Dataset Attributes#

Required dataset attributes#

Required dataset attributes are specified in a dataclass QDatasetAttrs. All attributes are mandatory to be present in the dataset but can be None or empty.

import datetime
from quantify_core.utilities import examples_support

examples_support.mk_dataset_attrs(
    dataset_name="Bias scan",
    timestamp_start=datetime.datetime.now().astimezone().isoformat(),
    timestamp_end=(datetime.datetime.now().astimezone() + datetime.timedelta(seconds=120)).isoformat(),
    dataset_state="done",
)
{'tuid': '20240228-040756-481-966d78',
 'dataset_name': 'Bias scan',
 'dataset_state': 'done',
 'timestamp_start': '2024-02-28T04:07:56.481834+01:00',
 'timestamp_end': '2024-02-28T04:09:56.481860+01:00',
 'quantify_dataset_version': '2.0.0',
 'software_versions': {},
 'relationships': [],
 'json_serialize_exclude': []}

It may be necessary to specify versions of the key software components that were used to generate a dataset. This can be done using software_versions attribute, using either a published version or Git commit hash:

examples_support.mk_dataset_attrs(
    dataset_name="My experiment",
    timestamp_start=datetime.datetime.now().astimezone().isoformat(),
    timestamp_end=(datetime.datetime.now().astimezone() + datetime.timedelta(seconds=120)).isoformat(),
    software_versions={
        "lab_fridge_magnet_driver": "1.4.2",  # software version/tag
        "my_lab_repo": "9d8acf63f48c469c1b9fa9f2c3cf230845f67b18",  # git commit hash
    },
)
{'tuid': '20240228-040756-494-72ac02',
 'dataset_name': 'My experiment',
 'dataset_state': None,
 'timestamp_start': '2024-02-28T04:07:56.494161+01:00',
 'timestamp_end': '2024-02-28T04:09:56.494176+01:00',
 'quantify_dataset_version': '2.0.0',
 'software_versions': {'lab_fridge_magnet_driver': '1.4.2',
  'my_lab_repo': '9d8acf63f48c469c1b9fa9f2c3cf230845f67b18'},
 'relationships': [],
 'json_serialize_exclude': []}

Required dataset coordinate attributes#

Required coordinate data array attributes are specified in a dataclass QCoordAttrs. All attributes are mandatory to be present in the dataset but can be None.

from quantify_core.utilities import examples_support
examples_support.mk_main_coord_attrs() 
{'unit': '',
 'long_name': '',
 'is_main_coord': True,
 'uniformly_spaced': True,
 'is_dataset_ref': False,
 'json_serialize_exclude': []}
examples_support.mk_secondary_coord_attrs()
{'unit': '',
 'long_name': '',
 'is_main_coord': False,
 'uniformly_spaced': True,
 'is_dataset_ref': False,
 'json_serialize_exclude': []}

Required dataset data variables attributes#

Required data variable data array attributes are specified in a dataclass QVarAttrs. All attributes are mandatory to be present in the dataset but can be None.

from quantify_core.utilities import examples_support
examples_support.mk_main_var_attrs(coords=["time"])
{'unit': '',
 'long_name': '',
 'is_main_var': True,
 'uniformly_spaced': True,
 'grid': True,
 'is_dataset_ref': False,
 'has_repetitions': False,
 'json_serialize_exclude': [],
 'coords': ['time']}
examples_support.mk_secondary_var_attrs(coords=["cal"])
{'unit': '',
 'long_name': '',
 'is_main_var': False,
 'uniformly_spaced': True,
 'grid': True,
 'is_dataset_ref': False,
 'has_repetitions': False,
 'json_serialize_exclude': [],
 'coords': ['cal']}

Relationship between primary and secondary variables#

This is how the attributes of a dataset containing a q0 main variable and q0_cal secondary variables would look like. The q0_cal corresponds to calibrations datapoints.

from quantify_core.data.dataset_attrs import QDatasetIntraRelationship
from quantify_core.utilities import examples_support

examples_support.mk_dataset_attrs(
    relationships=[
        QDatasetIntraRelationship(
            item_name="q0",
            relation_type="calibration",
            related_names=["q0_cal"],
        ).to_dict()
    ]
)
{'tuid': '20240228-040756-538-c6ee64',
 'dataset_name': '',
 'dataset_state': None,
 'timestamp_start': None,
 'timestamp_end': None,
 'quantify_dataset_version': '2.0.0',
 'software_versions': {},
 'relationships': [{'item_name': 'q0',
   'relation_type': 'calibration',
   'related_names': ['q0_cal'],
   'relation_metadata': {}}],
 'json_serialize_exclude': []}

See Quantify dataset - examples for examples with more context.