diff --git a/beta_spectrum/nuclear_data.py b/beta_spectrum/nuclear_data.py index 5fb0a0e..c558a9d 100644 --- a/beta_spectrum/nuclear_data.py +++ b/beta_spectrum/nuclear_data.py @@ -94,12 +94,15 @@ class BranchInfo: Branch intensity (fraction of decays). log_ft : float log(ft) value for this branch. + transition_type : str + Forbiddenness classification for this branch (A, F1, F1U, F2, ...). """ level_index: int level_energy_keV: float intensity: float log_ft: Optional[float] + transition_type: str = "A" def _parse_nuclide_symbol(symbol: str) -> Tuple[str, int, int]: @@ -422,24 +425,28 @@ def get_decay_info_from_paceENSDF( for k, v in beta_data.items(): for state in v: - # Use ground state branch (level_index == 0) for forbiddenness - if state[0] == 0 and len(state) > 15 and state[15] is not None: + # Extract per-branch forbiddenness code + branch_transition_type = "A" # default + if len(state) > 15 and state[15] is not None: code = str(state[15]) if code in FORBIDDENNESS_MAP: - forbidden_code = code - transition_type = FORBIDDENNESS_MAP[code] - # Fallback: use first branch's forbiddenness if no ground state - elif transition_type == "A" and len(state) > 15 and state[15] is not None: - code = str(state[15]) - if code in FORBIDDENNESS_MAP: - forbidden_code = code - transition_type = FORBIDDENNESS_MAP[code] + branch_transition_type = FORBIDDENNESS_MAP[code] + + # Use ground state branch (level_index == 0) for overall forbiddenness + if state[0] == 0: + forbidden_code = ( + str(state[15]) + if len(state) > 15 and state[15] is not None + else "0A" + ) + transition_type = branch_transition_type branch = BranchInfo( level_index=int(state[0]), level_energy_keV=float(state[1]), intensity=float(state[8]), log_ft=float(state[11]) if state[11] is not None else None, + transition_type=branch_transition_type, ) branches.append(branch) diff --git a/beta_spectrum/spectrum.py b/beta_spectrum/spectrum.py index fdb4bc9..565e364 100644 --- a/beta_spectrum/spectrum.py +++ b/beta_spectrum/spectrum.py @@ -29,6 +29,40 @@ if TYPE_CHECKING: from beta_spectrum.components.detector_response import DetectorResponse +@dataclass +class BranchConfig: + """ + Configuration for a single decay branch. + + Each branch corresponds to a decay to a specific daughter nuclear state, + with its own endpoint energy (Q_value - excitation_energy) and transition type. + + Attributes + ---------- + endpoint_MeV : float + Effective endpoint energy for this branch (Q_value - excitation_energy). + transition_type : str + Forbiddenness classification for this branch (A, F1, F1U, F2, ...). + intensity : float + Branch intensity as a fraction of total decays (0.0–1.0). + Intensities across all branches should sum to 1.0 (100%). + """ + + endpoint_MeV: float + transition_type: str = "A" + intensity: float = 1.0 + + def __post_init__(self) -> None: + if self.intensity < 0 or self.intensity > 1.0: + raise ValueError( + f"Branch intensity must be in [0, 1], got {self.intensity}" + ) + if self.endpoint_MeV <= 0: + raise ValueError( + f"Branch endpoint_MeV must be positive, got {self.endpoint_MeV}" + ) + + @dataclass class SpectrumConfig: """ @@ -37,6 +71,10 @@ class SpectrumConfig: Supports declarative detector response specification: set detector_model, detector_sigma_a_keV, and related parameters to enable automatic detector smearing via convolve_with_detector(). + + Supports multi-branch decay via the `branches` field. When branches are + provided, the total spectrum is the intensity-weighted sum of individual + branch spectra. Each branch has its own endpoint energy and transition type. """ Z_parent: int @@ -69,34 +107,67 @@ class SpectrumConfig: 0.35, ) # in m_e units (total energy) + # Multi-branch support + branches: Optional[List[BranchConfig]] = None # None → single-branch mode + intensity_cutoff: float = ( + 0.0 # Ignore branches below this fraction (default: 0.0 = all) + ) + class BetaSpectrum: """ Precise beta spectrum calculator. - Combines basic