
                             "number_of_summer", "number_of_autumn",
                             "number_of_winter", "average_compass_angle",
                             "average_relative_angle", "average_is_pano",
                             "number_of_users", "number_of_sequences",
                             "number_of_organizations", "average_speed_kmh". Defaults
                             to "all".
      :type indicator_list: str
      :param path_output: Path to save the output
                          metadata. Defaults to None.
      :type path_output: Union[str, Path]
      :param max_distance: The maximum distance to search for the
                           nearest street segment. Defaults to 50.
      :type max_distance: int

      :returns: A DataFrame containing the computed metadata.
      :rtype: pd.DataFrame