783 lines
26 KiB
Python
783 lines
26 KiB
Python
"""
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Visualize module — BetaSpectrumAnalyzer class.
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Visualization and plotting tools for BetaSpectrum.
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All nuclides (single- and multi-branch) are treated uniformly as one or more
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branches — single-branch is just a special case with one branch.
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"""
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from __future__ import annotations
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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 dataclasses import dataclass
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from typing import TYPE_CHECKING, Any, Dict, List, Optional
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import numpy as np
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import matplotlib.pyplot as plt
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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.figure import Figure
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from beta_spectrum.spectrum import BetaSpectrum, SpectrumConfig
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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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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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# Unified branch view: single-branch treated as one-branch multi-branch
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if not self._is_multi and self.spectrum.branch_spectra == []:
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self._unified_branches: List[_UnifiedBranch] = [
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_UnifiedBranch(
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endpoint_MeV=config.endpoint_MeV,
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transition_type=config.transition_type,
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intensity=1.0,
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)
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]
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else:
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self._unified_branches = [
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_UnifiedBranch(
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endpoint_MeV=b.endpoint_MeV,
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transition_type=b.transition_type,
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intensity=b.intensity,
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)
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for b in self.spectrum.branches
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]
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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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raw = self.spectrum.calculate_components(self.W)
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# Normalize keys: single-branch has bare names,
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# multi-branch has branch_0., branch_1., etc.
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# We keep the raw keys for export_to_csv compatibility.
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self._components_cache = raw
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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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"""Calculate the total spectrum."""
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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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# ---------------------------------------------------------------------------
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# Unified branch view
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# ---------------------------------------------------------------------------
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@property
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def _n_branches(self) -> int:
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"""Number of branches (unified view)."""
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return len(self._unified_branches)
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def _get_branch_spectrum(self, i: int) -> np.ndarray:
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"""Get the spectrum array for branch i."""
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if i < len(self.spectrum.branch_spectra):
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bs_obj = self.spectrum.branch_spectra[i]
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# branch_spectra stores BetaSpectrum objects — call them to get arrays
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if hasattr(bs_obj, "__call__"):
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val = bs_obj(self.W)
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# Clamp to zero beyond endpoint (phase space goes negative)
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W0 = T_to_W(self._unified_branches[i].endpoint_MeV)
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return np.where(self.W <= W0, val, 0.0)
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return np.asarray(bs_obj)
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# Single-branch: the spectrum itself is the only branch
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return self.spectrum(self.W)
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def _get_component_key(self, i: int, name: str) -> str:
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"""Get the canonical key for a per-branch component."""
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if self._is_multi:
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return f"branch_{i}.{name}"
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return name
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def _has_component(self, i: int, name: str) -> bool:
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"""Check if branch i has a given component."""
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key = self._get_component_key(i, name)
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return key in self.components
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def _get_component(self, i: int, name: str) -> np.ndarray:
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"""Get a per-branch component array."""
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key = self._get_component_key(i, name)
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return self.components[key]
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# ---------------------------------------------------------------------------
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# Plotting helpers
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# ---------------------------------------------------------------------------
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def _build_figure_header(self, fig: "Figure") -> None:
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"""Add a compact header with nuclide info, e_step, commit and timestamp outside axes."""
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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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e_step_keV = self.config.e_step_MeV * 1000
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header = (
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f"{parent}{self.config.A_number} -> {daughter}{self.config.A_number} "
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f"| E₀={self.config.endpoint_MeV * 1000:.1f} keV "
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f"| ΔE={e_step_keV:.1f} keV"
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)
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fig.text(
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0.01,
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0.98,
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header,
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transform=fig.transFigure,
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fontsize=9,
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verticalalignment="top",
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horizontalalignment="left",
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fontfamily="monospace",
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)
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# Add neutrino mass info to header if non-zero
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if self.config.neutrino_mass_MeV > 0:
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nu_mass_text = f"| m_ν={self.config.neutrino_mass_MeV:.6f} MeV"
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fig.text(
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0.01,
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0.96,
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nu_mass_text,
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transform=fig.transFigure,
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fontsize=8,
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verticalalignment="top",
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horizontalalignment="left",
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fontfamily="monospace",
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color="red",
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)
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id_text = f"{get_git_short_hash(6)} | {self._timestamp}"
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fig.text(
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0.01,
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0.01,
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id_text,
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transform=fig.transFigure,
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fontsize=8,
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verticalalignment="bottom",
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horizontalalignment="left",
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fontfamily="monospace",
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color="gray",
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)
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def _build_figure_title(self, fig: "Figure") -> str:
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"""Build a unified figure title."""
