Ejemplo n.º 1
0
g1 = rename(gaussian, ['x','mu1','sigma'])
g2 = rename(gaussian, ['x','mu2','sigma'])
print describe(g1)
print describe(g2)

# <codecell>

#make two likelihood and them up
ulh1 = UnbinnedLH(g1,data1)
ulh2 = UnbinnedLH(g2,data2)
sim = SimultaneousFit(ulh1,ulh2)
print describe(sim) #note the sigma merge

# <codecell>

sim.draw(args=(0.5, 1.5, 10.5))

# <codecell>

m = Minuit(sim, mu1=0.5, sigma=1.5, mu2=10.5)

# <codecell>

m.migrad();

# <codecell>

sim.show(m)

# <markdowncell>
Ejemplo n.º 2
0
Archivo: simul.py Proyecto: bks/probfit
from matplotlib import pyplot as plt
from numpy.random import randn, seed

seed(0)
width = 2.
data1 = randn(1000)*width + 1
data2 = randn(1000)*width + 2

#two gaussian with shared width
pdf1 = rename(gaussian, ('x', 'mu_1', 'sigma'))
pdf2 = rename(gaussian, ('x', 'mu_2', 'sigma'))

lh1 = UnbinnedLH(pdf1, data1)
lh2 = UnbinnedLH(pdf2, data2)

simlh = SimultaneousFit(lh1, lh2)

m = Minuit(simlh, mu_1=1.2, mu_2=2.2, sigma=1.5)

plt.figure(figsize=(8, 3))
plt.subplot(211)
simlh.draw(m)
plt.suptitle('Before')

m.migrad() # fit

plt.figure(figsize=(8, 3))
plt.subplot(212)
simlh.draw(m)
plt.suptitle('After')
Ejemplo n.º 3
0
g1 = rename(gaussian, ['x','mu1','sigma'])
g2 = rename(gaussian, ['x','mu2','sigma'])
print describe(g1)
print describe(g2)

# <codecell>

#make two likelihood and them up
ulh1 = UnbinnedLH(g1,data1)
ulh2 = UnbinnedLH(g2,data2)
sim = SimultaneousFit(ulh1,ulh2)
print describe(sim) #note the sigma merge

# <codecell>

sim.draw(args=(0.5, 1.5, 10.5))

# <codecell>

m = Minuit(sim, mu1=0.5, sigma=1.5, mu2=10.5)

# <codecell>

m.migrad();

# <codecell>

sim.show(m)

# <markdowncell>
Ejemplo n.º 4
0
from matplotlib import pyplot as plt
from numpy.random import randn, seed

seed(0)
width = 2.
data1 = randn(1000) * width + 1
data2 = randn(1000) * width + 2

#two gaussian with shared width
pdf1 = rename(gaussian, ('x', 'mu_1', 'sigma'))
pdf2 = rename(gaussian, ('x', 'mu_2', 'sigma'))

lh1 = UnbinnedLH(pdf1, data1)
lh2 = UnbinnedLH(pdf2, data2)

simlh = SimultaneousFit(lh1, lh2)

m = Minuit(simlh, mu_1=1.2, mu_2=2.2, sigma=1.5)

plt.figure(figsize=(8, 3))
plt.subplot(211)
simlh.draw(m)
plt.suptitle('Before')

m.migrad()  # fit

plt.figure(figsize=(8, 3))
plt.subplot(212)
simlh.draw(m)
plt.suptitle('After')