class RegionMatTimeSeriesImporterModel(UploaderViewModel):
data_file = Str(label='Please select file to import')
dataset_name = Str(label='Matlab dataset name',
doc='Name of the MATLAB dataset where data is stored')
structure_path = Str(
required=False,
default='',
label='For nested structures enter the field path (separated by .)')
transpose = Attr(
field_type=bool,
required=False,
default=False,
label='Transpose the array. Expected shape is (time, channel)')
slice = Str(
required=False,
default='',
label=
'Slice of the array in numpy syntax. Expected shape is (time, channel)'
)
sampling_rate = Int(required=False,
default=100,
label='sampling rate (Hz)')
start_time = Int(default=0, label='starting time (ms)')
datatype = DataTypeGidAttr(linked_datatype=Connectivity,
label='Connectivity')
class CSVConnectivityImporterModel(UploaderViewModel):
weights = Str(
label='Weights file (csv)'
)
weights_delimiter = Str(
choices=tuple(DELIMITER_OPTIONS.values()),
default=tuple(DELIMITER_OPTIONS.values())[0],
label='Field delimiter : '
)
tracts = Str(
label='Tracts file (csv)'
)
tracts_delimiter = Str(
choices=tuple(DELIMITER_OPTIONS.values()),
default=tuple(DELIMITER_OPTIONS.values())[0],
label='Field delimiter : '
)
input_data = DataTypeGidAttr(
linked_datatype=Connectivity,
label='Reference Connectivity Matrix (for node labels, 3d positions etc.)'
)
class GIFTISurfaceImporterModel(UploaderViewModel):
KEY_OPTION_READ_METADATA = 'Specified in the file metadata'
surface_types = ALL_SURFACES_SELECTION.copy()
surface_types[KEY_OPTION_READ_METADATA] = OPTION_READ_METADATA
file_type = Str(
label='Specify file type : ',
choices=tuple(surface_types.values()),
default=tuple(surface_types.values())[0]
)
data_file = Str(
label='Please select a .gii (LH if cortex)'
)
data_file_part2 = Str(
required=False,
label="Optionally select 2'nd .gii (RH if cortex)"
)
should_center = Attr(
field_type=bool,
required=False,
default=False,
label='Center surface using vertex means along axes'
)
class NIFTIImporterModel(UploaderViewModel):
data_file = Str(
label='Please select file to import (gz or nii)'
)
apply_corrections = Attr(
field_type=bool,
required=False,
label='Apply auto Corrections',
doc='Check this when the NII mapping has values outside [-1..N-1]. '
'All outside range will be set -1 (background).'
)
mappings_file = Str(
required=False,
label='Mapping File',
doc='Fill this for Region Mappings, when the indices in the NII do not match '
'the Connectivity [0..N-1] indices'
)
connectivity = DataTypeGidAttr(
linked_datatype=Connectivity,
required=False,
label='Connectivity',
doc='Optional Connectivity if the NII file is a volume2regions mapping'
)
class ZIPConnectivityImporterModel(UploaderViewModel):
uploaded = Str(label='Connectivity file (zip)')
normalization = Str(required=False,
choices=tuple(NORMALIZATION_OPTIONS.values()),
label='Weights Normalization',
doc='Normalization mode for weights')
def __init__(self, choices):
super(SimulatorPSEConfigurationFragment, self).__init__()
default_choice = list(choices.values())[0]
self.pse_param1 = SelectField(Str(default=default_choice,
label="PSE param1"),
choices=choices,
name='pse_param1')
self.pse_param2 = SelectField(Str(label="PSE param2", required=False),
choices=choices,
name='pse_param2')
class ObjSurfaceImporterModel(UploaderViewModel):
surface_type = Str(label='Specify file type :',
choices=tuple(ALL_SURFACES_SELECTION.values()),
default=tuple(ALL_SURFACES_SELECTION.values())[0])
data_file = Str(label='Please select file to import')
should_center = Attr(field_type=bool,
required=False,
default=False,
label='Center surface using vertex means along axes')
class UploaderViewModel(ViewModel):
REQUIRED_TYPE = None
data_subject = Str(default=DataTypeMetaData.DEFAULT_SUBJECT,
label='Subject')
encrypted_aes_key = Str(
required=False,
label='Encrypted AES Password (if your files come encrypted)',
doc=
'Check our demo notebook on how to produce this key and how we expect your files to be encrypted'
)
class SensorsImporterModel(UploaderViewModel):
OPTIONS = {
'EEG Sensors': SensorsEEG.sensors_type.default,
'MEG Sensors': SensorsMEG.sensors_type.default,
'Internal Sensors': SensorsInternal.sensors_type.default
}
sensors_file = Str(
label='Please upload sensors file (txt or bz2 format)',
doc='Expected a text/bz2 file containing sensor measurements.')
