def get_filtered_datatypes(self, dt_module, dt_class, filters, has_all_option, has_none_option): """ Given the name from the input tree, the dataType required and a number of filters, return the available dataType that satisfy the conditions imposed. """ index_class = getattr(sys.modules[dt_module], dt_class)() filters_dict = json.loads(filters) for idx in range(len(filters_dict['fields'])): if filters_dict['values'][idx] in ['True', 'False']: filters_dict['values'][idx] = string2bool( filters_dict['values'][idx]) filter = FilterChain(fields=filters_dict['fields'], operations=filters_dict['operations'], values=filters_dict['values']) project = common.get_current_project() data_type_gid_attr = DataTypeGidAttr( linked_datatype=REGISTRY.get_datatype_for_index(index_class)) data_type_gid_attr.required = not string2bool(has_none_option) select_field = TraitDataTypeSelectField( data_type_gid_attr, conditions=filter, has_all_option=string2bool(has_all_option)) self.algorithm_service.fill_selectfield_with_datatypes( select_field, project.id) return {'options': select_field.options()}
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, project_id=None): super(FFTAdapterForm, self).__init__(project_id) self.time_series = TraitDataTypeSelectField(FFTAdapterModel.time_series, self.project_id, name='time_series', conditions=self.get_filters(), has_all_option=True) self.segment_length = FloatField(FFTAdapterModel.segment_length, self.project_id) self.window_function = SelectField(FFTAdapterModel.window_function, self.project_id) self.detrend = BoolField(FFTAdapterModel.detrend, self.project_id)
def __init__(self, prefix='', project_id=None): super(NIFTIImporterForm, self).__init__(prefix, project_id) self.data_file = TraitUploadField(NIFTIImporterModel.data_file, ('.nii', '.gz', '.zip'), self, name='data_file') self.apply_corrections = BoolField(NIFTIImporterModel.apply_corrections, self, name='apply_corrections') self.mappings_file = TraitUploadField(NIFTIImporterModel.mappings_file, '.txt', self, name='mappings_file') self.connectivity = TraitDataTypeSelectField(NIFTIImporterModel.connectivity, self, name='connectivity')
def __init__(self, prefix='', project_id=None): super(RegionMatTimeSeriesImporterForm, self).__init__(prefix, project_id) self.data_file = TraitUploadField( RegionMatTimeSeriesImporterModel.data_file, '.mat', self, name='data_file') self.dataset_name = StrField( RegionMatTimeSeriesImporterModel.dataset_name, self, name='dataset_name') self.structure_path = StrField( RegionMatTimeSeriesImporterModel.structure_path, self, name='structure_path') self.transpose = BoolField(RegionMatTimeSeriesImporterModel.transpose, self, name='transpose') self.slice = StrField(RegionMatTimeSeriesImporterModel.slice, self, name='slice') self.sampling_rate = IntField( RegionMatTimeSeriesImporterModel.sampling_rate, self, name='sampling_rate') self.start_time = IntField(RegionMatTimeSeriesImporterModel.start_time, self, name='start_time') self.datatype = TraitDataTypeSelectField( RegionMatTimeSeriesImporterModel.datatype, self, name='tstype_parameters')
def __init__(self): super(PearsonCorrelationCoefficientAdapterForm, self).__init__() self.time_series = TraitDataTypeSelectField(PearsonCorrelationCoefficientAdapterModel.time_series, name=self.get_input_name(), conditions=self.get_filters(), has_all_option=True) self.t_start = FloatField(PearsonCorrelationCoefficientAdapterModel.t_start) self.t_end = FloatField(PearsonCorrelationCoefficientAdapterModel.t_end)
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=[SurfaceTypesEnum.CORTICAL_SURFACE.value]) self.surface = TraitDataTypeSelectField( RegionMappingImporterModel.surface, name='surface', conditions=surface_conditions) self.connectivity = TraitDataTypeSelectField( RegionMappingImporterModel.connectivity, name='connectivity')
