Simulate model objectΒΆ
In this example, we simulate 3 brain objects using a subset of 10 locations. We will impose a correlational structure (a toeplitz matrix) on our simulated brain objects. Then, we will create a model from these brain objects and plot it.
# Code source: Lucy Owen & Andrew Heusser
# License: MIT
import supereeg as se
# simulate 100 locations
locs = se.simulate_locations(n_elecs=100)
# simulate correlation matrix
R = se.create_cov(cov='toeplitz', n_elecs=len(locs))
# create list of simulated brain objects
model_bos = [se.simulate_model_bos(n_samples=1000, sample_rate=1000, cov=R,
locs=locs, sample_locs=10) for x in range(3)]
# create model from subsampled gray locations
model = se.Model(model_bos, locs=locs)
# plot the model
model.plot_data()
Total running time of the script: ( 0 minutes 2.548 seconds)