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Source code for tvb.adapters.visualizers.cross_coherence

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"""
A displayer for the cross coherence of a time series.

.. moduleauthor:: Marmaduke Woodman <marmaduke.woodman@univ-amu.fr>

"""

import json
from tvb.adapters.datatypes.db.spectral import CoherenceSpectrumIndex
from tvb.adapters.visualizers.matrix_viewer import ABCMappedArraySVGVisualizer
from tvb.core.adapters.abcadapter import ABCAdapterForm
from tvb.core.adapters.abcdisplayer import ABCDisplayer
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.spectral import CoherenceSpectrum


[docs]class CrossCoherenceVisualizerModel(ViewModel): datatype = DataTypeGidAttr( linked_datatype=CoherenceSpectrum, label='Coherence spectrum:' )
[docs]class CrossCoherenceVisualizerForm(ABCAdapterForm): def __init__(self, prefix='', project_id=None): super(CrossCoherenceVisualizerForm, self).__init__(prefix, project_id) self.datatype = TraitDataTypeSelectField(CrossCoherenceVisualizerModel.datatype, self, name='datatype', conditions=self.get_filters()) @staticmethod
[docs] def get_view_model(): return CrossCoherenceVisualizerModel
@staticmethod
[docs] def get_required_datatype(): return CoherenceSpectrumIndex
@staticmethod
[docs] def get_input_name(): return 'datatype'
@staticmethod
[docs] def get_filters(): return None
[docs]class CrossCoherenceVisualizer(ABCMappedArraySVGVisualizer): _ui_name = "Cross Coherence Visualizer" _ui_subsection = "coherence"
[docs] def get_form_class(self): return CrossCoherenceVisualizerForm
[docs] def launch(self, view_model): # type: (CrossCoherenceVisualizerModel) -> dict """Construct data for visualization and launch it.""" coherence_gid = view_model.datatype coherence_index = self.load_entity_by_gid(coherence_gid) with h5.h5_file_for_index(coherence_index) as datatype_h5: # get data from coherence datatype h5, convert to json frequency = ABCDisplayer.dump_with_precision(datatype_h5.frequency.load().flat) array_data = datatype_h5.array_data[:] params = self.compute_raw_matrix_params(array_data) params.update(frequency=frequency) params.update(matrix_strides=json.dumps([x / array_data.itemsize for x in array_data.strides])) return self.build_display_result("cross_coherence/view", params)