sweep: warn on unapplied parameters; add PyPI keywords

pyproject.toml

@@ -6,6 +6,16 @@ build-backend = "setuptools.build_meta"
 name = "vlab4mic"
 version = "0.1.1"
 description = "VLab4Mic: A virtual laboratory for microscopy simulation and validation"
+keywords = [
+    "microscopy",
+    "simulation",
+    "super-resolution",
+    "SMLM",
+    "STED",
+    "fluorescence",
+    "labeling",
+    "structural-biology"
+]
 authors = [
     { name = "Damián Martínez", email = "jdmartinezigc@gmail.com" },
     { name = "Bruno M. Saraiva", email = "bruno.msaraiva2@gmail.com" },

src/vlab4mic/sweep_generator.py

@@ -591,6 +591,16 @@ def set_sweep_parameters(
         exp_time=None,
         **kwargs,
     ):
+        # Snapshot the parameters the user actually provided so we can report
+        # back which ones will be swept and which were accepted but ignored.
+        _provided = {
+            name: value
+            for name, value in locals().items()
+            if name not in ("self", "kwargs") and value is not None
+        }
+        _provided.update(
+            {name: value for name, value in kwargs.items() if value is not None}
+        )
         if probe_distance_to_epitope is not None:
             self.set_parameter_values(
                 "probe",
@@ -714,8 +724,18 @@ def set_sweep_parameters(
             self.set_parameter_values(
                 "modality", "depth_of_field_nm", values=depth_of_field_nm
             )
-        if peptide_motif is not None:
-            pass
+        # Parameters accepted by the signature (or via kwargs) that are not yet
+        # wired into the sweep. They are silently discarded otherwise, so warn.
+        _not_applied = {"peptide_motif", "minimal_distance"} | set(kwargs)
+        applied = sorted(name for name in _provided if name not in _not_applied)
+        ignored = sorted(name for name in _provided if name in _not_applied)
+        if applied:
+            print(f"Parameters set for sweep: {', '.join(applied)}")
+        if ignored:
+            print(
+                "WARNING: the following parameters were provided but are not "
+                f"applied during the sweep and will be ignored: {', '.join(ignored)}"
+            )
 
     def clear_sweep_parameters(self):
         """

tests/test_sweep_generator_state.py

@@ -16,3 +16,39 @@ def test_analysis_dict_is_per_instance():
 
     assert "only_in_a" not in b.analysis["unsorted"]
     assert b.analysis["dataframes"] is None
+
+
+def test_set_sweep_parameters_reports_applied(capsys):
+    g = sweep_generator.sweep_generator()
+    capsys.readouterr()
+    g.set_sweep_parameters(probe_DoL=[0.3, 0.6], pixelsize_nm=[80, 100])
+    out = capsys.readouterr().out
+    assert "Parameters set for sweep:" in out
+    assert "probe_DoL" in out and "pixelsize_nm" in out
+    assert "WARNING" not in out
+
+
+def test_set_sweep_parameters_warns_on_ignored(capsys):
+    g = sweep_generator.sweep_generator()
+    capsys.readouterr()
+    g.set_sweep_parameters(
+        exp_time=[10, 20],
+        peptide_motif={"motif": 1},
+        minimal_distance=5,
+        bogus_param=7,
+    )
+    out = capsys.readouterr().out
+    assert "Parameters set for sweep: exp_time" in out
+    assert "WARNING" in out
+    for ignored in ("peptide_motif", "minimal_distance", "bogus_param"):
+        assert ignored in out
+    assert "exp_time" not in out.split("WARNING", 1)[1]
+
+
+def test_set_sweep_parameters_silent_when_empty(capsys):
+    g = sweep_generator.sweep_generator()
+    capsys.readouterr()
+    g.set_sweep_parameters()
+    out = capsys.readouterr().out
+    assert "Parameters set for sweep:" not in out
+    assert "WARNING" not in out