Esempio n. 1
0
from probfit.pdf import novosibirsk
from probfit.plotting import draw_normed_pdf
import matplotlib.pyplot as plt

bound = (5.22, 5.30)

arg = dict(width=0.005, peak=5.28, tail=0.2)
draw_normed_pdf(novosibirsk, arg=arg, bound=bound, label=str(arg), density=True)

arg = dict(width=0.002, peak=5.28, tail=0.2)
draw_normed_pdf(novosibirsk, arg=arg, bound=bound, label=str(arg), density=True)

arg = dict(width=0.005, peak=5.28, tail=0.1)
draw_normed_pdf(novosibirsk, arg=arg, bound=bound, label=str(arg), density=True)

plt.grid(True)
plt.legend(loc='upper left').get_frame().set_alpha(0.5)
Esempio n. 2
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from probfit.pdf import cruijff
from probfit.plotting import draw_normed_pdf
import matplotlib.pyplot as plt

bound = (5.22, 5.30)

arg = dict(m_0=5.28, sigma_L=0.005, sigma_R=0.005, alpha_R=0., alpha_L=0.1)
draw_normed_pdf(cruijff, arg=arg, bound=bound, label=str(arg), density=True)

arg = dict(m_0=5.28, sigma_L=0.005, sigma_R=0.005, alpha_R=0., alpha_L=0.5)
draw_normed_pdf(cruijff, arg=arg, bound=bound, label=str(arg), density=True)

arg = dict(m_0=5.28, sigma_L=0.002, sigma_R=0.005, alpha_R=0., alpha_L=0.01)
draw_normed_pdf(cruijff, arg=arg, bound=bound, label=str(arg), density=True)

plt.grid(True)
plt.legend(loc='upper left', prop={'size': 8}).get_frame().set_alpha(0.5)
Esempio n. 3
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from probfit.pdf import crystalball
from probfit.plotting import draw_normed_pdf
import matplotlib.pyplot as plt

bound = (5.22, 5.30)

arg = dict(alpha=1., n=2., mean=5.28, sigma=0.01)
draw_normed_pdf(crystalball, arg=arg, bound=bound, label=str(arg), density=True)

arg = dict(alpha=0.5, n=10., mean=5.28, sigma=0.005)
draw_normed_pdf(crystalball, arg=arg, bound=bound, label=str(arg), density=True)

plt.grid(True)
plt.legend().get_frame().set_alpha(0.5)
Esempio n. 4
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from probfit.pdf import doublegaussian
from probfit.plotting import draw_normed_pdf
import matplotlib.pyplot as plt

bound = (-10, 10)

arg = dict(mean=1.0, sigma_L=1, sigma_R=2)
draw_normed_pdf(doublegaussian, arg=arg, bound=bound, label=str(arg))

arg = dict(mean=1.0, sigma_L=0.5, sigma_R=3)
draw_normed_pdf(doublegaussian, arg=arg, bound=bound, label=str(arg))

plt.grid(True)
plt.legend().get_frame().set_alpha(0.5)