Source code for tvb.adapters.simulator.noise_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 do download
# TheVirtualBrain-Scientific Package (for simulators). See content of the
# documentation-folder for more details. See also
# (c) 2012-2022, 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,
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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
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# 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)
from tvb.adapters.simulator.equation_forms import get_form_for_equation
from tvb.adapters.simulator.form_with_ranges import FormWithRanges
from tvb.adapters.simulator.subforms_mapping import SubformsEnum, get_ui_name_to_equation_dict
from tvb.basic.neotraits.api import Attr, Range
from tvb.core.entities.file.simulator.view_model import NoiseViewModel, AdditiveNoiseViewModel, \
from tvb.core.entities.transient.range_parameter import RangeParameter
from tvb.core.neotraits.forms import ArrayField, SelectField, FloatField, IntField
from tvb.datatypes.equations import Equation

[docs]def get_form_for_noise(noise_class): noise_class_to_form = { AdditiveNoiseViewModel: AdditiveNoiseForm, MultiplicativeNoiseViewModel: MultiplicativeNoiseForm, } return noise_class_to_form.get(noise_class)
[docs]class NoiseForm(FormWithRanges):
[docs] def get_subform_key(self): return
def __init__(self): super(NoiseForm, self).__init__() self.ntau = FloatField(NoiseViewModel.ntau) self.noise_seed = IntField(NoiseViewModel.noise_seed)
[docs]class AdditiveNoiseForm(NoiseForm): def __init__(self): super(AdditiveNoiseForm, self).__init__() self.nsig = ArrayField(AdditiveNoiseViewModel.nsig)
[docs] def get_range_parameters(self): ntau_range_param = RangeParameter(NoiseViewModel.ntau.field_name, float, Range(lo=0.0, hi=20.0, step=1.0)) params_with_range_defined = super(NoiseForm, self).get_range_parameters() params_with_range_defined.append(ntau_range_param) return params_with_range_defined
[docs]class MultiplicativeNoiseForm(NoiseForm): def __init__(self): super(MultiplicativeNoiseForm, self).__init__() self.equation_choices = get_ui_name_to_equation_dict() default_equation = list(self.equation_choices.values())[0] self.nsig = ArrayField(MultiplicativeNoiseViewModel.nsig) self.equation = SelectField(Attr(Equation, label='Equation', default=default_equation), name='equation', choices=self.equation_choices, subform=get_form_for_equation(default_equation))
[docs] def fill_trait(self, datatype): super(MultiplicativeNoiseForm, self).fill_trait(datatype) datatype.nsig = if type(datatype.b) != datatype.b =
[docs] def fill_from_trait(self, trait): # type: (NoiseViewModel) -> None super(MultiplicativeNoiseForm, self).fill_from_trait(trait) = trait.b.__class__