frites.simulations.sim_local_cd_ss#
- frites.simulations.sim_local_cd_ss(n_conditions=2, n_epochs=10, n_times=100, n_roi=1, cl_index=[40, 60], cl_cov=[0.8], random_state=None)[source]#
Single-subject simulations for computing local MI (CD).
This function can be used for simulating local representations of mutual information between a continuous and a discret variable (CD) for a single subject.
- Parameters
- n_conditions
python:int| 2 Number of conditions
- n_epochs
python:int| 30 Number of trials
- n_times
python:int| 100 Number of time points
- n_roi
python:int| 1 Number of ROI
- cl_indexnumpy:array_like | [40, 60]
Sample indices where the clusters are located. Should be an array of shape (n_clusters, 2)
- cl_covnumpy:array_like | [.8]
Covariance level between the data and the regressor variable. Should be an array of shape (n_clusters,)
- random_state
python:int|python:None Random state (use it for reproducibility)
- n_conditions
- Returns
- xnumpy:array_like
Data array of shape (n_epochs, n_channels, n_times)
- ynumpy:array_like
Condition array of shape (n_epochs,)
- roinumpy:array_like
Array of ROI names of shape (n_roi,)
- timesnumpy:array_like
Time vector of shape (n_times,)