1028 lines
33 KiB
Python
1028 lines
33 KiB
Python
"""
|
||
Analyzer module — BetaSpectrumAnalyzer class.
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||
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||
Introspection, analysis, and debugging tools for BetaSpectrum.
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"""
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||
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from __future__ import annotations
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||
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import logging
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import pandas as pd
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from datetime import datetime, timezone
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from typing import TYPE_CHECKING, Any, Dict, List, Optional
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||
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import numpy as np
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import matplotlib.pyplot as plt
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||
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from beta_spectrum.logging_utils import get_git_short_hash
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from beta_spectrum.utils import T_to_W
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if TYPE_CHECKING:
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from matplotlib.axes import Axes
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||
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from beta_spectrum.spectrum import BetaSpectrum, SpectrumConfig
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from beta_spectrum.components.detector_response import DetectorResponse
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class BetaSpectrumAnalyzer:
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"""
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Introspection, analysis and debugging tools for BetaSpectrum.
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||
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Parameters
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----------
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spectrum : BetaSpectrum
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The spectrum to analyze.
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config : SpectrumConfig
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Configuration used to create the spectrum.
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logger : logging.Logger, optional
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Logger for progress output.
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"""
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def __init__(
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self,
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spectrum: BetaSpectrum,
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config: SpectrumConfig,
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logger: Optional[logging.Logger] = None,
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):
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"""
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Initialize analyzer with a spectrum and configuration.
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"""
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self.spectrum = spectrum
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self.config = config
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self.W, self.energies_MeV = spectrum.get_energy_grid(config)
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self._components_cache: Optional[Dict[str, np.ndarray]] = None
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self._branch_spectra_cache: Optional[List[np.ndarray]] = None
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self._logger = logger
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self._is_multi = spectrum._is_multi
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@property
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def components(self) -> Dict[str, np.ndarray]:
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if self._components_cache is None:
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self._components_cache = self.spectrum.calculate_components(self.W)
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assert self._components_cache is not None
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return self._components_cache
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@property
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def branch_spectra(self) -> List[np.ndarray]:
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"""Intensity-weighted branch spectra."""
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if self._branch_spectra_cache is None:
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self._branch_spectra_cache = self.spectrum.get_branch_normalized_spectra(
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self.W
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)
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assert self._branch_spectra_cache is not None
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return self._branch_spectra_cache
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def total_spectrum(self, normalize: bool = True) -> np.ndarray:
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"""
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Calculate the total_spectrum
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"""
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total = self.spectrum(self.W)
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if normalize:
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integral = np.trapezoid(total, self.energies_MeV)
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total = total / integral
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return total
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def convolved_spectrum(
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self,
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detector_response: Optional["DetectorResponse"] = None,
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normalize: bool = True,
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) -> np.ndarray:
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"""
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Calculate spectrum convolved with detector response.
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If detector_response is None and use_detector_response is True in config,
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creates a detector response from config parameters.
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Parameters
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----------
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detector_response : DetectorResponse, optional
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Detector response to convolve with. Created from config if None.
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normalize : bool
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If True, normalize to unit area.
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Returns
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-------
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np.ndarray
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Convolved spectrum.
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"""
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if detector_response is None and self.config.use_detector_response:
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detector_response = BetaSpectrum.create_detector_from_config(self.config)
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if detector_response is None:
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raise ValueError(
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"detector_response must be provided, or set "
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"use_detector_response=True in config"
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)
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convolved = self.spectrum.convolve_with_detector(
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detector_response, W=self.W, config=self.config
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)
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if normalize:
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integral = np.trapezoid(convolved, detector_response.channel_energies)
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if integral > 0:
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convolved = convolved / integral
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return convolved
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def plot_analysis(
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self,
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save_path: Optional[str] = None,
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show_components: bool = True,
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) -> None:
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"""
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Create visualization of the spectrum and all correction factors.
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In single-branch mode: standard 4-panel debug view or single spectrum plot.
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In multi-branch mode: spectrum plot with individual branches shown,
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and debug view with vertical layout for branch comparison.
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Parameters
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----------
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save_path : str, optional
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Path to save the figure.
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show_components : bool
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If True, show full debug view.
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If False, show only the spectrum plot with nuclear data header.
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If True, use logarithmic y-scale. Set to False for
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linear scale, which is better when branch intensities are similar.