spectrum shape (fermi * phase_space) with mutplicative corrections. + Supports both single-branch and multi-branch decay modes. + + In single-branch mode (branches=None), the spectrum is the product of + all enabled correction factors. + + In multi-branch mode (branches provided), each branch is calculated + independently with its own endpoint energy and transition type, then + summed with intensity weighting. Parameters ---------- - components : List[SpectrumComponent] - List of enabled spectral components. + components : List[SpectrumComponent], optional + List of enabled universal spectral components (Fermi, screening, etc.). + Only used in multi-branch mode or for universal components. + branch_spectra : List[BetaSpectrum], optional + List of per-branch spectrum calculators (each with its own PhaseSpace, etc.). + Only used in multi-branch mode. + branches : List[BranchConfig], optional + Branch configuration metadata (intensities, endpoint energies). logger : logging.Logger, optional Logger for debug/info output. """ def __init__( self, - components: List[SpectrumComponent], + components: Optional[List[SpectrumComponent]] = None, + branch_spectra: Optional[List[BetaSpectrum]] = None, + branches: Optional[List[BranchConfig]] = None, logger: Optional[logging.Logger] = None, ): - self.components = components - self._component_names = [self._get_component_name(c) for c in components] + self.components = components or [] + self._component_names = [self._get_component_name(c) for c in self.components] + self.branch_spectra = branch_spectra or [] + self.branches = branches or [] self._logger = logger + self._is_multi = len(self.branch_spectra) > 0 def __call__(self, W: np.ndarray) -> np.ndarray: """ - Calculate total spectrum as a product of enabled components + Calculate spectrum. + + In single-branch mode: product of all components. + In multi-branch mode: intensity-weighted sum of branch spectra. """ + if self._is_multi: + return self._multi_branch_call(W) + return self._single_branch_call(W) + + def _single_branch_call(self, W: np.ndarray) -> np.ndarray: + """Calculate spectrum as product of components (single branch).""" result: np.ndarray = np.ones_like(W, dtype=float) for comp in self.components: if self._logger: @@ -106,21 +177,74 @@ class BetaSpectrum: result = result * comp(W) return result.astype(np.float64) + def _multi_branch_call(self, W: np.ndarray) -> np.ndarray: + """Calculate total spectrum as intensity-weighted sum of branches. + + The total is: (universal_components_product) * sum(intensity_i * branch_spectrum_i) + """ + # Sum of intensity-weighted branch spectra + branch_sum = np.zeros_like(W, dtype=float) + for i, branch_spec in enumerate(self.branch_spectra): + if self._logger: + self._logger.debug( + "Evaluating branch %d/%d (endpoint=%.3f MeV, intensity=%.4f)", + i + 1, + len(self.branch_spectra), + self.branches[i].endpoint_MeV, + self.branches[i].intensity, + ) + branch_spectrum = branch_spec(W) + # Mask out energies beyond this branch's endpoint + W0_branch = T_to_W(self.branches[i].endpoint_MeV) + mask = W <= W0_branch + branch_sum += self.branches[i].intensity * np.where( + mask, branch_spectrum, 0.0 + ) + + # Multiply by universal components + result: np.ndarray = np.ones_like(W, dtype=float) + for comp in self.components: + result = result * comp(W) + + return np.asarray((result * branch_sum).astype(np.float64), dtype=np.float64) + def _get_component_name(self, comp: SpectrumComponent) -> str: - """ - Get human-readable component names - """ + """Get human-readable component name.""" class_name = comp.__class__.