qiskit/tools/qcvv/tomography.py
def marginal_counts(counts, meas_qubits):
    """
    Compute the marginal counts for a subset of measured qubits.

    Args:
        counts (dict): the counts returned from a backend ({str: int}).
        meas_qubits (list[int]): the qubits to return the marginal
                                 counts distribution for.

    Returns:
        dict: A counts dict for the meas_qubits.abs
        Example: if `counts = {'00': 10, '01': 5}`
            `marginal_counts(counts, [0])` returns `{'0': 15, '1': 0}`.
            `marginal_counts(counts, [0])` returns `{'0': 10, '1': 5}`.
    """
    # pylint: disable=cell-var-from-loop
    # Extract total number of qubits from count keys
    num_of_qubits = len(list(counts.keys())[0])

    # keys for measured qubits only
    qs = sorted(meas_qubits, reverse=True)

    meas_keys = count_keys(len(qs))

    # get regex match strings for summing outcomes of other qubits
    rgx = [
        reduce(lambda x, y: (key[qs.index(y)] if y in qs else '\\d') + x,
               range(num_of_qubits), '') for key in meas_keys
    ]

    # build the return list
    meas_counts = []
    for m in rgx:
        c = 0
        for key, val in counts.items():
            if match(m, key):
                c += val
        meas_counts.append(c)

    # return as counts dict on measured qubits only
    return dict(zip(meas_keys, meas_counts))
def marginal_counts(counts, meas_qubits):
    # pylint: disable=cell-var-from-loop
    # Extract total number of qubits from count keys
    num_of_qubits = len(list(counts.keys())[0])

    # keys for measured qubits only
    qs = sorted(meas_qubits, reverse=True)

    meas_keys = count_keys(len(qs))

    # get regex match strings for summing outcomes of other qubits
    rgx = [
        reduce(lambda x, y: (key[qs.index(y)] if y in qs else '\\d') + x,
               range(num_of_qubits), '') for key in meas_keys
    ]

    # build the return list
    meas_counts = []
    for m in rgx:
        c = 0
        for key, val in counts.items():
            if match(m, key):
                c += val
        meas_counts.append(c)

    # return as counts dict on measured qubits only
    return dict(zip(meas_keys, meas_counts))
def marginal_counts ( counts , meas_qubits ) : # pylint: disable=cell-var-from-loop # Extract total number of qubits from count keys num_of_qubits = len ( list ( counts . keys ( ) ) [ 0 ] ) # keys for measured qubits only qs = sorted ( meas_qubits , reverse = True ) meas_keys = count_keys ( len ( qs ) ) # get regex match strings for summing outcomes of other qubits rgx = [ reduce ( lambda x , y : ( key [ qs . index ( y ) ] if y in qs else '\\d' ) + x , range ( num_of_qubits ) , '' ) for key in meas_keys ] # build the return list meas_counts = [ ] for m in rgx : c = 0 for key , val in counts . items ( ) : if match ( m , key ) : c += val meas_counts . append ( c ) # return as counts dict on measured qubits only return dict ( zip ( meas_keys , meas_counts ) )
Compute the marginal counts for a subset of measured qubits.

    Args:
        counts (dict): the counts returned from a backend ({str: int}).
        meas_qubits (list[int]): the qubits to return the marginal
                                 counts distribution for.

    Returns:
        dict: A counts dict for the meas_qubits.abs
        Example: if `counts = {'00': 10, '01': 5}`
            `marginal_counts(counts, [0])` returns `{'0': 15, '1': 0}`.
            `marginal_counts(counts, [0])` returns `{'0': 10, '1': 5}`.
Compute the marginal counts for a subset of measured qubits .