Handle 0-D result streams in XarrayDataFetcher alongside swept arrays.

qualibration_libs/data/fetcher.py

@@ -198,6 +198,25 @@ def update_dataset(self):
         if dims_order[0] not in ["qubit", "qubit_pair"]:
             logger.error("first axis must be either qubit or qubit_pair")
 
+        # 0-D ndarray streams (e.g. shot counter "n" from n_st.save("n")) sit next to 1-D
+        # swept I/Q buffers. They must not participate in the uniform-shape check below.
+        # Expose scalars on self.data for progress_counter(..., data_fetcher.get("n", 0)).
+        for label in list(raw_data_arrays.keys()):
+            arr = raw_data_arrays[label]
+            if isinstance(arr, np.ndarray) and arr.ndim == 0:
+                self.data[label] = arr.item()
+                del raw_data_arrays[label]
+                logger.debug(
+                    "Extracted 0-D stream %r for fetcher.data; excluded from swept-array layout",
+                    label,
+                )
+
+        if not raw_data_arrays:
+            logger.debug(
+                "No swept-array handles after 0-D extraction; returning current dataset."
+            )
+            return self.dataset
+
         # Determine reference shape from non-None entries.
         data_arrays = [d for d in raw_data_arrays.values() if isinstance(d, np.ndarray)]
         if data_arrays:

qualibration_libs/tests/test_fetcher.py

@@ -1,7 +1,10 @@
 """Tests for exception handling in data/fetcher.py."""
 
+import numpy as np
 import pytest
-from unittest.mock import Mock
+import xarray as xr
+from unittest.mock import MagicMock, Mock, patch
+
 from qualibration_libs.data.fetcher import XarrayDataFetcher
 
 
@@ -29,3 +32,64 @@ def test_invalid_key_raises_keyerror(self):
         assert "Data key 'invalid_key' not found in XarrayDataFetcher" in error_msg
         assert "Available keys: 'dataset'" in error_msg
         assert exc_info.value.__cause__ is not None
+
+
+@patch("qualibration_libs.data.fetcher.fetching_tool")
+def test_zero_dim_shot_counter_with_swept_iq_does_not_raise(mock_fetching_tool):
+    """Regression: n_st.save('n') yields 0-D 'n' while I*/Q* are 1-D along detuning."""
+    mock_result = MagicMock()
+    mock_result.fetch_all.return_value = [
+        np.array(42, dtype=np.int64),
+        np.linspace(0, 1, 5),
+        np.linspace(1, 0, 5),
+    ]
+    mock_result.is_processing.return_value = False
+    mock_result.get_start_time.return_value = 0.0
+    mock_fetching_tool.return_value = mock_result
+
+    mock_job = Mock()
+    mock_job.result_handles.keys.return_value = ["n", "I1", "Q1"]
+
+    axes = {
+        "qubit": xr.DataArray(["q0"]),
+        "detuning": xr.DataArray(np.linspace(-1e6, 1e6, 5), attrs={"units": "Hz"}),
+    }
+    fetcher = XarrayDataFetcher(job=mock_job, axes=axes)
+    fetcher.retrieve_latest_data()
+    fetcher.update_dataset()
+
+    assert fetcher.get("n") == 42
+    assert "I" in fetcher.dataset.data_vars
+    assert "Q" in fetcher.dataset.data_vars
+    assert fetcher.dataset["I"].shape == (1, 5)
+    assert fetcher.dataset["Q"].shape == (1, 5)
+
+
+@patch("qualibration_libs.data.fetcher.fetching_tool")
+def test_zero_dim_n_two_qubits(mock_fetching_tool):
+    mock_result = MagicMock()
+    mock_result.fetch_all.return_value = [
+        np.array(100, dtype=np.int32),
+        np.arange(3.0),
+        np.arange(3.0, 6.0),
+        np.arange(6.0, 9.0),
+        np.arange(9.0, 12.0),
+    ]
+    mock_result.is_processing.return_value = False
+    mock_result.get_start_time.return_value = 0.0
+    mock_fetching_tool.return_value = mock_result
+
+    mock_job = Mock()
+    mock_job.result_handles.keys.return_value = ["n", "I1", "Q1", "I2", "Q2"]
+
+    axes = {
+        "qubit": xr.DataArray(["q0", "q1"]),
+        "detuning": xr.DataArray(np.zeros(3)),
+    }
+    fetcher = XarrayDataFetcher(job=mock_job, axes=axes)
+    fetcher.retrieve_latest_data()
+    fetcher.update_dataset()
+
+    assert fetcher.get("n") == 100
+    assert fetcher.dataset["I"].shape == (2, 3)
+    assert fetcher.dataset["Q"].shape == (2, 3)