resurfemg.data_connector.peakset_class module

Copyright 2022 Netherlands eScience Center and University of Twente Licensed under the Apache License, version 2.0. See LICENSE for details.

This file contains data classes for standardized peak data storage and method automation.

class resurfemg.data_connector.peakset_class.PeaksSet(signal, t_data, peak_idxs=None)

Bases: object

Data class to store, and process peak information.

detect_on_offset(baseline=None, method='default', fs=None, slope_window_s=None)

Detect the peak on- and offsets. See postprocessing.event_detection submodule.

evaluate_validity(tests_df_new)

Update peak validity based on previously and newly executed tests in self.quality_outcomes_df. ———————————————————————– :param tests_df_new: Dataframe of passed tests per peak :type tests_df_new: pandas.DataFrame

Returns:

None

Return type:

None

sanitize()

Delete invalid peak entries (self.peak_df[‘valid’] is False) from self.peak_df, self.quality_values_df, and self.quality_outcomes_df. ———————————————————————– :returns: None :rtype: None

update_test_outcomes(tests_df_new)

Add new peak quality test to self.quality_outcomes_df, and update existing entries. ———————————————————————– :param tests_df_new: Dataframe of test parameters per peak :type tests_df_new: pandas.DataFrame

Returns:

None

Return type:

None