eelbrain.table.difference¶
-
eelbrain.table.
difference
(y, x, c1, c0, match, sub=None, ds=None, by=None)¶ Subtract data in one cell from another
Parameters: - y : Var | NDVar
Dependent variable.
- x : categorial
Model for subtraction, providing categories to compute
c1 - c0
.- c1 : str | tuple
Name of the cell in
x
that forms the minuend.- c0 : str | tuple
Name of the cell in
x
that is to be subtracted fromc1
.- match : categorial
Units over which measurements were repeated.
c1 - c0
will be calculated separately for each level ofmatch
(e.g."subject"
, or"subject % condition"
).- sub : None | index
Only include a subset of the data.
- ds : None | Dataset
If a Dataset is specified other arguments can be str instead of data-objects and will be retrieved from
ds
.
Returns: - diff : Dataset
Dataset with the difference between
c1
andc0
ony
.
Examples
ERP difference wave: assuming a dataset
ds
with EEG data (ds['eeg']
), a variable named'condition'
with levels'expected'
and'unexpected'
, and multiple subjects, the following will generate theunexpected - expected
difference waves:>>> diff = table.difference('eeg', 'condition', 'unexpected', 'expected', ... 'subject', ds=ds)
If
ds
also contains a different factor crossed withcondition
, called'word'
with levels'verb'
abd'adjective'
, then separate difference waves for verbs and adjectives can be computed with:>>> diff = table.difference('eeg', 'condition', 'unexpected', 'expected', ... 'subject % word', ds=ds)
Given the latter, the difference of the difference waves could be computed with:
>>> diffdiff = table.difference('eeg', 'word', 'verb', 'adjective', ... 'subject', ds=diff)