resurfemg.pipelines.pipelines module

resurfemg.pipelines.pipelines.alternative_a_pipeline_multi(our_chosen_samples, our_chosen_leads, picker='heart')

This is a pipeline to pre-process an array of non-specific dimensions e.g. a five lead array into an EMG singal, of which we want leads 0 to 2 included. Note it only differs in the bandpass values from working_pipeline_pre_ml_multi

Parameters:

• our_chosen_samples (ndarray) – the read EMG file arrays

• our_chosen_leads (tuple) – the read EMG file arrays that should be included

• picker (str) – the picking strategy for independant components

Returns:

final_envelope_a

Return type:

ndarray

resurfemg.pipelines.pipelines.alternative_b_pipeline_multi(our_chosen_samples, our_chosen_leads, picker='heart')

This is a pipeline to pre-process an array of non-specific dimensions e.g. a five lead array into an EMG singal, of which we want leads 0 to 2 included. Note it only differs in the bandpass values from working_pipeline_pre_ml_multi or alternative_a_pipeline_multi

Parameters:

• our_chosen_samples (ndarray) – the read EMG file arrays

• our_chosen_leads (tuple) – the read EMG file arrays that should be included

• picker (str) – the picking strategy for independant components

Returns:

final_envelope_a

Return type:

ndarray

resurfemg.pipelines.pipelines.working_pipe_multi(our_chosen_samples, picker='heart', selected=(0, 2))

This is a pipeline to pre-process an array of any dimenstions (number of leads) into an EMG singal, you need to pick the leads

Parameters:

• our_chosen_samples (ndarray) – the read EMG file arrays

• picker (str) – the picking strategy for independant components

• selected (tuple) – the leads selected for the pipeline to run over

Returns:

final_envelope_a

Return type:

ndarray

resurfemg.pipelines.pipelines.working_pipeline_exp(our_chosen_file)

This function is legacy. It produces a filtered respiratory EMG signal from a 3 lead sEMG file. A better option is a corresponding function in multi_lead_type The inputs are our_chosen_file which we give the function as a string of filename. The output is the processed EMG signal filtered and seperated from ECG components. The algorithm to pick out the EMG here is by having more peaks.

Parameters:

our_chosen_file (Poly5Reader) – Poly5 file

Returns:

final_envelope_a

Return type:

ndarray

resurfemg.pipelines.pipelines.working_pipeline_pre_ml(our_chosen_samples, picker='heart')

This is a pipeline to pre-process an array of specific fixed dimensions i.e. a three lead array into an EMG singal, the function is legacy code, and most processsing should be done with multi_lead_type.working_pipeline_pre_ml_multi or multi_lead_type.working_pipeline_pre_ml_multi :param our_chosen_samples: the read EMG file arrays :type our_chosen_samples: ~numpy.ndarray :param picker: the picking strategy for independent components :type picker: str :returns: final_envelope_a :rtype: ~numpy.ndarray

resurfemg.pipelines.pipelines.working_pipeline_pre_ml_multi(our_chosen_samples, our_chosen_leads, picker='heart')

This is a pipeline to pre-process an array of non-specific dimensions e.g. a five lead array into an EMG singal, of which we want leads 0 to 2 included

Parameters:

• our_chosen_samples (ndarray) – the read EMG file arrays

• our_chosen_leads (tuple) – the read EMG file arrays that should be included

• picker (str) – the picking strategy for independant components

Returns:

final_envelope_a

Return type:

ndarray