Merge pull request #7891 from esbenh4/esh/add_shapes_to_dataset_def

Improvement: added shapes to DatasetDefinition

Author: jenshnielsen

docs/changes/newsfragments/7891.improved

@@ -0,0 +1 @@
+Enabled setting shape of Measurement in measurement_extensions.py. Added `shapes` to DataSetDefinition and use it in setup_measurement_isntances to set shape of measurement. Added new tests for new use cases.

src/qcodes/dataset/measurement_extensions.py

@@ -16,6 +16,7 @@
 from qcodes.parameters.parameter_base import ParameterBase
 
 if TYPE_CHECKING:
+    from qcodes.dataset.descriptions.versioning.rundescribertypes import Shapes
     from qcodes.dataset.experiment_container import Experiment
 
 TRACER = trace.get_tracer(__name__)
@@ -37,6 +38,11 @@ class DataSetDefinition:
     experiment: Experiment | None = None
     """An optional argument specifying which Experiment this dataset should be
     written to"""
+    shapes: Shapes | None = None
+    """An optional dictionary from dependent parameter names to a tuple of
+    integers describing the shape of the measurement. This is used to
+    specify the shape of the dataset.
+    See :class:`qcodes.dataset.measurements.Measurement.set_shapes`."""
     metadata: Mapping[str, Any] | None = None
     """An optional dictionary of metadata that will be added to the dataset
     generated by this definition"""
@@ -69,6 +75,8 @@ def setup_measurement_instances(
             meas.register_parameter(param)
         for param in ds_def.dependent:
             meas.register_parameter(param, setpoints=ds_def.independent)
+        if ds_def.shapes is not None:
+            meas.set_shapes(ds_def.shapes)
         measurements.append(meas)
     return measurements
 

tests/dataset/test_measurement_extensions.py

@@ -21,6 +21,7 @@
     LinSweeper,
     datasaver_builder,
     dond_into,
+    setup_measurement_instances,
 )
 from qcodes.parameters import Parameter, ParameterWithSetpoints
 from qcodes.validators import Arrays
@@ -490,3 +491,150 @@ def test_context_with_override_experiment(
 
