summary prettified

EasyReflectometryApp/Backends/Py/analysis.py

@@ -214,6 +214,7 @@ def _on_fit_progress(self, payload: dict) -> None:
     def _on_fit_finished(self, results: list) -> None:
         """Handle successful completion of threaded fit."""
         self._fitting_logic.on_fit_finished(results)
+        self._project_lib._last_fit_results = self._fitting_logic.last_fit_results
         self._fitter_thread = None
         self.fittingChanged.emit()
         self._clearCacheAndEmitParametersChanged()

EasyReflectometryApp/Backends/Py/logic/fitting.py

@@ -294,6 +294,10 @@ def on_fit_finished(self, results: FitResults | List[FitResults]) -> None:
             self._result = single_result
             self._results = [single_result] if single_result is not None else []
 
+    @property
+    def last_fit_results(self):
+        return self._results if self._results else None
+
     @property
     def fit_n_pars(self) -> int:
         """Return the global number of refined parameters for the fit."""
@@ -309,7 +313,7 @@ def fit_chi2(self) -> float:
         if self._results:
             try:
                 if len(self._results) == 1:
-                    return float(self._results[0].reduced_chi)
+                    return float(self._results[0].reduced_chi2)
                 total_chi2 = float(sum(result.chi2 for result in self._results))
                 total_points = sum(len(result.x) for result in self._results)
                 n_params = self._results[0].n_pars
@@ -322,7 +326,7 @@ def fit_chi2(self) -> float:
         if self._result is None:
             return 0.0
         try:
-            return float(self._result.reduced_chi)
+            return float(self._result.reduced_chi2)
         except (ValueError, TypeError):
             return 0.0
 

EasyReflectometryApp/Gui/Pages/Summary/MainContent/Summary.qml

@@ -53,4 +53,27 @@ Rectangle {
     }
     // Flickable
 
+    // Tooltip for truncated experiment datablock names.
+    // Python wraps long names in <a href="nametooltip:ENCODED_FULL_NAME">.
+    // TextEdit.hoveredLink fires when the mouse enters/leaves such a link;
+    // we decode the full name and show it in a native ToolTip near the cursor.
+    HoverHandler {
+        id: hoverHandler
+    }
+
+    ToolTip {
+        id: nameToolTip
+
+        readonly property string scheme: "nametooltip:"
+
+        visible: textArea.hoveredLink.startsWith(scheme)
+        text: visible ? decodeURIComponent(textArea.hoveredLink.substring(scheme.length)) : ""
+
+        x: hoverHandler.point.position.x + 12
+        y: hoverHandler.point.position.y + 12
+
+        delay: 300
+        timeout: 8000
+    }
+
 }

pyproject.toml

@@ -32,7 +32,7 @@ classifiers = [
 requires-python = '>=3.12'
 dependencies = [
   'easyapplication',
-  'easyreflectometry',
+  'easyreflectometry @ git+https://github.com/easyscience/reflectometry-lib.git@develop',
   'asteval',
   'PySide6',
   'toml',

tests/factories.py

@@ -292,12 +292,12 @@ def make_dependent_on(self, dependency_expression, dependency_map):
 
 
 class FakeFitResult:
-    def __init__(self, success=True, chi2=1.0, n_pars=1, x=None, reduced_chi=0.5, minimizer_engine='stub'):
+    def __init__(self, success=True, chi2=1.0, n_pars=1, x=None, reduced_chi2=0.5, minimizer_engine='stub'):
         self.success = success
         self.chi2 = chi2
         self.n_pars = n_pars
         self.x = [] if x is None else x
-        self.reduced_chi = reduced_chi
+        self.reduced_chi2 = reduced_chi2
         self.minimizer_engine = minimizer_engine
 
