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BitArray

class qiskit.primitives.BitArray(array, num_bits)

GitHub

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) – How many bit are in each outcome.

Raises

  • TypeError – If the input is not a NumPy array with type numpy.uint8.
  • ValueError – 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()

GitHub

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[Any, dtype[uint64]]

concatenate

static concatenate(bit_arrays, axis=0)

GitHub

Join a sequence of bit arrays along an existing axis.

Parameters

  • bit_arrays (Sequence[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) – The axis along which the arrays will be joined. Default is 0.

Returns

The concatenated bit array.

Raises

  • ValueError – If the sequence of bit arrays is empty.
  • ValueError – If any bit arrays has a different number of bits.
  • ValueError – If any bit arrays has a different number of shots.
  • ValueError – If any bit arrays has a different number of dimensions.

Return type

BitArray

concatenate_bits

static concatenate_bits(bit_arrays)

GitHub

Join a sequence of bit arrays along the bits axis.

Note

This method is equivalent to per-shot bitstring concatenation.

Parameters

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

Returns

The stacked bit array.

Raises

  • ValueError – If the sequence of bit arrays is empty.
  • ValueError – If any bit arrays has a different number of shots.
  • ValueError – If any bit arrays has a different shape.

Return type

BitArray

concatenate_shots

static concatenate_shots(bit_arrays)

GitHub

Join a sequence of bit arrays along the shots axis.

Parameters

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

Returns

The stacked bit array.

Raises

  • ValueError – If the sequence of bit arrays is empty.
  • ValueError – If any bit arrays has a different number of bits.
  • ValueError – If any bit arrays has a different shape.

Return type

BitArray

expectation_values

expectation_values(observables)

GitHub

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

Returns

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

Raises

  • ValueError – If the provided observables does not have a shape broadcastable with this bit array.
  • ValueError – If the provided observables does not have the same number of qubits as the number of bits of this bit array.
  • ValueError – If the provided observables are not diagonal.

Return type

ndarray[Any, dtype[float64]]

from_bool_array

static from_bool_array(array, order='big')

GitHub

Construct a new bit array from an array of bools.

Parameters

  • array (ndarray[Any, dtype[bool_]]) – The array to convert, with “bitstrings” along the last axis.
  • order (Literal['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

BitArray

from_counts

static from_counts(counts, num_bits=None)

GitHub

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

Returns

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

Raises

  • ValueError – If different mappings have different numbers of shots.
  • ValueError – If no counts dictionaries are supplied.

Return type

BitArray

from_samples

static from_samples(samples, num_bits=None)

GitHub

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] | Iterable[int]) – A list of bitstrings, a list of integers, or a list of hexstrings.
  • num_bits (int | None) – The desired number of bits per sample. If unset, the biggest sample provided is used to determine this value, with a minimum of one bit.

Returns

A new bit array.

Raises

ValueError – If no strings are given.

Return type

BitArray

get_bitstrings

get_bitstrings(loc=None)

GitHub

Return a list of bitstrings.

Parameters

loc (int |tuple[int, ...] | 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[str]

get_counts

get_counts(loc=None)

GitHub

Return a counts dictionary with bitstring keys.

Parameters

loc (int |tuple[int, ...] | 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[str, int]

get_int_counts

get_int_counts(loc=None)

GitHub

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

Parameters

loc (int |tuple[int, ...] | 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[int, int]

postselect

postselect(indices, selection)

GitHub

Post-select this bit array based on sliced equality with a given bitstring.

Note

If this bit array contains any shape axes, it is first flattened into a long list of shots before applying post-selection. This is done because BitArray cannot handle ragged numbers of shots across axes.

Parameters

  • indices (Sequence[int] | int) – A list of the indices of the cbits on which to postselect. If this bit array was produced by a sampler, then an index i corresponds to the ClassicalRegister location creg[i] (as in slice_bits()). Negative indices are allowed.
  • selection (Sequence[bool |int] | bool |int) – A list of binary values (will be cast to bool) of length matching indices, with indices[i] corresponding to selection[i]. Shots will be discarded unless all cbits specified by indices have the values given by selection.

Returns

A new bit array with shape=(), num_bits=data.num_bits, num_shots<=data.num_shots.

Raises

Return type

BitArray

reshape

reshape(*shape)

GitHub

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 |Iterable[int | Iterable[ShapeInput]]) – The new desired shape.

Returns

A new bit array.

Raises

ValueError – If the size corresponding to your new shape is not equal to either size, or the product of size and num_shots.

Return type

BitArray

slice_bits

slice_bits(indices)

GitHub

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 | Sequence[int]) – The bit positions of interest to slice along.

Returns

A bit array sliced along the bit axis.

Raises

IndexError – If there are any invalid indices of the bit axis.

Return type

BitArray

slice_shots

slice_shots(indices)

GitHub

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

Parameters

indices (int | Sequence[int]) – The shots positions of interest to slice along.

Returns

A bit array sliced along the shots axis.

Raises

IndexError – If there are any invalid indices of the shots axis.

Return type

BitArray

transpose

transpose(*axes)

GitHub

Return a bit array with axes transposed.

Parameters

axes – None, tuple of ints or n ints. See ndarray.transpose for the details.

Returns

A bit array with axes permuted.

Return type

BitArray

Raises

  • ValueError – If axes don’t match this bit array.
  • ValueError – If axes includes any indices that are out of bounds.
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