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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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n = self.config.A_number
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title = f"Beta-decay: {n}{parent} -> {n}{daughter}"
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if self._n_branches > 1:
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title += f" ({self._n_branches} branches)"
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return title
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def _format_branch_label(self, i: int) -> str:
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"""Abbreviated branch label for legend."""
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branch = self._unified_branches[i]
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e0 = branch.endpoint_MeV * 1000
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intensity_pct = branch.intensity * 100
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return f"Br. {i + 1}: {e0:.1f} keV ({intensity_pct:.1f}%)"
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# ---------------------------------------------------------------------------
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# Plotting — unified multi-branch approach
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# ---------------------------------------------------------------------------
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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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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.
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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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self._timestamp = datetime.now(timezone.utc).strftime("%Y-%m-%d %H:%M:%S UTC")
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if show_components:
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self._plot_debug_view(total, components, save_path)
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else:
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self._plot_spectra_view(total, components, save_path)
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def _plot_spectra_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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) -> None:
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"""Plot total spectrum with individual branch decomposition."""
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fig, ax = plt.subplots(figsize=(12, 7))
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branch_colors = [
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"#1f77b4",
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"#ff7f0e",
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"#2ca02c",
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"#d62728",
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"#9467bd",
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"#8c564b",
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"#e377c2",
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"#7f7f7f",
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"#bcbd22",
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"#17becf",
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]
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e_step_keV = self.config.e_step_MeV * 1000
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# Compute branch contributions (universal * intensity * branch_spectrum)
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branch_contribs = []
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# Universal components are shared (no per-branch key prefix)
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universal_names = [
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"Fermi",
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"Screening",
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"FiniteSizeL0",
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"ChargeDistributionU",
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"Exchange",
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]
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for i in range(self._n_branches):
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universal_product = np.ones_like(self.W)
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for name in universal_names:
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key = self._get_component_key(i, name)
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if key in components:
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universal_product *= components[key]
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elif name in components: # fallback: universal components
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universal_product *= components[name]
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bs = self._get_branch_spectrum(i)
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contrib = universal_product * self._unified_branches[i].intensity * bs
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branch_contribs.append(contrib)
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total_raw = sum(branch_contribs)
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ax.plot(
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self.energies_MeV,
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total_raw,
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"k-",
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lw=2.5,
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label="Total spectrum",
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zorder=10,
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)
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for i, contrib in enumerate(branch_contribs):
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color = branch_colors[i % len(branch_colors)]
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ax.plot(
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self.energies_MeV,
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contrib,
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color=color,
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lw=1.5,
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alpha=0.7,
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label=self._format_branch_label(i),
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)
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ax.set_xlabel(r"Electron kinetic energy $E$ [MeV]", fontsize=12)
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ax.set_ylabel(f"Normalized Counts / {e_step_keV:.1f} keV", fontsize=12)
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fig.suptitle(self._build_figure_title(fig), fontsize=14, fontweight="bold")
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ax.set_yscale("log")
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ax.grid(True, alpha=0.3)
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ax.legend(
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loc="best",
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fontsize=9,
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ncol=min(2, self._n_branches + 1),
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)
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self._build_figure_header(fig)
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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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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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) -> None:
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"""Debug view: vertical layout with 4 panels."""
