Merge branch 'master' into initial-state

qiskit/aqua/algorithms/classifiers/qsvm/_qsvm_binary.py

@@ -76,9 +76,10 @@ def train(self, data, labels):
         """
         scaling = 1.0 if self._qalgo.quantum_instance.is_statevector else None
         kernel_matrix = self._qalgo.construct_kernel_matrix(data)
+        lambda2 = self._qalgo.lambda2
         labels = labels * 2 - 1  # map label from 0 --> -1 and 1 --> 1
         labels = labels.astype(np.float)
-        [alpha, b, support] = optimize_svm(kernel_matrix, labels, scaling=scaling)
+        [alpha, b, support] = optimize_svm(kernel_matrix, labels, scaling=scaling, lambda2=lambda2)
         support_index = np.where(support)
         alphas = alpha[support_index]
         svms = data[support_index]

qiskit/aqua/algorithms/classifiers/qsvm/qsvm.py

@@ -80,6 +80,7 @@ def __init__(self, feature_map: Union[QuantumCircuit, FeatureMap],
                  test_dataset: Optional[Dict[str, np.ndarray]] = None,
                  datapoints: Optional[np.ndarray] = None,
                  multiclass_extension: Optional[MulticlassExtension] = None,
+                 lambda2: float = 0.001,
                  quantum_instance: Optional[
                      Union[QuantumInstance, BaseBackend, Backend]] = None) -> None:
         """
@@ -90,6 +91,7 @@ def __init__(self, feature_map: Union[QuantumCircuit, FeatureMap],
             datapoints: Prediction dataset.
             multiclass_extension: If number of classes is greater than 2 then a multiclass scheme
                 must be supplied, in the form of a multiclass extension.
+            lambda2: L2 norm regularization factor
             quantum_instance: Quantum Instance or Backend
 
         Raises:
@@ -118,6 +120,7 @@ def __init__(self, feature_map: Union[QuantumCircuit, FeatureMap],
         self.setup_training_data(training_dataset)
         self.setup_test_data(test_dataset)
         self.setup_datapoint(datapoints)
+        self.lambda2 = lambda2
 
         self.feature_map = feature_map
         self.num_qubits = self.feature_map.num_qubits

qiskit/aqua/algorithms/minimum_eigen_solvers/qaoa/var_form.py

@@ -17,7 +17,7 @@
 import numpy as np
 
 from qiskit import QuantumCircuit
-from qiskit.aqua.operators import (OperatorBase, X, I, H, Zero, CircuitStateFn,
+from qiskit.aqua.operators import (OperatorBase, X, I, H, CircuitStateFn,
                                    EvolutionFactory, LegacyBaseOperator)
 from qiskit.aqua.components.variational_forms import VariationalForm
 from qiskit.aqua.components.initial_states import InitialState
@@ -81,15 +81,13 @@ def construct_circuit(self, parameters, q=None):
                 self.num_parameters, len(parameters)
             ))
 
-        circuit = (H ^ self._num_qubits)
         # initialize circuit, possibly based on given register/initial state
         if isinstance(self._initial_state, QuantumCircuit):
             init_state = CircuitStateFn(self._initial_state)
         elif self._initial_state is not None:
             init_state = CircuitStateFn(self._initial_state.construct_circuit('circuit'))
         else:
-            init_state = Zero
-        circuit = circuit.compose(init_state)
+            circuit = (H ^ self._num_qubits)
 
         for idx in range(self._p):
             circuit = (self._cost_operator * parameters[idx]).exp_i().compose(circuit)

qiskit/aqua/algorithms/quantum_algorithm.py

@@ -60,8 +60,8 @@ def run(self,
             AquaError: If a quantum instance or backend has not been provided
         """
         if quantum_instance is None and self.quantum_instance is None:
-            raise AquaError("Quantum device or backend "
-                            "is needed since you are running quantum algorithm.")
+            raise AquaError("A QuantumInstance or Backend "
+                            "must be supplied to run the quantum algorithm.")
         if isinstance(quantum_instance, (BaseBackend, Backend)):
             self.set_backend(quantum_instance, **kwargs)
         else:

qiskit/aqua/operators/list_ops/list_op.py

@@ -504,16 +504,24 @@ def to_legacy_op(self, massive: bool = False) -> LegacyBaseOperator:
 
     # Array operations:
 
-    def __getitem__(self, offset: int) -> OperatorBase:
+    def __getitem__(self, offset: Union[int, slice]) -> OperatorBase:
         """ Allows array-indexing style access to the Operators in ``oplist``.
 
         Args:
             offset: The index of ``oplist`` desired.
 
