def sample_counts(self, shots, qargs=None):
"""Sample a dict of qubit measurement outcomes in the computational basis.
Args:
shots (int): number of samples to generate.
qargs (None or list): subsystems to sample measurements for,
if None sample measurement of all
subsystems (Default: None).
Returns:
Counts: sampled counts dictionary.
Additional Information:
This function *samples* measurement outcomes using the measure
:meth:`probabilities` for the current state and `qargs`. It does
not actually implement the measurement so the current state is
not modified.
The seed for random number generator used for sampling can be
set to a fixed value by using the stats :meth:`seed` method.
"""
# Sample list of outcomes
samples = self.sample_memory(shots, qargs=qargs)
# Combine all samples into a counts dictionary
inds, counts = np.unique(samples, return_counts=True)
return Counts(zip(inds, counts))
def get_counts(self, experiment=None):
"""Get the histogram data of an experiment.
Args:
experiment (str or QuantumCircuit or Schedule or int or None): the index of the
experiment, as specified by ``data([experiment])``.
Returns:
dict[str:int] or list[dict[str:int]]: a dictionary or a list of
dictionaries. A dictionary has the counts for each qubit with
the keys containing a string in binary format and separated
according to the registers in circuit (e.g. ``0100 1110``).
The string is little-endian (cr[0] on the right hand side).
Raises:
QiskitError: if there are no counts for the experiment.
"""
if experiment is None:
exp_keys = range(len(self.results))
else:
exp_keys = [experiment]
dict_list = []
for key in exp_keys:
exp = self._get_experiment(key)
try:
header = exp.header.to_dict()
except (AttributeError, QiskitError): # header is not available
header = None
if "counts" in self.data(key).keys():
if header:
counts_header = {
k: v
for k, v in header.items()
if k in {"time_taken", "creg_sizes", "memory_slots"}
}
else:
counts_header = {}
dict_list.append(
Counts(self.data(key)["counts"], **counts_header))
elif "statevector" in self.data(key).keys():
vec = postprocess.format_statevector(
self.data(key)["statevector"])
dict_list.append(
statevector.Statevector(vec).probabilities_dict(
decimals=15))
else:
raise QiskitError('No counts for experiment "{}"'.format(
repr(key)))
# Return first item of dict_list if size is 1
if len(dict_list) == 1:
return dict_list[0]
else:
return dict_list