def test_spinbitconversion():
a = np.array([0., 1., 0., 1., 0., 1., 0., 1., 0., 1.])
b = tools.bits2spins(a)
c = tools.spins2bits(b)
assert (np.all(a == [0, 1, 0, 1, 0, 1, 0, 1, 0, 1]))
assert (np.all(b == [1, -1, 1, -1, 1, -1, 1, -1, 1, -1]))
assert (np.all(c == a))
def getbitstr(vec):
""" Return bitstring from spin vector array. """
return reduce(lambda x, y: x + y,
[str(int(k)) for k in tools.spins2bits(vec)])
spinVector = spinVector_original.copy()
sa.Anneal(tannealingsched, preannealingmcsteps, spinVector, neighbors, rng)
print(sa.ClassicalIsingEnergy(spinVector, isingJ), getbitstr(spinVector))
# Try using SA (random start)
print("SA results using random state (start and end):")
for sa_itr in range(trotterslices):
spinVector = np.array([2 * rng.randint(2) - 1 for k in range(nspins)],
dtype=np.float)
starten, startstate = (sa.ClassicalIsingEnergy(spinVector, isingJ),
getbitstr(spinVector))
sa.Anneal(tannealingsched, preannealingmcsteps, spinVector, neighbors, rng)
print(starten, startstate, sa.ClassicalIsingEnergy(spinVector, isingJ),
getbitstr(spinVector))
# Now do PIQA
print("QA results:")
print("PIQMC starting state: ", getbitstr(spinVector))
qmc.QuantumAnneal(annealingsched, annealingmcsteps, trotterslices,
annealingtemp, nspins, configurations, neighbors, rng)
minEnergy, minConfiguration = np.inf, []
print("Final states of PIQMC replicas: ")
for col in configurations.T:
candidateEnergy = sa.ClassicalIsingEnergy(col, isingJ)
print(
candidateEnergy,
reduce(lambda x, y: x + y,
[str(int(k)) for k in tools.spins2bits(col)]))
if candidateEnergy < minEnergy:
minEnergy = candidateEnergy
minConfiguration = col
bitstr = getbitstr(spinVector)
coinc_sa[int(bitstr, 2)] += 1
# Now do PIQA
qmc_errors_diff = 0
for s in xrange(samples):
confs = np.tile(
np.array([2 * rng.randint(2) - 1 for k in range(nspins)],
dtype=np.float), (trotterslices, 1)).T
qmc.QuantumAnneal(annealingsched, annealingmcsteps, trotterslices,
annealingtemp, nspins, confs, neighbors, rng)
if not np.all(np.sum(confs, axis=1) / trotterslices == confs[:, 0]):
qmc_errors_diff += 1
else:
bitstr = reduce(lambda x, y: x + y,
[str(int(k)) for k in tools.spins2bits(confs[:, 0])])
coinc_qa[int(bitstr, 2)] += 1
print("QMC differing slices:", qmc_errors_diff)
print("Input:", getbitstr(vinput))
print("Memories:")
for k in memories:
print(k, getbitstr(k))
print("Coincidences (state, QA count, SA count):")
stuff = sorted(enumerate(zip(coinc_qa, coinc_sa)), key=lambda x: x[1][0])[::-1]
for idx, (qa, sa) in stuff[:16]:
print("%s\t%d\t%d" % (bin(idx)[2:].rjust(8, '0'), qa, sa))
def fsaveplot(path, ext='png', close=True, verbose=True):
def getbitstr(vec):
""" Return bitstring from spin vector array. """
return reduce(lambda x,y: x+y,
[ str(int(k)) for k in tools.spins2bits(vec) ])
getbitstr(spinVector))
# Try using SA (random start)
print ("SA results using random state (start and end):")
for sa_itr in range(trotterslices):
spinVector = np.array([ 2*rng.randint(2)-1 for k in range(nspins) ],
dtype=np.float)
starten, startstate = (sa.ClassicalIsingEnergy(spinVector, isingJ),
getbitstr(spinVector))
sa.Anneal(tannealingsched, preannealingmcsteps,
spinVector, neighbors, rng)
print(starten, startstate,
sa.ClassicalIsingEnergy(spinVector, isingJ),
getbitstr(spinVector))
# Now do PIQA
print ("QA results:")
print("PIQMC starting state: ", getbitstr(spinVector))
qmc.QuantumAnneal(annealingsched, annealingmcsteps,
trotterslices, annealingtemp, nspins,
configurations, neighbors, rng)
minEnergy, minConfiguration = np.inf, []
print ("Final states of PIQMC replicas: ")
for col in configurations.T:
candidateEnergy = sa.ClassicalIsingEnergy(col, isingJ)
print(candidateEnergy,
reduce(lambda x,y: x+y,
[ str(int(k)) for k in tools.spins2bits(col) ]))
if candidateEnergy < minEnergy:
minEnergy = candidateEnergy
minConfiguration = col
# Now do PIQA
qmc_errors_diff = 0
for s in xrange(samples):
confs = np.tile(np.array([ 2*rng.randint(2)-1 for k in range(nspins) ],
dtype=np.float), (trotterslices, 1)).T
qmc.QuantumAnneal(annealingsched, annealingmcsteps,
trotterslices, annealingtemp, nspins,
confs, neighbors, rng)
if not np.all(np.sum(confs, axis=1)/trotterslices
== confs[:,0]):
qmc_errors_diff += 1
else:
bitstr = reduce(
lambda x,y: x+y,
[ str(int(k)) for k in tools.spins2bits(confs[:,0]) ]
)
coinc_qa[int(bitstr, 2)] += 1
print("QMC differing slices:", qmc_errors_diff)
print("Input:", getbitstr(vinput))
print("Memories:")
for k in memories:
print(k,getbitstr(k))
print("Coincidences (state, QA count, SA count):")
stuff = sorted(enumerate(zip(coinc_qa, coinc_sa)),
key=lambda x: x[1][0])[::-1]
for idx, (qa, sa) in stuff[:16]:
print("%s\t%d\t%d" % (bin(idx)[2:].rjust(8,'0'), qa, sa))