sensors_type = Str(label='Sensors type: ',
choices=tuple(OPTIONS.values()),
default=tuple(OPTIONS.values())[0])
class CSVConnectivityImporterModel(UploaderViewModel):
weights = Str(label='Weights file (csv)')
weights_delimiter = EnumAttr(default=CSVDelimiterOptionsEnum.COMMA,
label='Field delimiter : ')
tracts = Str(label='Tracts file (csv)')
tracts_delimiter = EnumAttr(default=CSVDelimiterOptionsEnum.COMMA,
label='Field delimiter : ')
input_data = DataTypeGidAttr(
linked_datatype=Connectivity,
label=
'Reference Connectivity Matrix (for node labels, 3d positions etc.)')
class ZIPSurfaceImporterModel(UploaderViewModel):
uploaded = Str(label='Surface file (zip)')
surface_type = Str(choices=tuple(ALL_SURFACES_SELECTION.values()),
default=tuple(ALL_SURFACES_SELECTION.values())[0],
label='Surface type')
zero_based_triangles = Attr(field_type=bool,
required=False,
default=True,
label='Zero based triangles')
should_center = Attr(field_type=bool,
required=False,
label='Center surface using vertex means along axes')
class BRCOImporterModel(UploaderViewModel):
data_file = Str(label='Connectivity Annotations')
connectivity = DataTypeGidAttr(
linked_datatype=Connectivity,
label='Target Large Scale Connectivity',
doc='The Connectivity for which these annotations were made')
class UploaderViewModel(ViewModel):
REQUIRED_TYPE = None
data_subject = Str(
default=DataTypeMetaData.DEFAULT_SUBJECT,
label='Subject'
)
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')
class ProjectionMatrixImporterModel(UploaderViewModel):
projection_file = Str(
label='Projection matrix file (.mat or .npy format)',
doc='Expected a file containing projection matrix (one vector of length '
'number of surface vertices nd values in the sensors range).'
)
dataset_name = Attr(
field_type=str,
required=False,
default=DEFAULT_DATASET_NAME,
label='Matlab dataset name',
doc='Name of the MATLAB dataset where data is stored. Required only for .mat files'
)
surface = DataTypeGidAttr(
linked_datatype=Surface,
label='Brain Cortical Surface',
doc='The Brain Surface used by the uploaded projection matrix.'
)
sensors = DataTypeGidAttr(
linked_datatype=Sensors,
label='Sensors',
doc='The Sensors used in for current projection.'
)
class NetworkxImporterModel(UploaderViewModel):
data_file = Str(label='Please select file to import')
key_edge_weight = Attr(field_type=str,
required=False,
default=NetworkxParser.KEY_EDGE_WEIGHT[0],
label='Key Edge Weight')
key_edge_tract = Attr(field_type=str,
required=False,
default=NetworkxParser.KEY_EDGE_TRACT[0],
label='Key Edge Tract')
key_node_coordinates = Attr(field_type=str,
required=False,
default=NetworkxParser.KEY_NODE_COORDINATES[0],
label='Key Node Coordinates')
key_node_label = Attr(field_type=str,
required=False,
default=NetworkxParser.KEY_NODE_LABEL[0],
label='Key Node Label')
key_node_region = Attr(field_type=str,
required=False,
default=NetworkxParser.KEY_NODE_REGION[0],
label='Key Node Region')
key_node_hemisphere = Attr(field_type=str,
required=False,
default=NetworkxParser.KEY_NODE_HEMISPHERE[0],
label='Key Node Hemisphere')
class GIFTITimeSeriesImporterModel(UploaderViewModel):
data_file = Str(label='Please select file to import (.gii)')
surface = DataTypeGidAttr(
linked_datatype=Surface,
label='Brain Surface',
doc='The Brain Surface used to generate imported TimeSeries.')
def test_hidden_field(self):
hidden_str_attr = Str(label='Dummy Str', default='')
hidden_field = HiddenField(hidden_str_attr, self.name)
post_data = {'dummy_name': 'Dummy Hidden Str'}
hidden_field.fill_from_post(post_data)
assert hidden_field.data == post_data[self.name], "Hidden data was not set correctly on HiddenField!"
assert hidden_field.label == '', "Hidden field should have empty label!"
