# -*- 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 to download
# TheVirtualBrain-Scientific Package (for simulators). See content of the
# documentation-folder for more details. See also http://www.thevirtualbrain.org
#
# (c) 2012-2023, 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 explained here:
# https://www.thevirtualbrain.org/tvb/zwei/neuroscience-publications
#
#
"""
.. moduleauthor:: Lia Domide <lia.domide@codemart.ro>
"""
import numpy
from tvb.basic.neotraits.api import NArray, Attr, HasTraits
from tvb.core.neotraits.h5 import H5File, DataSet, Reference, STORE_STRING
from tvb.datatypes.connectivity import Connectivity
ANNOTATION_DTYPE = numpy.dtype([('id', 'i'),
('parent_id', 'i'),
('parent_left', 'i'),
('parent_right', 'i'),
('relation', STORE_STRING), # S16
('label', STORE_STRING), # S256
('definition', STORE_STRING), # S1024
('synonym', STORE_STRING), # S2048
('uri', STORE_STRING), # S256
('synonym_tvb_left', 'i'),
('synonym_tvb_right', 'i')
])
[docs]class ConnectivityAnnotations(HasTraits):
"""
Ontology annotations for a Connectivity.
"""
connectivity = Attr(field_type=Connectivity)
"""
Holds a flatten form for the annotations for a full connectivity.
Each region in the connectivity can have None, or a tree of AnnotationTerms
To be stored in a compound DS in H5.
"""
region_annotations = NArray(
default=numpy.array([], dtype=ANNOTATION_DTYPE), dtype=ANNOTATION_DTYPE,
label="Region Annotations",
doc="""Flat tree of annotations for every connectivity region.""")
[docs] def set_annotations(self, annotation_terms):
annotations = [ann.to_tuple() for ann in annotation_terms]
annotations = numpy.array(annotations, dtype=ANNOTATION_DTYPE)
self.region_annotations = annotations
[docs] def get_activation_patterns(self):
"""
Group Annotation terms by URI.
:return: map {brco_id: list of TVB regions IDs in which the same term is being subclass}
"""
map_by_uri = {}
for ann in self.region_annotations:
ann_uri = ann[8]
left, right = str(ann[2]), str(ann[3])
if ann_uri not in map_by_uri:
map_by_uri[ann_uri] = [left, right]
else:
if left not in map_by_uri[ann_uri]:
map_by_uri[ann_uri].append(left)
if right not in map_by_uri[ann_uri]:
map_by_uri[ann_uri].append(right)
map_by_brco_id = {}
for ann in self.region_annotations:
ann_uri = ann[8]
ann_id = ann[0]
map_by_brco_id[str(ann_id)] = map_by_uri[ann_uri]
return map_by_brco_id
[docs]class ConnectivityAnnotationsH5(H5File):
"""
Ontology annotations for a Connectivity.
"""
def __init__(self, path):
super(ConnectivityAnnotationsH5, self).__init__(path)
self.region_annotations = DataSet(ConnectivityAnnotations.region_annotations, self)
self.connectivity = Reference(ConnectivityAnnotations.connectivity, self)
[docs] def store(self, datatype, scalars_only=False, store_references=True):
# type: (ConnectivityAnnotations, bool, bool) -> None
super(ConnectivityAnnotationsH5, self).store(datatype, scalars_only, store_references)
