test: cover to_one/concise/single/plot normalization combinations

tests/physics/test_core_spectrum.py

@@ -564,3 +564,116 @@ class TestAnalyzerUniversalFactor:
         assert np.all(uni > 1.0)
         fermi_only = analyzer.components["Fermi"]
         assert np.allclose(uni, fermi_only, rtol=1e-12)
+
+
+class TestNormalizationModeMatrix:
+    """to_one and intensity modes must behave consistently across CSV
+    verbosity, branch count and the CSV-driven visualizer."""
+
+    def test_to_one_concise_multi_unit_area_no_total_no_components(
+        self, tmp_path: Any
+    ) -> None:
+        config = make_multi_config(normalize_to_one=True)
+        spectrum = BetaSpectrum.from_config(config)
+        analyzer = BetaSpectrumAnalyzer(spectrum, config)
+        path, df = export_and_read(
+            analyzer, tmp_path, "to_one_concise.csv", csv_verbosity="concise"
+        )
+
+        assert set(df.columns) == {
+            "energy_MeV",
+            "branch_1",
+            "branch_2",
+            "branch_3",
+        }
+        header = header_lines_of(path)
+        assert any("branch normalization: to_one" in h for h in header)
+        energies = df["energy_MeV"].to_numpy()
+        for col in ("branch_1", "branch_2", "branch_3"):
+            area = np.trapezoid(df[col].to_numpy(), energies)
+            assert np.isclose(area, 1.0, rtol=5e-4)
+
+    def test_to_one_single_mode_unit_area(self, tmp_path: Any) -> None:
+        config = make_single_config(normalize_to_one=True)
+        spectrum = BetaSpectrum.from_config(config)
+        analyzer = BetaSpectrumAnalyzer(spectrum, config)
+        _path, df = export_and_read(analyzer, tmp_path, "to_one_single.csv")
+
+        assert "total_spectrum" not in df.columns
+        area = np.trapezoid(
+            df["branch_1_spectrum"].to_numpy(), df["energy_MeV"].to_numpy()
+        )
+        assert np.isclose(area, 1.0, rtol=5e-4)
+
+    def test_intensity_concise_branch_columns_sum_to_total(
+        self, tmp_path: Any
+    ) -> None:
+        config = make_multi_config()
+        spectrum = BetaSpectrum.from_config(config)
+        analyzer = BetaSpectrumAnalyzer(spectrum, config)
+        _path, df = export_and_read(
+            analyzer, tmp_path, "intensity_concise.csv", csv_verbosity="concise"
+        )
+
+        summed = (
+            df["branch_1"].to_numpy()
+            + df["branch_2"].to_numpy()
+            + df["branch_3"].to_numpy()
+        )
+        total = df["total_spectrum"].to_numpy()
+        nonzero = total > 1e-12
+        assert np.all(
+            np.abs(summed[nonzero] - total[nonzero])
+            <= total[nonzero] * 5e-4
+        )
+
+    def test_plot_from_csv_to_one_plots_branches_without_total(
+        self, tmp_path: Any
+    ) -> None:
+        config = make_multi_config(normalize_to_one=True)
+        spectrum = BetaSpectrum.from_config(config)
+        analyzer = BetaSpectrumAnalyzer(spectrum, config)
+        path, df = export_and_read(analyzer, tmp_path, "to_one_plot.csv")
+
+        fig = Visualizer.plot_from_csv(
+            path, save_path=None, show_components=True
+        )
+        assert len(fig.axes) == 4
+        # Panel 1 has exactly the 3 branch curves — no total spectrum
+        # exists in to_one mode.
+        panel = fig.axes[0]
+        curves = [np.asarray(ln.get_xydata()) for ln in panel.lines]
+        assert len(curves) == 3
+        energies = df["energy_MeV"].to_numpy()
+        assert np.allclose(curves[0][:, 0], energies)
+        assert np.allclose(
+            curves[0][:, 1], df["branch_1_spectrum"].to_numpy()
+        )
+
+    def test_plot_analysis_to_one_returns_figure(self, tmp_path: Any) -> None:
+        config = make_multi_config(normalize_to_one=True)
+        spectrum = BetaSpectrum.from_config(config)
+        analyzer = BetaSpectrumAnalyzer(spectrum, config)
+        save = str(tmp_path / "analysis.png")
+        fig = Visualizer.plot_analysis(analyzer, save_path=save)
+        assert len(fig.axes) == 4
+        assert (tmp_path / "analysis.png").exists()
+
+    def test_plot_from_csv_to_one_concise_warns_and_falls_back(
+        self, tmp_path: Any, capsys: Any
+    ) -> None:
+        config = make_multi_config(normalize_to_one=True)
+        spectrum = BetaSpectrum.from_config(config)
+        analyzer = BetaSpectrumAnalyzer(spectrum, config)
+        path, df = export_and_read(
+            analyzer, tmp_path, "to_one_concise2.csv", csv_verbosity="concise"
+        )
+
+        fig = Visualizer.plot_from_csv(
+            path, save_path=None, show_components=True
+        )
+        captured = capsys.readouterr()
+        assert "Warning" in captured.out
+        # Simple spectra view: one axis, 3 branch curves, no total curve.
+        assert len(fig.axes) == 1
+        assert len(fig.axes[0].lines) == 3