Generate sparse (n_dipoles) sources time courses from data_fun.
This function randomly selects n_dipoles
vertices in the whole
cortex or one single vertex (randomly in or in the center of) each
label if labels is not None
. It uses data_fun
to generate
waveforms for each vertex.
SourceSpaces
The source space.
int
Number of dipoles to simulate.
array
Time array.
callable()
Function to generate the waveforms. The default is a 100 nAm, 10 Hz
sinusoid as 1e-7 * np.sin(20 * pi * t)
. The function should take
as input the array of time samples in seconds and return an array of
the same length containing the time courses.
None
| list
of Label
The labels. The default is None, otherwise its size must be n_dipoles.
None
| int
| instance of RandomState
A seed for the NumPy random number generator (RNG). If None
(default),
the seed will be obtained from the operating system
(see RandomState
for details), meaning it will most
likely produce different output every time this function or method is run.
To achieve reproducible results, pass a value here to explicitly initialize
the RNG with a defined state.
str
The label location to choose. Can be ‘random’ (default) or ‘center’
to use mne.Label.center_of_mass()
. Note that for ‘center’
mode the label values are used as weights.
New in version 0.13.
str
| None
The subject the label is defined for.
Only used with location='center'
.
New in version 0.13.
None
The path to the directory containing the FreeSurfer subjects
reconstructions. If None
, defaults to the SUBJECTS_DIR
environment
variable.
New in version 0.13.
str
The surface to use for Euclidean distance center of mass finding. The default here is “sphere”, which finds the center of mass on the spherical surface to help avoid potential issues with cortical folding.
New in version 0.13.
SourceEstimate
The generated source time courses.
See also
Notes
New in version 0.10.0.
mne.simulation.simulate_sparse_stc
#Generate simulated evoked data
Cortical Signal Suppression (CSS) for removal of cortical signals