2022-10-16 17:16:25 +08:00
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import numpy as np
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from matplotlib import pyplot as plt
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def read_data(file):
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with open(file, 'r') as f:
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data = f.readlines()
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k = 0
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while data[k][0] == '#':
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k += 1
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data = [list(float(s.replace('\n', '').strip()) for s in row.split(',')) for row in data[k:]]
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return np.array(data)
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E_proton = [0.1, 0.2, 0.4, 0.6, 0.8, 1, 2, 4, 6, 8, 10, 15, 20, 30, 50, 60, 80, 100, 150, 200, 300, 400, 700, 1200, 2000]
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E_electron = [0.04, 0.07, 0.1, 0.25, 0.5, 0.75, 1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5, 5.5, 6, 6.5, 7, 8.5, 10]
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data = read_data('assets/AP9_mean_flux.txt')
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proton = [np.mean(data[:, k]) for k in range(4, data.shape[1])]
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data = read_data('assets/AE9_mean_flux.txt')
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electron = [np.mean(data[:, k]) for k in range(4, data.shape[1])]
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_, ax = plt.subplots(1, 2, dpi=150, figsize=(16, 6))
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ax1, ax2 = ax[0], ax[1]
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ax1.plot(E_proton, proton)
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ax1.set_ylim([1e-3, 5 * 1e2])
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ax1.set_yscale('log')
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ax1.set_ylabel(r'$Differential\ Flux\ (\mathrm{cm^{-2}s^{-1}})$')
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ax1.set_title('Average spectra - Proton')
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ax1.set_xlabel(r'$Energy\ (\mathrm{MeV})$')
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ax1.set_xlim(1e-1, 2000)
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ax1.set_xscale('log')
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ax2.plot(E_electron, electron)
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ax2.set_ylim([1e-3, 1e6])
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ax2.set_yscale('log')
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ax2.set_ylabel(r'$Differential\ Flux\ (\mathrm{cm^{-2}s^{-1}MeV^{-1}})$')
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ax2.set_title('Average spectra - Electron')
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ax2.set_xlabel(r'$Energy\ (\mathrm{MeV})$')
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ax2.set_xlim(0.04, 10)
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ax2.set_xscale('log')
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plt.tight_layout()
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plt.savefig('docs/spectra-ep-9')
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