     assert datasets[0].exp_name == experiment2.name
     assert datasets[1].exp_name == experiment2.name
+
+
+def test_shapes_in_dataset_definition_with_scalar_params(
+    default_params, default_database_and_experiment
+):
+    """Test that shapes specified in DataSetDefinition are stored on the dataset."""
+    _ = default_database_and_experiment
+    set1, set2, _, meas1, meas2, _ = default_params
+
+    expected_shapes = {
+        meas1.register_name: (11, 11),
+        meas2.register_name: (11, 11),
+    }
+    dataset_definition = [
+        DataSetDefinition(
+            name="dataset_with_shapes",
+            independent=[set1, set2],
+            dependent=[meas1, meas2],
+            shapes=expected_shapes,
+        ),
+    ]
+    with datasaver_builder(dataset_definition) as datasavers:
+        for _ in LinSweeper(set1, 0, 10, 11, 0.001):
+            sweep1 = LinSweep(set2, 0, 10, 11, 0.001)
+            dond_into(datasavers[0], sweep1, meas1, meas2, additional_setpoints=(set1,))
+        datasets = [datasaver.dataset for datasaver in datasavers]
+
+    assert datasets[0].description.shapes == expected_shapes
+
+
+def test_shapes_in_dataset_definition_with_pws(
+    pws_params, default_database_and_experiment
+):
+    """Test that shapes for ParameterWithSetpoints are stored on the dataset."""
+    _ = default_database_and_experiment
+    pws1, set1 = pws_params
+
+    expected_shapes = {
+        pws1.register_name: (11, 11),
+    }
+    dataset_definition = [
+        DataSetDefinition(
+            name="dataset_pws_shapes",
+            independent=[set1],
+            dependent=[pws1],
+            shapes=expected_shapes,
+        ),
+    ]
+    with datasaver_builder(dataset_definition) as datasavers:
+        for _ in LinSweeper(set1, 0, 10, 11, 0.001):
+            dond_into(datasavers[0], pws1, additional_setpoints=(set1,))
+        datasets = [datasaver.dataset for datasaver in datasavers]
+
+    assert datasets[0].description.shapes == expected_shapes
+
+
+def test_shapes_none_by_default(default_params, default_database_and_experiment):
+    """Test that shapes is None when not specified in DataSetDefinition."""
+    _ = default_database_and_experiment
+    set1, _, _, meas1, _, _ = default_params
+
+    dataset_definition = [
+        DataSetDefinition(
+            name="dataset_no_shapes",
+            independent=[set1],
+            dependent=[meas1],
+        ),
+    ]
+    with datasaver_builder(dataset_definition) as datasavers:
+        for _ in LinSweeper(set1, 0, 5, 6, 0.001):
+            datasavers[0].add_result((set1, set1()), (meas1, meas1()))
+        datasets = [datasaver.dataset for datasaver in datasavers]
+
+    assert datasets[0].description.shapes is None
+
+
+def test_setup_measurement_instances_sets_shapes(
+    default_params, default_database_and_experiment
+):
+    """Test that setup_measurement_instances correctly sets shapes on Measurement."""
+    _ = default_database_and_experiment
+    set1, _, _, meas1, _, _ = default_params
+
+    expected_shapes = {meas1.register_name: (5,)}
+    dataset_definitions = [
+        DataSetDefinition(
+            name="test_shapes",
+            independent=[set1],
+            dependent=[meas1],
+            shapes=expected_shapes,
+        ),
+    ]
+    measurements = setup_measurement_instances(dataset_definitions)
+    assert len(measurements) == 1
+    assert measurements[0]._shapes == expected_shapes
+
+
+def test_setup_measurement_instances_no_shapes(
+    default_params, default_database_and_experiment
+):
+    """Test that setup_measurement_instances leaves shapes as None when not specified."""
+    _ = default_database_and_experiment
+    set1, _, _, meas1, _, _ = default_params
+
+    dataset_definitions = [
+        DataSetDefinition(
+            name="test_no_shapes",
+            independent=[set1],
+            dependent=[meas1],
+        ),
+    ]
+    measurements = setup_measurement_instances(dataset_definitions)
+    assert len(measurements) == 1
+    assert measurements[0]._shapes is None
+
+
+def test_shapes_with_multiple_datasets(default_params, default_database_and_experiment):
+    """Test shapes are correctly applied to multiple datasets independently."""
+    _ = default_database_and_experiment
+    set1, set2, set3, meas1, _, meas3 = default_params
+
+    shapes_1 = {meas1.register_name: (11, 11)}
+    shapes_2 = {meas3.register_name: (11, 11)}
+    dataset_definition = [
+        DataSetDefinition(
+            name="dataset_1",
+            independent=[set1, set2],
+            dependent=[meas1],
+            shapes=shapes_1,
+        ),
+        DataSetDefinition(
+            name="dataset_2",
+            independent=[set1, set3],
+            dependent=[meas3],
+            shapes=shapes_2,
+        ),
+    ]
+    with datasaver_builder(dataset_definition) as datasavers:
+        for _ in LinSweeper(set1, 0, 10, 11, 0.001):
+            sweep1 = LinSweep(set2, 0, 10, 11, 0.001)
+            sweep2 = LinSweep(set3, -10, 0, 11, 0.001)
+            dond_into(datasavers[0], sweep1, meas1, additional_setpoints=(set1,))
+            dond_into(datasavers[1], sweep2, meas3, additional_setpoints=(set1,))
+        datasets = [datasaver.dataset for datasaver in datasavers]
+
+    assert datasets[0].description.shapes == shapes_1
+    assert datasets[1].description.shapes == shapes_2