mne.AcqParserFIF#
- class mne.AcqParserFIF(info)[source]#
Parser for Elekta data acquisition settings.
This class parses parameters (e.g. events and averaging categories) that are defined in the Elekta TRIUX/VectorView data acquisition software (DACQ) and stored in
info['acq_pars']
. It can be used to reaverage raw data according to DACQ settings and modify original averaging settings if necessary.- Parameters:
See also
mne.io.Raw.acqparser
Access the parser through a Raw attribute.
Notes
Any averaging category (also non-active ones) can be accessed by indexing as
acqparserfif['category_name']
.- Attributes:
categories
list
Return list of averaging categories ordered by DACQ index.
events
list
Return events ordered by DACQ index.
- reject
dict
Rejection criteria from DACQ that can be used with mne.Epochs. Note that mne does not support all DACQ rejection criteria (e.g. spike, slope).
- flat
dict
Flatness rejection criteria from DACQ that can be used with mne.Epochs.
- acq_dict
dict
All DACQ parameters.
Methods
__getitem__
(item)Return an averaging category, or list of categories.
__len__
()Return number of averaging categories marked active in DACQ.
get_condition
(raw[, condition, ...])Get averaging parameters for a condition (averaging category).
- __getitem__(item)[source]#
Return an averaging category, or list of categories.
- Parameters:
- Returns:
- conds
dict
|list
ofdict
Each dict should have the following keys:
- comment: str
The comment field in DACQ.
- statebool
Whether the category was marked enabled in DACQ.
- indexint
The index of the category in DACQ. Indices start from 1.
- eventint
DACQ index of the reference event (trigger event, zero time for the corresponding epochs). Note that the event indices start from 1.
- startfloat
Start time of epoch relative to the reference event.
- endfloat
End time of epoch relative to the reference event.
- reqeventint
Index of the required (conditional) event.
- reqwhenint
Whether the required event is required before (1) or after (2) the reference event.
- reqwithinfloat
The time range within which the required event must occur, before or after the reference event.
- displaybool
Whether the category was displayed online in DACQ.
- naveint
Desired number of averages. DACQ stops collecting averages once this number is reached.
- subaveint
Whether to compute normal and alternating subaverages, and how many epochs to include. See the Elekta data acquisition manual for details. Currently the class does not offer any facility for computing subaverages, but it can be done manually by the user after collecting the epochs.
- conds
- __len__()[source]#
Return number of averaging categories marked active in DACQ.
- Returns:
- n_cat
int
The number of categories.
- n_cat
- property categories#
Return list of averaging categories ordered by DACQ index.
Only returns categories marked active in DACQ.
- property events#
Return events ordered by DACQ index.
Only returns events that are in use (referred to by a category).
- get_condition(raw, condition=None, stim_channel=None, mask=None, uint_cast=None, mask_type='and', delayed_lookup=True)[source]#
Get averaging parameters for a condition (averaging category).
Output is designed to be used with the Epochs class to extract the corresponding epochs.
- Parameters:
- raw
Raw
object An instance of Raw.
- condition
None
|str
|dict
|list
ofdict
Condition or a list of conditions. Conditions can be strings (DACQ comment field, e.g. ‘Auditory left’) or category dicts (e.g. acqp[‘Auditory left’], where acqp is an instance of AcqParserFIF). If None, get all conditions marked active in DACQ.
- stim_channel
None
|str
|list
ofstr
Name of the stim channel or all the stim channels affected by the trigger. If None, the config variables ‘MNE_STIM_CHANNEL’, ‘MNE_STIM_CHANNEL_1’, ‘MNE_STIM_CHANNEL_2’, etc. are read. If these are not found, it will fall back to ‘STI101’ or ‘STI 014’ if present, then fall back to the first channel of type ‘stim’, if present.
- mask
int
|None
The value of the digital mask to apply to the stim channel values. If None (default), no masking is performed.
- uint_cast
bool
If True (default False), do a cast to
uint16
on the channel data. This can be used to fix a bug with STI101 and STI014 in Neuromag acquisition setups that use channel STI016 (channel 16 turns data into e.g. -32768), similar tomne_fix_stim14 --32
in MNE-C.- mask_type‘and’ | ‘not_and’
The type of operation between the mask and the trigger. Choose ‘and’ for MNE-C masking behavior.
- delayed_lookup
bool
If True, use the ‘delayed lookup’ procedure implemented in Elekta software. When a trigger transition occurs, the lookup of the new trigger value will not happen immediately at the following sample, but with a 1-sample delay. This allows a slight asynchrony between trigger onsets, when they are intended to be synchronous. If you have accurate hardware and want to detect transitions with a resolution of one sample, use delayed_lookup=False.
- raw
- Returns:
- conds_data
dict
orlist
ofdict
Each dict has the following keys:
- eventsarray, shape (n_epochs_out, 3)
List of zero time points (t0) for the epochs matching the condition. Use as the
events
parameter to Epochs. Note that these are not (necessarily) actual events.- event_iddict
Name of condition and index compatible with
events
. Should be passed as theevent_id
parameter to Epochs.- tminfloat
Epoch starting time relative to t0. Use as the
tmin
parameter to Epochs.- tmaxfloat
Epoch ending time relative to t0. Use as the
tmax
parameter to Epochs.
- conds_data