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"""
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total = self.total_spectrum(normalize=True)
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components = self.components
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commit = get_git_short_hash(6)
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timestamp = datetime.now(timezone.utc).strftime("%Y-%m-%d %H:%M:%S UTC")
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if self._is_multi:
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if show_components:
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self._plot_multi_branch_debug(
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total, components, save_path, commit, timestamp
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)
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else:
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self._plot_multi_branch_spectra(
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total, components, save_path, commit, timestamp
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)
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else:
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if show_components:
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self._plot_debug_view(total, components, save_path, commit, timestamp)
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else:
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self._plot_spectrum_only(total, save_path, commit, timestamp)
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def _add_id_textbox(self, ax: "Axes", commit: str, timestamp: str) -> None:
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"""Add ID text box with commit hash and timestamp to plot."""
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id_text = f"commit: {commit} | {timestamp}"
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ax.text(
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0.01,
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0.01,
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id_text,
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transform=ax.transAxes,
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fontsize=8,
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color="gray",
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verticalalignment="bottom",
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horizontalalignment="left",
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fontfamily="monospace",
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)
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def _add_nuclear_data_header(self, ax: "Axes") -> None:
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"""Add nuclear data information header to plot."""
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parent = self._element_symbol(self.config.Z_parent)
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daughter = self._element_symbol(self.config.Z_daughter)
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enabled_corrections = []
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if self.config.use_phase_space:
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enabled_corrections.append("phase_space")
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if self.config.use_fermi:
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enabled_corrections.append("fermi")
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if self.config.use_screening:
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enabled_corrections.append("screening")
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if self.config.use_finite_size:
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enabled_corrections.append("finite_size")
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if self.config.use_charge_dist:
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enabled_corrections.append("charge_dist")
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if self.config.use_radiative:
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enabled_corrections.append("radiative")
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if self.config.use_exchange:
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enabled_corrections.append("exchange")
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header_lines = [
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f"Nuclide: {parent}{self.config.A_number} -> {daughter}{self.config.A_number}",
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f"Endpoint: {self.config.endpoint_MeV * 1000:.1f} keV",
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f"Transition: {self.config.transition_type}",
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f"Corrections: {', '.join(enabled_corrections)}",
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]
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if self.config.use_detector_response:
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header_lines.append(
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f"Detector: {self.config.detector_model} "
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f"(σ={self.config.detector_sigma_a_keV} keV)"
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)
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header_text = "\n".join(header_lines)
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ax.text(
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0.99,
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0.99,
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header_text,
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transform=ax.transAxes,
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fontsize=8,
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verticalalignment="top",
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horizontalalignment="right",
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bbox=dict(
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boxstyle="round,pad=0.3", facecolor="white", alpha=0.8, edgecolor="none"
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),
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)
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def _plot_spectrum_only(
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self,
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total: np.ndarray,
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save_path: Optional[str],
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commit: str,
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timestamp: str,
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||
) -> None:
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"""Plot only the total spectrum with nuclear data header."""
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fig, ax = plt.subplots(figsize=(10, 6))
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ax.plot(self.energies_MeV, total, "b-", lw=2, label="Normalized spectrum")
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ax.set_xlabel(r"Electron kinetic energy $E$ [MeV]", fontsize=11)
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ax.set_ylabel("Normalized Counts", fontsize=11)
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ax.set_title(
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f"Beta-decay: {self.config.Z_parent} -> {self.config.Z_daughter}, A={self.config.A_number}",
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fontsize=13,
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)
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ax.set_yscale("log")
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ax.grid(True, alpha=0.3)
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ax.legend(loc="best", fontsize=10)
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self._add_nuclear_data_header(ax)
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self._add_id_textbox(ax, commit, timestamp)
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plt.tight_layout()
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if save_path:
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fig.savefig(save_path, dpi=150, bbox_inches="tight")
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print(f"Figure saved to {save_path}")
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plt.show()
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def _plot_debug_view(
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self,
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total: np.ndarray,
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components: Dict[str, np.ndarray],
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||
save_path: Optional[str],
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||
commit: str,
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||
timestamp: str,
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||
) -> None:
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"""Full debug view with 4-panel spectrum analysis."""
