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


class CrossCoherenceVisualizerModel(ViewModel):
    datatype = DataTypeGidAttr(
        linked_datatype=CoherenceSpectrum,
        label='Coherence spectrum:'
    )


class CrossCoherenceVisualizerForm(ABCAdapterForm):

    def __init__(self):
        super(CrossCoherenceVisualizerForm, self).__init__()
        self.datatype = TraitDataTypeSelectField(CrossCoherenceVisualizerModel.datatype, name='datatype',
                                                 conditions=self.get_filters())

    @staticmethod
    def get_view_model():
        return CrossCoherenceVisualizerModel

    @staticmethod
    def get_required_datatype():
        return CoherenceSpectrumIndex

    @staticmethod
    def get_input_name():
        return 'datatype'

    @staticmethod
    def get_filters():
        return None


class CrossCoherenceVisualizer(ABCMappedArraySVGVisualizer):
    _ui_name = "Cross Coherence Visualizer"
    _ui_subsection = "coherence"

    def get_form_class(self):
        return CrossCoherenceVisualizerForm

    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)