perda.core_data_structures.single_run_data#

pydantic model perda.core_data_structures.single_run_data.SingleRunData[source]#

Bases: BaseModel

Pydantic model to store parsed CSV data with dictionary-like lookup.

Config:

arbitrary_types_allowed: bool = True

Fields:

concat_boundaries (List[int])
cpp_name_to_id (Dict[str, int])
data_end_time (int)
data_start_time (int)
id_to_cpp_name (Dict[int, str])
id_to_descript (Dict[int, str])
id_to_instance (Dict[int, perda.core_data_structures.data_instance.DataInstance])
timestamp_unit (perda.units.Timescale)
total_data_points (int)

field id_to_instance: Dict[int, DataInstance] [Required]#: Mapping from variable ID to DataInstance

field cpp_name_to_id: Dict[str, int] [Required]#: Mapping from variable name to variable ID

field id_to_cpp_name: Dict[int, str] [Required]#: Mapping from variable ID to variable name

field id_to_descript: Dict[int, str] [Required]#: Mapping from variable ID to variable description

field total_data_points: int [Required]#: Total number of data points across all variables

field data_start_time: int [Required]#: Start timestamp in log timestamp unit

field data_end_time: int [Required]#: End timestamp in log timestamp unit

field timestamp_unit: Timescale = Timescale.MS#: Timestamp logging unit for this run (ms/us)

field concat_boundaries: List[int] [Optional]#: Timestamps where concatenated runs begin (post-shift)