The Virtual Brain Project

Source code for tvb.adapters.visualizers.ica

# -*- 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
# (c) 2012-2017, 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 <>.
# 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)

A matrix displayer for the Independent Component Analysis.
It displays the mixing matrix of siae n_features x n_components

.. moduleauthor:: Paula Sanz Leon <Paula@tvb.invalid>


from tvb.adapters.visualizers.matrix_viewer import MappedArraySVGVisualizerMixin
from tvb.core.adapters.abcdisplayer import ABCDisplayer
from tvb.datatypes.mode_decompositions import IndependentComponents
from tvb.basic.logger.builder import get_logger

LOG = get_logger(__name__)

[docs]class ICA(MappedArraySVGVisualizerMixin, ABCDisplayer): _ui_name = "Independent Components Analysis Visualizer"
[docs] def get_input_tree(self): """Inform caller of the data we need""" return [{"name": "datatype", "type": IndependentComponents, "label": "Independent component analysis:", "required": True}, {"name": "i_svar", "type": 'int', 'default': 0, "label": "Index of state variable (defaults to first state variable)",}, {"name": "i_mode", "type": 'int', 'default': 0, "label": "Index of mode (defaults to first mode)",}]
[docs] def launch(self, datatype, i_svar=0, i_mode=0): """Construct data for visualization and launch it.""" # get data from IndependentComponents datatype, convert to json # HACK: dump only a 2D array unmixing_matrix = datatype.get_data('unmixing_matrix') prewhitening_matrix = datatype.get_data('prewhitening_matrix') unmixing_matrix = unmixing_matrix[..., i_svar, i_mode] prewhitening_matrix = prewhitening_matrix[..., i_svar, i_mode] Cinv = pars = self.compute_params(Cinv, 'ICA region contribution', '(Ellipsis, %d, 0)' % (i_svar)) return self.build_display_result("matrix/svg_view", pars)