# -*- 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) 2012-2024, 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
#
#
import bct
from abc import abstractmethod
from tvb.adapters.datatypes.db.connectivity import ConnectivityIndex
from tvb.adapters.datatypes.db.graph import ConnectivityMeasureIndex
from tvb.adapters.datatypes.db.mapped_value import ValueWrapperIndex
from tvb.adapters.datatypes.h5.mapped_value_h5 import ValueWrapper
from tvb.core.adapters.abcadapter import ABCAdapterForm, ABCAdapter
from tvb.core.entities.filters.chain import FilterChain
from tvb.core.entities.model.model_operation import AlgorithmTransientGroup
from tvb.core.neotraits.forms import TraitDataTypeSelectField
from tvb.core.neotraits.view_model import ViewModel, DataTypeGidAttr
from tvb.datatypes.connectivity import Connectivity
from tvb.datatypes.graph import ConnectivityMeasure
BCT_GROUP_MODULARITY = AlgorithmTransientGroup("Modularity Algorithms", "Brain Connectivity Toolbox", "bct")
BCT_GROUP_DISTANCE = AlgorithmTransientGroup("Distance Algorithms", "Brain Connectivity Toolbox", "bctdistance")
LABEL_CONNECTIVITY_BINARY = "Binary (directed/undirected) connection matrix"
LABEL_CONN_WEIGHTED_DIRECTED = "Weighted directed connection matrix"
LABEL_CONN_WEIGHTED_UNDIRECTED = "Weighted undirected connection matrix"
[docs]
class BaseBCTModel(ViewModel):
connectivity = DataTypeGidAttr(
linked_datatype=Connectivity,
label='Connectivity',
)
[docs]
class BaseBCT(ABCAdapter):
"""
Interface between Brain Connectivity Toolbox of Olaf Sporns and TVB Framework.
"""
[docs]
def get_output(self):
return [ConnectivityMeasureIndex, ValueWrapperIndex]
[docs]
def get_required_memory_size(self, view_model):
# We do not know how much memory is needed.
return -1
[docs]
def get_required_disk_size(self, view_model):
return 0
[docs]
def get_connectivity(self, view_model):
return self.load_traited_by_gid(view_model.connectivity)
[docs]
def build_connectivity_measure(self, array_data, connectivity, title="", label_x="", label_y=""):
measure = ConnectivityMeasure()
measure.array_data = array_data
measure.connectivity = connectivity
measure.title = title
measure.label_x = label_x
measure.label_y = label_y
return self.store_complete(measure)
[docs]
def build_float_value_wrapper(self, result_value, title=""):
value = ValueWrapper()
value.data_value = str(float(result_value))
value.data_type = 'float'
value.data_name = title
return self.store_complete(value)
[docs]
def build_int_value_wrapper(self, result_int, title=""):
value = ValueWrapper()
value.data_value = str(int(result_int))
value.data_type = 'int'
value.data_name = title
return self.store_complete(value)
[docs]
@abstractmethod
def launch(self, view_model):
pass
[docs]
class BaseUndirected(BaseBCT):
"""
"""
[docs]
@abstractmethod
def launch(self, view_model):
pass
[docs]
class ModularityOCSM(BaseBCT):
"""
"""
_ui_group = BCT_GROUP_MODULARITY
_ui_name = "Compute optimal Community Structure and Modularity from a Directed (weighted or binary) connection " \
"matrix: "
_ui_description = bct.modularity_dir.__doc__
[docs]
def launch(self, view_model):
connectivity = self.get_connectivity(view_model)
result = bct.modularity_dir(connectivity.weights)
measure = self.build_connectivity_measure(result[0], connectivity, "Optimal Community Structure")
value = self.build_float_value_wrapper(result[1], title="Maximized Modularity")
return [measure, value]
[docs]
class ModularityOpCSMU(ModularityOCSM):
"""
"""
_ui_name = "Optimal Community Structure and Modularity (Undirected):"
_ui_description = bct.modularity_und.__doc__
[docs]
def launch(self, view_model):
connectivity = self.get_connectivity(view_model)
result = bct.modularity_und(connectivity.weights)
measure = self.build_connectivity_measure(result[0], connectivity, "Optimal Community Structure")
value = self.build_float_value_wrapper(result[1], title="Maximized Modularity")
return [measure, value]
DISTANCE_MATRIX_TITLE = "Distance matrix"
[docs]
class DistanceDBIN(BaseBCT):
"""
"""
_ui_group = BCT_GROUP_DISTANCE
_ui_name = "Distance binary matrix"
_ui_description = bct.distance_bin.__doc__
[docs]
def launch(self, view_model):
connectivity = self.get_connectivity(view_model)
result_arr = bct.distance_bin(connectivity.weights)
measure = self.build_connectivity_measure(result_arr, connectivity, DISTANCE_MATRIX_TITLE)
return [measure]
[docs]
class DistanceDWEI(DistanceDBIN):
"""
"""
_ui_name = "Distance weighted matrix over a Weighted (directed/undirected) connection matrix"
_ui_description = bct.distance_wei.__doc__
[docs]
def launch(self, view_model):
connectivity = self.get_connectivity(view_model)
result = bct.distance_wei(connectivity.weights)[0]
measure = self.build_connectivity_measure(result, connectivity, DISTANCE_MATRIX_TITLE)
return [measure]
[docs]
class DistanceRDM(DistanceDBIN):
"""
"""
_ui_name = "Reachability and distance matrices (Breadth-first search)"
_ui_description = bct.breadthdist.__doc__
[docs]
def launch(self, view_model):
connectivity = self.get_connectivity(view_model)
result = bct.breadthdist(connectivity.weights)
measure1 = self.build_connectivity_measure(result[0], connectivity, "Reachability matrix")
measure2 = self.build_connectivity_measure(result[1], connectivity, DISTANCE_MATRIX_TITLE)
return [measure1, measure2]
[docs]
class DistanceRDA(DistanceRDM):
"""
"""
_ui_name = "Reachability and distance matrices (Algebraic path count)"
_ui_description = bct.reachdist.__doc__
[docs]
def launch(self, view_model):
connectivity = self.get_connectivity(view_model)
result = bct.reachdist(connectivity.weights)
measure1 = self.build_connectivity_measure(result[0], connectivity, "Reachability matrix")
measure2 = self.build_connectivity_measure(result[1], connectivity, DISTANCE_MATRIX_TITLE)
return [measure1, measure2]
[docs]
class DistanceNETW(DistanceDBIN):
"""
"""
_ui_name = "Network walks"
_ui_description = bct.findwalks.__doc__
[docs]
def launch(self, view_model):
connectivity = self.get_connectivity(view_model)
result = bct.findwalks(connectivity.weights)
measure1 = self.build_connectivity_measure(result[0], connectivity, "3D matrix")
measure2 = self.build_connectivity_measure(result[2], connectivity, "Walk length distribution")
value = self.build_float_value_wrapper(result[1], title="Total number of walks found")
return [measure1, value, measure2]