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fig = plt.figure(figsize=(14, 10))
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||
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# 1. Main spectrum plot (top-left)
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ax1 = plt.subplot(2, 2, 1)
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ax1.plot(
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self.energies_MeV, total, "b-", lw=2, label="Total spectrum (log scale)"
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)
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ax1.set_xlabel(r"Electron kinetic energy $E$ [MeV]", fontsize=10)
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ax1.set_ylabel(
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f"Normalized Counts per {self.config.e_step_MeV:.3e} MeV", fontsize=10
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||
)
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ax1.set_title(
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f"Beta-decay: Z={self.config.Z_parent} -> {self.config.Z_daughter}, A={self.config.A_number}",
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fontsize=12,
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)
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ax1.set_yscale("log")
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ax1.grid(True, alpha=0.3)
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ax1.legend()
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# 2. Correction plots (top-right)
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ax2 = plt.subplot(2, 2, 2)
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# Set color order for correction plots
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component_order = [
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"PhaseSpace",
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||
"Fermi",
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||
"Screening",
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"Exchange",
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||
"FiniteSizeL0",
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||
"ChargeDistributionU",
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"Radiative",
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]
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colors = ["gray", "red", "green", "blue", "orange", "purple", "brown"]
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||
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for name, color in zip(component_order, colors):
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if name in components:
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values = components[name]
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# For Fermi and PhaseSpace, scale for visibility
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if name in ["Fermi", "PhaseSpace"]:
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values = values / np.max(values)
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label = f"{name} (norm)"
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else:
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||
label = name
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||
ax2.plot(
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self.energies_MeV,
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values,
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color=color,
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lw=1.5,
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||
label=label,
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||
alpha=0.8,
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||
)
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||
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ax2.set_xlabel("Electron kinetic energy E [MeV]", fontsize=10)
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||
ax2.set_ylabel("Correction factor", fontsize=10)
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||
ax2.set_title("Spectrum components", fontsize=12)
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||
ax2.grid(True, alpha=0.3)
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ax2.legend(loc="best", fontsize=8)