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n_branches = self._n_branches
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e_step_keV = self.config.e_step_MeV * 1000
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fig, axes = plt.subplots(4, 1, figsize=(12, 16), sharex=True)
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fig.suptitle(self._build_figure_title(fig), fontsize=14, fontweight="bold")
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branch_colors = [
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"#1f77b4",
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"#ff7f0e",
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"#2ca02c",
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"#d62728",
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"#9467bd",
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"#8c564b",
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"#e377c2",
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"#7f7f7f",
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"#bcbd22",
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"#17becf",
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]
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# Panel 1: Total spectrum + per-branch spectra
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branch_contribs = []
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universal_names = [
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"Fermi",
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"Screening",
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"FiniteSizeL0",
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"ChargeDistributionU",
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"Exchange",
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]
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for i in range(n_branches):
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universal_product = np.ones_like(self.W)
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for name in universal_names:
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key = self._get_component_key(i, name)
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if key in components:
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universal_product *= components[key]
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elif name in components:
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universal_product *= components[name]
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bs = self._get_branch_spectrum(i)
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contrib = universal_product * self._unified_branches[i].intensity * bs
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branch_contribs.append(contrib)
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total_raw = sum(branch_contribs)
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ax = axes[0]
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ax.plot(
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self.energies_MeV,
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total_raw,
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"k-",
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lw=2,
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label="Total spectrum",
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zorder=10,
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)
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for i, contrib in enumerate(branch_contribs):
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color = branch_colors[i % len(branch_colors)]
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ax.plot(
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self.energies_MeV,
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contrib,
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color=color,
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lw=1.5,
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alpha=0.7,
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label=self._format_branch_label(i),
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)
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ax.set_yscale("log")
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ax.set_ylabel(f"Normalized Counts / {e_step_keV:.1f} keV", fontsize=10)
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ax.set_title("Spectrum", fontsize=11)
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ax.grid(True, alpha=0.3)
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ax.legend(fontsize=8, loc="best", ncol=min(2, n_branches + 1))
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# Panel 2: Fermi function + all phase spaces
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ax = axes[1]
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if "Fermi" in components:
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fermi_vals = components["Fermi"]
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fermi_scaled = fermi_vals / np.max(fermi_vals)
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ax.plot(
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self.energies_MeV,
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fermi_scaled,
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"r-",
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lw=1.5,
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label="Fermi",
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alpha=0.8,
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)
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for i in range(n_branches):
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color = branch_colors[i % len(branch_colors)]
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branch = self._unified_branches[i]
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key = self._get_component_key(i, "PhaseSpace")
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if key in components:
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ps_vals = components[key]
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W0_branch = T_to_W(branch.endpoint_MeV)
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mask = self.W <= W0_branch
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ps_masked = np.where(mask, ps_vals, 0.0)
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ps_max = np.max(ps_masked)
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if ps_max > 0:
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ps_scaled = ps_masked / ps_max
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else:
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ps_scaled = ps_masked
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ax.plot(
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self.energies_MeV,
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ps_scaled,
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color=color,
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lw=1.5,
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alpha=0.7,
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label=f"PS Br. {i + 1}",
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)
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ax.set_ylabel("Normalized Factor", fontsize=10)
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ax.set_title("Fermi & Phase Space", fontsize=11)
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ax.grid(True, alpha=0.3)
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ax.legend(fontsize=8, loc="best")
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# Panel 3: Universal W0-independent corrections
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ax = axes[2]
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universal_components = [
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"Screening",
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"FiniteSizeL0",
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"ChargeDistributionU",
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"Exchange",
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]
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colors = ["green", "orange", "purple", "brown"]
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for name, color in zip(universal_components, colors):
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if name in components:
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values = components[name]
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values_scaled = values / np.max(values)
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ax.plot(
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self.energies_MeV,
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values_scaled,
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color=color,
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lw=1.5,
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label=name,
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alpha=0.8,
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)
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ax.set_ylabel("Normalized Factor", fontsize=10)
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ax.set_title("Universal Corrections", fontsize=11)
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ax.grid(True, alpha=0.3)
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ax.legend(fontsize=8, loc="best")
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# Panel 4: W0-dependent corrections (Radiative for each branch)
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ax = axes[3]
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for i in range(n_branches):
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color = branch_colors[i % len(branch_colors)]
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key = self._get_component_key(i, "Radiative")
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if key in components:
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rad_vals = components[key]
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ax.plot(
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self.energies_MeV,
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rad_vals,
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color=color,
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lw=1.5,
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alpha=0.7,
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label=f"Br. {i + 1}",
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)
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ax.set_ylabel("Radiative Correction", fontsize=10)
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ax.set_xlabel(r"Electron kinetic energy $E$ [MeV]", fontsize=10)
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ax.set_title("Radiative Corrections", fontsize=11)
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ax.grid(True, alpha=0.3)
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ax.legend(fontsize=8, loc="best", ncol=min(2, n_branches + 1))
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self._build_figure_header(fig)
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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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def _element_symbol(self, Z: int) -> str:
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"""Return chemical symbol for atomic number Z."""
