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Source code for tvb.adapters.visualizers.pearson_edge_bundle

# -*- coding: utf-8 -*-
#
#
# TheVirtualBrain-Framework Package. This package holds all Data Management, and
# Web-UI helpful to run brain-simulations. To use it, you also need do download
# TheVirtualBrain-Scientific Package (for simulators). See content of the
# documentation-folder for more details. See also http://www.thevirtualbrain.org
#
# (c) 2012-2020, Baycrest Centre for Geriatric Care ("Baycrest") and others
#
# This program is free software: you can redistribute it and/or modify it under the
# terms of the GNU General Public License as published by the Free Software Foundation,
# either version 3 of the License, or (at your option) any later version.
# This program is distributed in the hope that it will be useful, but WITHOUT ANY
# WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A
# PARTICULAR PURPOSE.  See the GNU General Public License for more details.
# You should have received a copy of the GNU General Public License along with this
# program.  If not, see <http://www.gnu.org/licenses/>.
#
#
#   CITATION:
# When using The Virtual Brain for scientific publications, please cite it as follows:
#
#   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.
#   Frontiers in Neuroinformatics (7:10. doi: 10.3389/fninf.2013.00010)
#
#


import json
import numpy
from tvb.adapters.visualizers.pearson_cross_correlation import PearsonCorrelationCoefficientVisualizerForm, \
    PearsonCorrelationCoefficientVisualizerModel
from tvb.adapters.visualizers.time_series import ABCSpaceDisplayer
from tvb.core.adapters.abcdisplayer import URLGenerator
from tvb.datatypes.graph import CorrelationCoefficients


[docs]class PearsonEdgeBundle(ABCSpaceDisplayer): """ Viewer for Pearson CorrelationCoefficients. Very similar to the CrossCorrelationVisualizer - this one done with Matplotlib """ _ui_name = "Pearson Edge Bundle" _ui_subsection = "correlation_pearson_edge"
[docs] def get_form_class(self): return PearsonCorrelationCoefficientVisualizerForm
[docs] def get_required_memory_size(self, view_model): # type: (PearsonCorrelationCoefficientVisualizerModel) -> numpy.ndarray """Return required memory.""" datatype_index = self.load_entity_by_gid(view_model.datatype) input_size = (datatype_index.data_length_1d, datatype_index.data_length_2d, datatype_index.data_length_3d, datatype_index.data_length_4d) return numpy.prod(input_size) * 8.0
[docs] def launch(self, view_model): # type: (PearsonCorrelationCoefficientVisualizerModel) -> dict """Construct data for visualization and launch it.""" datatype_h5_class, datatype_h5_path = self._load_h5_of_gid(view_model.datatype.hex) with datatype_h5_class(datatype_h5_path) as datatype_h5: matrix_shape = datatype_h5.array_data.shape[0:2] ts_gid = datatype_h5.source.load() ts_index = self.load_entity_by_gid(ts_gid) state_list = ts_index.get_labels_for_dimension(1) mode_list = list(range(ts_index.data_length_4d)) ts_h5_class, ts_h5_path = self._load_h5_of_gid(ts_index.gid) with ts_h5_class(ts_h5_path) as ts_h5: labels = self.get_space_labels(ts_h5) if not labels: labels = None pars = dict(matrix_labels=json.dumps(labels), matrix_shape=json.dumps(matrix_shape), viewer_title='Pearson Edge Bundle', url_base=URLGenerator.build_h5_url(view_model.datatype.hex, 'get_correlation_data', flatten="True", parameter=''), state_variable=0, mode=mode_list[0], state_list=state_list, mode_list=mode_list, pearson_min=CorrelationCoefficients.PEARSON_MIN, pearson_max=CorrelationCoefficients.PEARSON_MAX, thresh=0.5 ) return self.build_display_result("pearson_edge_bundle/view", pars)