__name__ return class_name.replace("Correction", "").replace("Function", "") def calculate_components(self, W: np.ndarray) -> Dict[str, np.ndarray]: """ - Calculate individual components for debugging and analysis + Calculate individual components. + + In single-branch mode: returns per-component values. + In multi-branch mode: returns universal components + per-branch + branch-dependent components (PhaseSpace, Radiative). """ - components_dict = {} + if self._is_multi: + return self._multi_branch_components(W) + + result: Dict[str, np.ndarray] = {} for name, comp in zip(self._component_names, self.components): - components_dict[name] = comp(W) - return components_dict + result[name] = comp(W) + return result + + def _multi_branch_components(self, W: np.ndarray) -> Dict[str, np.ndarray]: + """Return universal + per-branch components for multi-branch mode.""" + result: Dict[str, np.ndarray] = {} + + # Universal components (same for all branches) + for name, comp in zip(self._component_names, self.components): + result[name] = comp(W) + + # Per-branch components (branch-dependent) + for i, branch_spec in enumerate(self.branch_spectra): + branch_name = f"branch_{i}" + branch_components = branch_spec.calculate_components(W) + for comp_name, values in branch_components.items(): + result[f"{branch_name}.{comp_name}"] = values + + return result @classmethod def from_config( @@ -129,6 +253,9 @@ class BetaSpectrum: """ Create a BetaSpectrum from configuration. + In single-branch mode: creates a single spectrum calculator. + In multi-branch mode: creates per-branch calculators + universal components. + Parameters ---------- config : SpectrumConfig @@ -136,6 +263,15 @@ class BetaSpectrum: logger : logging.Logger, optional Logger for progress output. """ + if config.branches is not None and len(config.branches) > 1: + return cls._from_config_multi(config, logger) + return cls._from_config_single(config, logger) + + @classmethod + def _from_config_single( + cls, config: SpectrumConfig, logger: Optional[logging.Logger] = None + ) -> BetaSpectrum: + """Create single-branch spectrum calculator.""" components: List[SpectrumComponent] = [] W0 = float(T_to_W(config.endpoint_MeV)) @@ -185,17 +321,163 @@ class BetaSpectrum: return cls(components, logger=logger) + @classmethod + def _from_config_multi( + cls, config: SpectrumConfig, logger: Optional[logging.Logger] = None + ) -> BetaSpectrum: + """Create multi-branch spectrum calculator. + + Creates per-branch calculators (each with its own PhaseSpace, Radiative, etc.) + and universal components (Fermi, screening, finite_size, etc.) shared across + all branches. + + Note: Radiative correction is branch-dependent (depends on W0), so it goes + into each branch's calculator, not the universal components. + """ + if logger: + logger.info("Multi-branch mode: %d branches", len(config.branches)) + + # Create per-branch calculators + branch_spectra: List[BetaSpectrum] = [] + for i, branch in enumerate(config.branches): + if logger: + logger.info( + " Branch %d: endpoint=%.3f MeV, transition=%s, intensity=%.4f", + i + 1, + branch.endpoint_MeV, + branch.transition_type, + branch.intensity, + ) + + # Create a per-branch config with the branch's endpoint and transition type + branch_config = SpectrumConfig( + Z_parent=config.Z_parent, + Z_daughter=config.Z_daughter, + A_number=config.A_number, + endpoint_MeV=branch.endpoint_MeV, + transition_type=branch.transition_type, + e_step_MeV=config.e_step_MeV, + # Branch-dependent components + use_phase_space=config.use_phase_space, + use_radiative=config.use_radiative, + # Universal components disabled (handled separately) + use_fermi=False, + use_screening=False, + use_finite_size=False, + use_charge_dist=False, + use_exchange=False, + ) + + branch_spectrum = cls._from_config_single(branch_config, logger) + branch_spectra.append(branch_spectrum) + + # Create universal components (shared across all branches) + # Note: Radiative is NOT included here because it depends on W0 + universal_components: List[SpectrumComponent] = [] + + if config.use_fermi: + universal_components.append( + FermiFunction(Z=config.Z_daughter, A=config.A_number, logger=logger) + ) + + if config.use_finite_size: + universal_components.append( + FiniteSizeL0(Z=config.Z_daughter, A=config.A_number, logger=logger) + ) + + if