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||
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# 3. Cumulative effect (botom-left)
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ax3 = plt.subplot(2, 2, 3)
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||
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# Cumulative product
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cumulative = np.ones_like(self.W)
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||
baseline_norm = np.ones_like(cumulative)
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||
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# Plot baseline
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||
ax3.plot(
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self.energies_MeV, baseline_norm, "k--", lw=1.5, label="Baseline", alpha=0.7
|
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)
|
||
|
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# Add components one by one
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||
for name, color in zip(component_order, colors):
|
||
if name in components:
|
||
cumulative *= components[name]
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||
norm_cumulative = cumulative / np.max(cumulative)
|
||
ax3.plot(
|
||
self.energies_MeV,
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norm_cumulative,
|
||
color=color,
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||
lw=1.5,
|
||
label=f"+ {name}",
|
||
alpha=0.7,
|
||
)
|
||
|
||
ax3.set_xlabel("Electron kinetic energy E [MeV]", fontsize=10)
|
||
ax3.set_ylabel("Normalized spectrum", fontsize=10)
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||
ax3.set_title("Cumulative effect", fontsize=12)
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||
ax3.grid(True, alpha=0.3)
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||
ax3.legend(loc="best", fontsize=8)
|
||
|
||
# 4. Deviation from unity (bottom-right)
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||
ax4 = plt.subplot(2, 2, 4)
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||
|
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for name, color in zip(component_order, colors):
|
||
if name in components and name not in ["Fermi", "PhaseSpace"]:
|
||
deviation = components[name] - 1.0
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||
ax4.plot(
|
||
self.energies_MeV,
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||
deviation,
|
||
color=color,
|
||
lw=1.5,
|
||
label=f"{name}",
|
||
alpha=0.7,
|
||
)
|
||
|
||
ax4.set_xlabel("Electron kinetic energy E [MeV]", fontsize=10)
|
||
ax4.set_ylabel("Deviation from unity", fontsize=10)
|
||
ax4.set_title("Correction deviations (C - 1)", fontsize=12)
|
||
ax4.grid(True, alpha=0.3)
|
||
ax4.legend(loc="best", fontsize=8)
|
||
ax4.axhline(y=0, color="k", linestyle="-", lw=0.5)
|
||
|
||
plt.suptitle(
|
||
f"Beta-decay spectrum {self.config.A_number}{self._element_symbol(self.config.Z_parent)} -> {self.config.A_number}{self._element_symbol(self.config.Z_daughter)}",
|
||
fontsize=14,
|
||
fontweight="bold",
|
||
)
|
||
plt.tight_layout()
|
||
|
||
if save_path:
|
||
fig.savefig(save_path, dpi=150, bbox_inches="tight")
|
||
print(f"Figure saved to {save_path}")
|
||
|
||
plt.show()
|
||
|
||
def _element_symbol(self, Z: int) -> str:
|
||
symbols = [
|
||
"",
|
||
"H",
|
||
"He",
|
||
"Li",
|
||
"Be",
|
||
"B",
|
||
"C",
|
||
"N",
|
||
"O",
|
||
"F",
|
||
"Ne",
|
||
"Na",
|
||
"Mg",
|
||
"Al",
|
||
"Si",
|
||
"P",
|
||
"S",
|
||
"Cl",
|
||
"Ar",
|
||
"K",
|
||
"Ca",
|
||
"Sc",
|
||
"Ti",
|
||
"V",
|
||
"Cr",
|
||
"Mn",
|
||
"Fe",
|
||
"Co",
|
||
"Ni",
|
||
"Cu",
|
||
"Zn",
|
||
"Ga",
|
||
"Ge",
|
||
"As",
|
||
"Se",
|
||
"Br",
|
||
"Kr",
|
||
"Rb",
|
||
"Sr",
|
||
"Y",
|
||
"Zr",
|
||
"Nb",
|
||
"Mo",
|
||
"Tc",
|
||
"Ru",
|
||
"Rh",
|
||
"Pd",
|
||
"Ag",
|
||
"Cd",
|
||
"In",
|
||
"Sn",
|
||
"Sb",
|
||
"Te",
|
||
"I",
|
||
"Xe",
|
||
"Cs",
|
||
"Ba",
|
||
"La",
|
||
"Ce",
|
||
"Pr",
|
||
"Nd",
|
||
"Pm",
|
||
"Sm",
|
||
"Eu",
|
||
"Gd",
|
||
"Tb",
|
||
"Dy",
|
||
"Ho",
|
||
"Er",
|
||
"Tm",
|
||
"Yb",
|
||
"Lu",
|
||
"Hf",
|
||
"Ta",
|
||
"W",
|
||
"Re",
|
||
"Os",
|
||
"Ir",
|
||
"Pt",
|
||
"Au",
|
||
"Hg",
|
||
"Tl",
|
||
"Pb",
|
||
"Bi",
|
||
"Po",
|
||
"At",
|
||
"Rn",
|
||
"Fr",
|
||
"Ra",
|
||
"Ac",
|
||
"Th",
|
||
"Pa",
|
||
"U",
|
||
"Np",
