def __init__(self,
variables_of_interest_indexes={},
prefix='',
project_id=None):
super(EEGMonitorForm, self).__init__(variables_of_interest_indexes,
prefix, project_id)
sensor_filter = FilterChain(
fields=[FilterChain.datatype + '.sensors_type'],
operations=["=="],
values=[EEG_S])
projection_filter = FilterChain(
fields=[FilterChain.datatype + '.projection_type'],
operations=["=="],
values=[EEG_P])
self.projection = TraitDataTypeSelectField(
EEGViewModel.projection,
self,
name='projection',
conditions=projection_filter)
self.reference = ScalarField(EEG.reference, self)
self.sensors = TraitDataTypeSelectField(EEGViewModel.sensors,
self,
name='sensors',
conditions=sensor_filter)
self.sigma = ScalarField(EEG.sigma, self)
def __init__(self, prefix='', project_id=None):
super(PearsonCorrelationCoefficientAdapterForm, self).__init__(prefix, project_id)
self.time_series = TraitDataTypeSelectField(PearsonCorrelationCoefficientAdapterModel.time_series, self,
name=self.get_input_name(), conditions=self.get_filters(),
has_all_option=True)
self.t_start = ScalarField(PearsonCorrelationCoefficientAdapterModel.t_start, self)
self.t_end = ScalarField(PearsonCorrelationCoefficientAdapterModel.t_end, self)
def __init__(self,
session_stored_simulator=None,
prefix='',
project_id=None):
super(EEGMonitorForm, self).__init__(session_stored_simulator, prefix,
project_id)
sensor_filter = FilterChain(
fields=[FilterChain.datatype + '.sensors_type'],
operations=["=="],
values=[SensorTypes.TYPE_EEG.value])
projection_filter = FilterChain(
fields=[FilterChain.datatype + '.projection_type'],
operations=["=="],
values=[ProjectionsType.EEG.value])
self.projection = TraitDataTypeSelectField(
EEGViewModel.projection,
self,
name='projection',
conditions=projection_filter)
self.reference = ScalarField(EEG.reference, self)
self.sensors = TraitDataTypeSelectField(EEGViewModel.sensors,
self,
name='sensors',
conditions=sensor_filter)
self.sigma = ScalarField(EEG.sigma, self)
def __init__(self, prefix='', project_id=None):
super(FFTAdapterForm, self).__init__(prefix, project_id)
self.time_series = TraitDataTypeSelectField(FFTAdapterModel.time_series, self, name='time_series',
conditions=self.get_filters(), has_all_option=True)
self.segment_length = ScalarField(FFTAdapterModel.segment_length, self)
self.window_function = SelectField(FFTAdapterModel.window_function, self)
self.detrend = ScalarField(FFTAdapterModel.detrend, self)
def __init__(self,
variables_of_interest_indexes,
prefix='',
project_id=None):
super(EEGMonitorForm, self).__init__(variables_of_interest_indexes,
prefix, project_id)
sensor_filter = FilterChain(
fields=[FilterChain.datatype + '.sensors_type'],
operations=["=="],
values=[EEG_S])
projection_filter = FilterChain(
fields=[FilterChain.datatype + '.projection_type'],
operations=["=="],
values=[EEG_P])
self.projection = DataTypeSelectField(ProjectionMatrixIndex,
self,
name='projection',
required=True,
label=EEG.projection.label,
doc=EEG.projection.label,
conditions=projection_filter)
self.reference = ScalarField(EEG.reference, self)
self.sensors = DataTypeSelectField(SensorsIndex,
self,
name='sensors',
required=True,
label=EEG.sensors.label,
doc=EEG.sensors.doc,
conditions=sensor_filter)
self.sigma = ScalarField(EEG.sigma, self)
def __init__(self, equation_choices, prefix='', project_id=None):
super(LocalConnectivityCreatorForm, self).__init__(prefix, project_id)
filter_for_cortical = FilterChain(
fields=[FilterChain.datatype + '.surface_type'],
operations=["=="],
values=[CORTICAL])
self.surface = TraitDataTypeSelectField(
LocalConnectivityCreatorModel.surface,
self,
name=self.get_input_name(),
conditions=filter_for_cortical)
self.spatial = SelectField(LocalConnectivityCreatorModel.equation,