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 _add_pse_field(self, param, param_key=KEY_PARAM1):
# type: (RangeParameter, str) -> None
pse_param_name = HiddenField(Str(default=param.name, required=False),
self.NAME_FIELD.format(param_key))
self.__setattr__(self.NAME_FIELD.format(param_key), pse_param_name)
if param.type is float:
self._add_fields_for_float(param, param_key)
else:
self._add_field_for_gid(param, param_key)
def test_upload_field(self):
connectivity_file = os.path.join(os.path.dirname(tvb_data.__file__), 'connectivity', 'connectivity_96.zip')
data_file = Str('Test Upload Field')
required_type = '.zip'
upload_field = TraitUploadField(data_file, required_type, self.name)
post_data = {'Data_Subject': 'John Doe', self.name: connectivity_file, 'normalization': 'explicit-None-value'}
upload_field.fill_from_post(post_data)
assert post_data[self.name] == upload_field.data, "Path was not set correctly on TraitUploadField!"
class LocalConnectivityCreatorModel(ViewModel, LocalConnectivity):
surface = DataTypeGidAttr(
linked_datatype=Surface,
label=LocalConnectivity.surface.label
)
display_name = Str(
label='Display name',
required=False
)
class RegionStimulusCreatorModel(ViewModel, StimuliRegion):
temporal = EnumAttr(field_type=TemporalEquationsEnum,
label="Temporal Equation",
default=TemporalEquationsEnum.PULSETRAIN.instance)
connectivity = DataTypeGidAttr(field_type=uuid.UUID,
linked_datatype=Connectivity,
label="Connectivity")
display_name = Str(label='Display name', required=False)
class TrackImporterModel(UploaderViewModel):
data_file = Str(
label='Please select file to import'
)
region_volume = DataTypeGidAttr(
linked_datatype=RegionVolumeMapping,
required=False,
label='Reference Volume Map'
)
class RegionStimulusCreatorModel(ViewModel, StimuliRegion):
temporal = Attr(field_type=TemporalApplicableEquation,
label="Temporal Equation",
default=PulseTrain())
connectivity = DataTypeGidAttr(field_type=uuid.UUID,
linked_datatype=Connectivity,
label="Connectivity")
display_name = Str(label='Display name', required=False)
class ObjSurfaceImporterModel(UploaderViewModel):
surface_type = EnumAttr(label='Specify file type :',
default=SurfaceTypesEnum.CORTICAL_SURFACE)
data_file = Str(label='Please select file to import')
should_center = Attr(field_type=bool,
required=False,
default=False,
label='Center surface using vertex means along axes')
class RegionStimulusCreatorModel(ViewModel, StimuliRegion):
connectivity = DataTypeGidAttr(
field_type=uuid.UUID,
linked_datatype=Connectivity,
label="Connectivity"
)
display_name = Str(
label='Display name',
required=False
)
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!"
class ConnectivityMeasureImporterModel(UploaderViewModel):
data_file = Str(label='Connectivity measure file (.mat format)')
dataset_name = Attr(field_type=str,
default='M',
label='Matlab dataset name',
doc='Name of the MATLAB dataset where data is stored')
connectivity = DataTypeGidAttr(
linked_datatype=Connectivity,
label='Large Scale Connectivity',
doc='The Connectivity for which these measurements were made')
class SurfaceStimulusCreatorModel(ViewModel, StimuliSurface):
spatial = Attr(field_type=FiniteSupportEquation,
label="Spatial Equation",
default=Sigmoid())
temporal = Attr(field_type=TemporalApplicableEquation,
label="Temporal Equation",
default=PulseTrain())
surface = DataTypeGidAttr(linked_datatype=CorticalSurface,
label=StimuliSurface.surface.label)
display_name = Str(label='Display name', required=False)
