def test_add_attribute(self):
spec = GroupSpec('A test group',
name='root_constructor',
groups=self.subgroups,
datasets=self.datasets,
linkable=False)
for attrspec in self.attributes:
spec.add_attribute(**attrspec)
self.assertListEqual(spec['attributes'], self.attributes)
self.assertListEqual(spec['datasets'], self.datasets)
self.assertNotIn('data_type_def', spec)
self.assertIs(spec, self.subgroups[0].parent)
self.assertIs(spec, self.subgroups[1].parent)
self.assertIs(spec, spec.attributes[0].parent)
self.assertIs(spec, spec.attributes[1].parent)
self.assertIs(spec, self.datasets[0].parent)
self.assertIs(spec, self.datasets[1].parent)
json.dumps(spec)
def main():
# these arguments were auto-generated from your cookie-cutter inputs
ns_builder = NamespaceBuilder(
doc='An extension for storing point clouds in an NWB file',
name='ndx-point-cloud-table',
version='0.1.0',
author=list(map(str.strip, 'Ben Dichter'.split(','))),
contact=list(map(str.strip, '*****@*****.**'.split(','))))
ns_builder.include_type('DynamicTable', namespace='hdmf-common')
ns_builder.include_type('VectorData', namespace='hdmf-common')
ns_builder.include_type('VectorIndex', namespace='hdmf-common')
PointCloudTable = GroupSpec(
doc='type for storing time-varying 3D point clouds',
data_type_def='PointCloudTable',
data_type_inc='DynamicTable',
default_name='PointCloudTable')
PointCloudTable.add_dataset(name='timestamps',
data_type_inc='VectorData',
doc='time of each frame in seconds',
dims=('num_frames', ),
shape=(None, ),
dtype='float')
PointCloudTable.add_dataset(
name='point_cloud',
data_type_inc='VectorData',
doc='datapoints locations over time',
dims=('time', '[x, y, z]'),
shape=(None, 3),
dtype='float',
)
PointCloudTable.add_dataset(
name='point_cloud_index',
data_type_inc='VectorIndex',
doc='datapoints indices',
dims=('index', ),
shape=(None, ),
)
PointCloudTable.add_dataset(name='color',
data_type_inc='VectorData',
doc='datapoints color',
dims=('time', '[r, g, b]'),
shape=(None, 3),
dtype='float',
quantity='?')
PointCloudTable.add_dataset(name='color_index',
data_type_inc='VectorIndex',
doc='datapoints colors indices',
dims=('index', ),
shape=(None, ),
quantity='?')
PointCloudTable.add_attribute(
name='colnames',
dims=('num_columns', ),
shape=(None, ),
doc=
'The names of the columns in this table. This should be used to specify '
'an order to the columns.',
default_value=('point_cloud', ),
dtype='text')
new_data_types = [PointCloudTable]
# export the spec to yaml files in the spec folder
output_dir = os.path.abspath(
os.path.join(os.path.dirname(__file__), '..', '..', 'spec'))
export_spec(ns_builder, new_data_types, output_dir)