# -*- coding: utf-8 -*- import matplotlib.pyplot as plt from probfit.pdf import doublegaussian from probfit.plotting import draw_normed_pdf 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)
# -*- coding: utf-8 -*-
import matplotlib.pyplot as plt
from probfit.pdf import doublecrystalball
from probfit.plotting import draw_normed_pdf
bound = (-2, 12)
arg = dict(alpha=1.0, alpha2=2.0, n=2.0, n2=4, mean=5, sigma=1)
draw_normed_pdf(doublecrystalball,
arg=arg,
bound=bound,
label=str(arg),
density=True)
arg = dict(alpha=2, alpha2=1, n=7.0, n2=10.0, mean=5, sigma=1)
draw_normed_pdf(doublecrystalball,
arg=arg,
bound=bound,
label=str(arg),
density=True)
plt.grid(True)
plt.legend().get_frame().set_alpha(0.5)
# -*- coding: utf-8 -*- import matplotlib.pyplot as plt from probfit.pdf import argus from probfit.plotting import draw_normed_pdf bound = (5.22, 5.30) arg = dict(c=5.29, chi=1.0, p=0.5) draw_normed_pdf(argus, arg=arg, bound=bound, label=str(arg), density=True) arg = dict(c=5.29, chi=1.0, p=0.4) draw_normed_pdf(argus, arg=arg, bound=bound, label=str(arg), density=True) arg = dict(c=5.29, chi=2.0, p=0.5) draw_normed_pdf(argus, arg=arg, bound=bound, label=str(arg), density=True) plt.grid(True) plt.legend().get_frame().set_alpha(0.5)
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)
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)
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)
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)
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)