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Source code for tvb.adapters.visualizers.pca

# -*- 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.
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# 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)
#
#

"""
A displayer for the principal components analysis.

.. moduleauthor:: Marmaduke Woodman <marmaduke.woodman@univ-amu.fr>

"""
import json
from tvb.adapters.visualizers.time_series import ABCSpaceDisplayer
from tvb.adapters.datatypes.db.mode_decompositions import PrincipalComponentsIndex
from tvb.core.adapters.abcdisplayer import URLGenerator
from tvb.core.adapters.abcadapter import ABCAdapterForm
from tvb.core.neotraits.forms import TraitDataTypeSelectField
from tvb.core.neotraits.view_model import ViewModel, DataTypeGidAttr
from tvb.datatypes.mode_decompositions import PrincipalComponents


[docs]class PCAModel(ViewModel): pca = DataTypeGidAttr( linked_datatype=PrincipalComponents, label='Principal component analysis:' )
[docs]class PCAForm(ABCAdapterForm): def __init__(self, prefix='', project_id=None): super(PCAForm, self).__init__(prefix, project_id) self.pca = TraitDataTypeSelectField(PCAModel.pca, self, name='pca', conditions=self.get_filters()) @staticmethod
[docs] def get_view_model(): return PCAModel
@staticmethod
[docs] def get_input_name(): return 'pca'
@staticmethod
[docs] def get_filters(): return None
@staticmethod
[docs] def get_required_datatype(): return PrincipalComponentsIndex
[docs]class PCA(ABCSpaceDisplayer): _ui_name = "Principal Components Analysis Visualizer"
[docs] def get_form_class(self): return PCAForm
[docs] def get_required_memory_size(self, view_model): # type: (PCAModel) -> int """Return required memory. Here, it's unknown/insignificant.""" return -1
[docs] def launch(self, view_model): # type: (PCAModel) -> dict """Construct data for visualization and launch it.""" ts_h5_class, ts_h5_path = self._load_h5_of_gid(view_model.pca.hex) with ts_h5_class(ts_h5_path) as ts_h5: source_gid = ts_h5.source.load() source_h5_class, source_h5_path = self._load_h5_of_gid(source_gid.hex) with source_h5_class(source_h5_path) as source_h5: labels_data = self.get_space_labels(source_h5) fractions_update_url = URLGenerator.build_h5_url(view_model.pca, 'read_fractions_data') weights_update_url = URLGenerator.build_h5_url(view_model.pca, 'read_weights_data') return self.build_display_result("pca/view", dict(labels_data=json.dumps(labels_data), fractions_update_url=fractions_update_url, weights_update_url=weights_update_url))
[docs] def generate_preview(self, pca, figure_size=None): return self.launch(pca)