Several fixes and improvements

src/access/profiling/experiment.py

@@ -15,6 +15,18 @@
 logger = logging.getLogger(__name__)
 
 
+def _make_unique_region_names(regions: list[object]) -> list[object]:
+    """Return region names with deterministic suffixes for duplicates."""
+
+    counts: dict[object, int] = {}
+    unique_regions: list[object] = []
+    for region in regions:
+        count = counts.get(region, 0) + 1
+        counts[region] = count
+        unique_regions.append(region if count == 1 else f"{region}_{count}")
+    return unique_regions
+
+
 class ProfilingLog:
     """Represents a profiling log file.
 
@@ -61,7 +73,7 @@ def parse(self) -> xr.Dataset:
 
         has_pe = "pe" in data
         dims = ["region", "pe"] if has_pe else ["region"]
-        coords: dict = {"region": data["region"]}
+        coords: dict = {"region": _make_unique_region_names(list(data["region"]))}
         if has_pe:
             coords["pe"] = data["pe"]
 

src/access/profiling/manager.py

@@ -65,9 +65,11 @@ def __repr__(self) -> str:
         if self.data == {}:
             summary += indent * 2 + "No parsed data.\n"
         else:
-            for name, ds in self.data.items():
+            for name, exp_data in self.data.items():
                 summary += indent * 2 + f"'{name}':\n"
-                summary += textwrap.indent(f"{ds}\n", indent * 3)
+                for comp_name, ds in exp_data.items():
+                    summary += indent * 3 + f"'{comp_name}':\n"
+                    summary += textwrap.indent(f"{ds}\n", indent * 4)
         return summary
 
     @abstractmethod
@@ -202,9 +204,20 @@ def plot_scaling_data(
             region_relabel_map (dict | None): Optional mapping to relabel regions in the plots.
         """
 
+        exp_names = experiments if experiments is not None else list(self.data.keys())
+        if not exp_names:
+            raise ValueError("No experiments selected for scaling plot.")
+
+        missing_experiments = [exp_name for exp_name in exp_names if exp_name not in self.data]
+        if missing_experiments:
+            raise ValueError(
+                f"No parsed profiling data found for experiment(s): {missing_experiments}. "
+                f"Available experiments: {list(self.data.keys())}."
+            )
+
         # Find number of cpus used for each experiment
         ncpus = {}
-        for exp_name in self.data:
+        for exp_name in exp_names:
             with self.experiments[exp_name].directory() as (exp_path, run_path):
                 # Find number of cpus used
                 ncpus[exp_name] = self.parse_ncpus(exp_path, run_path)
@@ -213,15 +226,19 @@ def plot_scaling_data(
         scaling_data = []
         for component, component_regions in zip(components, regions, strict=True):
             component_data = None
-            for exp_name in self.data:
-                # Skip experiments not in the specified list
-                if experiments is not None and exp_name not in experiments:
-                    continue
-
+            for exp_name in exp_names:
                 ds = self.data[exp_name].get(component)
                 if ds is None:
                     raise ValueError(f"No profiling data found for component '{component}' in experiment '{exp_name}'.")
 
+                available_regions = ds.coords["region"].values.tolist()
+                missing_regions = [region for region in component_regions if region not in available_regions]
+                if missing_regions:
+                    raise ValueError(
+                        f"Requested region(s) {missing_regions} not found for component '{component}' "
+                        f"in experiment '{exp_name}'. Available regions: {available_regions}."
+                    )
+
                 # Select only the desired regions
                 ds = ds.sel(region=component_regions)
 

tests/test_experiment.py

@@ -44,6 +44,28 @@ def test_profiling_log():
     mock_parser.parse.assert_called_once_with(mock_path)
 
 
+def test_profiling_log_duplicate_regions():
+    """Test duplicate region names are renamed correctly during parsing."""
+
+    mock_parser = mock.MagicMock(autospec=True)
+    mock_parser.metrics = [tavg]
+    mock_parser.parse.return_value = {
+        "region": ["Region 1", "Region 1", "Region 2", "Region 1"],
+        tavg: [1.0, 2.0, 3.0, 4.0],
+    }
+
+    mock_path = mock.MagicMock()
+    profiling_log = ProfilingLog(filepath=mock_path, parser=mock_parser)
+
+    dataset = profiling_log.parse()
+
+    expected_unique_regions = ["Region 1", "Region 1_2", "Region 2", "Region 1_3"]
+    assert list(dataset["region"].values) == expected_unique_regions
+    assert list(dataset[tavg].values) == [1.0, 2.0, 3.0, 4.0]
+    assert mock_parser.parse.call_count == 1
+    assert mock_parser.parse.return_value["region"] == ["Region 1", "Region 1", "Region 2", "Region 1"]
+
+
 def test_profiling_log_hierarchical():
     """Test ProfilingLog.parse() with hierarchical (nested dict) parser output."""
     mock_parser = mock.MagicMock(autospec=True)

tests/test_manager.py

@@ -316,6 +316,60 @@ def test_scaling_data(mock_plot, scaling_data):
     assert (Path("4cpu"), Path("/fake/runs/4cpu")) in manager._parse_ncpus_calls
 
 
+def test_scaling_data_missing_region_raises_value_error(scaling_data):
+    """Test plot_scaling_data raises a clear error when a requested region is missing."""
+
+    paths, ncpus, datasets = scaling_data
+    manager = MockProfilingManager(paths, ncpus, datasets)
+
+    with pytest.raises(ValueError, match="Requested region\\(s\\)") as exc_info:
+        manager.plot_scaling_data(
+            components=["component"],
+            regions=[["Missing Region"]],
+            metric=tavg,
+            experiments=["1cpu"],
+        )
+
+    message = str(exc_info.value)
+    assert "Missing Region" in message
+    assert "component 'component'" in message
+    assert "experiment '1cpu'" in message
+
+
+def test_scaling_data_no_selected_experiments_raises_value_error(scaling_data):
+    """Test plot_scaling_data raises when no experiments are selected."""
+
+    paths, ncpus, datasets = scaling_data
+    manager = MockProfilingManager(paths, ncpus, datasets)
+
+    with pytest.raises(ValueError, match="No experiments selected for scaling plot"):
+        manager.plot_scaling_data(
+            components=["component"],
+            regions=[["Region 1"]],
+            metric=tavg,
+            experiments=[],
+        )
+
+
+def test_scaling_data_missing_experiment_data_raises_value_error(scaling_data):
+    """Test plot_scaling_data raises when selected experiments have no parsed data."""
+
+    paths, ncpus, datasets = scaling_data
+    manager = MockProfilingManager(paths, ncpus, datasets)
+
+    with pytest.raises(ValueError, match="No parsed profiling data found for experiment\(s\)") as exc_info:
+        manager.plot_scaling_data(
+            components=["component"],
+            regions=[["Region 1"]],
+            metric=tavg,
+            experiments=["missing_exp"],
+        )
+
+    message = str(exc_info.value)
+    assert "missing_exp" in message
+    assert "Available experiments" in message
+
+
 @mock.patch("access.profiling.manager.plot_bar_metrics")
 def test_bar_chart_data(mock_plot, scaling_data):
     """Test the plot_bar_chart method of ProfilingManager.