137 lines
4.2 KiB
Python
Executable File
137 lines
4.2 KiB
Python
Executable File
#!/usr/bin/env python
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from matplotlib import pyplot as plt
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import numpy as np
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import argparse
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import sys
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# -i → agrs.show → open plot in interactive mode
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# -s → args.save → save plot
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#
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# -n → agrs.note → do the Landau plot with the notes
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# -b → args.both → do the Landau-Moyal plot
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# -m → args.area → do the Landau median plot
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# -c → args.cauchy → do the Cauchy PDF plot
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def moyal(x, μ, σ):
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N = (1)/(np.sqrt(2 * np.pi) * σ)
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return N * np.exp(- 0.5 * ((x - μ)/σ + np.exp(- (x - μ)/σ)))
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def cauchy(x):
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return 1/(np.pi*(1 + x**2))
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def main(args):
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# prepare figure
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if args.show:
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plt.figure()
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elif args.save:
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plt.rcParams['font.size'] = 8
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if (args.both or args.area):
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plt.figure(figsize=(3, 2))
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elif args.note:
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plt.figure(figsize=(5, 3))
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elif args.cauchy:
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plt.figure(figsize=(3, 2))
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if args.note:
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# useful coordinates
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y_min = -0.0086 # y min axes
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y_max = 0.1895 # y max axes
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me = -0.22 # mode
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f_me = 0.1806 # f(mode)
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h_f_me = f_me/2 # falf f(mode)
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x_m = -1.5867 # x₋
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x_p = 2.4330 # x₊
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# draw the lines
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plt.plot([-10, me], [f_me, f_me], color='gray')
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plt.plot([me, me], [f_me, y_min], color='gray')
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plt.plot([-10, x_p], [h_f_me, h_f_me], color='gray')
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plt.plot([x_m, x_m], [y_min, h_f_me], color='gray')
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plt.plot([x_p, x_p], [y_min, h_f_me], color='gray')
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# draw the notes
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s = 0.012
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S = 0.2
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plt.annotate('$f(m_e)$', [-10 + S, f_me - s])
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plt.annotate('$f(m_e)/2$', [-10 + S, h_f_me - s])
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plt.annotate('$x_-$', [x_m + S, y_min + s/2])
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plt.annotate('$x_+$', [x_p + S, y_min + s/2])
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plt.annotate('$m_e$', [me + S, y_min + s/2])
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# prepare plot
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plt.title('Landau distribution', loc='right')
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plt.xlim(-10, 10)
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plt.ylim(y_min, y_max)
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if args.both:
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plt.ylim(-0.015, 0.265)
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# draw Landau plot
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x, y = np.loadtxt(sys.stdin, unpack=True)
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plt.plot(x, y, color='#92182b', label='Landau')
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# Color the area under the function
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if args.area:
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median = 1.3557804
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x0 = np.argmin(abs(median - x))
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plt.fill_between(x[:x0], y[:x0], color='#ff99a8')
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plt.fill_between(x[x0:], y[x0:], color='#b28e94')
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# do Moyal plot
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if args.both:
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μ = -0.22278298
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σ = 1.1191486
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x = np.arange(-10, 30, 0.01)
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plt.plot(x, moyal(x, μ, σ), color='gray', label='Moyal')
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plt.legend()
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# do Cauchy plot
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if args.cauchy:
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x = np.arange(-10, 10, 0.01)
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plt.plot(x, cauchy(x), color='gray', label='Cauchy')
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plt.legend()
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# save figure
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plt.tight_layout()
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if args.show:
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plt.show()
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elif args.save:
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if args.note:
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plt.savefig('notes/images/1-notes.pdf')
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if args.both:
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plt.savefig('slides/images/both-pdf.pdf', transparent=True)
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if args.area:
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plt.savefig('slides/images/median.pdf', transparent=True)
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if args.cauchy:
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plt.savefig('slides/images/cauchy-pdf.pdf', transparent=True)
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if __name__ == '__main__':
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# Parse data
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parser = argparse.ArgumentParser()
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parser.add_argument('-i', '--show',
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action='store_true', default=False,
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help='show the plots')
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parser.add_argument('-s', '--save',
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action='store_true', default=False,
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help='save the plots')
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parser.add_argument('-b', '--both',
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action='store_true', default=False,
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help='do the both plot')
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parser.add_argument('-n', '--note',
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action='store_true', default=False,
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help='do the note plot')
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parser.add_argument('-a', '--area',
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action='store_true', default=False,
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help='do the area plot')
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parser.add_argument('-c', '--cauchy',
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action='store_true', default=False,
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help='do the cauchy plot')
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args = parser.parse_args()
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main(args)
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