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):
super(ContinuousWaveletTransformAdapterForm, self).__init__()
self.time_series = TraitDataTypeSelectField(WaveletAdapterModel.time_series, name=self.get_input_name(),
conditions=self.get_filters(), has_all_option=True)
self.mother = StrField(WaveletAdapterModel.mother)
self.sample_period = FloatField(WaveletAdapterModel.sample_period)
self.normalisation = StrField(WaveletAdapterModel.normalisation)
self.q_ratio = FloatField(WaveletAdapterModel.q_ratio)
self.frequencies = FormField(RangeForm, name='frequencies', label=WaveletAdapterModel.frequencies.label,
doc=WaveletAdapterModel.frequencies.doc)
def __init__(self):
super(BalloonModelAdapterForm, self).__init__()
self.time_series = TraitDataTypeSelectField(
BalloonModelAdapterModel.time_series,
name=self.get_input_name(),
conditions=self.get_filters(),
has_all_option=True)
self.dt = FloatField(BalloonModelAdapterModel.dt)
self.tau_s = FloatField(BalloonModelAdapterModel.tau_s)
self.tau_f = FloatField(BalloonModelAdapterModel.tau_f)
self.neural_input_transformation = StrField(
BalloonModelAdapterModel.neural_input_transformation)
self.bold_model = StrField(BalloonModelAdapterModel.bold_model)
self.RBM = BoolField(BalloonModelAdapterModel.RBM)
def __init__(self, prefix='', project_id=None):
super(ConnectivityMeasureImporterForm, self).__init__(prefix, project_id)
self.data_file = TraitUploadField(ConnectivityMeasureImporterModel.data_file, '.mat', self, name='data_file')
self.dataset_name = StrField(ConnectivityMeasureImporterModel.dataset_name, self, name='dataset_name')
self.connectivity = TraitDataTypeSelectField(ConnectivityMeasureImporterModel.connectivity, self,
name='connectivity')
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(VolumeVisualizerForm, self).__init__()
self.measure = TraitDataTypeSelectField(VolumeVisualizerModel.measure, name='measure',
conditions=self.get_filters())
self.region_mapping_volume = TraitDataTypeSelectField(VolumeVisualizerModel.region_mapping_volume,
name='region_mapping_volume')
self.data_slice = StrField(VolumeVisualizerModel.data_slice, name='data_slice')
def __init__(self):
super(_InputTreeFragment, self).__init__()
self.dynamic_name = StrField(Str(
label='Parameter configuration name',
doc="""The name of this parameter configuration"""),
self.project_id,
name='dynamic_name')
def __init__(self,
session_stored_simulator=None,
is_period_disabled=False):
super(EEGMonitorForm, self).__init__(session_stored_simulator,
is_period_disabled)
sensor_filter = FilterChain(
fields=[FilterChain.datatype + '.sensors_type'],
operations=["=="],
values=[SensorTypesEnum.TYPE_EEG.value])
projection_filter = FilterChain(
fields=[FilterChain.datatype + '.projection_type'],
operations=["=="],
values=[ProjectionsTypeEnum.EEG.value])
self.projection = TraitDataTypeSelectField(
EEGViewModel.projection,
name='projection',
conditions=projection_filter)
self.reference = StrField(EEG.reference)
self.sensors = TraitDataTypeSelectField(EEGViewModel.sensors,
name='sensors',
conditions=sensor_filter)
self.sigma = FloatField(EEG.sigma)
def test_str_field_optional(self):
str_attr = Str(label='Dummy Str', default='', required=False)
str_field = StrField(str_attr, self.name)
post_data = {'dummy_name': ''}
str_field.fill_from_post(post_data)
assert str_field.data == '', "Str data was not set correctly on StrField!"
assert str_field.validate(), "Validation should not have failed on StrField!"