|
||
"Pu",
|
||
"Am",
|
||
"Cm",
|
||
"Bk",
|
||
"Cf",
|
||
"Es",
|
||
"Fm",
|
||
]
|
||
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.
|
||
|
||
Parameters
|
||
----------
|
||
filename : str
|
||
Output CSV file path.
|
||
source_type : str
|
||
Data source type (paceENSDF, json, cli) for the header.
|
||
"""
|
||
total = self.total_spectrum(normalize=True)
|
||
components = self.components
|
||
|
||
# Build enabled corrections list
|
||
enabled = []
|
||
if self.config.use_phase_space:
|
||
enabled.append("phase_space")
|
||
if self.config.use_fermi:
|
||
enabled.append("fermi")
|
||
if self.config.use_screening:
|
||
enabled.append("screening")
|
||
if self.config.use_finite_size:
|
||
enabled.append("finite_size")
|
||
if self.config.use_charge_dist:
|
||
enabled.append("charge_dist")
|
||
if self.config.use_radiative:
|
||
enabled.append("radiative")
|
||
if self.config.use_exchange:
|
||
enabled.append("exchange")
|
||
|
||
# Build metadata header
|
||
def _element_symbol(Z: int) -> str:
|
||
symbols = [
|
||
"",
|
||
"H",
|
||
"He",
|
||
"Li",
|
||
"Be",
|
||
"B",
|
||
"C",
|
||
"N",
|
||
"O",
|
||
"F",
|
||
"Ne",
|
||
"Na",
|
||
"Mg",
|
||
"Al",
|
||
"Si",
|
||
"P",
|
||
"S",
|
||
"Cl",
|
||
"Ar",
|
||
"K",
|
||
"Ca",
|
||
"Sc",
|
||
"Ti",
|
||
"V",
|
||
"Cr",
|
||
"Mn",
|
||
"Fe",
|
||
"Co",
|
||
"Ni",
|
||
"Cu",
|
||
"Zn",
|
||
"Ga",
|
||
"Ge",
|
||
"As",
|
||
"Se",
|
||
"Br",
|
||
"Kr",
|
||
"Rb",
|
||
"Sr",
|
||
"Y",
|
||
"Zr",
|
||
"Nb",
|
||
"Mo",
|
||
"Tc",
|
||
"Ru",
|
||
"Rh",
|
||
"Pd",
|
||
"Ag",
|
||
"Cd",
|
||
"In",
|
||
"Sn",
|
||
"Sb",
|
||
"Te",
|
||
"I",
|
||
"Xe",
|
||
"Cs",
|
||
"Ba",
|
||
"La",
|
||
"Ce",
|
||
"Pr",
|
||
"Nd",
|
||
"Pm",
|
||
"Sm",
|
||
"Eu",
|
||
"Gd",
|
||
"Tb",
|
||
"Dy",
|
||
"Ho",
|
||
"Er",
|
||
"Tm",
|
||
"Yb",
|
||
"Lu",
|
||
"Hf",
|
||
"Ta",
|
||
"W",
|
||
"Re",
|
||
"Os",
|
||
"Ir",
|
||
"Pt",
|
||
"Au",
|
||
"Hg",
|
||
"Tl",
|
||
"Pb",
|
||
"Bi",
|
||
"Po",
|
||
"At",
|
||
"Rn",
|
||
"Fr",
|
||
"Ra",
|
||
"Ac",
|
||
"Th",
|
||
"Pa",
|
||
"U",
|
||
"Np",
|
||
"Pu",
|
||
"Am",
|
||
"Cm",
|
||
"Bk",
|
||
"Cf",
|
||
"Es",
|
||
"Fm",
|
||
]
|
||
return symbols[Z] if Z < len(symbols) else f"Z{Z}"
|
||
|
||
parent_symbol = _element_symbol(self.config.Z_parent)
|
||
daughter_symbol = _element_symbol(self.config.Z_daughter)
|
||
|
||
header_lines = [
|
||
f"# beta-spectrum v{__import__('beta_spectrum').__version__}",
|
||
f"# timestamp: {datetime.now(timezone.utc).isoformat()}",
|
||
f"# source: {source_type}",
|
||
f"# nuclide: {parent_symbol}{self.config.A_number} -> {daughter_symbol}{self.config.A_number} (Z={self.config.Z_parent}->{self.config.Z_daughter})",
|
||
f"# endpoint: {self.config.endpoint_MeV * 1000:.1f} keV",
|
||
f"# transition: {self.config.transition_type}",
|
||
f"# corrections: {', '.join(enabled)}",
|
||
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} "
|
||
f"(sigma={self.config.detector_sigma_a_keV} keV, "
|
||
f"tail={self.config.detector_tail_fraction})"
|
||
)
|
||
else:
|
||
header_lines.append("# detector: disabled")
|
||
|
||
header_lines.append(f"# git_commit: {get_git_short_hash()}")
|
||
|
||
# Write CSV with header
|
||
data: Dict[str, np.ndarray] = {
|
||
"energy_MeV": self.energies_MeV,
|
||
"spectrum": total,
|
||
}
|
||
|
||
if self._is_multi and self.spectrum.branches:
|
||
# Multi-branch mode: total spectrum + per-branch spectra + components
|
||
# (branch info — intensity, endpoint, transition — is in the header, not repeated columns)
|
||
for i, branch_spec in enumerate(self.spectrum.branch_spectra):
|
||
data[f"branch_{i+1}_spectrum"] = branch_spec(self.W)
|
||
|
||
# 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 (same for all branches — no prefix needed)
|
||
for name, values in components.items():
|
||
if not name.startswith("branch_"):
|
||
data[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")
|
||
|
||
# Prepend header
|
||
with open(filename, "r") as f:
|
||
content = f.read()
|
||
with open(filename, "w") as f:
|
||
f.write("\n".join(header_lines) + "\n" + content)
|
||
|
||
if self._logger:
|
||
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."""
|
||
return {
|
||
"energies_MeV": self.energies_MeV,
|
||
"energies_W": self.W,
|
||
"spectrum": self.total_spectrum(normalize=True),
|
||
"components": self.components,
|
||
"config": self.config,
|
||
}
|