Source code for tvb.adapters.visualizers.cross_coherence
# -*- coding: utf-8 -*-
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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 CrossCoherenceVisualizer(ABCMappedArraySVGVisualizer):
_ui_name = "Cross Coherence Visualizer"
_ui_subsection = "coherence"
[docs]
def launch(self, view_model):
# type: (CrossCoherenceVisualizerModel) -> dict
"""Construct data for visualization and launch it."""
with h5.h5_file_for_gid(view_model.datatype) 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)