wonambi.attr.chan module

Module to work with channels.

It provides a general class to work with channels. Channels is the general term that refers to the points where signal comes from, it’s an abstract concept. Electrodes, magnetometer, axiometers and gradiometers are the actual recording devices measuring the signal. For example, in the case of EEG, you need two electrodes to have one signal, where one signal is the difference between the two electrodes.

In other words, the channel is where you want to plot the signal.

class wonambi.attr.chan.Chan(label, xyz=None, unit=None, attr=None)

Bases: object

Provide class Chan, for individual channels.

Parameters:

• label (str) – name of the channel

• xyz (numpy.ndarray or list or tuple) – 1d vector of 3 elements

• chtype (str, optional) – channel type (can be any string)

• unit (str, optional) – units, using SI

• attr (dict) – dictionary where you can store additional information per channel. Use chan.attr.update({‘new_key’: new_value})

class wonambi.attr.chan.Channels(*args)

Bases: object

Provide class Chan, generic class for channel location.

You can read from a file, and then you pass only one argument. Or you can directly assign the chan names and the coordinates.

Parameters:

• chan (list of instance of Chan) – list of channels (which are instances of Chan)

• chan_input (various formats) – information about the channels

• labels (list of str) – the name of the channel

• coords (numpy.ndarray) – location in 3D, with shape (n_chan, 3)

chan

list of channels

Type:

list of instance of wonambi.attr.chan.Chan

Raises:

UnrecognizedFormat – If the format is not recognized

Notes

chan_input can be a csv file without header and with format: label, x-pos, y-pos, z-pos or an sfp file without header and with format: label x-pos y-pos z-pos

export(elec_file)

Export channel name and location to file.

Parameters:

elec_file (Path or str) – path to file where to save csv

property n_chan

Returns the number of channels.

return_attr(attr, labels=None)

return the attributes for each channels.

Parameters:

attr (str) – attribute specified in Chan.attr.keys()

return_label()

Returns the labels for all the channels.

Returns:

list of str – list of the channel labels.

return_xy(labels=None)

Returns the location in xy for some channels.

Parameters:

labels (list of str, optional) – the names of the channels.

Returns:

numpy.ndarray – a 2xn vector with the position of a channel.

Notes

Simplest implementation. We should at least use project onto a 2D plane

return_xyz(labels=None)

Returns the location in xy for some channels.

Parameters:

labels (list of str, optional) – the names of the channels.

Returns:

numpy.ndarray – a 3xn vector with the position of a channel.

wonambi.attr.chan.assign_region_to_channels(channels, anat, parc_type='aparc', max_approx=3, exclude_regions=None)

Assign a brain region based on the channel location.

Parameters:

• channels (instance of wonambi.attr.chan.Channels) – channels to assign regions to

• anat (instance of wonambi.attr.anat.Freesurfer) – anatomical information taken from freesurfer.

• parc_type (str) – ‘aparc’, ‘aparc.a2009s’, ‘BA’, ‘BA.thresh’, or ‘aparc.DKTatlas40’ ‘aparc.DKTatlas40’ is only for recent freesurfer versions

• max_approx (int, optional) – approximation to define position of the electrode.

• exclude_regions (list of str or empty list) – do not report regions if they contain these substrings. None means that it does not exclude any region. For example, to exclude white matter regions and unknown regions you can use exclude_regions=(‘White’, ‘WM’, ‘Unknown’)

Returns:

instance of wonambi.attr.chan.Channels – same instance as before, now Chan have attr ‘region’

wonambi.attr.chan.create_sphere_around_elec(xyz, template_mri, distance=8, freesurfer=None)

Create an MRI mask around an electrode location,

Parameters:

• xyz (ndarray) – 3x0 array

• template_mri (path or str (as path) or nibabel.Nifti) – (path to) MRI to be used as template

• distance (float) – distance in mm between electrode and selected voxels

• freesurfer (instance of Freesurfer) – to adjust RAS coordinates, see Notes

Returns:

3d bool ndarray – mask where True voxels are within selected distance to the electrode

Notes

Freesurfer uses two coordinate systems: one for volumes (“RAS”) and one for surfaces (“tkReg”, “tkRAS”, and “Surface RAS”), so the electrodes might be stored in one of the two systems. If the electrodes are in surface coordinates (f.e. if you can plot surface and electrodes in the same space), then you need to convert the coordinate system. This is done by passing an instance of Freesurfer.

wonambi.attr.chan.detect_format(filename)

Detect file format of the channels based on extension.

Parameters:

filename (Path) – name of the filename

Returns:

str – file format

wonambi.attr.chan.find_chan_in_region(channels, anat, region_name)

Find which channels are in a specific region.

Parameters:

• channels (instance of wonambi.attr.chan.Channels) – channels, that have locations

• anat (instance of wonambi.attr.anat.Freesurfer) – anatomical information taken from freesurfer.

• region_name (str) – the name of the region, according to FreeSurferColorLUT.txt

Returns:

chan_in_region (list of str) – list of the channels that are in one region.

wonambi.attr.chan.find_channel_groups(chan)

Channels are often organized in groups (different grids / strips or channels in different brain locations), so we use a simple heuristic to get these channel groups.

Parameters:

chan (instance of Channels) – channels to group

Returns:

groups (dict) – channel groups: key is the common string, and the item is a list of labels