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GasChallengeAnalyser

GasChallengeAnalyser#

class patato.GasChallengeAnalyser(smoothing_window_size=10, display_output=True, smoothing_sigma=2, start_skip=0, challenge_type=1, buffer_width=5)#

Bases: SpatialProcessingAlgorithm

Analyser for oxygen-enhanced datasets. Takes in a time-series of sO2 data (or any other parameter) and produces a delta sO2.

__init__(smoothing_window_size=10, display_output=True, smoothing_sigma=2, start_skip=0, challenge_type=1, buffer_width=5)[source]#

Gas challenge analyser.

Parameters:

  • smoothing_window_size (int) – The size of the window to use for smoothing the data.

  • display_output (bool) – Whether to display the output, and ask for a response to confirm the fit is good.

  • smoothing_sigma (float) – The sigma to use for the gaussian smoothing.

  • start_skip (int) – The number of frames to skip at the start of the data.

  • challenge_type (int) – The type of challenge to use. 1 is the standard challenge (air -> oxygen), -1 is the reverse (oxygen -> air).

  • buffer_width (int) – The number of frames to use as a buffer at the start and end of the challenge.

Methods

__init__([smoothing_window_size, ...])

Gas challenge analyser.

add_child(child)

get_algorithm_id()

run(so2, pa_data[, reference_name])

This algorithm takes in a so2 time series and a PA data object (pa_data) and returns a tuple containing the delta sO2 (change in sO2 between the baseline and the challenge), an empty dictionary (for compatibility with other processing methods), and a list containing the mean and standard deviation of the baseline sO2.
run(so2: SingleParameterData, pa_data: PAData, reference_name=('reference_', '0'), **kwargs) → Tuple[SingleImage, dict, List[ProcessingResult] | None] | None[source]#

This algorithm takes in a so2 time series and a PA data object (pa_data) and returns a tuple containing the delta sO2 (change in sO2 between the baseline and the challenge), an empty dictionary (for compatibility with other processing methods), and a list containing the mean and standard deviation of the baseline sO2.

Parameters:

  • so2 (SingleParameterData) – The sO2 time series.

  • pa_data (PAData) – The PA data object.

  • reference_name (Tuple[str, str] or ROI) – The name of the reference region to use.

  • kwargs (dict) – Additional keyword arguments, provided for compatibility with other processing methods.

Returns:

A tuple containing the delta sO2, an empty dictionary (for compatibility with other processing methods), and a list containing the mean and standard deviation of the baseline sO2.

Return type:

Tuple[SingleImage, dict, Optional[List[ProcessingResult]]] or None

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