def test_pts_from_p4s(nevents, nparticles):
p4s = ef.gen_random_events(nevents, nparticles, dim=4,
mass='random').reshape(nevents, nparticles, 4)
pts = ef.pts_from_p4s(p4s)
slow_pts = []
for i in range(nevents):
event_pts = []
for j in range(nparticles):
event_pts.append(np.sqrt(p4s[i, j, 1]**2 + p4s[i, j, 2]**2))
slow_pts.append(event_pts)
slow_pts = np.asarray(slow_pts)
assert epsilon_diff(slow_pts, pts)
def test_ys_from_pts_etas_ms(nevents, nparticles):
p4s = ef.gen_random_events(nevents, nparticles, dim=4,
mass='random').reshape(nevents, nparticles, 4)
ys = ef.ys_from_p4s(p4s)
y_primes = ef.ys_from_pts_etas_ms(ef.pts_from_p4s(p4s),
ef.etas_from_p4s(p4s),
ef.ms_from_p4s(p4s))
assert epsilon_diff(ys, y_primes, 1e-12)
# test cutoff
pts, ms = 1000 * np.random.rand(25), 10 * np.random.rand(25)
etas = np.random.choice([-1., 1.], size=25) * 100 * np.random.rand(25)
for c1, c2 in zip(np.linspace(20, 100, 5), 20 + 80 * np.random.rand(5)):
ys_c1 = ef.ys_from_pts_etas_ms(pts, etas, ms, _cutoff=c1)
ys_c2 = ef.ys_from_pts_etas_ms(pts, etas, ms, _cutoff=c2)
assert epsilon_diff(ys_c1, ys_c2, 1e-12)
def test_efms(v, measure, normed, M):
events = ef.gen_random_events(2, M)
e = ef.EFM(v, measure=measure, normed=normed, coords='epxpypz')
for event in events:
if measure == 'hadrefm':
zs = np.atleast_1d(ef.pts_from_p4s(event))
elif measure == 'eeefm':
zs = event[:, 0]
nhats = event / zs[:, np.newaxis]
if normed:
zs = zs / zs.sum()
e_ans = e.compute(event)
if v == 0:
assert epsilon_percent(e_ans, zs.sum(), 10**-13)
else:
s_ans = slow_efm(zs, nhats, v)
assert epsilon_percent(s_ans, e_ans, 10**-13)