qlearnkit.encodings package¶
Submodules¶
qlearnkit.encodings.amplitude_encoding module¶
- class qlearnkit.encodings.amplitude_encoding.AmplitudeEncoding[source]¶
Bases:
qlearnkit.encodings.encoding_map.EncodingMap
Amplitude Encoding algorithm
qlearnkit.encodings.angle_encoding module¶
- class qlearnkit.encodings.angle_encoding.AngleEncoding(rotation='Y', scaling=1.5707963267948966)[source]¶
Bases:
qlearnkit.encodings.encoding_map.EncodingMap
Angle Encoding algorithm. Assumes data is feature-normalized.
- circuit(x)[source]¶
- Parameters
x (np.array) – The input data to encode
- Returns
- The circuit that encodes x
Assumes data is feature-normalized. Assumes every element in x is in [0, 1].
- Return type
(qiskit.QuantumCircuit)
qlearnkit.encodings.basis_encoding module¶
- class qlearnkit.encodings.basis_encoding.BasisEncoding[source]¶
qlearnkit.encodings.encoding_map module¶
- class qlearnkit.encodings.encoding_map.EncodingMap[source]¶
Bases:
abc.ABC
Abstract Base class for qlearnkit encoding maps
Module contents¶
- class qlearnkit.encodings.AmplitudeEncoding[source]¶
Bases:
qlearnkit.encodings.encoding_map.EncodingMap
Amplitude Encoding algorithm
- class qlearnkit.encodings.AngleEncoding(rotation='Y', scaling=1.5707963267948966)[source]¶
Bases:
qlearnkit.encodings.encoding_map.EncodingMap
Angle Encoding algorithm. Assumes data is feature-normalized.
- circuit(x)[source]¶
- Parameters
x (np.array) – The input data to encode
- Returns
- The circuit that encodes x
Assumes data is feature-normalized. Assumes every element in x is in [0, 1].
- Return type
(qiskit.QuantumCircuit)
- class qlearnkit.encodings.BasisEncoding[source]¶
- class qlearnkit.encodings.EncodingMap[source]¶
Bases:
abc.ABC
Abstract Base class for qlearnkit encoding maps