Python ThreeDeeBrain Exemples

Exemple #1

linear_filter = processors.LinearFilter(lower_cutoff=8.0, upper_cutoff=12.0)
pipeline.add_processor(linear_filter)

inverse_model = processors.InverseModel(method='MNE',
                                        snr=1.0,
                                        forward_model_path=fwd_path)
pipeline.add_processor(inverse_model)

envelope_extractor = processors.EnvelopeExtractor(0.99)
pipeline.add_processor(envelope_extractor)

# Outputs
global_mode = outputs.ThreeDeeBrain.LIMITS_MODES.GLOBAL
three_dee_brain = outputs.ThreeDeeBrain(limits_mode=global_mode,
                                        buffer_length=6,
                                        surfaces_dir=SURF_DIR)
pipeline.add_output(three_dee_brain)
# pipeline.add_output(outputs.LSLStreamOutput())

signal_viewer = outputs.SignalViewer()
pipeline.add_output(signal_viewer, input_node=linear_filter)

# Создаем окно

window = GUIWindow(pipeline=pipeline)
window.init_ui()
window.setWindowFlags(QtCore.Qt.WindowStaysOnTopHint)
# window.show() # Will show after init

# Инициализируем все узлы

Exemple #2

Fichier : ica_rejection_pipeline.py Projet : google-python-student/cognigraph

linear_filter = processors.LinearFilter(lower_cutoff=8, upper_cutoff=12)
pipeline.add_processor(linear_filter)

inverse_model = processors.InverseModel(method='dSPM', snr=1.0)
pipeline.add_processor(inverse_model)

envelope_extractor = processors.EnvelopeExtractor(0.99)
pipeline.add_processor(envelope_extractor)

# Outputs
signal_viewer = outputs.SignalViewer()
pipeline.add_output(signal_viewer, input_node=linear_filter)

global_mode = outputs.ThreeDeeBrain.LIMITS_MODES.GLOBAL
three_dee_brain = outputs.ThreeDeeBrain(limits_mode=global_mode,
                                        buffer_length=6)
pipeline.add_output(three_dee_brain)

window = GUIWindow(pipeline=pipeline)
window.init_ui()
window.setWindowFlags(QtCore.Qt.WindowStaysOnTopHint)
window.show()

# base_controls = window._controls._base_controls
# processors_controls = base_controls.processors_controls

window.initialize()

bad_channel_labels = ['Fp2', 'F5', 'C5', 'F2', 'PPO10h', 'POO1', 'FCC2h']
preprocessing.mne_info['bads'] = bad_channel_labels
preprocessing._samples_to_be_collected = 0

Exemple #3

from cognigraph import TIME_AXIS
from cognigraph.gui.window import GUIWindow

app = QtGui.QApplication(sys.argv)

# BOBE
pipeline = Pipeline()

file_path = r"/home/evgenii/Downloads/brainvision/Bulavenkova_A_2017-10-24_15-33-18_Rest.vhdr"
source = sources.FileSource(file_path=file_path)
pipeline.source = source

inverse = processors.InverseModel()
pipeline.add_processor(inverse)

three_dee = outputs.ThreeDeeBrain()
pipeline.add_output(three_dee)

pipeline.initialize_all_nodes()

three_dee.widget.show()

source.output = source.data.take(indices=(0,), axis=TIME_AXIS)

inverse.update()
three_dee.update()

# Sample
pipeline = Pipeline()

source = sources.FileSource(file_path='')