update tests

qiskit_experiments/curve_analysis/composite_curve_analysis.py

@@ -320,9 +320,9 @@ def _run_analysis(
 
             # After the quality is determined, plot can become a boolean flag for whether
             # to generate the figure
-            plot = plot == "always" or (plot == "selective" and quality == "bad")
+            plot_bool = plot == "always" or (plot == "selective" and quality == "bad")
 
-            if plot:
+            if plot_bool:
                 if analysis.options.plot_raw_data:
                     for model in analysis.models:
                         sub_data = processed_data.get_subset_of(model._name)
@@ -359,7 +359,7 @@ def _run_analysis(
                 )
 
                 # Draw fit result
-                if plot:
+                if plot_bool:
                     x_interp = np.linspace(
                         np.min(formatted_data.x), np.max(formatted_data.x), num=100
                     )

qiskit_experiments/curve_analysis/curve_analysis.py

@@ -422,9 +422,9 @@ def _run_analysis(
 
         # After the quality is determined, plot can become a boolean flag for whether
         # to generate the figure
-        plot = plot == "always" or (plot == "selective" and quality == "bad")
+        plot_bool = plot == "always" or (plot == "selective" and quality == "bad")
 
-        if plot:
+        if plot_bool:
             self.plotter.set_supplementary_data(fit_red_chi=fit_data.reduced_chisq)
             for model in self._models:
                 if self.options.plot_raw_data:
@@ -464,7 +464,7 @@ def _run_analysis(
             self.plotter.set_supplementary_data(primary_results=primary_results)
 
             # Draw fit curves and report
-            if plot:
+            if plot_bool:
                 for model in self._models:
                     sub_data = formatted_data.get_subset_of(model._name)
                     if sub_data.x.size == 0:

releasenotes/notes/selective-figure-generation-0864216f34d3486f.yaml

@@ -1,12 +1,12 @@
 ---
 features:
   - |
-    The ``generate_figures`` parameter has been added to composite experiments to control figure
+    The ``generate_figures`` parameter has been added to :class:`.CompositeExperiment` to control figure
     generation. By default, ``generate_figures`` is ``always``, meaning figures will always be generated.
     If ``generate_figures`` is set to ``selective``, then only figures for analysis results of bad
     quality will be generated. If ``generate_figures`` is set to ``never``, then figures will never be
     generated. This behavior can be overridden for individual analyses by setting the analysis option
-    ``plot``. In the next release, the default behavior of ``generate_figures`` will change to ``selective``.
+    ``plot`` for :class:`.CurveAnalysis`.
 fixes:
   - |
     Fixed a bug where setting the analysis option ``plot_raw_data`` to ``True`` still caused formatted data

test/curve_analysis/test_baseclass.py

@@ -31,6 +31,7 @@
 from qiskit_experiments.data_processing import DataProcessor, Probability
 from qiskit_experiments.exceptions import AnalysisError
 from qiskit_experiments.framework import ExperimentData, AnalysisResultData, CompositeAnalysis
+from qiskit_experiments.database_service.exceptions import ExperimentEntryNotFound
 
 
 class CurveAnalysisTestCase(QiskitExperimentsTestCase):
@@ -405,7 +406,7 @@ def _initialize(self, experiment_data):
     @unpack
     def test_end_to_end_parallel_analysis(self, plot_flag, figure_flag, n_figures):
         """Integration test for running two curve analyses in parallel, including
-           selective figure generation."""
+        selective figure generation."""
 
         analysis1 = CurveAnalysis(models=[ExpressionModel(expr="amp * exp(-x/tau)", name="test")])
         analysis1.set_options(
@@ -450,6 +451,46 @@ def test_end_to_end_parallel_analysis(self, plot_flag, figure_flag, n_figures):
 
         self.assertEqual(len(result._figures), n_figures)
 
+    def test_selective_figure_generation(self):
+        """Test that selective figure generation based on quality works as expected."""
+
+        # analysis with intentionally bad fit
+        analysis1 = CurveAnalysis(models=[ExpressionModel(expr="amp * exp(-x)", name="test")])
+        analysis1.set_options(
+            data_processor=DataProcessor(input_key="counts", data_actions=[Probability("1")]),
+            p0={"amp": 0.7},
+            result_parameters=["amp"],
+        )
+        analysis2 = CurveAnalysis(models=[ExpressionModel(expr="amp * exp(-x/tau)", name="test")])
+        analysis2.set_options(
+            data_processor=DataProcessor(input_key="counts", data_actions=[Probability("1")]),
+            p0={"amp": 0.7, "tau": 0.5},
+            result_parameters=["amp", "tau"],
+        )
+        composite = CompositeAnalysis(
+            [analysis1, analysis2], flatten_results=True, generate_figures="selective"
+        )
+        amp1 = 0.7
+        tau1 = 0.5
+        amp2 = 0.7
+        tau2 = 0.5
+
+        x = np.linspace(0, 1, 100)
+        y1 = amp1 * np.exp(-x / tau1)
+        y2 = amp2 * np.exp(-x / tau2)
+
+        test_data = self.parallel_sampler(x, y1, y2)
+        result = composite.run(test_data)
+        self.assertExperimentDone(result)
+
+        for i, res in enumerate(result.analysis_results()):
+            # only generate a figure if the quality is bad
+            if res.quality == "bad":
+                result.figure(i)
+            else:
+                with self.assertRaises(ExperimentEntryNotFound):
+                    result.figure(i)
+
     def test_end_to_end_zero_yerr(self):
         """Integration test for an edge case of having zero y error.