def __init__(self, project_id=None): super(LocalConnectivitySelectorForm, self).__init__(project_id) traited_attr = Attr(self.get_required_datatype(), label='Load Local Connectivity', required=False) self.existentEntitiesSelect = TraitDataTypeSelectField( traited_attr, self.project_id, name='existentEntitiesSelect')
def __init__(self, project_id=None): super(HistogramViewerForm, self).__init__(project_id) self.input_data = TraitDataTypeSelectField( HistogramViewerModel.input_data, self.project_id, name='input_data', conditions=self.get_filters())
def __init__(self): super(ICAAdapterForm, self).__init__() self.time_series = TraitDataTypeSelectField( ICAAdapterModel.time_series, name='time_series', conditions=self.get_filters(), has_all_option=True) self.n_components = IntField(ICAAdapterModel.n_components)
def __init__(self, prefix='', project_id=None): super(RegionVolumeMappingVisualiserForm, self).__init__(prefix, project_id) self.region_mapping_volume = TraitDataTypeSelectField( RegionVolumeMappingVisualiserModel.region_mapping_volume, self, name='region_mapping_volume', conditions=self.get_filters()) cm_conditions = FilterChain(fields=[FilterChain.datatype + '.ndim'], operations=["=="], values=[1]) self.connectivity_measure = TraitDataTypeSelectField( RegionVolumeMappingVisualiserModel.connectivity_measure, self, name='connectivity_measure', conditions=cm_conditions)
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', FilterChain.datatype + '.has_surface_mapping' ], operations=["==", "=="], values=[1, True]) 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, 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='', project_id=None): super(MatrixVisualizerForm, self).__init__(prefix, project_id, False) self.datatype = TraitDataTypeSelectField( MatrixVisualizerModel.datatype, self, name='datatype', conditions=self.get_filters()) self.slice = StrField(MatrixVisualizerModel.slice, self, name='slice')
def __init__(self, prefix='', project_id=None): super(PearsonCorrelationCoefficientVisualizerForm, self).__init__(prefix, project_id) self.datatype = TraitDataTypeSelectField( PearsonCorrelationCoefficientVisualizerModel.datatype, self, name='datatype', conditions=self.get_filters())
def __init__(self): super(NodeCoherenceForm, self).__init__() self.time_series = TraitDataTypeSelectField( NodeCoherenceModel.time_series, name=self.get_input_name(), conditions=self.get_filters(), has_all_option=True) self.nfft = IntField(NodeCoherenceModel.nfft)
def __init__(self, prefix='', project_id=None): super(TimeSeriesForm, self).__init__(prefix, project_id, False) self.time_series = TraitDataTypeSelectField( TimeSeriesModel.time_series, self, name='time_series', conditions=self.get_filters())
def __init__(self, prefix='', project_id=None): super(WaveletSpectrogramVisualizerForm, self).__init__(prefix, project_id) self.input_data = TraitDataTypeSelectField( WaveletSpectrogramVisualizerModel.input_data, self, name='input_data', conditions=self.get_filters())
def __init__(self, variables_of_interest_indexes={}, prefix='', project_id=None): super(ProjectionMonitorForm, self).__init__(variables_of_interest_indexes, prefix, project_id) self.region_mapping = TraitDataTypeSelectField( ProjectionViewModel.region_mapping, self, name='region_mapping')
def __init__(self): super(RegionStimulusCreatorForm, self).__init__() self.connectivity = TraitDataTypeSelectField( RegionStimulusCreatorModel.connectivity, name='connectivity') self.temporal = SelectField(RegionStimulusCreatorModel.temporal, name='temporal', subform=get_form_for_equation( self.default_temporal.value))
