Raise user warning when numbers contain multiple series

qiskit_experiments/curve_analysis/scatter_table.py

@@ -14,6 +14,7 @@
 from __future__ import annotations
 
 import logging
+import warnings
 from collections.abc import Iterator
 from typing import Any
 from itertools import groupby
@@ -116,6 +117,7 @@ def get_x(
         kind: int | str | None = None,
         category: str | None = None,
         analysis: str | None = None,
+        check_unique: bool = True,
     ) -> np.ndarray:
         """Get subset of X values.
 
@@ -125,11 +127,16 @@ def get_x(
             kind: Identifier of the data, either data UID or name.
             category: Name of data category.
             analysis: Name of analysis.
+            check_unique: Set True to check if multiple series are contained.
+                When multiple series are contained, it raises a user warning.
 
         Returns:
             Numpy array of X values.
         """
-        return self.filter(kind, category, analysis).x
+        sub_table = self.filter(kind, category, analysis)
+        if check_unique:
+            self._warn_composite_data(sub_table)
+        return sub_table.x
 
     @property
     def y(self) -> np.ndarray:
@@ -145,6 +152,7 @@ def get_y(
         kind: int | str | None = None,
         category: str | None = None,
         analysis: str | None = None,
+        check_unique: bool = True,
     ) -> np.ndarray:
         """Get subset of Y values.
 
@@ -154,11 +162,16 @@ def get_y(
             kind: Identifier of the data, either data UID or name.
             category: Name of data category.
             analysis: Name of analysis.
+            check_unique: Set True to check if multiple series are contained.
+                When multiple series are contained, it raises a user warning.
 
         Returns:
             Numpy array of Y values.
         """
-        return self.filter(kind, category, analysis).y
+        sub_table = self.filter(kind, category, analysis)
+        if check_unique:
+            self._warn_composite_data(sub_table)
+        return sub_table.y
 
     @property
     def y_err(self) -> np.ndarray:
@@ -174,6 +187,7 @@ def get_y_err(
         kind: int | str | None = None,
         category: str | None = None,
         analysis: str | None = None,
+        check_unique: bool = True,
     ) -> np.ndarray:
         """Get subset of standard deviation of Y values.
 
@@ -183,11 +197,16 @@ def get_y_err(
             kind: Identifier of the data, either data UID or name.
             category: Name of data category.
             analysis: Name of analysis.
+            check_unique: Set True to check if multiple series are contained.
+                When multiple series are contained, it raises a user warning.
 
         Returns:
             Numpy array of Y error values.
         """
-        return self.filter(kind, category, analysis).y_err
+        sub_table = self.filter(kind, category, analysis)
+        if check_unique:
+            self._warn_composite_data(sub_table)
+        return sub_table.y_err
 
     @property
     def name(self) -> np.ndarray:
@@ -339,6 +358,27 @@ def _format_table(cls, data: pd.DataFrame) -> pd.DataFrame:
             .reset_index(drop=True)
         )
 
+    @staticmethod
+    def _warn_composite_data(table: ScatterTable):
+        if len(table._data.name.unique()) > 1:
+            warnings.warn(
+                "Returned data contains multiple series. "
+                "You may want to filter the data by a specific kind identifier.",
+                UserWarning,
+            )
+        if len(table._data.category.unique()) > 1:
+            warnings.warn(
+                "Returned data contains multiple categories. "
+                "You may want to filter the data by a specific category name.",
+                UserWarning,
+            )
+        if len(table._data.analysis.unique()) > 1:
+            warnings.warn(
+                "Returned data contains multiple datasets from different component analyses. "
+                "You may want to filter the data by a specific analysis name.",
+                UserWarning,
+            )
+
     @property
     @deprecate_func(
         since="0.6",

test/curve_analysis/test_scatter_table.py

@@ -13,7 +13,6 @@
 """Test scatter table."""
 
 from test.base import QiskitExperimentsTestCase
-
 import pandas as pd
 import numpy as np
 
@@ -152,16 +151,23 @@ def test_get_subset_numbers(self):
         """Test end-user shortcut for getting the subset of x, y, y_err data."""
         obj = ScatterTable.from_dataframe(self.reference)
 
+        np.testing.assert_array_equal(obj.get_x("model1", "raw", "Fit1"), np.array([0.100, 0.200]))
+        np.testing.assert_array_equal(obj.get_y("model1", "raw", "Fit1"), np.array([0.192, 0.854]))
         np.testing.assert_array_equal(
-            obj.get_x("model1", "raw"), np.array([0.100, 0.200, 0.100, 0.200])
-        )
-        np.testing.assert_array_equal(
-            obj.get_y("model1", "raw"), np.array([0.192, 0.854, 0.567, 0.488])
-        )
-        np.testing.assert_array_equal(
-            obj.get_y_err("model1", "raw"), np.array([0.002, 0.090, 0.033, 0.038])
+            obj.get_y_err("model1", "raw", "Fit1"), np.array([0.002, 0.090])
         )
 
+    def test_warn_composite_values(self):
+        """Test raise warning when returned x, y, y_err data contains multiple data series."""
+        obj = ScatterTable.from_dataframe(self.reference)
+
+        with self.assertWarns(UserWarning):
+            obj.get_x()
+        with self.assertWarns(UserWarning):
+            obj.get_y()
+        with self.assertWarns(UserWarning):
+            obj.get_y_err()
+
     def test_filter_data_by_class_id(self):
         """Test filter table data with data UID."""
         obj = ScatterTable.from_dataframe(self.reference)