Modules
This guide documents all the necessary information needed to use the modules in the CEAMSModules package. Modules are the building blocks of Snooz processes. Each module performs a specific operation on signals, events, files, or parameters.
Modules are grouped by category as they appear in the Snooz Module Library. Select a category below to browse module documentation.
How to use modules
In Snooz, go to Dev Tools -> New process.
Open the Module Library and enable the CEAMSModules package if needed.
Drag modules from a category onto the process canvas.
Connect module inputs and outputs to define your analysis pipeline.
Configure each module via its Settings tab and run the process.
For a hands-on introduction to processes and modules, see Explore examples.
Categories
Module categories:
- Connectivity Analysis
- Detectors
- Events Analysis
- Events Utilities
- Connectivity Details
- Define Event Group
- Discard Events
- Drop/Rename Events
- Event Combine
- Event Compare
- Event Creator
- Event Subdivision
- Events Splitter
- Extend Events
- Filter Events
- Performance By Event
- PSA Pics Generator
- REMs Details
- REMs to mini-epochs
- Replace Event In Signals
- Scoring Completeness
- Signals From Events
- Sleep Stage Events
- Sleep Stage Rename
- Slow Wave Pics Generator
- Slow Waves Details
- Spindles Details
- Windows To Samples
- Quick reference
- Files I/O
- Hypnogram Analysis
- Parameters
- Signal Processing
- Statistics
All modules
Module |
Category |
Version |
Description |
|---|---|---|---|
Connectivity Analysis |
2.1.0 |
Computes per-epoch, surrogate-corrected Directed Phase Lag Index (dPLI) matrices from EEG epochs. |
|
Connectivity Analysis |
2.1.0 |
Computes per-epoch, surrogate-corrected Weighted Phase Lag Index (wPLI) matrices from EEG epochs. |
|
Detectors |
2.0.0 |
Refines onset and duration of events detected by the a4 spindle detector. |
|
Detectors |
2.0.0 |
Detects events based on the absolute signal amplitude. |
|
Detectors |
2.0.0 |
Detects events based on maximum amplitude variation in a narrow time windows. |
|
Detectors |
2.0.0 |
Organizes detection information and saves it into the cache in order to plot it. |
|
Detectors |
2.4.0 |
Analyzes the oxygen channel, detect oxygen desaturations and export oxygen saturation report. |
|
Detectors |
3.1.0 |
Detects Rapid Eye Movements (REMs) in EOG sleep recordings using YASA REM detection algorithm. |
|
Detectors |
2.2.0 |
Detects slow wave events based on the Carrier method. |
|
Detectors |
2.2.0 |
Detects events based on the spectrum. |
|
Detectors |
3.0.0 |
Detects spindles based on the a7 algorithm. |
|
Detectors |
3.0.0 |
Detects spindles based on the SUMO deep learning algorithm. |
|
Events Analysis |
2.0.0 |
Generates event sleep report. |
|
Events Analysis |
2.0.0 |
Generates temporal links listed in the input temporal_links. |
|
Events Utilities |
2.0.0 |
Saving connectivity results to disk. |
|
Events Utilities |
2.0.0 |
Defines groups to events. |
|
Events Utilities |
2.1.0 |
Discards too long, too short or events that occur during artefacts. |
|
Events Utilities |
2.0.0 |
Drops events and/or rename events group and/or name. |
|
Events Utilities |
2.0.0 |
Combines two lists of events, with or without selection. |
|
Events Utilities |
2.0.0 |
Compares two sets of events . |
|
Events Utilities |
2.0.0 |
Creates a pandas Dataframe of events. |
|
Events Utilities |
0.0.0 |
Creates a new pandas DataFrame of events with subwindow of every input events named events_names. |
|
Events Utilities |
2.0.0 |
Used to split too long events. |
|
Events Utilities |
2.0.0 |
Extend or shrink events by a percentage of their duration, applied to each side. |
|
Events Utilities |
2.0.0 |
Selects events from specific sleep stages. |
|
Events Utilities |
2.0.0 |
Compares two sets of events . |
|
Events Utilities |
2.0.1 |
Used to generate figures of Power Spectral Analysis (PSA) data from PSA report files. |
|
Events Utilities |
2.2.0 |
Averages REMs events characteristics such as duration, amplitude and density per stage and sleep cycle. |
|
Events Utilities |
0.0.0 |
Used to generate a list of mini-epochs identified as a Phasic or Tonic based on the list of detected REMs. |
|
Events Utilities |
2.1.0 |
Inserts samples from event dataframe inside a signals. |
|
Events Utilities |
2.0.0 |
Evaluates if the scoring (events) is unique, complete and specific to the sleep staging. |
|
Events Utilities |
3.0.0 |
Manages a list of SignalModel from specific events during a recording. |
|
Events Utilities |
2.1.0 |
Creates a list of event from specific sleep stages during a recording. |
|
