def __init__(self, prefix='', project_id=None): super(ProjectionMatrixImporterForm, self).__init__(prefix, project_id) self.projection_file = TraitUploadField(ProjectionMatrixImporterModel.projection_file, ('.mat', '.npy'), self, name='projection_file') self.dataset_name = StrField(ProjectionMatrixImporterModel.dataset_name, self, name='dataset_name') surface_conditions = FilterChain(fields=[FilterChain.datatype + '.surface_type'], operations=['=='], values=['Cortical Surface']) self.surface = TraitDataTypeSelectField(ProjectionMatrixImporterModel.surface, self, name='surface', conditions=surface_conditions) self.sensors = TraitDataTypeSelectField(ProjectionMatrixImporterModel.sensors, self, name='sensors')
def __init__(self): super(RegionMappingImporterForm, self).__init__() self.mapping_file = TraitUploadField(RegionMappingImporterModel.mapping_file, ('.txt', '.zip', '.bz2'), 'mapping_file') surface_conditions = FilterChain(fields=[FilterChain.datatype + '.surface_type'], operations=['=='], values=[CORTICAL]) self.surface = TraitDataTypeSelectField(RegionMappingImporterModel.surface, name='surface', conditions=surface_conditions) self.connectivity = TraitDataTypeSelectField(RegionMappingImporterModel.connectivity, name='connectivity')
def __init__(self, project_id=None): super(BrainViewerForm, self).__init__(project_id) self.time_series = TraitDataTypeSelectField( BrainViewerModel.time_series, self.project_id, name='time_series', conditions=self.get_filters()) self.shell_surface = TraitDataTypeSelectField( BrainViewerModel.shell_surface, self.project_id, name='shell_surface')
def __init__(self, is_surface_simulation=False): super(SimulatorStimulusFragment, self).__init__() stimuli_index_class = StimuliRegionIndex if is_surface_simulation: stimuli_index_class = SpatioTemporalPatternIndex traited_field = Attr(stimuli_index_class, doc=SimulatorAdapterModel.stimulus.doc, label=SimulatorAdapterModel.stimulus.label, required=SimulatorAdapterModel.stimulus.required) self.stimulus = TraitDataTypeSelectField(traited_field, name='stimulus')
def __init__(self, prefix='', project_id=None): super(EegMonitorForm, self).__init__(prefix, project_id) self.input_data = TraitDataTypeSelectField(EegMonitorModel.input_data, self, name='input_data') self.data_2 = TraitDataTypeSelectField(EegMonitorModel.data_2, self, name='data_2') self.data_3 = TraitDataTypeSelectField(EegMonitorModel.data_3, self, name='data_3')
def __init__(self): super(RegionVolumeMappingVisualiserForm, self).__init__() self.region_mapping_volume = TraitDataTypeSelectField(RegionVolumeMappingVisualiserModel.region_mapping_volume, name='region_mapping_volume', conditions=self.get_filters()) cm_conditions = FilterChain( fields=[FilterChain.datatype + '.ndim', FilterChain.datatype + '.has_volume_mapping'], operations=["==", "=="], values=[1, True]) self.connectivity_measure = TraitDataTypeSelectField(RegionVolumeMappingVisualiserModel.connectivity_measure, name='connectivity_measure', conditions=cm_conditions)
def __init__(self, prefix='', project_id=None): super(TimeSeriesVolumeVisualiserForm, self).__init__(prefix, project_id) self.time_series = TraitDataTypeSelectField( TimeSeriesVolumeVisualiserModel.time_series, self, name='time_series', conditions=self.get_filters()) self.background = TraitDataTypeSelectField( TimeSeriesVolumeVisualiserModel.background, self, name='background')
def __init__(self, session_stored_simulator=None): super(MEGMonitorForm, self).__init__(session_stored_simulator) sensor_filter = FilterChain(fields=[FilterChain.datatype + '.sensors_type'], operations=["=="], values=[SensorTypes.TYPE_MEG.value]) projection_filter = FilterChain(fields=[FilterChain.datatype + '.projection_type'], operations=["=="], values=[ProjectionsType.MEG.value]) self.projection = TraitDataTypeSelectField(MEGViewModel.projection, name='projection', conditions=projection_filter) self.sensors = TraitDataTypeSelectField(MEGViewModel.sensors, name='sensors', conditions=sensor_filter)
def __init__(self, prefix='', project_id=None): super(SensorsViewerForm, self).__init__(prefix, project_id) self.sensors = TraitDataTypeSelectField(SensorsViewerModel.sensors, self, name='sensors', conditions=self.get_filters()) self.projection_surface = TraitDataTypeSelectField( SensorsViewerModel.projection_surface, self, name='projection_surface') self.shell_surface = TraitDataTypeSelectField( SensorsViewerModel.shell_surface, self, name='shell_surface')