config.use_charge_dist: + universal_components.append( + ChargeDistributionU( + Z=config.Z_daughter, A=config.A_number, logger=logger + ) + ) + + if config.use_screening: + universal_components.append( + ScreeningCorrection( + FermiFunction(Z=config.Z_parent, A=config.A_number, logger=logger), + logger=logger, + ) + ) + + if config.use_exchange: + universal_components.append( + ExchangeCorrection(Z=config.Z_parent, logger=logger) + ) + + return cls( + components=universal_components, + branch_spectra=branch_spectra, + branches=list(config.branches), + logger=logger, + ) + def get_energy_grid(self, config: SpectrumConfig) -> Tuple[np.ndarray, np.ndarray]: """ Generate array of energy values for spectrum calculation. + + In multi-branch mode, uses the maximum endpoint across all branches. """ - kinetic_MeV = np.arange( - config.e_step_MeV, config.endpoint_MeV, config.e_step_MeV - ) + if self._is_multi and self.branches: + max_endpoint = max(b.endpoint_MeV for b in self.branches) + else: + max_endpoint = config.endpoint_MeV + + kinetic_MeV = np.arange(config.e_step_MeV, max_endpoint, config.e_step_MeV) W = T_to_W(kinetic_MeV) return W, kinetic_MeV.astype(np.float64) + def get_branch_spectra(self, W: np.ndarray) -> List[np.ndarray]: + """ + Get individual branch spectra for multi-branch mode. + + Each branch spectrum is masked to zero beyond its endpoint. + + Parameters + ---------- + W : np.ndarray + Energy grid in m_e units. + + Returns + ------- + List[np.ndarray] + Per-branch spectrum arrays (unweighted). Empty in single-branch mode. + """ + if not self._is_multi: + return [] + result = [] + for i, branch_spec in enumerate(self.branch_spectra): + branch_spectrum = branch_spec(W) + # Use np.maximum to smoothly approach zero at endpoint, + # and clamp negative values beyond endpoint to zero + result.append(np.maximum(0.0, branch_spectrum)) + return result + + def get_branch_normalized_spectra(self, W: np.ndarray) -> List[np.ndarray]: + """ + Get intensity-weighted branch spectra for multi-branch mode. + + Each branch spectrum is masked to zero beyond its endpoint. + + Parameters + ---------- + W : np.ndarray + Energy grid in m_e units. + + Returns + ------- + List[np.ndarray] + Per-branch spectrum arrays weighted by intensity. Empty in single-branch mode. + """ + if not self._is_multi: + return [] + result = [] + for i, branch_spec in enumerate(self.branch_spectra): + branch_spectrum = branch_spec(W) + result.append(self.branches[i].intensity * np.maximum(0.0, branch_spectrum)) + return result + @staticmethod def create_detector_from_config( config: SpectrumConfig, @@ -353,7 +635,9 @@ class BetaSpectrumAnalyzer: self.config = config self.W, self.energies_MeV = spectrum.get_energy_grid(config) self._components_cache: Optional[Dict[str, np.ndarray]] = None + self._branch_spectra_cache: Optional[List[np.ndarray]] = None self._logger = logger + self._is_multi = spectrum._is_multi @property def components(self) -> Dict[str, np.ndarray]: @@ -362,6 +646,16 @@ class BetaSpectrumAnalyzer: assert self._components_cache is not None return self._components_cache + @property + def branch_spectra(self) -> List[np.ndarray]: + """Intensity-weighted branch spectra.""" + if self._branch_spectra_cache is None: + self._branch_spectra_cache = self.spectrum.get_branch_normalized_spectra( + self.W + ) + assert self._branch_spectra_cache is not None + return self._branch_spectra_cache + def total_spectrum(self, normalize: bool = True) -> np.ndarray: """ Calculate the total_spectrum @@ -425,23 +719,39 @@ class BetaSpectrumAnalyzer: """ Create visualization of the spectrum and all correction factors. + In single-branch mode: standard 4-panel debug view or single spectrum plot. + In multi-branch mode: spectrum plot with individual branches shown, + and debug view with vertical layout for branch comparison. + Parameters ---------- save_path : str, optional Path to save the figure. show_components : bool - If True, show full debug view (4-panel