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
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
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='')