Source code for tvb.adapters.visualizers.cross_correlation

# -*- coding: utf-8 -*-
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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


class CrossCorrelationVisualizerModel(ViewModel):
    datatype = DataTypeGidAttr(
        linked_datatype=CrossCorrelation,
        label='Cross correlation'
    )


class CrossCorrelationVisualizerForm(ABCAdapterForm):

    def __init__(self):
        super(CrossCorrelationVisualizerForm, self).__init__()
        self.datatype = TraitDataTypeSelectField(CrossCorrelationVisualizerModel.datatype, name='datatype')

    @staticmethod
    def get_view_model():
        return CrossCorrelationVisualizerModel

    @staticmethod
    def get_required_datatype():
        return CrossCorrelationIndex

    @staticmethod
    def get_input_name():
        return 'datatype'

    @staticmethod
    def get_filters():
        return None


class CrossCorrelationVisualizer(ABCMappedArraySVGVisualizer):
    _ui_name = "Cross Correlation Visualizer"
    _ui_subsection = "correlation"

    def get_form_class(self):
        return CrossCorrelationVisualizerForm

    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)