Source code for tvb.adapters.forms.noise_forms

# -*- coding: utf-8 -*-
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# TheVirtualBrain-Framework Package. This package holds all Data Management, and
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from tvb.adapters.forms.equation_forms import get_form_for_equation, TemporalEquationsEnum
from tvb.adapters.forms.form_with_ranges import FormWithRanges
from tvb.basic.neotraits.api import EnumAttr, Range
from tvb.core.entities.file.simulator.view_model import NoiseViewModel, AdditiveNoiseViewModel, \
    MultiplicativeNoiseViewModel
from tvb.core.entities.transient.range_parameter import RangeParameter
from tvb.core.neotraits.forms import ArrayField, SelectField, FloatField, IntField


[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] @staticmethod def get_subform_key(): return 'NOISE'
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, prefix): 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(prefix) self.ensure_correct_prefix_for_param_name(ntau_range_param, prefix) 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.nsig = ArrayField(MultiplicativeNoiseViewModel.nsig) self.equation = SelectField(EnumAttr(label='Equation', default=TemporalEquationsEnum.LINEAR), name='equation', subform=get_form_for_equation(TemporalEquationsEnum.LINEAR.value))
[docs] def fill_trait(self, datatype): super(MultiplicativeNoiseForm, self).fill_trait(datatype) datatype.nsig = self.nsig.data if type(datatype.b) != self.equation.data.value: datatype.b = self.equation.data.instance
[docs] def fill_from_trait(self, trait): # type: (NoiseViewModel) -> None super(MultiplicativeNoiseForm, self).fill_from_trait(trait) self.equation.data = type(trait.b)