def sample_from_wavefunction(
wavefunction: Wavefunction,
n_samples: int,
seed: Optional[int] = None,
) -> List[Tuple[int, ...]]:
"""Sample bitstrings from a wavefunction.
Args:
wavefunction: the wavefunction to sample from.
n_samples: the number of samples taken. Needs to be greater than 0.
seed: the seed of the sampler
Returns:
List[Tuple[int]]: A list of tuples where the each tuple is a sampled bitstring.
"""
assert isinstance(n_samples, int) and n_samples > 0
rng = np.random.default_rng(seed)
outcomes_str, probabilities_np = zip(
*wavefunction.get_outcome_probs().items())
probabilities = [
x[0] if isinstance(x, (list, np.ndarray)) else x
for x in list(probabilities_np)
]
samples_ndarray = rng.choice(a=outcomes_str,
size=n_samples,
p=probabilities)
samples = [
tuple(int(y) for y in list(x)[::-1]) for x in list(samples_ndarray)
]
return samples
def test_get_outcome_probs(self, wf_vec):
wf = Wavefunction(wf_vec)
probs_dict = wf.get_outcome_probs()
assert all([len(key) == wf.n_qubits for key in probs_dict.keys()])
for key in probs_dict.keys():
assert len(key) == wf.n_qubits
assert wf.probabilities()[int(key, 2)] == probs_dict[key]