with all corrections). + If True, show full debug view. If False, show only the spectrum plot with nuclear data header. + If True, use logarithmic y-scale. Set to False for + linear scale, which is better when branch intensities are similar. """ total = self.total_spectrum(normalize=True) components = self.components commit = get_git_short_hash(6) timestamp = datetime.now(timezone.utc).strftime("%Y-%m-%d %H:%M:%S UTC") - if show_components: - self._plot_debug_view(total, components, save_path, commit, timestamp) + if self._is_multi: + if show_components: + self._plot_multi_branch_debug( + total, components, save_path, commit, timestamp + ) + else: + self._plot_multi_branch_spectra( + total, components, save_path, commit, timestamp + ) else: - self._plot_spectrum_only(total, save_path, commit, timestamp) + if show_components: + self._plot_debug_view(total, components, save_path, commit, timestamp) + else: + self._plot_spectrum_only(total, save_path, commit, timestamp) def _add_id_textbox(self, ax: "Axes", commit: str, timestamp: str) -> None: """Add ID text box with commit hash and timestamp to plot.""" @@ -780,6 +1090,302 @@ class BetaSpectrumAnalyzer: ] return symbols[Z] if Z < len(symbols) else f"Z{Z}" + # --------------------------------------------------------------------------- + # Multi-branch plotting + # --------------------------------------------------------------------------- + + def _get_branch_label(self, i: int) -> str: + """Generate branch label for legend.""" + if i >= len(self.spectrum.branches): + return f"Branch {i+1}" + branch = self.spectrum.branches[i] + return f"Branch {i+1}: {branch.transition_type}, E₀={branch.endpoint_MeV*1000:.1f} keV" + + def _plot_multi_branch_spectra( + self, + total: np.ndarray, + components: Dict[str, np.ndarray], + save_path: Optional[str], + commit: str, + timestamp: str, + ) -> None: + """Plot total spectrum with individual branch decomposition. + + All curves use raw (un-normalized) values so that the total is + the arithmetic sum of branch contributions, and branch amplitudes + are proportional to their intensities. + """ + fig, ax = plt.subplots(figsize=(12, 7)) + + branch_colors = [ + "#1f77b4", + "#ff7f0e", + "#2ca02c", + "#d62728", + "#9467bd", + "#8c564b", + "#e377c2", + "#7f7f7f", + "#bcbd22", + "#17becf", + ] + + # Compute branch contributions (universal * intensity * branch_spectrum) + branch_contribs = [] + for i, branch_spec in enumerate(self.spectrum.branch_spectra): + universal_product = np.ones_like(self.W) + for name in [ + "Fermi", + "Screening", + "FiniteSizeL0", + "ChargeDistributionU", + "Exchange", + ]: + if name in components: + universal_product *= components[name] + bs = self.spectrum.get_branch_spectra(self.W) + contrib = universal_product * self.spectrum.branches[i].intensity * bs[i] + branch_contribs.append(contrib) + + # Total = arithmetic sum of all branches (raw, un-normalized) + total_raw = sum(branch_contribs) + + ax.plot( + self.energies_MeV, + total_raw, + "k-", + lw=2.5, + label="Total spectrum", + zorder=10, + ) + + # Plot each branch contribution (raw, un-normalized) + for i, (contrib, branch) in enumerate( + zip(branch_contribs, self.spectrum.branches) + ): + color = branch_colors[i % len(branch_colors)] + ax.plot( + self.energies_MeV, + contrib, + color=color, + lw=1.5, + alpha=0.7, + label=self._get_branch_label(i), + ) + + ax.set_xlabel(r"Electron kinetic energy $E$ [MeV]", fontsize=12) + ax.set_ylabel("Normalized Counts", fontsize=12) + parent = self._element_symbol(self.config.Z_parent) + daughter = self._element_symbol(self.config.Z_daughter) + ax.set_title( + f"Beta-decay: {parent}{self.config.A_number} -> {daughter}{self.config.A_number} — {len(self.spectrum.branches)} branches", + fontsize=14, + ) + ax.set_yscale("log") + ax.grid(True, alpha=0.3) + ax.legend(loc="best", fontsize=10, ncol=min(2, len(self.spectrum.branches) + 1)) + + self._add_nuclear_data_header(ax) + self._add_id_textbox(ax, commit, timestamp) + + plt.tight_layout() + + if