Detections Cohort Review

Module name: DetectionsCohortReview

Package: CEAMSModules 7.4.0

Version: 2.1.0

Overview

Class to read the spindle/sw output files and generate the “Detected events cohort report” file clean or transposed.

Inputs

Input	Format	Default	Description
filenames	List of String	[]	List of filename (including path) to the PSA output file.
subject_chans_label	dict	{}	Keys are the subjects Each item is a list of 3 elements [original chan label, modified chan label, bool selection flag]
ROIs_cohort	dict	{}	Dict to manage the ROI created at the cohort level keys are ROIs labels Each item is a list of 2 elements [channel list to average, blank flag]
ROIs_subjects	dict	{}	Dict to manage the ROI at the subject level keys are the subjects Each item is a list of n_ROIs with its selection label [ROI#1 label, bool selection flag] [ROI#2 label, bool selection flag] …
activity_label	string	Total	The activity variable to export/save i.e. ‘Total’, ‘distribution per sleep cycle’, ‘distribution per clock hour’, ‘distribution per hour spent in each sleep stage’.
clean_flag	bool	0	Flag to generate and save the output file with only selected channels.
transposed_flag	bool	1	Flag to generate and save the transposed file (1 subject per row)
output_file	string	—	Output path to save the file clean and/or transposed.

Outputs

Output	Format	Description
out_df	pandas DataFrame	Detection events data converted into a dataframe with modifications applied.

Usage in a process

1. Open Dev Tools -> New process in Snooz.

2. In the Module Library, find Detections Cohort Review under the Files I/O category.

3. Drag the module onto the process canvas.

4. Connect the required inputs from upstream modules (or set values in the Settings tab).

5. Connect outputs to downstream modules as needed.

6. Double-click the module to configure parameters in the Settings tab.

7. Run the process and inspect results in the Results tab.

Note

For general guidance on building processes with modules, see Explore examples.