perun.processing

Processing Module.

Attributes

log

Functions

processEnergyData(→ tuple[Any, Any])	Calculate total energy and average power from an energy or power time series.
processSensorData(→ perun.data_model.data.DataNode)	Calculate metrics based on raw values.
processDataNode(→ perun.data_model.data.DataNode)	Recursively calculate metrics on the dataNode tree.
processRegionsWithSensorData(→ None)	Complete region information using sensor data found on the data node (in place op).
addRunAndRuntimeInfoToRegion(→ None)	Process run and runtime stats in region objects (in place operation).
getInterpolatedValues(...)	Extract a time range out of a time series, and interpolate the values at the edges.

Module Contents

perun.processing.log

perun.processing.processEnergyData(raw_data: perun.data_model.data.RawData, start: perun.data_model.measurement_type.Number | None = None, end: perun.data_model.measurement_type.Number | None = None) → tuple[Any, Any]

Calculate total energy and average power from an energy or power time series.

Using the start and end parameters the results can be limited to certain areas of the application run.

Parameters:

• raw_data (RawData) – Raw Data from sensor

• start (Optional[Number], optional) – Start time of region, by default None

• end (Optional[Number], optional) – End time of region, by default None

Returns:

Tuple with total energy in joules and avg power in watts.

Return type:

_type_

perun.processing.processSensorData(sensorData: perun.data_model.data.DataNode) → perun.data_model.data.DataNode

Calculate metrics based on raw values.

Parameters:

sensorData (DataNode) – DataNode with raw sensor data.

Returns:

DataNode with computed metrics.

Return type:

DataNode

perun.processing.processDataNode(dataNode: perun.data_model.data.DataNode, perunConfig: configparser.ConfigParser, force_process: bool = False) → perun.data_model.data.DataNode

Recursively calculate metrics on the dataNode tree.

Parameters:

• dataNode (DataNode) – Root data node tree.

• perunConfig (ConfigParser) – Perun configuration

• force_process (bool, optional) – Force recomputation of child node metrics, by default False

Returns:

Data node with computed metrics.

Return type:

DataNode

perun.processing.processRegionsWithSensorData(regions: list[perun.data_model.data.Region], dataNode: perun.data_model.data.DataNode) → None

Complete region information using sensor data found on the data node (in place op).

Parameters:

• regions (List[Region]) – List of regions that use the same data node.

• dataNode (DataNode) – Data node with sensor data.

perun.processing.addRunAndRuntimeInfoToRegion(region: perun.data_model.data.Region) → None

Process run and runtime stats in region objects (in place operation).

Parameters:

region (Region) – Region object

perun.processing.getInterpolatedValues(t: numpy.typing.NDArray[numpy.floating], x: numpy.typing.NDArray[numpy.floating], start: perun.data_model.measurement_type.Number, end: perun.data_model.measurement_type.Number) → tuple[numpy.typing.NDArray[numpy.floating], numpy.typing.NDArray[numpy.floating]]

Extract a time range out of a time series, and interpolate the values at the edges.

Parameters:

• t (np.ndarray) – Original time steps

• x (np.ndarray) – Original values

• start (Number) – Start of the roi

• end (Number) – End of the roi

Returns:

Tuple with the new time steps and values.

Return type:

Tuple[np.ndarray, np.ndarray]