self,
name='spatial',
choices=equation_choices,
display_none_choice=False)
self.spatial_params = FormField(GaussianEquationForm,
self,
name=self.NAME_EQUATION_PARAMS_DIV,
label='Equation parameters')
self.cutoff = ScalarField(LocalConnectivityCreatorModel.cutoff, self)
self.display_name = ScalarField(
LocalConnectivityCreatorModel.display_name,
self,
name='display_name')
def __init__(self, equation_choices, prefix='', project_id=None):
super(LocalConnectivityCreatorForm, self).__init__(prefix, project_id)
self.surface = TraitDataTypeSelectField(LocalConnectivityCreatorModel.surface, self, name=self.get_input_name(),
conditions=self.get_filters())
self.spatial = SelectField(LocalConnectivityCreatorModel.equation, self, name='spatial',
choices=equation_choices, display_none_choice=False, subform=GaussianEquationForm)
self.cutoff = ScalarField(LocalConnectivityCreatorModel.cutoff, self)
self.display_name = ScalarField(LocalConnectivityCreatorModel.display_name, self, name='display_name')
def __init__(self, prefix=''):
super(PreSigmoidalCouplingForm, self).__init__(prefix)
self.H = ArrayField(PreSigmoidal.H, self)
self.Q = ArrayField(PreSigmoidal.Q, self)
self.G = ArrayField(PreSigmoidal.G, self)
self.P = ArrayField(PreSigmoidal.P, self)
self.theta = ArrayField(PreSigmoidal.theta, self)
self.dynamic = ScalarField(PreSigmoidal.dynamic, self)
self.globalT = ScalarField(PreSigmoidal.globalT, self)
def __init__(self, prefix='', project_id=None):
super(BalloonModelAdapterForm, self).__init__(prefix, project_id)
self.time_series = TraitDataTypeSelectField(BalloonModelAdapterModel.time_series, self,
name=self.get_input_name(),
conditions=self.get_filters(), has_all_option=True)
self.dt = ScalarField(BalloonModelAdapterModel.dt, self)
self.neural_input_transformation = ScalarField(BalloonModelAdapterModel.neural_input_transformation, self)
self.bold_model = ScalarField(BalloonModelAdapterModel.bold_model, self)
self.RBM = ScalarField(BalloonModelAdapterModel.RBM, self)
def __init__(self, prefix='', project_id=None):
super(AllenConnectomeBuilderForm, self).__init__(prefix, project_id)
self.resolution = SelectField(AllenConnectModel.resolution,
self,
choices=RESOLUTION_OPTIONS)
self.weighting = SelectField(AllenConnectModel.weighting,
self,
choices=WEIGHTS_OPTIONS)
self.inj_f_thresh = ScalarField(AllenConnectModel.inj_f_thresh, self)
self.vol_thresh = ScalarField(AllenConnectModel.vol_thresh, self)
def __init__(self, prefix='', project_id=None):
super(FCDAdapterForm, self).__init__(prefix, project_id)
self.time_series = TraitDataTypeSelectField(
FCDAdapterModel.time_series,
self,
name=self.get_input_name(),
conditions=self.get_filters(),
has_all_option=True)
self.sw = ScalarField(FCDAdapterModel.sw, self)
self.sp = ScalarField(FCDAdapterModel.sp, self)
def __init__(self, prefix='', project_id=None):
super(TimeseriesMetricsAdapterForm, self).__init__(prefix, project_id)
self.time_series = TraitDataTypeSelectField(
TimeseriesMetricsAdapterModel.time_series,
self,
name="time_series")
self.start_point = ScalarField(
TimeseriesMetricsAdapterModel.start_point, self)
self.segment = ScalarField(TimeseriesMetricsAdapterModel.segment, self)
self.algorithms = MultiSelectField(
TimeseriesMetricsAdapterModel.algorithms, self, name="algorithms")
def __init__(self, prefix='', project_id=None):
super(LocalConnectivityCreatorForm, self).__init__(prefix, project_id)
self.surface = DataTypeSelectField(
self.get_required_datatype(),
self,
name=self.get_input_name(),
required=LocalConnectivity.surface.required,
label=LocalConnectivity.surface.label,
doc=LocalConnectivity.surface.doc)
self.equation = ScalarField(LocalConnectivity.equation, self)
self.cutoff = ScalarField(LocalConnectivity.cutoff, self)
