pycrostates.io.ChData#

class pycrostates.io.ChData(data, info)[source]#

ChData stores atemporal data with its spatial information.

ChData is similar to a raw instance where temporality has been removed. Only the spatial information, stored as a ChInfo is retained.

Parameters:

dataarray: Data array of shape (n_channels, n_samples).
infomne.Info | ChInfo: Atemporal measurement information. If a mne.Info is provided, it is converted to a ChInfo.

Attributes:

ch_names: Channel names.
compensation_grade: The current gradient compensation grade.
info: Atemporal measurement information.
preload: Preload required by some MNE functions.

Methods

`copy`([deep])	Return a copy of the instance.
`get_channel_types`([picks, unique, only_data_chs])	Get a list of channel type for each channel.
`get_data`([picks])	Retrieve the data array.
`get_montage`()	Get a DigMontage from instance.
`pick`(picks[, exclude])	Pick a subset of channels.
`set_montage`(montage[, match_case, ...])	Set EEG/sEEG/ECoG/DBS/fNIRS channel positions and digitization points.

__contains__(ch_type)#

Check channel type membership.

Parameters:

ch_typestr: Channel type to check for. Can be e.g. 'meg', 'eeg', 'stim', etc.

Returns:

inbool: Whether or not the instance contains the given channel type.

Examples

Channel type membership can be tested as:

>>> 'meg' in inst  
True
>>> 'seeg' in inst  
False

copy(deep=True)[source]#

Return a copy of the instance.

Parameters:

deepbool: If True, deepcopy is used instead of copy.

get_channel_types(picks=None, unique=False, only_data_chs=False)#

Get a list of channel type for each channel.

Parameters:

picksstr | array_like | slice | None: Channels to include. Slices and lists of integers will be interpreted as channel indices. In lists, channel type strings (e.g., ['meg', 'eeg']) will pick channels of those types, channel name strings (e.g., ['MEG0111', 'MEG2623'] will pick the given channels. Can also be the string values “all” to pick all channels, or “data” to pick data channels. None (default) will pick all channels. Note that channels in info['bads'] will be included if their names or indices are explicitly provided.
uniquebool: Whether to return only unique channel types. Default is False.
only_data_chsbool: Whether to ignore non-data channels. Default is False.

Returns:

channel_typeslist: The channel types.

get_data(picks=None)[source]#

Retrieve the data array.

Parameters:

picksstr | array_like | slice | None: Channels to include. Slices and lists of integers will be interpreted as channel indices. In lists, channel type strings (e.g., ['meg', 'eeg']) will pick channels of those types, channel name strings (e.g., ['MEG0111', 'MEG2623'] will pick the given channels. Can also be the string values “all” to pick all channels, or “data” to pick data channels. None (default) will pick all channels. Note that channels in info['bads'] will be included if their names or indices are explicitly provided.

Returns:

dataarray: Data array of shape (n_channels, n_samples).

get_montage()#

Get a DigMontage from instance.

Returns:

montageNone | str | DigMontage: A montage containing channel positions. If a string or DigMontage is specified, the existing channel information will be updated with the channel positions from the montage. Valid strings are the names of the built-in montages that ship with MNE-Python; you can list those via mne.channels.get_builtin_montages(). If None (default), the channel positions will be removed from the Info.

pick(picks, exclude='bads')[source]#

Pick a subset of channels.

Parameters:

picksstr | array_like | slice | None: Channels to include. Slices and lists of integers will be interpreted as channel indices. In lists, channel type strings (e.g., ['meg', 'eeg']) will pick channels of those types, channel name strings (e.g., ['MEG0111', 'MEG2623'] will pick the given channels. Can also be the string values “all” to pick all channels, or “data” to pick data channels. None (default) will pick all channels. Note that channels in info['bads'] will be included if their names or indices are explicitly provided.
excludelist | str: Set of channels to exclude, only used when picking based on types (e.g., exclude="bads" when picks="meg").

Returns:

instChData: The instance modified in-place.

set_montage(montage, match_case=True, match_alias=False, on_missing='raise', verbose=None)#

Set EEG/sEEG/ECoG/DBS/fNIRS channel positions and digitization points.

Parameters:

montageNone | str | DigMontage: A montage containing channel positions. If a string or DigMontage is specified, the existing channel information will be updated with the channel positions from the montage. Valid strings are the names of the built-in montages that ship with MNE-Python; you can list those via mne.channels.get_builtin_montages(). If None (default), the channel positions will be removed from the Info.
match_casebool: If True (default), channel name matching will be case sensitive.

Added in version 0.20.
match_aliasbool | dict: Whether to use a lookup table to match unrecognized channel location names to their known aliases. If True, uses the mapping in mne.io.constants.CHANNEL_LOC_ALIASES. If a dict is passed, it will be used instead, and should map from non-standard channel names to names in the specified montage. Default is False.

Added in version 0.23.
on_missing‘raise’ | ‘warn’ | ‘ignore’: Can be 'raise' (default) to raise an error, 'warn' to emit a warning, or 'ignore' to ignore when channels have missing coordinates.

Added in version 0.20.1.
verbosebool | str | int | None: Control verbosity of the logging output. If None, use the default verbosity level. See the logging documentation and mne.verbose() for details. Should only be passed as a keyword argument.

Returns:

instinstance of Raw | Epochs | Evoked: The instance, modified in-place.

Examples using `pycrostates.io.ChData`#

Global Field Power peaks

Subject level analysis with resampling

Group-level analysis from individual clusters

Group level analysis from individual GFP peaks

Evaluating clustering fits

pycrostates.io.ChData#

Examples using pycrostates.io.ChData#

Examples using `pycrostates.io.ChData`#