Shadab Hussain techwithshadab

💻

Playing with Data

techwithshadab / qaoa_prob.py

Created November 3, 2021 21:14

	f, ax = plt.subplots(figsize=(20, 8))
	optimized_value = sns.barplot(state, probabilities)
	for item in optimized_value.get_xticklabels():
	item.set_rotation(45)
	plt.title("Probabilites of Each Possible Combination of Assets", fontsize=25) # Probability of Max Return at given risk level
	plt.xlabel('Possible Combinations of Assets',fontsize =20)
	plt.ylabel('Probability',fontsize = 20)
	plt.show()

techwithshadab / qaoa_benchmark.py

Created November 3, 2021 21:13

	%time
	state, values, probabilities = qaoa(qubitOp) # ['FB.O', 'AAPL.O', 'AMZN.O', 'NFLX.O', 'GOOGL.O']

techwithshadab / qaoa.py

Created November 3, 2021 21:12

	def qaoa(qubitOp):
	backend = Aer.get_backend('statevector_simulator') # You can switch to different backends by providing the name of backend.
	seed = 50
	cobyla = COBYLA()
	cobyla.set_options(maxiter=1000)
	qaoa = QAOA(qubitOp, cobyla, 3)
	qaoa.random_seed = seed
	quantum_instance = QuantumInstance(backend=backend, seed_simulator=seed, seed_transpiler=seed)
	results= qaoa.run(quantum_instance)
	selection, state, values, probabilities = print_result(results)

techwithshadab / vqe_prob.py

Created November 3, 2021 21:11

	f, ax = plt.subplots(figsize=(20, 8))
	optimized_value = sns.barplot(state, probabilities)
	for item in optimized_value.get_xticklabels():
	item.set_rotation(45)
	plt.title("Probabilites of Each Possible Combination of Assets", fontsize=25) # Probability of Max Return at given risk level
	plt.xlabel('Possible Combinations of Assets',fontsize =20)
	plt.ylabel('Probability',fontsize = 20)
	plt.show()

techwithshadab / vqe_benchmark.py

Created November 3, 2021 21:09

	%time
	state, values, probabilities = vqe(qubitOp) # ['FB.O', 'AAPL.O', 'AMZN.O', 'NFLX.O', 'GOOGL.O']

techwithshadab / vqe.py

Created November 3, 2021 21:08

	def vqe(qubitOp):
	backend = Aer.get_backend('statevector_simulator') # You can switch to different backends by providing the name of backend.
	seed = 50
	cobyla = COBYLA()
	cobyla.set_options(maxiter=1000)
	ry = TwoLocal(qubitOp.num_qubits, 'ry', 'cz', reps=3, entanglement='full')
	vqe = VQE(qubitOp, ry, cobyla)
	vqe.random_seed = seed
	quantum_instance = QuantumInstance(backend=backend, seed_simulator=seed, seed_transpiler=seed)
	result = vqe.run(quantum_instance)

techwithshadab / classical_prob.py

Created November 3, 2021 21:07

	f, ax = plt.subplots(figsize=(20, 8))
	optimized_value = sns.barplot(state, probabilities)
	for item in optimized_value.get_xticklabels():
	item.set_rotation(45)
	plt.title("Probabilites of Each Possible Combination of Assets", fontsize=25) # Probability of Max Return at given risk level
	plt.xlabel('Possible Combinations of Assets',fontsize =20)
	plt.ylabel('Probability',fontsize = 20)
	plt.show()

techwithshadab / classical_benchmark.py

Created November 3, 2021 21:06

	%time
	state, values, probabilities = numpyEigensolver(qubitOp) # ['FB.O', 'AAPL.O', 'AMZN.O', 'NFLX.O', 'GOOGL.O']

techwithshadab / numpyEigensolver.py

Created November 3, 2021 21:04

	def numpyEigensolver(qubitOp):
	selections = []
	exact_eigensolver = NumPyMinimumEigensolver(qubitOp)
	result = exact_eigensolver.run()
	selection, state, values, probabilities = print_result(result)
	print(selection_to_picks(num_assets, selection))
	return state, values, probabilities

techwithshadab / print_result.py

Created November 3, 2021 21:03

	def print_result(result):
	selection = sample_most_likely(result.eigenstate)
	value = portfolio.portfolio_value(selection, mu, sigma, risk_factor, budget, penalty)
	print('Optimal: selection {}, value {:.4f}'.format(selection, value))
	eigenvector = result.eigenstate if isinstance(result.eigenstate, np.ndarray) else result.eigenstate.to_matrix()
	probabilities = np.abs(eigenvector)**2
	i_sorted = reversed(np.argsort(probabilities))
	print('\n----------------- Full result ---------------------')
	print('selection\tvalue\t\tprobability')
	print('---------------------------------------------------')