def __init__(self, prefix='', project_id=None):
super(ContinuousWaveletTransformAdapterForm, self).__init__(prefix, project_id)
self.time_series = TraitDataTypeSelectField(WaveletAdapterModel.time_series, self,
name=self.get_input_name(), conditions=self.get_filters(),
has_all_option=True)
self.mother = ScalarField(ContinuousWaveletTransform.mother, self)
self.sample_period = ScalarField(ContinuousWaveletTransform.sample_period, self)
self.normalisation = ScalarField(ContinuousWaveletTransform.normalisation, self)
self.q_ratio = ScalarField(ContinuousWaveletTransform.q_ratio, self)
self.frequencies = FormField(RangeForm, self, name='frequencies',
label=ContinuousWaveletTransform.frequencies.label,
doc=ContinuousWaveletTransform.frequencies.doc)
def __init__(self,
prefix='',
project_id=None,
default_simulation_name="simulation_1"):
super(SimulatorFinalFragment, self).__init__(prefix, project_id)
self.simulation_length = ScalarField(Simulator.simulation_length, self)
self.simulation_name = ScalarField(Attr(
str,
doc='Name for the current simulation configuration',
default=default_simulation_name,
label='Simulation name'),
self,
name='input_simulation_name_id')
def __init__(self, prefix='', project_id=None):
super(FCDAdapterForm, self).__init__(prefix, project_id)
self.time_series = DataTypeSelectField(
self.get_required_datatype(),
self,
name=self.get_input_name(),
required=True,
label=FcdCalculator.time_series.label,
doc=FcdCalculator.time_series.doc,
conditions=self.get_filters(),
has_all_option=True)
self.sw = ScalarField(FcdCalculator.sw, self)
self.sp = ScalarField(FcdCalculator.sp, self)
def __init__(self, prefix='', project_id=None):
super(FFTAdapterForm, self).__init__(prefix, project_id)
self.time_series = DataTypeSelectField(self.get_required_datatype(),
self,
name='time_series',
required=True,
label=fft.FFT.time_series.label,
doc=fft.FFT.time_series.doc,
conditions=self.get_filters(),
has_all_option=True)
self.segment_length = ScalarField(fft.FFT.segment_length, self)
self.window_function = ScalarField(fft.FFT.window_function, self)
self.detrend = ScalarField(fft.FFT.detrend, self)
def __init__(self, prefix='', project_id=None):
super(PearsonCorrelationCoefficientAdapterForm,
self).__init__(prefix, project_id)
self.time_series = DataTypeSelectField(
self.get_required_datatype(),
self,
name=self.get_input_name(),
required=True,
label=CorrelationCoefficient.time_series.label,
doc=CorrelationCoefficient.time_series.doc,
conditions=self.get_filters(),
has_all_option=True)
self.t_start = ScalarField(CorrelationCoefficient.t_start, self)
self.t_end = ScalarField(CorrelationCoefficient.t_end, self)
def __init__(self, prefix='', project_id=None):
super(ICAAdapterForm, self).__init__(prefix, project_id)
self.time_series = DataTypeSelectField(self.get_required_datatype(), self, name='time_series', required=True,
label=FastICA.time_series.label, doc=FastICA.time_series.doc,
conditions=self.get_filters(), has_all_option=True)
self.n_components = ScalarField(FastICA.n_components, self)
self.project_id = project_id
def __init__(self, prefix=''):
super(BarAndBazForm, self).__init__(prefix)
self.bar = FormField(BarForm, self, 'bar', label='bar') # BarAndBaz.bar
self.baz = FormField(BazForm, self, 'baz', label='baaz')
# not from trait
self.happy = ScalarField(Attr(bool, label='clap'), self, 'clasp')
self.array = ArrayField(BarAndBaz.array, self)
def __init__(self, variables_of_interest_indexes, prefix='', project_id=None):
super(MonitorForm, self).__init__(prefix)
self.project_id = project_id
self.period = ScalarField(Monitor.period, self)
self.variables_of_interest_indexes = variables_of_interest_indexes
self.variables_of_interest = MultiSelectField(List(of=str, label='Model Variables to watch',