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symbols = [
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"",
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"H",
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"He",
|
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"Li",
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"Be",
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"B",
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"C",
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"N",
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"O",
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"F",
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"Ne",
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"Na",
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"Mg",
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"Al",
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"Si",
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"P",
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"S",
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"Cl",
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"Ar",
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"K",
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"Ca",
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"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",
|
||
]
|
||
return symbols[Z] if Z < len(symbols) else f"Z{Z}"
|
||
|
||
# ---------------------------------------------------------------------------
|
||
# Export
|
||
# ---------------------------------------------------------------------------
|
||
|
||
def export_to_csv(
|
||
self, filename: str, source_type: str = "unknown", csv_verbosity: str = "full"
|
||
) -> None:
|
||
"""Export spectrum data to CSV with metadata header.
|
||
|
||
Parameters
|
||
----------
|
||
filename : str
|
||
Output CSV file path.
|
||
source_type : str
|
||
Source type (paceENSDF, json, etc.).
|
||
csv_verbosity : str
|
||
Verbosity level: 'full' (all components) or 'concise' (total spectrum and normalized branch components only).
|
||
"""
|
||
total = self.total_spectrum(normalize=True)
|
||
components = self.components
|
||
|
||
# Only include enabled corrections that are not basic components
|
||
# Basic components (phase_space and fermi) are always used and should not be listed
|
||
enabled = []
|
||
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")
|
||
|
||
parent_symbol = self._element_symbol(self.config.Z_parent)
|
||
daughter_symbol = self._element_symbol(self.config.Z_daughter)
|
||
|
||
# Get git commit hash
|
||
git_commit = get_git_short_hash()
|
||
|
||
# Format source line with paceENSDF URL if applicable
|
||
if source_type == "paceENSDF":
|
||
source_line = "# source: paceENSDF (https://pypi.org/project/paceENSDF/)"
|
||
else:
|
||
source_line = f"# source: {source_type}"
|
||
|
||
header_lines = [
|
||
f"# beta-spectrum v{__import__('beta_spectrum').__version__}(build.{git_commit})",
|
||
f"# timestamp: {datetime.now(timezone.utc).isoformat()}",
|
||
source_line,
|
||
f"# nuclide: {parent_symbol}{self.config.A_number} -> {daughter_symbol}{self.config.A_number} (Z={self.config.Z_parent}->{self.config.Z_daughter})",
|
||
f"# basic_endpoint: {self.config.endpoint_MeV * 1000:.1f} keV",
|
||
]
|
||
|
||
# Add neutrino mass info if non-zero
|
||
if self.config.neutrino_mass_MeV > 0:
|
||
header_lines.append(
|
||
f"# neutrino_mass_MeV: {self.config.neutrino_mass_MeV:.6f} (non-zero neutrino mass effects included)"
|
||
)
|
||
else:
|
||
header_lines.append(
|
||
f"# neutrino_mass_MeV: {self.config.neutrino_mass_MeV:.6f}"
|
||
)
|
||
|
||
header_lines.append(f"# corrections: {', '.join(enabled)}")
|
||
header_lines.append(f"# e_step: {self.config.e_step_MeV:.4f} MeV")