 

tests/test_logic_fitting.py

@@ -89,30 +89,47 @@ def test_on_fit_finished_and_fit_properties_cover_multi_and_single_results(monke
 
     logic.prepare_for_threaded_fit()
     logic.on_fit_finished([
-        make_fit_result(success=True, chi2=4.0, n_pars=2, x=[1, 2, 3], reduced_chi=1.1),
-        make_fit_result(success=True, chi2=6.0, n_pars=2, x=[1, 2, 3, 4], reduced_chi=1.2),
+        make_fit_result(success=True, chi2=4.0, n_pars=2, x=[1, 2, 3], reduced_chi2=1.1),
+        make_fit_result(success=True, chi2=6.0, n_pars=2, x=[1, 2, 3, 4], reduced_chi2=1.2),
     ])
 
     assert logic.fit_finished is True
     assert logic.fit_success is True
     assert logic.fit_n_pars == 2
     assert logic.fit_chi2 == 2.0
 
-    logic.on_fit_finished(make_fit_result(success=False, chi2=9.0, n_pars=1, x=[1, 2], reduced_chi=4.5))
+    logic.on_fit_finished(make_fit_result(success=False, chi2=9.0, n_pars=1, x=[1, 2], reduced_chi2=4.5))
     assert logic.fit_success is False
     assert logic.fit_n_pars == 1
     assert logic.fit_chi2 == 4.5
 
 
+def test_last_fit_results_reflects_stored_results():
+    project = make_project()
+    logic = fitting_module.Fitting(project)
+
+    assert logic.last_fit_results is None
+
+    multi_results = [
+        make_fit_result(success=True, chi2=2.0, n_pars=1, x=[1, 2], reduced_chi2=1.0),
+        make_fit_result(success=True, chi2=3.0, n_pars=1, x=[1, 2, 3], reduced_chi2=1.5),
+    ]
+    logic.on_fit_finished(multi_results)
+    assert logic.last_fit_results is multi_results
+
+    logic.on_fit_finished(make_fit_result(success=True, chi2=1.0, n_pars=1, x=[1], reduced_chi2=1.0))
+    assert len(logic.last_fit_results) == 1
+
+
 def test_fit_n_pars_uses_global_free_parameter_count_for_multi_experiment_results(monkeypatch):
     project = make_project()
     logic = fitting_module.Fitting(project)
     monkeypatch.setattr(fitting_module, 'count_free_parameters', lambda current_project: 3)
 
     logic.prepare_for_threaded_fit()
     logic.on_fit_finished([
-        make_fit_result(success=True, chi2=4.0, n_pars=3, x=[1, 2, 3], reduced_chi=1.1),
-        make_fit_result(success=True, chi2=6.0, n_pars=3, x=[1, 2, 3, 4], reduced_chi=1.2),
+        make_fit_result(success=True, chi2=4.0, n_pars=3, x=[1, 2, 3], reduced_chi2=1.1),
+        make_fit_result(success=True, chi2=6.0, n_pars=3, x=[1, 2, 3, 4], reduced_chi2=1.2),
     ])
 
     assert logic.fit_n_pars == 3
@@ -149,7 +166,7 @@ def test_fit_progress_state_resets_on_finish_failure_and_stop():
 
     logic.prepare_for_threaded_fit()
     logic.on_fit_progress({'iteration': 3, 'chi2': 8.0, 'parameter_values': {'beta': 1.0}})
-    logic.on_fit_finished(make_fit_result(success=True, chi2=8.0, n_pars=1, x=[1, 2], reduced_chi=4.0))
+    logic.on_fit_finished(make_fit_result(success=True, chi2=8.0, n_pars=1, x=[1, 2], reduced_chi2=4.0))
 
     assert logic.fit_iteration == 0
     assert logic.fit_progress_message == ''
@@ -191,7 +208,7 @@ def test_fit_failure_and_cancellation_state_transitions():
 
 def test_start_stop_handles_success_and_fiterror():
     project = make_project(models=[object()])
-    project.fitter = SimpleNamespace(fit_single_data_set_1d=lambda exp_data: make_fit_result(success=True, chi2=1.7, reduced_chi=1.7))
+    project.fitter = SimpleNamespace(fit_single_data_set_1d=lambda exp_data: make_fit_result(success=True, chi2=1.7, reduced_chi2=1.7))
     logic = fitting_module.Fitting(project)
 
     logic.start_stop()