save_path: + fig.savefig(save_path, dpi=150, bbox_inches="tight") + print(f"Figure saved to {save_path}") + + def _plot_multi_branch_debug( + self, + total: np.ndarray, + components: Dict[str, np.ndarray], + save_path: Optional[str], + commit: str, + timestamp: str, + ) -> None: + """Debug view for multi-branch: vertical layout with 4 panels. + + Panel 1: Total spectrum + intensity-scaled branch spectra (log scale) + Panel 2: Fermi function + all phase spaces (shape comparison, no intensity) + Panel 3: Universal W0-independent corrections (Fermi, Screening, etc.) + Panel 4: W0-dependent corrections (Radiative for each branch) + """ + n_branches = len(self.spectrum.branches) + + fig, axes = plt.subplots(4, 1, figsize=(12, 16), sharex=True) + + branch_colors = [ + "#1f77b4", + "#ff7f0e", + "#2ca02c", + "#d62728", + "#9467bd", + "#8c564b", + "#e377c2", + "#7f7f7f", + "#bcbd22", + "#17becf", + ] + parent = self._element_symbol(self.config.Z_parent) + daughter = self._element_symbol(self.config.Z_daughter) + + # Panel 1: Total spectrum + per-branch spectra + # All curves use raw (un-normalized) values so total = sum of branches + branch_contribs = [] + for i, branch_spec in enumerate(self.spectrum.branch_spectra): + universal_product = np.ones_like(self.W) + for name in [ + "Fermi", + "Screening", + "FiniteSizeL0", + "ChargeDistributionU", + "Exchange", + ]: + if name in components: + universal_product *= components[name] + bs = self.spectrum.get_branch_spectra(self.W) + contrib = universal_product * self.spectrum.branches[i].intensity * bs[i] + branch_contribs.append(contrib) + + total_raw = sum(branch_contribs) + + ax = axes[0] + ax.plot( + self.energies_MeV, + total_raw, + "k-", + lw=2, + label="Total spectrum", + zorder=10, + ) + + for i, (contrib, branch) in enumerate( + zip(branch_contribs, self.spectrum.branches) + ): + color = branch_colors[i % len(branch_colors)] + ax.plot( + self.energies_MeV, + contrib, + color=color, + lw=1.5, + alpha=0.7, + label=f"Branch {i+1}: {branch.transition_type}, " + f"E₀={branch.endpoint_MeV*1000:.1f} keV", + ) + ax.set_yscale("log") + ax.set_ylabel("Normalized Counts", fontsize=10) + ax.set_title( + f"Multi-branch: {parent}{self.config.A_number} -> {daughter}{self.config.A_number} ({n_branches} branches)", + fontsize=12, + fontweight="bold", + ) + ax.grid(True, alpha=0.3) + ax.legend(fontsize=8, loc="best", ncol=min(2, n_branches + 1)) + + # Panel 2: Fermi function + all phase spaces (shape comparison) + # Phase space is masked beyond endpoint before normalizing to avoid + # negative values from the sqrt term + ax = axes[1] + if "Fermi" in components: + fermi_vals = components["Fermi"] + fermi_scaled = fermi_vals / np.max(fermi_vals) + ax.plot( + self.energies_MeV, + fermi_scaled, + "r-", + lw=1.5, + label="Fermi (normalized)", + alpha=0.8, + ) + for i, (branch_spec, branch) in enumerate( + zip(self.spectrum.branch_spectra, self.spectrum.branches) + ): + color = branch_colors[i % len(branch_colors)] + if f"branch_{i}.PhaseSpace" in components: + ps_vals = components[f"branch_{i}.PhaseSpace"] + # Mask beyond endpoint to avoid negative values + W0_branch = T_to_W(branch.endpoint_MeV) + mask = self.W <= W0_branch + ps_masked = np.where(mask, ps_vals, 0.0) + ps_max = np.max(ps_masked) + if ps_max > 0: + ps_scaled = ps_masked / ps_max + else: + ps_scaled = ps_masked + ax.plot( + self.energies_MeV, + ps_scaled, + color=color, + lw=1.5, + alpha=0.7, + label=f"PS Branch {i+1} (normalized)", + ) + ax.set_ylabel("Normalized Factor", fontsize=10) + ax.set_title( + "Fermi Function & Phase Space Shapes", fontsize=11, fontweight="bold" + ) + ax.grid(True, alpha=0.3) + ax.legend(fontsize=8, loc="best") + + # Panel 3: Universal W0-independent corrections + ax = axes[2] + universal_components = [ + "Screening", + "FiniteSizeL0", + "ChargeDistributionU", + "Exchange", + ] + colors = ["green", "orange", "purple", "brown"] + for name, color in