def __init__(self, prefix='', project_id=None): super(ConnectivityMeasureVolumeVisualizerForm, self).__init__(prefix, project_id) self.connectivity_measure = TraitDataTypeSelectField( ConnectivityMeasureVolumeVisualizerModel.connectivity_measure, self, name='connectivity_measure', conditions=self.get_filters()) self.region_mapping_volume = TraitDataTypeSelectField( ConnectivityMeasureVolumeVisualizerModel.region_mapping_volume, self, name='region_mapping_volume')
def __init__(self): super(ConnectivityAnnotationsViewForm, self).__init__() # Used for filtering self.connectivity_index = TraitDataTypeSelectField( ConnectivityAnnotationsViewModel.connectivity_index, 'connectivity_index') self.annotations_index = TraitDataTypeSelectField( ConnectivityAnnotationsViewModel.annotations_index, 'annotations_index', conditions=self.get_filters()) self.region_mapping_index = TraitDataTypeSelectField( ConnectivityAnnotationsViewModel.region_mapping_index, 'region_mapping_index')
def __init__(self, session_stored_simulator=None, prefix='', project_id=None): super(iEEGMonitorForm, self).__init__(session_stored_simulator, prefix, project_id) sensor_filter = FilterChain(fields=[FilterChain.datatype + '.sensors_type'], operations=["=="], values=[SensorTypes.TYPE_INTERNAL.value]) projection_filter = FilterChain(fields=[FilterChain.datatype + '.projection_type'], operations=["=="], values=[ProjectionsType.SEEG.value]) self.projection = TraitDataTypeSelectField(iEEGViewModel.projection, self, name='projection', conditions=projection_filter) self.sigma = ScalarField(iEEG.sigma, self) self.sensors = TraitDataTypeSelectField(iEEGViewModel.sensors, self, name='sensors', conditions=sensor_filter)
def __init__(self, prefix='', project_id=None): super(VolumeVisualizerForm, self).__init__(prefix, project_id) self.measure = TraitDataTypeSelectField(VolumeVisualizerModel.measure, self, name='measure', conditions=self.get_filters()) self.region_mapping_volume = TraitDataTypeSelectField( VolumeVisualizerModel.region_mapping_volume, self, name='region_mapping_volume') self.data_slice = StrField(VolumeVisualizerModel.data_slice, self, name='data_slice')
def __init__(self, prefix='', project_id=None): super(BaseSurfaceViewerForm, self).__init__(prefix, project_id) self.region_map = TraitDataTypeSelectField( BaseSurfaceViewerModel.region_map, self, name='region_map') conn_filter = FilterChain(fields=[FilterChain.datatype + '.ndim'], operations=["=="], values=[1]) self.connectivity_measure = TraitDataTypeSelectField( BaseSurfaceViewerModel.connectivity_measure, self, name='connectivity_measure', conditions=conn_filter) self.shell_surface = TraitDataTypeSelectField( BaseSurfaceViewerModel.shell_surface, self, name='shell_surface')
def __init__(self, project_id=None): super(TopographicViewerForm, self).__init__(project_id) self.data_0 = TraitDataTypeSelectField(TopographicViewerModel.data_0, self.project_id, name='data_0', conditions=self.get_filters()) self.data_1 = TraitDataTypeSelectField(TopographicViewerModel.data_1, self.project_id, name='data_1', conditions=self.get_filters()) self.data_2 = TraitDataTypeSelectField(TopographicViewerModel.data_2, self.project_id, name='data_2', conditions=self.get_filters())
def __init__(self, prefix='', project_id=None): super(FourierSpectrumForm, self).__init__(prefix, project_id) self.input_data = TraitDataTypeSelectField( FourierSpectrumModel.input_data, self, name='input_data', conditions=self.get_filters())
def __init__(self, prefix='', project_id=None): super(DiscretePSEAdapterForm, self).__init__(prefix, project_id) self.datatype_group = TraitDataTypeSelectField( DiscretePSEAdapterModel.datatype_group, self, name='datatype_group', conditions=self.get_filters())
def __init__(self): super(ConnectivityEdgeBundleForm, self).__init__() self.connectivity = TraitDataTypeSelectField( ConnectivityEdgeBundleModel.connectivity, name="connectivity", conditions=self.get_filters(), has_all_option=False)
def __init__(self): super(BaseBCTForm, self).__init__() self.connectivity = TraitDataTypeSelectField( BaseBCTModel.connectivity, name="connectivity", conditions=self.get_filters(), has_all_option=True)