def __init__(self, equation_choices, project_id): super(RegionStimulusCreatorForm, self).__init__() self.project_id = project_id self.connectivity = TraitDataTypeSelectField(RegionStimulusCreatorModel.connectivity, self, name='connectivity') self.temporal = SelectField(RegionStimulusCreatorModel.temporal, self, name='temporal', choices=equation_choices) self.temporal_params = FormField(get_form_for_equation(self.default_temporal), self, name=self.NAME_TEMPORAL_PARAMS_DIV)
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(TestAdapterDatatypeInputForm, self).__init__(prefix, project_id) self.test1_dt_input = TraitDataTypeSelectField(Attr(DummyDataType), self, name="test1_dt_input") self.test1_non_dt_input = SimpleIntField(self, name='test1_non_dt_input', default=0)
def __init__(self, prefix='', project_id=None): super(ConnectivityCreatorForm, self).__init__(prefix, project_id) self.original_connectivity = TraitDataTypeSelectField(ConnectivityCreatorModel.original_connectivity, self, name='original_connectivity', conditions=self.get_filters()) self.new_weights = ArrayField(ConnectivityCreatorModel.new_weights, self) self.new_tracts = ArrayField(ConnectivityCreatorModel.new_tracts, self) self.interest_area_indexes = ArrayField(ConnectivityCreatorModel.interest_area_indexes, self) self.is_branch = BoolField(ConnectivityCreatorModel.is_branch, self)
def __init__(self): super(ProjectionMatrixImporterForm, self).__init__() self.projection_file = TraitUploadField( ProjectionMatrixImporterModel.projection_file, ('.mat', '.npy'), 'projection_file') self.dataset_name = StrField( ProjectionMatrixImporterModel.dataset_name, name='dataset_name') surface_conditions = FilterChain( fields=[FilterChain.datatype + '.surface_type'], operations=['=='], values=['Cortical Surface']) self.surface = TraitDataTypeSelectField( ProjectionMatrixImporterModel.surface, name='surface', conditions=surface_conditions) self.sensors = TraitDataTypeSelectField( ProjectionMatrixImporterModel.sensors, name='sensors')
def __init__(self, prefix='', project_id=None): super(ICAForm, self).__init__(prefix, project_id) self.datatype = TraitDataTypeSelectField(ICAModel.datatype, self, name='datatype', conditions=self.get_filters()) self.i_svar = IntField(ICAModel.i_svar, self, name='i_svar') self.i_mode = IntField(ICAModel.i_mode, self, name='i_mode')
def __init__(self, project_id=None): super(PCAAdapterForm, self).__init__(project_id) self.time_series = TraitDataTypeSelectField( PCAAdapterModel.time_series, self.project_id, name=self.get_input_name(), conditions=self.get_filters(), has_all_option=True)
def __init__(self, prefix='', project_id=None, draw_ranges=True): super(BaseBCTForm, self).__init__(prefix, project_id, draw_ranges) self.connectivity = TraitDataTypeSelectField( BaseBCTModel.connectivity, self, name="connectivity", conditions=self.get_filters(), has_all_option=True)
def __init__(self): super(TimeseriesMetricsAdapterForm, self).__init__() self.time_series = TraitDataTypeSelectField( TimeseriesMetricsAdapterModel.time_series, name="time_series") self.start_point = FloatField( TimeseriesMetricsAdapterModel.start_point) self.segment = IntField(TimeseriesMetricsAdapterModel.segment) self.algorithms = MultiSelectField( TimeseriesMetricsAdapterModel.algorithms, name="algorithms")
def __init__(self, prefix='', project_id=None): super(RegionMappingImporterForm, self).__init__(prefix, project_id) self.mapping_file = TraitUploadField( RegionMappingImporterModel.mapping_file, ('.txt', '.zip', '.bz2'), self, name='mapping_file') surface_conditions = FilterChain( fields=[FilterChain.datatype + '.surface_type'], operations=['=='], values=[CORTICAL]) self.surface = TraitDataTypeSelectField( RegionMappingImporterModel.surface, self, name='surface', conditions=surface_conditions) self.connectivity = TraitDataTypeSelectField( RegionMappingImporterModel.connectivity, self, name='connectivity')