zip(universal_components, colors): + if name in components: + values = components[name] + values_scaled = values / np.max(values) + ax.plot( + self.energies_MeV, + values_scaled, + color=color, + lw=1.5, + label=f"{name} (normalized)", + alpha=0.8, + ) + ax.set_ylabel("Normalized Factor", fontsize=10) + ax.set_title( + "Universal W0-Independent Corrections", fontsize=11, fontweight="bold" + ) + ax.grid(True, alpha=0.3) + ax.legend(fontsize=8, loc="best") + + # Panel 4: W0-dependent corrections (Radiative for each branch) + ax = axes[3] + for i, (branch_spec, branch) in enumerate( + zip(self.spectrum.branch_spectra, self.spectrum.branches) + ): + color = branch_colors[i % len(branch_colors)] + if f"branch_{i}.Radiative" in components: + rad_vals = components[f"branch_{i}.Radiative"] + ax.plot( + self.energies_MeV, + rad_vals, + color=color, + lw=1.5, + alpha=0.7, + label=f"Branch {i+1} Radiative (E₀={branch.endpoint_MeV*1000:.1f} keV)", + ) + ax.set_ylabel("Radiative Correction", fontsize=10) + ax.set_xlabel(r"Electron kinetic energy $E$ [MeV]", fontsize=10) + ax.set_title( + "W0-Dependent Corrections (Radiative)", fontsize=11, fontweight="bold" + ) + ax.grid(True, alpha=0.3) + ax.legend(fontsize=8, loc="best", ncol=min(2, n_branches + 1)) + + self._add_id_textbox(axes[3], commit, timestamp) + + plt.tight_layout() + + if save_path: + fig.savefig(save_path, dpi=150, bbox_inches="tight") + print(f"Figure saved to {save_path}") + def export_to_csv(self, filename: str, source_type: str = "unknown") -> None: """ Export spectrum data to CSV with metadata header. @@ -934,6 +1540,17 @@ class BetaSpectrumAnalyzer: f"# e_step: {self.config.e_step_MeV:.4f} MeV", ] + if self._is_multi and self.spectrum.branches: + header_lines.append(f"# branches: {len(self.spectrum.branches)}") + for i, branch in enumerate(self.spectrum.branches): + header_lines.append( + f"# branch_{i+1}: E₀={branch.endpoint_MeV*1000:.1f} keV, " + f"transition={branch.transition_type}, " + f"intensity={branch.intensity:.4f}" + ) + else: + header_lines.append("# branches: 1 (single)") + if self.config.use_detector_response: header_lines.append( f"# detector: {self.config.detector_model} " @@ -952,8 +1569,37 @@ class BetaSpectrumAnalyzer: "energy_MeV": self.energies_MeV, "spectrum": total, } - for name, values in components.items(): - data[name] = values + + if self._is_multi and self.spectrum.branches: + # Multi-branch mode: total spectrum + per-branch spectra + components + for i, (branch, branch_spec) in enumerate( + zip(self.spectrum.branches, self.spectrum.branch_spectra) + ): + data[f"branch_{i+1}_spectrum"] = branch_spec(self.W) + data[f"branch_{i+1}_intensity"] = np.full_like( + self.energies_MeV, branch.intensity + ) + data[f"branch_{i+1}_endpoint"] = np.full_like( + self.energies_MeV, branch.endpoint_MeV + ) + data[f"branch_{i+1}_transition"] = np.full_like( + self.energies_MeV, branch.transition_type, dtype=object + ) + + # Per-branch components (PhaseSpace, Radiative, etc.) + for i, branch_spec in enumerate(self.spectrum.branch_spectra): + branch_comps = branch_spec.calculate_components(self.W) + for comp_name, values in branch_comps.items(): + data[f"branch_{i+1}_{comp_name}"] = values + + # Universal components only (skip per-branch keys) + for name, values in components.items(): + if not name.startswith("branch_"): + data[f"universal_{name}"] = values + else: + # Single-branch mode: standard export + for name, values in components.items(): + data[name] = values df = pd.DataFrame(data) df.to_csv(filename, index=False, float_format="%.4e") @@ -965,7 +1611,8 @@ class BetaSpectrumAnalyzer: f.write("\n".join(header_lines) + "\n" + content) if self._logger: - self._logger.info("CSV exported to %s with metadata header", filename) + mode = "multi-branch" if self._is_multi else "single-branch" + self._logger.info("CSV exported to %s (%s mode)", filename, mode) def get_data(self) -> Dict[str, Any]: """Get all numerical data for custom analysis."""