Source code for tvb.adapters.forms.integrator_forms

# -*- 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
# (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 <>.
# When using The Virtual Brain for scientific publications, please cite it as explained here:
from tvb.adapters.forms.noise_forms import get_form_for_noise
from tvb.basic.neotraits.api import TupleEnum, EnumAttr
from tvb.core.entities.file.simulator.view_model import HeunDeterministicViewModel, HeunStochasticViewModel, \
    EulerDeterministicViewModel, EulerStochasticViewModel, RungeKutta4thOrderDeterministicViewModel, IdentityViewModel, \
    VODEViewModel, VODEStochasticViewModel, Dopri5ViewModel, Dopri5StochasticViewModel, Dop853ViewModel, \
    Dop853StochasticViewModel, IntegratorViewModel, AdditiveNoiseViewModel, MultiplicativeNoiseViewModel
from tvb.core.entities.file.simulator.view_model import IntegratorStochasticViewModel
from tvb.core.neotraits.forms import Form, SelectField, FloatField

[docs] def get_integrator_name_list(): return ['Heun', 'Stochastic Heun', 'Euler', 'Euler-Maruyama', 'Runge-Kutta 4th order', 'Difference equation', 'Variable-order Adams / BDF', 'Stochastic variable-order Adams / BDF', 'Dormand-Prince, order(4, 5)', 'Stochastic Dormand-Prince, order (4, 5)', 'Dormand-Prince, order 8 (5, 3)', 'Stochastic Dormand-Prince, order 8 (5, 3)']
[docs] def get_integrator_to_form_dict(): integrator_class_to_form = { HeunDeterministicViewModel: IntegratorForm, HeunStochasticViewModel: IntegratorStochasticForm, EulerDeterministicViewModel: IntegratorForm, EulerStochasticViewModel: IntegratorStochasticForm, RungeKutta4thOrderDeterministicViewModel: IntegratorForm, IdentityViewModel: IntegratorForm, VODEViewModel: IntegratorForm, VODEStochasticViewModel: IntegratorStochasticForm, Dopri5ViewModel: IntegratorForm, Dopri5StochasticViewModel: IntegratorStochasticForm, Dop853ViewModel: IntegratorForm, Dop853StochasticViewModel: IntegratorStochasticForm } return integrator_class_to_form
[docs] def get_form_for_integrator(integrator_class): return get_integrator_to_form_dict().get(integrator_class)
[docs] class NoiseTypesEnum(TupleEnum): ADDITIVE = (AdditiveNoiseViewModel, "Additive") MULTIPLICATIVE = (MultiplicativeNoiseViewModel, "Multiplicative")
[docs] class IntegratorForm(Form):
[docs] @staticmethod def get_subform_key(): return 'INTEGRATOR'
def __init__(self, is_dt_disabled=False): super(IntegratorForm, self).__init__() self.is_dt_disabled = is_dt_disabled self.dt = FloatField(IntegratorViewModel.dt)
[docs] def fill_from_trait(self, trait): # type: (IntegratorViewModel) -> None super(IntegratorForm, self).fill_from_trait(trait) if self.is_dt_disabled: self.dt.disabled = True
[docs] class IntegratorStochasticForm(IntegratorForm): template = 'form_fields/select_field.html' def __init__(self, is_dt_disabled=False): super(IntegratorStochasticForm, self).__init__(is_dt_disabled) self.noise = SelectField(EnumAttr(label='Noise', default=NoiseTypesEnum.ADDITIVE), name='noise', subform=get_form_for_noise(NoiseTypesEnum.ADDITIVE.value))
[docs] def fill_trait(self, datatype): super(IntegratorStochasticForm, self).fill_trait(datatype) if and type(datatype.noise) != datatype.noise =
[docs] def fill_from_trait(self, trait): # type: (IntegratorStochasticViewModel) -> None super(IntegratorStochasticForm, self).fill_from_trait(trait) = trait.noise.__class__