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')
