def sample(self, bqm, num_reads=10):
"""Gives random samples.
Args:
todo
Returns:
:obj:`.Response`: The vartype will match the given binary quadratic model.
Notes:
For each variable in each sample, the value is chosen by a coin flip.
"""
values = np.asarray(list(bqm.vartype.value), dtype='int8')
samples = np.random.choice(values, (num_reads, len(bqm)))
variable_labels = list(bqm.linear)
label_to_idx = {v: idx for idx, v in enumerate(variable_labels)}
energies = [
bqm.energy(SampleView(idx, samples, label_to_idx))
for idx in range(num_reads)
]
return Response.from_matrix(samples, {'energy': energies},
vartype=bqm.vartype,
variable_labels=variable_labels)
def sample(self, bqm):
M = bqm.binary.to_numpy_matrix()
sample = np.zeros((len(bqm),), dtype=bool)
# now we iterate, flipping one bit at a time until we have
# traversed all samples. This is a Gray code.
# https://en.wikipedia.org/wiki/Gray_code
def iter_samples():
sample = np.zeros((len(bqm)), dtype=bool)
energy = 0.0
yield sample.copy(), energy
for i in range(1, 1 << len(bqm)):
v = _ffs(i)
# flip the bit in the sample
sample[v] = not sample[v]
# for now just calculate the energy, but there is a more clever way by calculating
# the energy delta for the single bit flip, don't have time, pull requests
# appreciated!
energy = sample.dot(M).dot(sample.transpose())
yield sample.copy(), float(energy) + bqm.offset
samples, energies = zip(*iter_samples())
response = Response.from_matrix(np.asarray(samples), {'energy': energies})
# finally make sure the response matches the given vartype, in-place.
response.change_vartype(bqm.vartype)
return response
def sample(self, bqm):
"""Sample from a binary quadratic model.
Args:
bqm (:obj:`~dimod.BinaryQuadraticModel`):
Binary quadratic model to be sampled from.
Returns:
:obj:`~dimod.Response`: A `dimod` :obj:`.~dimod.Response` object.
Examples:
This example provides samples for a two-variable Ising model.
>>> import dimod
>>> sampler = dimod.ExactSolver()
>>> bqm = dimod.BinaryQuadraticModel({0: 0.0, 1: 1.0}, {(0, 1): 0.5}, -0.5, dimod.SPIN)
>>> response = sampler.sample(bqm)
>>> response.data_vectors['energy']
array([-1., -2., 1., 0.])
"""
M = bqm.binary.to_numpy_matrix()
off = bqm.binary.offset
if M.shape == (0, 0):
return Response.empty(bqm.vartype)
sample = np.zeros((len(bqm), ), dtype=bool)
# now we iterate, flipping one bit at a time until we have
# traversed all samples. This is a Gray code.
# https://en.wikipedia.org/wiki/Gray_code
def iter_samples():
sample = np.zeros((len(bqm)), dtype=bool)
energy = 0.0
yield sample.copy(), energy + off
for i in range(1, 1 << len(bqm)):
v = _ffs(i)
# flip the bit in the sample
sample[v] = not sample[v]
# for now just calculate the energy, but there is a more clever way by calculating
# the energy delta for the single bit flip, don't have time, pull requests
# appreciated!
energy = sample.dot(M).dot(sample.transpose())
yield sample.copy(), float(energy) + off
samples, energies = zip(*iter_samples())
response = Response.from_matrix(np.matrix(samples, dtype='int8'),
{'energy': energies},
vartype=Vartype.BINARY)
# make sure the response matches the given vartype, in-place.
response.change_vartype(bqm.vartype, inplace=True)
return response
