import mne
from mne.io import read_raw_fif
from mne.datasets import visual_92_categories
from neurora import rsa_plot
from neurora.nps_cal import nps
from neurora.rdm_cal import eegRDM
from neurora.rdm_corr import rdm_correlation_spearman
from neurora.corr_cal_by_rdm import rdms_corr
from neurora.rsa_plot import plot_rdm, plot_corrs_by_time, plot_nps_hotmap, plot_corrs_hotmap
#%%
"""********** Section 1: loading example data **********"""
""" Here, we use MNE-Python toolbox for loading data and processing """
""" you can learn this process from MNE-Python (https://mne-tools.github.io/stable/index.html) """
data_path = visual_92_categories.data_path()
fname = op.join(data_path, 'visual_stimuli.csv')
conds = read_csv(fname)
conditions = []
for c in conds.values:
cond_tags = list(c[:2])
cond_tags += [('not-' if i == 0 else '') + conds.columns[k]
for k, i in enumerate(c[2:], 2)]
conditions.append('/'.join(map(str, cond_tags)))
event_id = dict(zip(conditions, conds.trigger + 1))
print(event_id)
sub_id = [0, 1, 2]
megdata = np.zeros([3, 92, 306, 1101], dtype=np.float32)
subindex = 0
for id in sub_id:
fname = op.join(data_path, 'sample_subject_' + str(id) + '_tsss_mc.fif')
import matplotlib.pyplot as plt from sklearn.model_selection import StratifiedKFold from sklearn.pipeline import make_pipeline from sklearn.preprocessing import StandardScaler from sklearn.linear_model import LogisticRegression from sklearn.metrics import roc_auc_score from sklearn.manifold import MDS import mne from mne.io import read_raw_fif, concatenate_raws from mne.datasets import visual_92_categories print(__doc__) data_path = visual_92_categories.data_path() # Define stimulus - trigger mapping fname = op.join(data_path, 'visual_stimuli.csv') conds = read_csv(fname) print(conds.head(5)) ############################################################################## # Let's restrict the number of conditions to speed up computation max_trigger = 24 conds = conds[:max_trigger] # take only the first 24 rows ############################################################################## # Define stimulus - trigger mapping conditions = [] for c in conds.values: