def __init__(self, **kwargs):
device, description, excitation_lambda, location = popargs(
'device', 'description', 'excitation_lambda', 'location', kwargs)
call_docval_func(super(OptogeneticStimulusSite, self).__init__, kwargs)
self.device = device
self.description = description
self.excitation_lambda = excitation_lambda
self.location = location
def __init__(self, **kwargs):
data, bits_per_pixel, dimension, format, field_of_view = popargs(
'data', 'bits_per_pixel', 'dimension', 'format', 'field_of_view', kwargs)
call_docval_func(super(AImage, self).__init__, kwargs)
self.data = data
self.bits_per_pixel = bits_per_pixel
self.dimension = format
self.field_of_view = field_of_view
def add_unit(self, **kwargs):
"""
Add a unit to the unit table.
See :py:meth:`~pynwb.core.DynamicTable.add_row` for more details.
"""
self.__check_units()
call_docval_func(self.units.add_unit, kwargs)
def __init__(self, **kwargs):
"""Construct a new PoseEstimationSeries representing pose estimates for a particular body part."""
reference_frame, confidence, confidence_definition = popargs(
'reference_frame', 'confidence', 'confidence_definition', kwargs)
call_docval_func(super().__init__, kwargs)
self.reference_frame = reference_frame
self.confidence = confidence
self.confidence_definition = confidence_definition
def __init__(self, **kwargs):
bits_per_pixel, dimension, format, field_of_view = popargs(
'bits_per_pixel', 'dimension', 'format', 'field_of_view', kwargs)
call_docval_func(super().__init__, kwargs)
self.bits_per_pixel = bits_per_pixel
self.dimension = dimension
self.format = format
self.field_of_view = field_of_view
def __init__(self, **kwargs):
super().__init__(
**{
kwargs_item: kwargs[kwargs_item]
for kwargs_item in kwargs.copy() if kwargs_item != 'devices'
})
call_docval_func(super(NwbImageSeries, self).__init__, kwargs)
self.devices = kwargs['devices']
def _func(self, **kwargs):
call_docval_func(super(cls, self).__init__, kwargs)
for conf in clsconf:
attr_name = conf['attr']
add_name = conf['add']
container = popargs(attr_name, kwargs)
add = getattr(self, add_name)
add(container)
def add_epoch_column(self, **kwargs):
"""
Add a column to the electrode table.
See :py:meth:`~pynwb.core.TimeIntervals.add_column` for more details
"""
self.__check_epochs()
self.epoch_tags.update(kwargs.pop('tags', list()))
call_docval_func(self.epochs.add_column, kwargs)
def __init__(self, **kwargs):
field_of_view, imaging_plane, pmt_gain, scan_line_rate = popargs(
'field_of_view', 'imaging_plane', 'pmt_gain', 'scan_line_rate',
kwargs)
call_docval_func(super(TwoPhotonSeries, self).__init__, kwargs)
self.field_of_view = field_of_view
self.imaging_plane = imaging_plane
self.pmt_gain = pmt_gain
self.scan_line_rate = scan_line_rate
def __init__(self, **kwargs):
call_docval_func(super(MultiContainerInterface, self).__init__, kwargs)
if isinstance(self.__clsconf__, dict):
attr_name = self.__clsconf__['attr']
self.fields[attr_name] = LabelledDict(attr_name)
else:
for d in self.__clsconf__:
attr_name = d['attr']
self.fields[attr_name] = LabelledDict(attr_name)
def __init__(self, **kwargs):
if kwargs.get('description', None) is None:
kwargs['description'] = "data on spiking units"
call_docval_func(super(Units, self).__init__, kwargs)
if 'spike_times' not in self.colnames:
self.__has_spike_times = False
self.__electrode_table = getargs('electrode_table', kwargs)
self.waveform_rate = getargs('waveform_rate', kwargs)
self.waveform_unit = getargs('waveform_unit', kwargs)
self.resolution = getargs('resolution', kwargs)
def __init__(self, **kwargs):
super().__init__(
**{
kwargs_item: kwargs[kwargs_item]
for kwargs_item in kwargs.copy()
if kwargs_item not in ['description', 'content']
})
call_docval_func(super(AssociatedFiles, self).__init__, kwargs)
self.description = kwargs['description']
self.content = kwargs['content']
def add_invalid_time_interval(self, **kwargs):
"""
Add a trial to the trial table.
See :py:meth:`~hdmf.common.DynamicTable.add_row` for more details.
Required fields are *start_time*, *stop_time*, and any columns that have
been added (through calls to `add_invalid_times_columns`).
"""
self.__check_invalid_times()
call_docval_func(self.invalid_times.add_interval, kwargs)
def __init__(self, **kwargs):
imaging_plane, reference_images = popargs('imaging_plane', 'reference_images', kwargs)
if kwargs.get('name') is None:
kwargs['name'] = imaging_plane.name
columns, colnames = getargs('columns', 'colnames', kwargs)
call_docval_func(super(PlaneSegmentation, self).__init__, kwargs)
self.imaging_plane = imaging_plane
if isinstance(reference_images, ImageSeries):
reference_images = (reference_images,)
self.reference_images = reference_images
def __init__(self, **kwargs):
call_docval_func(super(ElectrodeGroup, self).__init__, kwargs)
description, location, device, position = popargs('description', 'location', 'device', 'position', kwargs)
self.description = description
self.location = location
self.device = device
if position and len(position) != 3:
raise Exception('ElectrodeGroup position argument must have three elements: x, y, z, but received: %s'
% position)
self.position = position
def __init__(self, **kwargs):
bits_per_pixel, dimension, external_file, starting_frame, format = popargs(
'bits_per_pixel', 'dimension', 'external_file', 'starting_frame', 'format', kwargs)
call_docval_func(super(ImageSeries, self).__init__, kwargs)
if external_file is None and self.data is None:
raise ValueError('must supply either external_file or data to ' + self.name)
self.bits_per_pixel = bits_per_pixel
self.dimension = dimension
self.external_file = external_file
self.starting_frame = starting_frame
self.format = format
def __init__(self, **kwargs):
lower_tier_table = popargs('lower_tier_table', kwargs)
# Initialize the DynamicTable
call_docval_func(super().__init__, kwargs)
if self['next_tier'].target.table is None:
if lower_tier_table is not None:
self['next_tier'].target.table = lower_tier_table
else:
raise ValueError(
'lower_tier_table constructor argument required')
def __init__(self, **kwargs):
super().__init__(**{kwargs_item: kwargs[kwargs_item]
for kwargs_item in kwargs.copy()
if kwargs_item != 'system'
if kwargs_item != 'amplifier'
if kwargs_item != 'adc_circuit'
})
call_docval_func(super(DataAcqDevice, self).__init__, kwargs)
self.system = kwargs['system']
self.amplifier = kwargs['amplifier']
self.adc_circuit = kwargs['adc_circuit']
def __init__(self, **kwargs):
super().__init__(
**{
kwargs_item: kwargs[kwargs_item]
for kwargs_item in kwargs.copy() if kwargs_item not in
['meters_per_pixel', 'camera_name', 'model', 'lens']
})
call_docval_func(super(CameraDevice, self).__init__, kwargs)
self.meters_per_pixel = kwargs['meters_per_pixel']
self.camera_name = kwargs['camera_name']
self.model = kwargs['model']
self.lens = kwargs['lens']
def __init__(self, **kwargs):
slice, seal, description, location, resistance, filtering, initial_access_resistance, device = popargs(
'slice', 'seal', 'description', 'location', 'resistance',
'filtering', 'initial_access_resistance', 'device', kwargs)
call_docval_func(super().__init__, kwargs)
self.slice = slice
self.seal = seal
self.description = description
self.location = location
self.resistance = resistance
self.filtering = filtering
self.initial_access_resistance = initial_access_resistance
self.device = device
def __init__(self, **kwargs):
seq_table, taxa_table, distances, tree = popargs('seq_table', 'taxa_table', 'distances', 'tree', kwargs)
call_docval_func(super().__init__, {'name': 'root'})
self.seq_table = seq_table
self.taxa_table = taxa_table
self.distances = distances
self.tree = tree
self._sanity = False
self._sanity_features = 5
self.__labels = None
self.__n_emb_components = self.taxa_table['embedding'].data.shape[1] if 'embedding' in self.taxa_table else 0
self.label_key = 'id'
self.__rev = False
def __init__(self, **kwargs):
subject = popargs('subject', kwargs)
ontology_objects, ontology_terms = popargs('ontology_objects', 'ontology_terms', kwargs)
call_docval_func(super().__init__, kwargs)
self.subject = subject
if ontology_objects is not None:
self.ontology_objects = ontology_objects
else:
self.ontology_objects = OntologyTable()
if ontology_terms is not None:
self.ontology_terms = ontology_terms
else:
self.ontology_terms = OntologyMap()
def add_epoch(self, **kwargs):
"""
Creates a new Epoch object. Epochs are used to track intervals
in an experiment, such as exposure to a certain type of stimuli
(an interval where orientation gratings are shown, or of
sparse noise) or a different paradigm (a rat exploring an
enclosure versus sleeping between explorations)
"""
self.__check_epochs()
if kwargs['tags'] is not None:
self.epoch_tags.update(kwargs['tags'])
call_docval_func(self.epochs.add_interval, kwargs)
def __init__(self, **kwargs):
axis_1_phase_map, axis_1_power_map, axis_2_phase_map, axis_2_power_map, axis_descriptions, \
focal_depth_image, sign_map, vasculature_image = popargs(
'axis_1_phase_map', 'axis_1_power_map', 'axis_2_phase_map', 'axis_2_power_map',
'axis_descriptions', 'focal_depth_image', 'sign_map', 'vasculature_image', kwargs)
call_docval_func(super(ImagingRetinotopy, self).__init__, kwargs)
self.axis_1_phase_map = axis_1_phase_map
self.axis_1_power_map = axis_1_power_map
self.axis_2_phase_map = axis_2_phase_map
self.axis_2_power_map = axis_2_power_map
self.axis_descriptions = axis_descriptions
self.focal_depth_image = focal_depth_image
self.sign_map = sign_map
self.vasculature_image = vasculature_image
def __init__(self, **kwargs):
super().__init__(**{kwargs_item: kwargs[kwargs_item]
for kwargs_item in kwargs.copy()
if kwargs_item != 'targeted_location'
if kwargs_item != 'targeted_x'
if kwargs_item != 'targeted_y'
if kwargs_item != 'targeted_z'
if kwargs_item != 'units'
})
call_docval_func(super(NwbElectrodeGroup, self).__init__, kwargs)
self.targeted_location = kwargs['targeted_location']
self.targeted_x = kwargs['targeted_x']
self.targeted_y = kwargs['targeted_y']
self.targeted_z = kwargs['targeted_z']
self.units = kwargs['units']
def add_electrode(self, **kwargs):
"""
Add a unit to the unit table.
See :py:meth:`~hdmf.common.DynamicTable.add_row` for more details.
Required fields are *x*, *y*, *z*, *imp*, *location*, *filtering*,
*group* and any columns that have been added
(through calls to `add_electrode_columns`).
"""
self.__check_electrodes()
d = _copy.copy(
kwargs['data']) if kwargs.get('data') is not None else kwargs
if d.get('group_name', None) is None:
d['group_name'] = d['group'].name
call_docval_func(self.electrodes.add_row, d)
def __init__(self, **kwargs):
kwargs['name'] = 'subject'
call_docval_func(super(Subject, self).__init__, kwargs)
self.age = getargs('age', kwargs)
self.description = getargs('description', kwargs)
self.genotype = getargs('genotype', kwargs)
self.sex = getargs('sex', kwargs)
self.species = getargs('species', kwargs)
self.subject_id = getargs('subject_id', kwargs)
self.weight = getargs('weight', kwargs)
date_of_birth = getargs('date_of_birth', kwargs)
if date_of_birth and date_of_birth.tzinfo is None:
self.date_of_birth = _add_missing_timezone(date_of_birth)
else:
self.date_of_birth = date_of_birth
def get_manager(**kwargs):
'''
Get a BuildManager to use for I/O using the given extensions. If no extensions are provided,
return a BuildManager that uses the core namespace
'''
type_map = call_docval_func(get_type_map, kwargs)
return BuildManager(type_map)
def __init__(self, **kwargs):
call_docval_func(super().__init__, kwargs)
notes, description = getargs('notes', 'description', kwargs)
if notes != '':
warn(
'The `notes` argument of ScratchData.__init__ will be deprecated. Use description instead.',
PendingDeprecationWarning)
if notes != '' and description != '':
raise ValueError(
'Cannot provide both notes and description to ScratchData.__init__. The description '
'argument is recommended.')
description = notes
if not description:
warn(
'ScratchData.description will be required in a future major release of PyNWB.',
PendingDeprecationWarning)
self.description = description
def __init__(self, **kwargs):
columns = kwargs['columns']
if columns is None:
taxon_id, rep_idx, taxa_table = popargs('taxon_id', 'rep_idx',
'taxa_table', kwargs)
if not isinstance(taxon_id, VectorData):
taxon_id = VectorData('taxon_id',
'NCBI accession',
data=taxon_id)
if not isinstance(rep_idx, VectorData):
if taxa_table is None:
raise ValueError('taxa_table must be provided if writing')
rep_idx = DynamicTableRegion('rep_idx', rep_idx,
'representative taxon',
taxa_table)
kwargs['columns'] = [taxon_id, rep_idx]
call_docval_func(super().__init__, kwargs)