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Source code for tvb.adapters.visualizers.cross_correlation

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#   Paula Sanz Leon, Stuart A. Knock, M. Marmaduke Woodman, Lia Domide,
#   Jochen Mersmann, Anthony R. McIntosh, Viktor Jirsa (2013)
#       The Virtual Brain: a simulator of primate brain network dynamics.
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"""
A visualizer for cross correlation.

.. moduleauthor:: Paula Popa <paula.popa@codemart.ro>
.. moduleauthor:: Lia Domide <lia.domide@codemart.ro>
.. moduleauthor:: Marmaduke Woodman <marmaduke.woodman@univ-amu.fr>

"""

from tvb.adapters.datatypes.db.temporal_correlations import CrossCorrelationIndex
from tvb.adapters.visualizers.matrix_viewer import ABCMappedArraySVGVisualizer
from tvb.core.adapters.abcadapter import ABCAdapterForm
from tvb.core.neocom import h5
from tvb.core.neotraits.forms import TraitDataTypeSelectField
from tvb.core.neotraits.view_model import ViewModel, DataTypeGidAttr
from tvb.datatypes.temporal_correlations import CrossCorrelation


[docs]class CrossCorrelationVisualizerModel(ViewModel): datatype = DataTypeGidAttr( linked_datatype=CrossCorrelation, label='Cross correlation' )
[docs]class CrossCorrelationVisualizerForm(ABCAdapterForm): def __init__(self, prefix='', project_id=None): super(CrossCorrelationVisualizerForm, self).__init__(prefix, project_id) self.datatype = TraitDataTypeSelectField(CrossCorrelationVisualizerModel.datatype, self, name='datatype') @staticmethod
[docs] def get_view_model(): return CrossCorrelationVisualizerModel
@staticmethod
[docs] def get_required_datatype(): return CrossCorrelationIndex
@staticmethod
[docs] def get_input_name(): return 'datatype'
@staticmethod
[docs] def get_filters(): return None
[docs]class CrossCorrelationVisualizer(ABCMappedArraySVGVisualizer): _ui_name = "Cross Correlation Visualizer" _ui_subsection = "correlation"
[docs] def get_form_class(self): return CrossCorrelationVisualizerForm
[docs] def launch(self, view_model): # type: (CrossCorrelationVisualizerModel) -> dict """Construct data for visualization and launch it.""" correlation_gid = view_model.datatype correlation_index = self.load_entity_by_gid(correlation_gid) labels = self.extract_source_labels(correlation_index) with h5.h5_file_for_index(correlation_index) as dt_h5: matrix = dt_h5.array_data[:] matrix = matrix.mean(axis=0)[:, :, 0, 0] pars = self.compute_params(correlation_index, matrix, 'Correlation matrix plot', labels=[labels, labels]) pars['show_slice_info'] = False return self.build_display_result("matrix/svg_view", pars)