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):
super(LocalConnectivityCreatorForm, self).__init__()
self.surface = TraitDataTypeSelectField(LocalConnectivityCreatorModel.surface, name=self.get_input_name(),
conditions=self.get_filters())
self.spatial = SelectField(LocalConnectivityCreatorModel.equation, name='spatial',
choices=self.possible_equations,
display_none_choice=False, subform=GaussianEquationForm)
self.cutoff = FloatField(LocalConnectivityCreatorModel.cutoff)
self.display_name = StrField(LocalConnectivityCreatorModel.display_name, name='display_name')
def __init__(self):
super(ConnectivityMeasureImporterForm, self).__init__()
self.data_file = TraitUploadField(
ConnectivityMeasureImporterModel.data_file, '.mat', 'data_file')
self.dataset_name = StrField(
ConnectivityMeasureImporterModel.dataset_name, 'dataset_name')
self.connectivity = TraitDataTypeSelectField(
ConnectivityMeasureImporterModel.connectivity, name='connectivity')
def __init__(self):
super(StimulusSurfaceSelectorForm, self).__init__()
traited_attr = Attr(StimuliSurfaceIndex,
label='Load Surface Stimulus',
required=False)
self.surface_stimulus = TraitDataTypeSelectField(
traited_attr, name='existentEntitiesSelect')
self.display_name = StrField(SurfaceStimulusCreatorModel.display_name,
name='display_name')
def __init__(self, project_id=None):
super(StimulusRegionSelectorForm, self).__init__(project_id=project_id)
traited_attr = Attr(StimuliRegionIndex,
label='Load Region Stimulus',
required=False)
self.region_stimulus = TraitDataTypeSelectField(
traited_attr, self.project_id, name='existentEntitiesSelect')
self.display_name = StrField(RegionStimulusCreatorModel.display_name,
self.project_id,
name='display_name')
def __init__(self):
super(EquationForm, self).__init__()
self.equation = StrField(self.get_traited_equation().equation,
disabled=True)
for param_key, param in self.get_traited_equation().parameters.default(
).items():
setattr(
self, param_key,
FloatField(Float(label=param_key, default=param),
name=param_key))
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, default_simulation_name="simulation_1"):
super(SimulatorFinalFragment, self).__init__()
self.simulation_length = FloatField(
SimulatorAdapterModel.simulation_length)
self.simulation_name = StrField(Attr(
str,
doc='Name for the current simulation configuration',
default=default_simulation_name,
label='Simulation name'),
name='input_simulation_name_id')
def test_str_field_required(self):
str_attr = Str(label='Dummy Str', default='')
str_field = StrField(str_attr, self.name)
post_data = {'dummy_name': 'dummy_str'}
str_field.fill_from_post(post_data)
assert str_field.data == post_data[self.name], "Str data was not set correctly on StrField!"
post_data = {'dummy_name': ''}
str_field.fill_from_post(post_data)
assert str_field.validate() is False, "Validation should have failed on StrField!"
def __init__(self):
super(LocalConnectivityCreatorForm, self).__init__()
self.surface = TraitDataTypeSelectField(LocalConnectivityCreatorModel.surface, name=self.get_input_name(),
conditions=self.get_filters())
self.spatial = SelectField(EnumAttr(field_type=SpatialEquationsEnum,
default=SpatialEquationsEnum.GAUSSIAN.instance, required=True),
name='spatial', display_none_choice=False, subform=GaussianEquationForm)
self.cutoff = FloatField(LocalConnectivityCreatorModel.cutoff)
self.display_name = StrField(LocalConnectivityCreatorModel.display_name, name='display_name')
del self.spatial.choices[-1]
def __init__(self):
super(ABCUploaderForm, self).__init__()
self.subject_field = StrField(UploaderViewModel.data_subject,
name='Data_Subject')
# Show Encryption field only when the current TVB installation is capable of decryption
supports_encrypted_files = (
TvbProfile.current.UPLOAD_KEY_PATH is not None
and os.path.exists(TvbProfile.current.UPLOAD_KEY_PATH))
if supports_encrypted_files:
self.encrypted_aes_key = TraitUploadField(
UploaderViewModel.encrypted_aes_key, '.pem',
'encrypted_aes_key')
def __init__(self, prefix='', project_id=None):
super(NetworkxConnectivityImporterForm, self).__init__(prefix, project_id)
self.data_file = TraitUploadField(NetworkxImporterModel.data_file, '.gpickle', self, name='data_file')
self.key_edge_weight = StrField(NetworkxImporterModel.key_edge_weight, self, name='key_edge_weight')
self.key_edge_tract = StrField(NetworkxImporterModel.key_edge_tract, self, name='key_edge_tract')
self.key_node_coordinates = StrField(NetworkxImporterModel.key_node_coordinates, self,
name='key_node_coordinates')
self.key_node_label = StrField(NetworkxImporterModel.key_node_label, self, name='key_node_label')
self.key_node_region = StrField(NetworkxImporterModel.key_node_region, self, name='key_node_region')
self.key_node_hemisphere = StrField(NetworkxImporterModel.key_node_hemisphere, self, name='key_node_hemisphere')
def __init__(self):
super(BarForm, self).__init__()
self.airplane_meal = StrField(Bar.airplane_meal)
self.portions = IntField(Bar.portions)
self.is_fancy = BoolField(Bar.is_fancy)
def __init__(self):
super(BaBazeForm, self).__init__()
# these beg for metaprogramming
self.s = StrField(BaBaze.s)
self.sign = IntField(BaBaze.sign)
def __init__(self, prefix='', project_id=None):
super(ABCUploaderForm, self).__init__(prefix, project_id)
self.subject_field = StrField(UploaderViewModel.data_subject,
self,
name='Data_Subject')
self.temporary_files = []