choices=tuple(self.variables_of_interest_indexes.keys())),
self, name='variables_of_interest')
def __init__(self, prefix='', project_id=None):
super(TimeseriesMetricsAdapterForm, self).__init__(prefix, project_id)
self.time_series = DataTypeSelectField(self.get_required_datatype(), self, name="time_series",
required=True, label=BaseTimeseriesMetricAlgorithm.time_series.label,
doc = BaseTimeseriesMetricAlgorithm.time_series.doc)
self.start_point = ScalarField(BaseTimeseriesMetricAlgorithm.start_point, self)
self.segment = ScalarField(BaseTimeseriesMetricAlgorithm.segment, self)
algo_names = list(ALGORITHMS)
algo_names.sort()
choices = OrderedDict()
for name in algo_names:
choices[name] = name
self.algorithms = MultipleSelectField(choices, self, name="algorithms", include_none=False,
label='Selected metrics to be applied',
doc='The selected algorithms will all be applied on the input TimeSeries')
def __init__(self, variables_of_interest_indexes, prefix='', project_id=None):
super(BoldMonitorForm, self).__init__(variables_of_interest_indexes, prefix, project_id)
self.hrf_kernel_choices = get_ui_name_to_monitor_equation_dict()
default_hrf_kernel = list(self.hrf_kernel_choices.values())[0]
self.period = ScalarField(Bold.period, self)
self.hrf_kernel = SelectField(Attr(HRFKernelEquation, label='Equation', default=default_hrf_kernel),
self, name='hrf_kernel', choices=self.hrf_kernel_choices)
def __init__(self,
session_stored_simulator=None,
prefix='',
project_id=None):
super(SpatialAverageMonitorForm,
self).__init__(session_stored_simulator, prefix, project_id)
self.spatial_mask = ArrayField(SpatialAverage.spatial_mask, self)
self.default_mask = ScalarField(SpatialAverage.default_mask, self)
def __init__(self, prefix='', project_id=None):
super(SimulatorFinalFragment, self).__init__(prefix, project_id)
self.simulation_name = ScalarField(Attr(
str,
doc='Name for the current simulation configuration',
label='Simulation name'),
self,
name='input-simulation-name-id')
def __init__(self,
variables_of_interest_indexes={},
prefix='',
project_id=None):
super(SpatialAverageMonitorForm,
self).__init__(variables_of_interest_indexes, prefix, project_id)
self.spatial_mask = ArrayField(SpatialAverage.spatial_mask, self)
self.default_mask = ScalarField(SpatialAverage.default_mask, self)
def __init__(self, prefix='', project_id=None):
super(NodeCoherenceForm, self).__init__(prefix, project_id)
self.time_series = TraitDataTypeSelectField(
NodeCoherenceModel.time_series,
self,
name=self.get_input_name(),
conditions=self.get_filters(),
has_all_option=True)
self.nfft = ScalarField(NodeCoherenceModel.nfft, self)
def __init__(self, prefix='', project_id=None):
super(BoldMonitorForm, self).__init__(prefix, project_id)
self.period = ScalarField(Bold.period, self)
self.equation_choices = get_ui_name_to_monitor_equation_dict()
self.equation = SimpleSelectField(self.equation_choices,
self,
name='equation',
required=True,
label='Equation')
def __init__(self, prefix='', project_id=None):
super(ICAAdapterForm, self).__init__(prefix, project_id)
self.time_series = TraitDataTypeSelectField(
ICAAdapterModel.time_series,
self,
name='time_series',
conditions=self.get_filters(),
has_all_option=True)
self.n_components = ScalarField(ICAAdapterModel.n_components, self)
self.project_id = project_id
def __init__(self, prefix='', project_id=None):
super(NodeCoherenceForm, self).__init__(prefix, project_id)
self.time_series = DataTypeSelectField(
self.get_required_datatype(),
self,
name=self.get_input_name(),
required=True,
label=NodeCoherence.time_series.label,
doc=NodeCoherence.time_series.doc,
conditions=self.get_filters(),
has_all_option=True)
self.nfft = ScalarField(NodeCoherence.nfft, self)
