sylvchev

name: moabb
channels:
  - conda-forge
  - defaults
dependencies:
- python>=3.9
- numpy
- scipy
- scikit-learn
- mne

sylvchev

import moabb
from moabb.datasets import BNCI2014001, Zhou2016
from moabb.paradigms import LeftRightImagery
from moabb.evaluations import WithinSessionEvaluation

from sklearn.discriminant_analysis import LinearDiscriminantAnalysis as LDA
from sklearn.pipeline import make_pipeline

from mne.decoding import CSP

sylvchev

sylvchev

from moabb.datasets import Cho2017, BNCI2014001, PhysionetMI
from moabb.paradigms import MotorImagery
from moabb.datasets.utils import find_intersecting_channels

datasets = [Cho2017(), BNCI2014001(), PhysionetMI()]

common_channels, _ = find_intersecting_channels(datasets)
chans = common_channels[:3]
paradigm = MotorImagery(channels=chans)

sylvchev

from mne import find_events, events_from_annotations
import mne

# get some raw data, replace by your own files
from moabb.datasets import BNCI2014001
sessions = BNCI2014001().get_data(subjects=[1])
raw = sessions[1]['session_T']['run_1']
ev = find_events(raw)

# Annotate plot

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######################################################################################################
#  ________   _________   ___    ___ ___  ___  ________  ________  ___  __      _______   _______
# |\   ___  \|\___   ___\|\  \  /  /|\  \|\  \|\   __  \|\   ____\|\  \|\  \   /  ___  \ /  ___  \
# \ \  \\ \  \|___ \  \_|\ \  \/  / | \  \\\  \ \  \|\  \ \  \___|\ \  \/  /|_/__/|_/  //__/|_/  /|
#  \ \  \\ \  \   \ \  \  \ \    / / \ \   __  \ \   __  \ \  \    \ \   ___  \__|//  / /__|//  / /
#   \ \  \\ \  \   \ \  \  /     \/   \ \  \ \  \ \  \ \  \ \  \____\ \  \\ \  \  /  /_/__  /  /_/__
#    \ \__\\ \__\   \ \__\/  /\   \    \ \__\ \__\ \__\ \__\ \_______\ \__\\ \__\|\________\\________\
#     \|__| \|__|    \|__/__/ /\ __\    \|__|\|__|\|__|\|__|\|_______|\|__| \|__| \|_______|\|_______|
#                        |__|/ \|__|
######################################################################################################

sylvchev

from mne import create_info, EpochsArray
from mne.decoding import CSP as CSP_MNE
from moabb.datasets import BNCI2014001
from moabb.paradigms import LeftRightImagery
import numpy as np
from pyriemann.estimation import Covariances
from pyriemann.spatialfilters import CSP as CSP_Pyr

n_components=8

sylvchev

import numpy as np
from numpy.random import chisquare
from scipy.stats import lognorm
import scipy as sp

import pyriemann

from sklearn.pipeline import Pipeline
from sklearn.decomposition import PCA
from pyriemann.tangentspace import TangentSpace

sylvchev