|
||
header_lines.append(f"# n_points: {len(self.energies_MeV)}")
|
||
|
||
# Add normalization mode
|
||
header_lines.append("# branch normalization: intensity")
|
||
|
||
# Separate branches into active and excluded lists
|
||
active_branches = []
|
||
excluded_branches = []
|
||
|
||
for i, branch in enumerate(self._unified_branches):
|
||
branch_endpoint_keV = branch.endpoint_MeV * 1000
|
||
neutrino_mass_keV = self.config.neutrino_mass_MeV * 1000
|
||
|
||
# Check if branch is excluded due to neutrino mass
|
||
if branch_endpoint_keV <= neutrino_mass_keV:
|
||
excluded_branches.append(
|
||
f" branch_{i + 1}: E₀={branch_endpoint_keV:.1f} keV, transition={branch.transition_type}, intensity={branch.intensity:.4f} - excluded: endpoint < m_nu"
|
||
)
|
||
# Check if branch is excluded due to intensity cutoff
|
||
elif branch.intensity < self.config.intensity_cutoff:
|
||
excluded_branches.append(
|
||
f" branch_{i + 1}: E₀={branch_endpoint_keV:.1f} keV, transition={branch.transition_type}, intensity={branch.intensity:.4f} - excluded: intensity < cutoff"
|
||
)
|
||
else:
|
||
active_branches.append(
|
||
f" branch_{i + 1}: E₀={branch_endpoint_keV:.1f} keV, transition={branch.transition_type}, intensity={branch.intensity:.4f}"
|
||
)
|
||
|
||
# Add active branches list
|
||
if active_branches:
|
||
header_lines.append("# active branches:")
|
||
for branch_info in active_branches:
|
||
header_lines.append(f"# {branch_info}")
|
||
|
||
# Add excluded branches list if there are any
|
||
if excluded_branches:
|
||
header_lines.append("# excluded branches:")
|
||
for branch_info in excluded_branches:
|
||
header_lines.append(f"# {branch_info}")
|
||
|
||
# Create data dictionary with concise column headers
|
||
data: Dict[str, np.ndarray] = {
|
||
"energy_MeV": self.energies_MeV,
|
||
"total_spectrum": total,
|
||
}
|
||
|
||
if csv_verbosity == "full":
|
||
# Per-branch spectra and components with concise branch naming
|
||
for i in range(self._n_branches):
|
||
data[f"branch_{i + 1}_spectrum"] = self._get_branch_spectrum(i)
|
||
for comp_name in ["PhaseSpace", "Radiative"]:
|
||
key = self._get_component_key(i, comp_name)
|
||
if key in components:
|
||
data[f"branch_{i + 1}_{comp_name}"] = components[key]
|
||
|
||
# Universal components (no prefix)
|
||
for name, values in components.items():
|
||
if not name.startswith("branch_"):
|
||
data[name] = values
|
||
elif csv_verbosity == "concise":
|
||
# Only total spectrum and normalized branch components with concise naming
|
||
for i in range(self._n_branches):
|
||
branch_spectrum = self._get_branch_spectrum(i)
|
||
# Check if branch is degenerate (neutrino mass >= branch endpoint)
|
||
branch_endpoint_keV = self._unified_branches[i].endpoint_MeV * 1000
|
||
neutrino_mass_keV = self.config.neutrino_mass_MeV * 1000
|
||
if branch_endpoint_keV <= neutrino_mass_keV:
|
||
# Branch is degenerate, spectrum should be all zeros
|
||
data[f"branch_{i + 1}_spectrum_normalized"] = np.zeros_like(branch_spectrum)
|
||
else:
|
||
# Branch is valid, normalize as usual
|
||
sum_spectrum = np.sum(branch_spectrum)
|
||
if sum_spectrum > 0:
|
||
data[f"branch_{i + 1}_spectrum_normalized"] = branch_spectrum / sum_spectrum
|
||
else:
|
||
data[f"branch_{i + 1}_spectrum_normalized"] = branch_spectrum
|
||
|
||
df = pd.DataFrame(data)
|
||
df.to_csv(filename, index=False, float_format="%.4e")
|
||
|
||
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:
|
||
self._logger.info("CSV exported to %s", filename)
|
||
|
||
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,
|
||
}
|
||
|
||
|
||
@dataclass
|
||
class _UnifiedBranch:
|
||
"""Unified branch view for both single- and multi-branch modes."""
|
||
|
||
endpoint_MeV: float
|
||
transition_type: str
|
||
intensity: float
|