qiskit.aqua.components.feature_maps.RawFeatureVector

class RawFeatureVector(feature_dimension=2)

Raw Feature Vector feature map.

The Raw Feature Vector can be directly used as a feature map, where the raw feature vectors will be automatically padded with ending 0s as necessary, to make sure vector length is a power of 2, and normalized such that it can be treated and used as an initial quantum state vector.

Parameters

feature_dimension (int) – The feature dimension, has a minimum value of 1.

__init__(feature_dimension=2)

Parameters

feature_dimension (int) – The feature dimension, has a minimum value of 1.

Methods

__init__([feature_dimension])	type feature_dimension int
construct_circuit(x[, qr, inverse])	Construct the second order expansion based on given data.
get_entangler_map(map_type, num_qubits)	get entangle map
validate_entangler_map(entangler_map, num_qubits)	validate entangler map

Attributes

feature_dimension	returns feature dimension
num_qubits	returns number of qubits
support_parameterized_circuit	returns whether or not the sub-class support parameterized circuit

construct_circuit(x, qr=None, inverse=False)

Construct the second order expansion based on given data.

Parameters

• x (numpy.ndarray) – 1-D to-be-encoded data.

• qr (QuantumRegister) – the QuantumRegister object for the circuit, if None, generate new registers with name q.

• inverse (bool) – inverse

Returns

a quantum circuit transform data x.

Return type

QuantumCircuit

Raises

• TypeError – invalid input

• ValueError – invalid input

property feature_dimension

returns feature dimension

static get_entangler_map(map_type, num_qubits)

get entangle map

property num_qubits

returns number of qubits

property support_parameterized_circuit

returns whether or not the sub-class support parameterized circuit

static validate_entangler_map(entangler_map, num_qubits)

validate entangler map