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[[_TOC_]]
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# Introduction
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There are different ways to get data from AnyWave depending on what you want to do in the plugin.
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# Selecting channels
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Depending on the context (AnyWave is running in GUI mode or in Command Line mode) you can tune your request to get data from the channels you want.
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## Scenario 1 (do not specify any options)
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### the flags defined in desc.txt will be applied
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| input_flags | GUI mode | Command line mode |
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| ------ | ------ | ------ |
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| getcurrentmontage | get data from channels in the current montage | get data from channels in the current montage |
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| getasrecordedchannels | get data from raw channels (skip montage) | get data from raw channels (skip montage) |
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| modifiers_flags | GUI mode | Command line mode |
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| ------ | ------ | ------ |
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| acceptchannelselection | get data from selected channels (if there are) otherwise use the current montage | not applicable |
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if there are no input_flags neither modifier_flags in desc.txt the default behavior is to provide data from the current montage by default.
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## Scenario 2 (fine tune the channels you want to get data from)
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This will override flags set in desc.txt file.
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### Get current montage
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MATLAB:
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````matlab
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cfg = [];
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cfg.channels_source = 'montage'; % default behavior anyway.
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````
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Python:
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````python
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cfg = dict()
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cfg['channels_source'] = ['montage']
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````
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### Get current selection (only in GUI context)
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MATLAB:
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````matlab
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cfg = [];
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cfg.channels_source = 'selection';
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````
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Python:
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````python
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cfg = dict()
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cfg['channels_source'] = ['selection']
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````
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### Get raw channels
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Raw channels are physical channels stored in the data file. This will skip the current montage and also all the virtual channels like ICA time courses.
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MATLAB:
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````matlab
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cfg = [];
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cfg.channels_source = 'raw';
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````
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Python:
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````python
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cfg = dict()
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cfg['channels_source'] = ['raw']
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````
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### Pick channels
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You can request for channels with or without using raw/selection/montage options by providing a list of electrode labels you want:
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MATLAB:
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````matlab
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cfg = [];
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cfg.labels = {'Fp1', 'ECG', 'A1', 'A2-A3'};
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````
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Python:
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````python
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cfg = dict()
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cfg['labels'] = ['Fp1', 'ECG', 'A1', 'A2-A3']
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````
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Note: 'A2-A3' will request a bipolar channel, this will be applied on the fly by AnyWave.
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Electrodes labels must exist or will be skipped. You may have errors or an empty variable as the result of the request.
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### Get channels by their types
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Get EEG channels or EEG and ECG for example:
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````matlab
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cfg = [];
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% only EEG
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cfg.types = {'EEG'};
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% EEG and ECG
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cfg.types = {'EEG', 'ECG'};
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````
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Python:
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````python
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cfg = dict()
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# only EEG
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cfg['types'] = ['EEG']
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# EEG and ECG
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cfg['types'] = ['EEG', 'ECG']
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````
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# Selecting data chunks
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## I want data between time positions
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````matlab
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cfg = [];
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% get 10s of data starting 1s after the beginning of the file
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cfg.start = 1;
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cfg.duration = 10;
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output = anywave('get_data', cfg);
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````
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````python
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cfg = {'start': 1, 'duration' : 10}
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output = anywave.get_data_ex(cfg)
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````
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## I want several data chunks appended
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````matlab
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cfg = [];
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cfg.data_chunks = [ 1 10 2 4 ]; % specify several time selections at once
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output = anywave('get_data_ex', cfg); % data will be appended to the same output structure.
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````
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````python
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cfg = {'data_chunks' : [0, 10, 2, 4] }
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output = anywave.get_data_ex(cfg)
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````
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## I want several data chunks splitted
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Sometimes you want to get data chunks and apply processing on each ones.
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You must specify the split_data option when requesting data:
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````matlab
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cfg = [];
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cfg.data_chunks = [ 1 10 2 4 ]; % specify several time selections at once
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cfg.split_data = true; % key option to specify splitted data as result
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output = anywave('get_data', cfg);
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%%
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% output is a struct array. The number of elements is the number of data chunks requested.
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% As there are splitted each element contains the data and information of one data chunk.
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%%
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````
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````python
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cfg = {'data_chunks' : [0, 10, 2, 4], 'split_data' : True }
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output = anywave.get_data_ex(cfg)
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###
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### output is a list of dict containing the data and information of each data chunks requested.
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````
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## I want data chunks marked by markers
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````matlab
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cfg = [];
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cfg.use_markers = { 'section2', 'h2' ]; % the labels of markers
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% the markers section2 and h2 must exist in the data file otherwise AnyWave will send back the whole data file...
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output = anywave('get_data_ex', cfg); % the different data chunks marked are appended in one data matrix.
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% use split_data to separate data chunks
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cfg.split_data = true;
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output = anywave('get_data', cfg);
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%%
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% output is a struct array. The number of elements is the number of data chunks requested.
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% As there are splitted each element contains the data and information of one data chunk.
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%%
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````
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````python
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cfg = {'use_markers' : ['section2', 'h2'], 'split_data' : True }
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output = anywave.get_data_ex(cfg) # data chunks will be splitted here
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````
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## I want all data BUT artefacted/unused data chunks
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Getting all the data except chunks marked as bad is easy:
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````matlab
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cfg = [];
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cfg.skip_markers = { 'artefact', 'bad'};
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output = anywave('get_data', cfg); % data chunks appended
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````
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````python
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cfg = {'skip_markers' : ['artefact', 'bad'], 'split_data' : True }
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output = anywave.get_data_ex(cfg) # data chunks will be splitted here
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````
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## I want marked data chunks AND avoid bad ones
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This can happen when you marked data chunk of interest but some samples are also marked as bad afterwards by other processing.
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````matlab
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cfg = [];
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cfg.use_markers = { 'section2', 'h2' ]; % the labels of markers
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cfg.skip_markers = { 'artefact', 'bad'};
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output = anywave('get_data', cfg); % data chunks appended
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````
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````python
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cfg = {'skip_markers' : ['artefact', 'bad'], 'use_markers' : ['section2', 'h2'], 'split_data' : True }
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output = anywave.get_data_ex(cfg) # data chunks will be splitted here
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````
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# Filtering data
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````matlab
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cfg = [];
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cfg.filters = [1 130]; % apply a 1Hz high pass and 130Hz low pass filter
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...
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cfg.filters = [ 0 0 50]; % apply a notch filter at 50Hz.
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% filters values by order : High pass - Low Pass - Notch (optional)
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% force getting raw data (do not use filters set in AnyWave)
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cfg.raw_data = true;
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````
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