unzhakov
876e1e3ab8
- Add neutrino mass parameter to SpectrumConfig and CLI interface - Update PhaseSpace component to handle neutrino mass effects properly - Update CSV headers to show basic endpoint and all transition types - Add --csv-verbosity option to CLI with 'full' and 'concise' options - Fix comparison plots to properly show linear scale variations - Add comprehensive tests for neutrino mass functionality
145 lines
4.2 KiB
Python
145 lines
4.2 KiB
Python
#!/usr/bin/env python3
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"""
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Script to create a comparison plot of total beta spectra for edge neutrino masses (1.5 keV and 2.5 keV)
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"""
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import pandas as pd
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import matplotlib.pyplot as plt
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import numpy as np
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# Input files
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mass_1_5_csv = "/home/unzhakov/workspace/massive_nu_pr/pr144_nu_mass_1_50keV.csv"
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mass_2_45_csv = "/home/unzhakov/workspace/massive_nu_pr/pr144_nu_mass_2_45keV.csv"
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# Output file
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output_png = (
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"/home/unzhakov/workspace/massive_nu_pr/pr144_comparison_1_5_vs_2_45_keV.png"
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)
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print(f"Reading data from {mass_1_5_csv} and {mass_2_45_csv}...")
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# Read CSV files, skipping metadata headers
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# The metadata headers start with '#'
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def read_csv_with_metadata(filepath):
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with open(filepath, "r") as f:
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lines = f.readlines()
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# Find the line where data starts (not starting with '#')
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data_start_line = 0
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for i, line in enumerate(lines):
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if not line.startswith("#"):
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data_start_line = i
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break
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# Read the data
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df = pd.read_csv(filepath, skiprows=data_start_line)
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return df
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# Read the data
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df_1_5 = read_csv_with_metadata(mass_1_5_csv)
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df_2_45 = read_csv_with_metadata(mass_2_45_csv)
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print("Data loaded successfully.")
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# Extract energy and spectrum data
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energies_1_5 = df_1_5["energy_MeV"].values
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spectrum_1_5 = df_1_5["spectrum"].values
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energies_2_45 = df_2_45["energy_MeV"].values
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spectrum_2_45 = df_2_45["spectrum"].values
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print(
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f"Energy range: {energies_1_5[0] * 1000:.1f} eV to {energies_1_5[-1] * 1000:.1f} eV"
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)
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# Create comparison plot
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fig, ax = plt.subplots(figsize=(12, 8))
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# Plot both spectra
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ax.plot(energies_1_5 * 1000, spectrum_1_5, "b-", lw=2, label="m_ν = 1.5 keV")
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ax.plot(energies_2_45 * 1000, spectrum_2_45, "r--", lw=2, label="m_ν = 2.45 keV")
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# Set labels and title
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ax.set_xlabel(r"Electron kinetic energy $E$ [keV]", fontsize=12)
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ax.set_ylabel("Normalized Spectrum", fontsize=12)
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ax.set_title(
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"Pr144 -> Nd144 Beta Decay: Comparison of Neutrino Mass Effects\n"
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"(1.5 keV vs 2.45 keV)",
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fontsize=14,
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)
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# Set log scale for y-axis to see the endpoint region clearly
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ax.set_yscale("log")
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# Add grid
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ax.grid(True, alpha=0.3)
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# Add legend
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ax.legend(fontsize=12)
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# Focus on the endpoint region (last part of the spectrum)
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# Find the energy range near the endpoint
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max_energy_keV = max(energies_1_5) * 1000
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# Show last 10 keV of the spectrum
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start_energy_keV = max_energy_keV - 10.0
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ax.set_xlim(start_energy_keV, max_energy_keV)
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# Save the plot
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plt.tight_layout()
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plt.savefig(output_png, dpi=150, bbox_inches="tight")
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print(f"Comparison plot saved to {output_png}")
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# Also create a linear scale plot for the endpoint region
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fig_linear, ax_linear = plt.subplots(figsize=(12, 6))
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# Plot both spectra in linear scale
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ax_linear.plot(energies_1_5 * 1000, spectrum_1_5, "b-", lw=2, label="m_ν = 1.5 keV")
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ax_linear.plot(energies_2_45 * 1000, spectrum_2_45, "r--", lw=2, label="m_ν = 2.45 keV")
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# Set labels and title
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ax_linear.set_xlabel(r"Electron kinetic energy $E$ [keV]", fontsize=12)
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ax_linear.set_ylabel("Normalized Spectrum", fontsize=12)
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ax_linear.set_title(
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"Pr144 -> Nd144 Beta Decay: Comparison of Neutrino Mass Effects (Endpoint Region)\n"
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"(1.5 keV vs 2.45 keV) - Linear Scale",
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fontsize=14,
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)
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# Set linear scale for y-axis
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ax_linear.set_yscale("linear")
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# Set y-axis limits to show the variation in the spectrum
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# Find the min and max values in the endpoint region to set appropriate limits
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min_spec_1_5 = np.min(spectrum_1_5[-100:]) # Last 100 points
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max_spec_1_5 = np.max(spectrum_1_5[-100:])
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min_spec_2_45 = np.min(spectrum_2_45[-100:])
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max_spec_2_45 = np.max(spectrum_2_45[-100:])
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overall_min = (
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min(min_spec_1_5, min_spec_2_45) * 0.9
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if min(min_spec_1_5, min_spec_2_45) > 0
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else 0
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)
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overall_max = max(max_spec_1_5, max_spec_2_45) * 1.1
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ax_linear.set_ylim(overall_min, overall_max)
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# Add grid
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ax_linear.grid(True, alpha=0.3)
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# Add legend
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ax_linear.legend(fontsize=12)
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# Focus on the endpoint region (last part of the spectrum)
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ax_linear.set_xlim(start_energy_keV, max_energy_keV)
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# Save the linear plot
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plt.tight_layout()
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linear_output_png = (
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"/home/unzhakov/workspace/massive_nu_pr/pr144_comparison_1_5_vs_2_45_keV_linear.png"
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)
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plt.savefig(linear_output_png, dpi=150, bbox_inches="tight")
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print(f"Linear comparison plot saved to {linear_output_png}")
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