Events Utilities |
2.0.0 |
Renames sleep stage annotation. |
|
Events Utilities |
3.0.0 |
Used to generate pictures of slow wave events. |
|
Events Utilities |
2.2.0 |
Averages slow wave events characteristics such as duration, amplitude, frequency and so on per stage and sleep cycle. |
|
Events Utilities |
2.2.0 |
Computes spindles events characteristics such as duration, amplitude, frequency and so on. |
|
Events Utilities |
2.0.0 |
Converts information based on windows (i.e. RMS energy) into a time series. |
|
Files I/O |
2.0.0 |
Reads events from a CSV file. |
|
Files I/O |
2.1.0 |
Reads the spindle/sw output files and generates the “Detected events cohort report” file clean or transposed. |
|
Files I/O |
2.1.0 |
Converts DOMINO accessory files (ASCII) in one Snooz accessory tsv file. |
|
Files I/O |
2.0.0 |
Used to read the EDF Annotations signal and create a pandas dataframe with the events. |
|
Files I/O |
2.0.0 |
Reads events from a EDF.XML file. |
|
Files I/O |
2.0.0 |
Reads events from a EDF.XML files or .XML files. |
|
Files I/O |
2.0.0 |
Creates an XML file based on compumedic format. |
|
Files I/O |
3.0.0 |
Reads events from a Tsv file. |
|
Files I/O |
2.0.0 |
Edits JSON files by replacing paths within the JSON structure. |
|
Files I/O |
2.5.0 |
Reads the PSA output file and generates the PSA file clean or transposed. |
|
Files I/O |
2.3.0 |
Reads a PSG file. |
|
Files I/O |
2.2.0 |
Writes a PSG file. |
|
Files I/O |
2.1.0 |
Renames files based on input parameters such as prefix. |
|
Files I/O |
2.1.0 |
Imports sleep stages from a textfile into the sleep_stages dataframe. |
|
Files I/O |
2.0.0 |
Validates TSV files by checking their encoding and structure. |
|
Files I/O |
2.0.0 |
Saves events to a CSV file. |
|
Hypnogram Analysis |
2.1.0 |
Displays in the results view an hypnogram and its sleep cycles. |
|
Hypnogram Analysis |
2.0.0 |
Supports sleep bouts operations within a Snooz process. |
|
Hypnogram Analysis |
2.4.0 |
Compute the sleep cycles. |
|
Hypnogram Analysis |
2.1.0 |
Generates a sleep report in CSV file. |
|
Parameters |
2.0.0 |
Extract only the signals with a specific Alias. |
|
Parameters |
2.0.0 |
Passes a value to the next node. |
|
Parameters |
2.0.0 |
Transforms key-value inputs into a dictionary output while preserving the original value. |
|
Parameters |
2.0.0 |
Creates a list of tuples that has two values of group and name. |
|
Parameters |
2.0.0 |
Creates a tuple from two input values. |
|
Parameters |
2.0.0 |
Returns a value based on a key received in input. |
|
Parameters |
2.0.0 |
Allows string manipulaiton. |
|
Signal Processing |
2.0.0 |
Segments EEG signals into overlapping or non-overlapping epochs of fixed duration. |
|
Signal Processing |
2.1.0 |
Applies a FIR/IIR filter to EEG signals. |
|
Signal Processing |
2.0.0 |
Find components of a signal with idependant component analysis. |
|
Signal Processing |
2.0.0 |
Reconstructs signal from ICA components. |
|
Signal Processing |
2.0.0 |
Inverts signals. |
|
Signal Processing |
0.0.0 |
Spectral power decomposition using IRASA algorithm. |
|
Signal Processing |
2.0.0 |
Computes RMS value on a moving window. |
|
Signal Processing |
0.0.0 |
Analyses and reports the PSD output designed specifically for FOOOF analysis. |
|
Signal Processing |
2.0.0 |
Removes full-channel artefacts from signals and events. |
|
Signal Processing |
2.0.0 |
Resamples a signal. |
|
Signal Processing |
2.1.0 |
Creates a list of dictionaries with the channels from specific epochs during a recording. |
|
Signal Processing |
2.1.0 |
Resets the signal that occurs during an artefact. |
|
Signal Processing |
2.0.0 |
Automatic sleep stage classification using YASA’s machine learning model. |
|
Signal Processing |
2.1.0 |
Computes the STFT on the signal split into sliding windows. |
|
Signal Processing |
2.0.0 |
Subtracts signals from a specific channel from the signals of a list of channels. |
|
Signal Processing |
2.0.0 |
Trims continuous/discontinuous signal segments and their associated events to a time window defined by. |
|
Statistics |
2.0.0 |
Finds the mutual information between two lists of signals. |
|
Statistics |
2.2.0 |
Analyses and reports the PSD output. |
|
Statistics |
2.1.0 |
Compiles the PSA run on selected events. |
|
Statistics |
2.0.0 |
Computes the mean and standard deviation of the input signals per epoch, per channel. |
|
Statistics |
2.0.0 |
Processes and visualizes sleep staging results. |
|
Statistics |
2.0.0 |
Classifies slow wave events based on a gaussian mixture. |
|
Statistics |
2.1.0 |
Computes the value to threshold (i.e. µV) from a signals (i.e. EEG time series) |