         Returns:
-            The ``OperatorBase`` at index ``offset`` of ``oplist``.
+            The ``OperatorBase`` at index ``offset`` of ``oplist``,
+            or another ListOp with the same properties as this one if offset is a slice.
         """
-        return self.oplist[offset]
+        if isinstance(offset, slice):
+            return ListOp(self._oplist[offset],
+                          self._combo_fn,
+                          self._coeff,
+                          self._abelian,
+                          self._grad_combo_fn)
+        else:
+            return self.oplist[offset]
 
     def __iter__(self) -> Iterator:
         """ Returns an iterator over the operators in ``oplist``.

qiskit/aqua/operators/primitive_ops/circuit_op.py

@@ -35,9 +35,8 @@ class CircuitOp(PrimitiveOp):
     """
 
     def __init__(self,
-                 primitive: Union[Instruction, QuantumCircuit] = None,
-                 coeff: Optional[Union[int, float, complex,
-                                       ParameterExpression]] = 1.0) -> None:
+                 primitive: Union[Instruction, QuantumCircuit],
+                 coeff: Union[int, float, complex, ParameterExpression] = 1.0) -> None:
         """
         Args:
             primitive: The QuantumCircuit which defines the

qiskit/aqua/operators/primitive_ops/matrix_op.py

@@ -12,7 +12,7 @@
 
 """ MatrixOp Class """
 
-from typing import Union, Optional, Set, Dict, List, cast
+from typing import Union, Optional, Set, Dict, List, cast, get_type_hints
 import logging
 import numpy as np
 from scipy.sparse import spmatrix
@@ -40,8 +40,8 @@ class MatrixOp(PrimitiveOp):
     """
 
     def __init__(self,
-                 primitive: Union[list, np.ndarray, spmatrix, Operator] = None,
-                 coeff: Optional[Union[int, float, complex, ParameterExpression]] = 1.0) -> None:
+                 primitive: Union[list, np.ndarray, spmatrix, Operator],
+                 coeff: Union[int, float, complex, ParameterExpression] = 1.0) -> None:
         """
         Args:
             primitive: The matrix-like object which defines the behavior of the underlying function.
@@ -51,16 +51,18 @@ def __init__(self,
             TypeError: invalid parameters.
             ValueError: invalid parameters.
         """
+        primitive_orig = primitive
         if isinstance(primitive, spmatrix):
             primitive = primitive.toarray()
 
         if isinstance(primitive, (list, np.ndarray)):
             primitive = Operator(primitive)
 
         if not isinstance(primitive, Operator):
-            raise TypeError(
-                'MatrixOp can only be instantiated with MatrixOperator, '
-                'not {}'.format(type(primitive)))
+            type_hints = get_type_hints(MatrixOp.__init__).get('primitive')
+            valid_cls = [cls.__name__ for cls in type_hints.__args__]
+            raise TypeError(f"MatrixOp can only be instantiated with {valid_cls}, "
+                            f"not '{primitive_orig.__class__.__name__}'")
 
         if not primitive.input_dims() == primitive.output_dims():
             raise ValueError('Cannot handle non-square matrices yet.')

qiskit/aqua/operators/primitive_ops/pauli_op.py

@@ -39,7 +39,7 @@ class PauliOp(PrimitiveOp):
     """
 
     def __init__(self,
-                 primitive: Union[Pauli] = None,
+                 primitive: Union[Pauli],
                  coeff: Union[int, float, complex, ParameterExpression] = 1.0) -> None:
         """
             Args:

qiskit/aqua/operators/primitive_ops/primitive_op.py

@@ -48,8 +48,9 @@ class PrimitiveOp(OperatorBase):
     @staticmethod
     # pylint: disable=unused-argument
     def __new__(cls,
-                primitive: Union[Instruction, QuantumCircuit, List,
-                                 np.ndarray, spmatrix, MatrixOperator, Pauli] = None,
+                primitive:
+                Optional[Union[Instruction, QuantumCircuit, List,
+                               np.ndarray, spmatrix, MatrixOperator, Pauli]] = None,
                 coeff: Union[int, float, complex, ParameterExpression] = 1.0) -> 'PrimitiveOp':
         """ A factory method to produce the correct type of PrimitiveOp subclass
         based on the primitive passed in. Primitive and coeff arguments are passed into
@@ -85,9 +86,10 @@ def __new__(cls,
                         'factory constructor'.format(type(primitive)))
 
     def __init__(self,
-                 primitive: Union[Instruction, QuantumCircuit, List,
-                                  np.ndarray, spmatrix, MatrixOperator, Pauli] = None,
-                 coeff: Optional[Union[int, float, complex, ParameterExpression]] = 1.0) -> None:
+                 primitive:
+                 Optional[Union[Instruction, QuantumCircuit, List,
+                                np.ndarray, spmatrix, MatrixOperator, Pauli]] = None,
+                 coeff: Union[int, float, complex, ParameterExpression] = 1.0) -> None:
         """
             Args:
                 primitive: The operator primitive being wrapped.