def test_measure_ee(event, beta, theta_eps, kappa, normed):
if kappa == 'pf' and normed:
pytest.skip()
Es = event[:, 0]
emeas = ef.Measure('ee', beta, kappa, normed, 'epxpypz', True)
ezs, ethetas = emeas.evaluate(event)
# compute naively
if kappa == 'pf':
zs = np.ones(len(Es))
phats = event
else:
if normed:
zs = Es**kappa / np.sum(Es**kappa)
else:
zs = Es**kappa
phats = event / Es[:, np.newaxis]
thetas = np.asarray([[
2 * abs(phti[0] * phtj[0] - np.dot(phti[1:], phtj[1:]))
for phti in phats
] for phtj in phats])**(beta / 2)
assert epsilon_diff(ezs, zs, 10**-13)
assert epsilon_diff(ethetas, thetas, 10**-theta_eps)
def test_measure_hadrdot_ptyphi(event, beta, theta_eps, kappa, normed):
if normed and kappa == 'pf':
pytest.skip()
pTs = event[:, 0]
ps = np.asarray([
pT * np.asarray(
[np.cosh(y), np.cos(phi),
np.sin(phi), np.sinh(y)]) for (pT, y, phi) in event
])
# compute using the energyflow package
hmeas = ef.Measure('hadrdot', beta, kappa, normed, 'ptyphim', True)
hzs, hthetas = hmeas.evaluate(event)
# compute naively
norm = 1 if not normed else np.sum(pTs**kappa)
zs = (pTs**kappa) / norm if kappa != 'pf' else np.ones(len(pTs))
phats = np.asarray(
[p / (pT if kappa != 'pf' else 1) for p, pT in zip(ps, pTs)])
thetas = np.asarray([[
2 * abs(phti[0] * phtj[0] - np.dot(phti[1:], phtj[1:]))
for phti in phats
] for phtj in phats])**(beta / 2)
assert epsilon_diff(hzs, zs, 10**-13)
assert epsilon_diff(hthetas, thetas, 10**-theta_eps)
def test_measure_hadrdot_p4s(event, beta, theta_eps, kappa, normed,
kappa_normed_behavior):
if normed and kappa == 'pf':
pytest.skip()
pTs = np.sqrt(event[:, 1]**2 + event[:, 2]**2)
ps = event
# compute using the energyflow package
hmeas = ef.Measure('hadrdot', beta, kappa, normed, 'epxpypz', True,
kappa_normed_behavior)
hzs, hthetas = hmeas.evaluate(event)
# compute naively
norm = 1 if not normed else (np.sum(pTs**kappa) if kappa_normed_behavior
== 'orig' else np.sum(pTs)**kappa)
zs = (pTs**kappa) / norm if kappa != 'pf' else np.ones(len(pTs))
phats = np.asarray(
[p / (pT if kappa != 'pf' else 1) for p, pT in zip(ps, pTs)])
thetas = np.asarray([[
2 * abs(phti[0] * phtj[0] - np.dot(phti[1:], phtj[1:]))
for phti in phats
] for phtj in phats])**(beta / 2)
assert epsilon_diff(hzs, zs, 10**-13)
assert epsilon_diff(hthetas, thetas, 10**-theta_eps)
def test_measure_list_input(measure, event, check_input):
meas = ef.Measure(measure, check_input=check_input)
list_event = event.tolist()
nd0, nd1 = meas.evaluate(event)
try:
list0, list1 = meas.evaluate(list_event)
except:
assert not check_input
else:
assert check_input
assert epsilon_diff(nd0, list0, 10**-14)
assert epsilon_diff(nd1, list1, 10**-14)
def test_measure_hadr_ptyphi(pts, ys, phis, beta, kappa, normed):
M = len(pts)
# compute using the energyflow package
hmeas = ef.Measure('hadr', beta, kappa, normed, 'ptyphim', True)
hzs, hthetas = hmeas.evaluate(np.vstack((pts,ys,phis)).T)
# compute naively
norm = 1 if not normed else np.sum(pts**kappa)
zs = (pts**kappa)/norm
thetas = np.asarray([[(ys[i]-ys[j])**2 + min(abs(phis[i]-phis[j]), 2*np.pi-abs(phis[i]-phis[j]))**2
for i in range(M)] for j in range(M)])**(beta/2)
assert epsilon_diff(hzs, zs, 10**-13)
assert epsilon_diff(hthetas, thetas, 10**-13)
def test_measure_ee(event, beta, theta_eps, kappa, normed, kappa_normed_behavior):
if kappa == 'pf' and normed:
pytest.skip()
Es = event[:,0]
emeas = ef.Measure('ee', beta, kappa, normed, 'epxpypz', True, kappa_normed_behavior)
ezs, ethetas = emeas.evaluate(event)
# compute naively
norm = 1 if not normed else (np.sum(Es**kappa) if kappa_normed_behavior == 'orig' else np.sum(Es)**kappa)
zs = (Es**kappa)/norm if kappa != 'pf' else np.ones(len(Es))
phats = np.asarray([p/(E if kappa != 'pf' else 1) for p,E in zip(event,Es)])
thetas = np.asarray([[2*abs(phti[0]*phtj[0]-np.dot(phti[1:],phtj[1:])) for phti in phats] for phtj in phats])**(beta/2)
assert epsilon_diff(ezs, zs, 10**-13)
assert epsilon_diff(ethetas, thetas, 10**-theta_eps)
def test_measure_hadr_p4s(event, beta, kappa, normed):
M = len(event)
pTs = np.sqrt(event[:,1]**2 + event[:,2]**2)
ys = 0.5*np.log((event[:,0] + event[:,3])/(event[:,0] - event[:,3]))
phis = np.arctan2(event[:,2], event[:,1])
# compute using the energyflow package
hmeas = ef.Measure('hadr', beta, kappa, normed, 'epxpypz', True)
hzs, hthetas = hmeas.evaluate(event)
# compute naively
norm = 1 if not normed else np.sum(pTs**kappa)
zs = (pTs**kappa)/norm
thetas = np.asarray([[(ys[i]-ys[j])**2 + min(abs(phis[i]-phis[j]), 2*np.pi-abs(phis[i]-phis[j]))**2
for i in range(M)] for j in range(M)])**(beta/2)
assert epsilon_diff(hzs, zs, 10**-12)
assert epsilon_diff(hthetas, thetas, 10**-12)
