BitArray

class qiskit.primitives.BitArray(array, num_bits)

Bases: ShapedMixin

Stores an array of bit values.

This object contains a single, contiguous block of data that represents an array of bitstrings. The last axis is over packed bits, the second last axis is over shots, and the preceding axes correspond to the shape of the pub that was executed to sample these bits.

Parameters

array (NDArray[np.uint8]) – The uint8 data array.
num_bits (int(opens in a new tab)) – How many bit are in each outcome.

Raises

TypeError(opens in a new tab) – If the input is not a NumPy array with type numpy.uint8.
ValueError(opens in a new tab) – If the input array has fewer than two axes, or the size of the last axis is not the smallest number of bytes that can contain num_bits.

Attributes

array

The raw NumPy array of data.

ndim

num_bits

The number of bits in the register that this array stores data for.

For example, a ClassicalRegister(5, "meas") would result in num_bits=5.

num_shots

The number of shots sampled from the register in each configuration.

More precisely, the length of the second last axis of array.

shape

size

Methods

bitcount

bitcount()

Compute the number of ones appearing in the binary representation of each shot.

Returns

A numpy.uint64-array with shape (*shape, num_shots).

Return type

ndarray(opens in a new tab)[Any(opens in a new tab), dtype(opens in a new tab)[uint64]]

concatenate

static concatenate(bit_arrays, axis=0)

Join a sequence of bit arrays along an existing axis.

Parameters

bit_arrays (Sequence(opens in a new tab)[BitArray]) – The bit arrays must have (1) the same number of bits, (2) the same number of shots, and (3) the same shape, except in the dimension corresponding to axis (the first, by default).
axis (int(opens in a new tab)) – The axis along which the arrays will be joined. Default is 0.

Returns

The concatenated bit array.

Raises

ValueError(opens in a new tab) – If the sequence of bit arrays is empty.
ValueError(opens in a new tab) – If any bit arrays has a different number of bits.
ValueError(opens in a new tab) – If any bit arrays has a different number of shots.
ValueError(opens in a new tab) – If any bit arrays has a different number of dimensions.

Return type

concatenate_bits

static concatenate_bits(bit_arrays)

Join a sequence of bit arrays along the bits axis.

Note

This method is equivalent to per-shot bitstring concatenation.

Parameters

bit_arrays (Sequence(opens in a new tab)[BitArray]) – Bit arrays that have (1) the same number of shots, and (2) the same shape.

Returns

The stacked bit array.

Raises

ValueError(opens in a new tab) – If the sequence of bit arrays is empty.
ValueError(opens in a new tab) – If any bit arrays has a different number of shots.
ValueError(opens in a new tab) – If any bit arrays has a different shape.

Return type

concatenate_shots

static concatenate_shots(bit_arrays)

Join a sequence of bit arrays along the shots axis.

Parameters

bit_arrays (Sequence(opens in a new tab)[BitArray]) – The bit arrays must have (1) the same number of bits, and (2) the same shape.

Returns

The stacked bit array.

Raises

ValueError(opens in a new tab) – If the sequence of bit arrays is empty.
ValueError(opens in a new tab) – If any bit arrays has a different number of bits.
ValueError(opens in a new tab) – If any bit arrays has a different shape.

Return type

expectation_values

expectation_values(observables)

Compute the expectation values of the provided observables, broadcasted against this bit array.

Note

This method returns the real part of the expectation value even if the operator has complex coefficients due to the specification of sampled_expectation_value().

Parameters

observables (str(opens in a new tab) |Pauli |SparsePauliOp |Mapping(opens in a new tab)[str(opens in a new tab) |Pauli, float(opens in a new tab)] | _SupportsArray[dtype(opens in a new tab)[Any(opens in a new tab)]] | _NestedSequence[_SupportsArray[dtype(opens in a new tab)[Any(opens in a new tab)]]] | bool(opens in a new tab) |int(opens in a new tab) |float(opens in a new tab) |complex(opens in a new tab) |bytes(opens in a new tab) | _NestedSequence[bool(opens in a new tab) |int(opens in a new tab) |float(opens in a new tab) |complex(opens in a new tab) |str(opens in a new tab) |bytes(opens in a new tab)]) – The observable(s) to take the expectation value of.
and (Must have a shape broadcastable with with this bit array) –
array. (the same number of qubits as the number of bits of this bit) –
diagonal (The observables must be) –

Returns

An array of expectation values whose shape is the broadcast shape of observables and this bit array.

Raises

ValueError(opens in a new tab) – If the provided observables does not have a shape broadcastable with this bit array.
ValueError(opens in a new tab) – If the provided observables does not have the same number of qubits as the number of bits of this bit array.
ValueError(opens in a new tab) – If the provided observables are not diagonal.

Return type

ndarray(opens in a new tab)[Any(opens in a new tab), dtype(opens in a new tab)[float64]]

from_bool_array

static from_bool_array(array, order='big')

Construct a new bit array from an array of bools.

Parameters

array (ndarray(opens in a new tab)[Any(opens in a new tab), dtype(opens in a new tab)[bool_]]) – The array to convert, with “bitstrings” along the last axis.
order (Literal(opens in a new tab)['big', 'little']) – One of "big" or "little", indicating whether array[..., 0] correspond to the most significant bits or the least significant bits of each bitstring, respectively.

