'''simple docstring'''





import math

import numpy as np
import qiskit
from qiskit import Aer, ClassicalRegister, QuantumCircuit, QuantumRegister, execute
def 						__A							(     UpperCAmelCase = 3					)     ->			qiskit.result.counts.Counts:




						'''simple docstring'''
						if isinstance(UpperCAmelCase     ,UpperCAmelCase					):
												raise TypeError("number of qubits must be a integer."					)
						if number_of_qubits <= 0:
												raise ValueError("number of qubits must be > 0."					)
						if math.floor(UpperCAmelCase					) != number_of_qubits:
												raise ValueError("number of qubits must be exact integer."					)
						if number_of_qubits > 1_0:
												raise ValueError("number of qubits too large to simulate(>10)."					)

						_UpperCamelCase			:			int   			=						QuantumRegister(UpperCAmelCase     ,"qr"					)
						_UpperCamelCase			:			int   			=						ClassicalRegister(UpperCAmelCase     ,"cr"					)

						_UpperCamelCase			:			Optional[Any]   			=						QuantumCircuit(UpperCAmelCase     ,UpperCAmelCase					)

						_UpperCamelCase			:			List[Any]   			=						number_of_qubits

						for i in range(UpperCAmelCase					):
												quantum_circuit.h(number_of_qubits - i - 1					)
												counter -= 1
												for j in range(UpperCAmelCase					):
																		quantum_circuit.cp(np.pi / 2 ** (counter - j)     ,UpperCAmelCase     ,UpperCAmelCase					)

						for k in range(number_of_qubits // 2					):
												quantum_circuit.swap(UpperCAmelCase     ,number_of_qubits - k - 1					)

						# measure all the qubits
						quantum_circuit.measure(UpperCAmelCase     ,UpperCAmelCase					)
						# simulate with 10000 shots
						_UpperCamelCase			:			List[Any]   			=						Aer.get_backend("qasm_simulator"					)
						_UpperCamelCase			:			Dict   			=						execute(UpperCAmelCase     ,UpperCAmelCase     ,shots=1_0_0_0_0					)

						return job.result().get_counts(UpperCAmelCase					)


if __name__ == "__main__":
			print(
			    f"""Total count for quantum fourier transform state is: \
    {quantum_fourier_transform(3)}"""
			)



'''simple docstring'''





def 						__A							(     UpperCAmelCase     ,UpperCAmelCase     ,UpperCAmelCase=False					)     ->			Optional[int]:




						'''simple docstring'''

						if isinstance(UpperCAmelCase     ,UpperCAmelCase					) and isinstance(UpperCAmelCase     ,UpperCAmelCase					):
												_UpperCamelCase			:			Any   			=						len(set_a.intersection(UpperCAmelCase					)					)

												if alternative_union:
																		_UpperCamelCase			:			List[str]   			=						len(UpperCAmelCase					) + len(UpperCAmelCase					)
												else:
																		_UpperCamelCase			:			List[str]   			=						len(set_a.union(UpperCAmelCase					)					)

												return intersection / union

						if isinstance(UpperCAmelCase     ,(list, tuple)					) and isinstance(UpperCAmelCase     ,(list, tuple)					):
												_UpperCamelCase			:			List[Any]   			=						[element for element in set_a if element in set_b]

												if alternative_union:
																		_UpperCamelCase			:			str   			=						len(UpperCAmelCase					) + len(UpperCAmelCase					)
																		return len(UpperCAmelCase					) / union
												else:
																		_UpperCamelCase			:			int   			=						set_a + [element for element in set_b if element not in set_a]
																		return len(UpperCAmelCase					) / len(UpperCAmelCase					)

												return len(UpperCAmelCase					) / len(UpperCAmelCase					)
						return None


if __name__ == "__main__":
			lowerCAmelCase_	:		List[str]			=     {"""a""", """b""", """c""", """d""", """e"""}
			lowerCAmelCase_	:		Dict			=     {"""c""", """d""", """e""", """f""", """h""", """i"""}
			print(jaccard_similarity(set_a, set_b))


