def test_draw_simultaneous():
np.random.seed(0)
data = np.random.randn(10000)
shifted = data + 3.
g1 = rename(gaussian, ['x', 'lmu', 'sigma'])
g2 = rename(gaussian, ['x', 'rmu', 'sigma'])
ulh1 = UnbinnedLH(g1, data)
ulh2 = UnbinnedLH(g2, shifted)
sim = SimultaneousFit(ulh1, ulh2)
sim.draw(args=(0, 1, 3))
def test_draw_simultaneous_prefix():
np.random.seed(0)
data = np.random.randn(10000)
shifted = data + 3.
g1 = rename(gaussian, ['x', 'lmu', 'sigma'])
g2 = rename(gaussian, ['x', 'rmu', 'sigma'])
ulh1 = UnbinnedLH(g1, data)
ulh2 = UnbinnedLH(g2, shifted)
sim = SimultaneousFit(ulh1, ulh2, prefix=['g1_', 'g2_'])
minuit = Minuit(sim, g1_lmu=0., g1_sigma=1., g2_rmu=0., g2_sigma=1.,
print_level=0)
minuit.migrad()
sim.draw(minuit)
def test_draw_simultaneous_prefix():
np.random.seed(0)
data = np.random.randn(10000)
shifted = data + 3.0
g1 = rename(gaussian, ["x", "lmu", "sigma"])
g2 = rename(gaussian, ["x", "rmu", "sigma"])
ulh1 = UnbinnedLH(g1, data)
ulh2 = UnbinnedLH(g2, shifted)
sim = SimultaneousFit(ulh1, ulh2, prefix=["g1_", "g2_"])
minuit = Minuit(
sim, g1_lmu=0.0, g1_sigma=1.0, g2_rmu=0.0, g2_sigma=1.0, print_level=0
)
minuit.migrad()
sim.draw(minuit)