def __init__(self): super(MatrixVisualizerForm, self).__init__() self.datatype = TraitDataTypeSelectField( MatrixVisualizerModel.datatype, name='datatype', conditions=self.get_filters()) self.slice = StrField(MatrixVisualizerModel.slice, name='slice')
def __init__(self): super(BaseSurfaceViewerForm, self).__init__() self.region_map = TraitDataTypeSelectField( BaseSurfaceViewerModel.region_map, name='region_map') conn_filter = FilterChain(fields=[ FilterChain.datatype + '.ndim', FilterChain.datatype + '.has_surface_mapping' ], operations=["==", "=="], values=[1, True]) self.connectivity_measure = TraitDataTypeSelectField( BaseSurfaceViewerModel.connectivity_measure, name='connectivity_measure', conditions=conn_filter) self.shell_surface = TraitDataTypeSelectField( BaseSurfaceViewerModel.shell_surface, name='shell_surface')
def __init__(self, prefix='', project_id=None): super(ImaginaryCoherenceDisplayForm, self).__init__(prefix, project_id) self.input_data = TraitDataTypeSelectField( ImaginaryCoherenceDisplayModel.input_data, self, 'input_data', conditions=self.get_filters())
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, spatial_equation_choices, temporal_equation_choices, project_id): super(SurfaceStimulusCreatorForm, self).__init__() self.project_id = project_id # TODO: filter CorticalSurafces self.surface = TraitDataTypeSelectField( SurfaceStimulusCreatorModel.surface, self, name='surface', conditions=self.get_filters()) self.spatial = SelectField(SurfaceStimulusCreatorModel.spatial, self, name='spatial', choices=spatial_equation_choices) self.spatial_params = FormField(get_form_for_equation( self.default_spatial), self, name=self.NAME_SPATIAL_PARAMS_DIV) self.temporal = SelectField(SurfaceStimulusCreatorModel.temporal, self, name='temporal', choices=temporal_equation_choices) self.temporal_params = FormField(get_form_for_equation( self.default_temporal), self, name=self.NAME_TEMPORAL_PARAMS_DIV)
def __init__(self): super(TrackImporterForm, self).__init__() self.data_file = TraitUploadField(TrackImporterModel.data_file, '.trk', 'data_file') self.region_volume = TraitDataTypeSelectField( TrackImporterModel.region_volume, name='region_volume')
def __init__(self, project_id=None): super(RegionMatTimeSeriesImporterForm, self).__init__(project_id) self.data_file = TraitUploadField( RegionMatTimeSeriesImporterModel.data_file, '.mat', self.project_id, 'data_file', self.temporary_files) self.dataset_name = StrField( RegionMatTimeSeriesImporterModel.dataset_name, self.project_id, name='dataset_name') self.structure_path = StrField( RegionMatTimeSeriesImporterModel.structure_path, self.project_id, name='structure_path') self.transpose = BoolField(RegionMatTimeSeriesImporterModel.transpose, self.project_id, name='transpose') self.slice = StrField(RegionMatTimeSeriesImporterModel.slice, self.project_id, name='slice') self.sampling_rate = IntField( RegionMatTimeSeriesImporterModel.sampling_rate, self.project_id, name='sampling_rate') self.start_time = IntField(RegionMatTimeSeriesImporterModel.start_time, self.project_id, name='start_time') self.datatype = TraitDataTypeSelectField( RegionMatTimeSeriesImporterModel.datatype, self.project_id, name='tstype_parameters')
def __init__(self, prefix='', project_id=None): super(NodeComplexCoherenceForm, self).__init__(prefix, project_id) self.time_series = TraitDataTypeSelectField( NodeComplexCoherenceModel.time_series, self, name=self.get_input_name(), conditions=self.get_filters())
def __init__(self): super(LocalConnectivitySelectorForm, self).__init__() traited_attr = Attr(self.get_required_datatype(), label='Load Local Connectivity', required=False) self.existentEntitiesSelect = TraitDataTypeSelectField( traited_attr, name='existentEntitiesSelect')
def __init__(self): super(ICAForm, self).__init__() self.datatype = TraitDataTypeSelectField(ICAModel.datatype, name='datatype', conditions=self.get_filters()) self.i_svar = IntField(ICAModel.i_svar, name='i_svar') self.i_mode = IntField(ICAModel.i_mode, name='i_mode')
def __init__(self): super(NodeCovarianceAdapterForm, self).__init__() self.time_series = TraitDataTypeSelectField( NodeCovarianceAdapterModel.time_series, name=self.get_input_name(), conditions=self.get_filters(), has_all_option=True)