Returns

A new bit array.

Return type

from_counts

static from_counts(counts, num_bits=None)

Construct a new bit array from one or more Counts-like objects.

The counts can have keys that are (uniformly) integers, hexstrings, or bitstrings. Their values represent numbers of occurrences of that value.

Parameters

counts (Mapping[str(opens in a new tab) |int(opens in a new tab), int(opens in a new tab)] | Iterable[Mapping[str(opens in a new tab) |int(opens in a new tab), int(opens in a new tab)]]) – One or more counts-like mappings with the same number of shots.
num_bits (int(opens in a new tab) | None) – The desired number of bits per shot. If unset, the biggest value found sets this value.

Returns

A new bit array with shape () for single input counts, or (N,) for an iterable of $N$ counts.

Raises

ValueError(opens in a new tab) – If different mappings have different numbers of shots.
ValueError(opens in a new tab) – If no counts dictionaries are supplied.

Return type

from_samples

static from_samples(samples, num_bits=None)

Construct a new bit array from an iterable of bitstrings, hexstrings, or integers.

All samples are assumed to be integers if the first one is. Strings are all assumed to be bitstrings whenever the first string doesn’t start with "0x".

Consider pairing this method with reshape() if your samples represent nested data.

Parameters

samples (Iterable[str(opens in a new tab)] | Iterable[int(opens in a new tab)]) – A list of bitstrings, a list of integers, or a list of hexstrings.
num_bits (int(opens in a new tab) | None) – The desired number of bits per sample. If unset, the biggest sample provided is used to determine this value.

Returns

A new bit array.

Raises

ValueError(opens in a new tab) – If no strings are given.

Return type

get_bitstrings

get_bitstrings(loc=None)

Return a list of bitstrings.

Parameters

loc (int(opens in a new tab) |tuple(opens in a new tab)[int(opens in a new tab), ...] | None) – Which entry of this array to return a dictionary for. If None, counts from all positions in this array are unioned together.

Returns

A list of bitstrings.

Return type

list(opens in a new tab)[str(opens in a new tab)]

get_counts

get_counts(loc=None)

Return a counts dictionary with bitstring keys.

Parameters

loc (int(opens in a new tab) |tuple(opens in a new tab)[int(opens in a new tab), ...] | None) – Which entry of this array to return a dictionary for. If None, counts from all positions in this array are unioned together.

Returns

A dictionary mapping bitstrings to the number of occurrences of that bitstring.

Return type

dict(opens in a new tab)[str(opens in a new tab), int(opens in a new tab)]

get_int_counts

get_int_counts(loc=None)

Return a counts dictionary, where bitstrings are stored as ints.

Parameters

loc (int(opens in a new tab) |tuple(opens in a new tab)[int(opens in a new tab), ...] | None) – Which entry of this array to return a dictionary for. If None, counts from all positions in this array are unioned together.

Returns

A dictionary mapping ints to the number of occurrences of that int.

Return type

dict(opens in a new tab)[int(opens in a new tab), int(opens in a new tab)]

reshape

reshape(*shape)

Return a new reshaped bit array.

The num_shots axis is either included or excluded from the reshaping procedure depending on which picture the new shape is compatible with. For example, for a bit array with shape (20, 5) and 64 shots, a reshape to (100,) would leave the number of shots intact, whereas a reshape to (200, 32) would change the number of shots to 32.

Parameters

*shape (int(opens in a new tab) |Iterable(opens in a new tab)[int(opens in a new tab) | Iterable[ShapeInput]]) – The new desired shape.

Returns

A new bit array.

Raises

ValueError(opens in a new tab) – If the size corresponding to your new shape is not equal to either size, or the product of size and num_shots.

Return type

slice_bits

slice_bits(indices)

Return a bit array sliced along the bit axis of some indices of interest.

Note

The convention used by this method is that the index 0 corresponds to the least-significant bit in the array, or equivalently the right-most bitstring entry as returned by get_counts() or get_bitstrings(), etc.

If this bit array was produced by a sampler, then an index i corresponds to the ClassicalRegister location creg[i].

Parameters

indices (int(opens in a new tab) | Sequence[int(opens in a new tab)]) – The bit positions of interest to slice along.

Returns

A bit array sliced along the bit axis.

Raises

ValueError(opens in a new tab) – If there are any invalid indices of the bit axis.

Return type

slice_shots

slice_shots(indices)

Return a bit array sliced along the shots axis of some indices of interest.

Parameters

indices (int(opens in a new tab) | Sequence[int(opens in a new tab)]) – The shots positions of interest to slice along.

Returns

A bit array sliced along the shots axis.

Raises

ValueError(opens in a new tab) – If there are any invalid indices of the shots axis.

Return type

transpose

transpose(*axes)

Return a bit array with axes transposed.

Parameters

axes – None, tuple of ints or n ints. See ndarray.transpose(opens in a new tab) for the details.

Returns

A bit array with axes permuted.

Return type

Raises

ValueError(opens in a new tab) – If axes don’t match this bit array.
ValueError(opens in a new tab) – If axes includes any indices that are out of bounds.

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