Add QuantumInstance/Backend to algorithm init

.pylintrc

@@ -72,7 +72,8 @@ disable=no-self-use,        # disabled as it is too verbose
     too-many-public-methods, too-few-public-methods, too-many-ancestors,
     unnecessary-pass,   # allow for methods with just "pass", for clarity
     no-else-return,     # relax "elif" after a clause with a return
-    docstring-first-line-empty # relax docstring style
+    docstring-first-line-empty, # relax docstring style
+    import-outside-toplevel
 
 
 
@@ -119,7 +120,7 @@ evaluation=10.0 - ((float(5 * error + warning + refactor + convention) / stateme
 # op = operation iterator
 # b = basis iterator
 good-names=i,j,k,n,m,ex,v,w,x,y,z,Run,_,logger,q,c,r,qr,cr,qc,nd,pi,op,b,ar,br,
-    __unittest
+    __unittest,iSwapGate
 
 # Bad variable names which should always be refused, separated by a comma
 bad-names=foo,bar,toto,tutu,tata
@@ -172,7 +173,7 @@ attr-rgx=[a-z_][a-z0-9_]{2,30}$
 attr-name-hint=[a-z_][a-z0-9_]{2,30}$
 
 # Regular expression matching correct argument names
-argument-rgx=[a-z_][a-z0-9_]{2,30}$
+argument-rgx=[a-z_][a-z0-9_]{2,30}|ax|dt$
 
 # Naming hint for argument names
 argument-name-hint=[a-z_][a-z0-9_]{2,30}$
@@ -297,7 +298,7 @@ ignore-mixin-members=yes
 # (useful for modules/projects where namespaces are manipulated during runtime
 # and thus existing member attributes cannot be deduced by static analysis. It
 # supports qualified module names, as well as Unix pattern matching.
-ignored-modules=matplotlib.cm,numpy.random
+ignored-modules=matplotlib.cm,numpy.random,retworkx
 
 # List of class names for which member attributes should not be checked (useful
 # for classes with dynamically set attributes). This supports the use of

.travis.yml

@@ -87,25 +87,22 @@ stage_test_aqua: &stage_test_aqua
   install:
     - |
       cat > selection.txt <<EOF
-      test.aqua.operators.test_tpb_grouped_weigted_pauli_operator
+      test.aqua.operators.test_tpb_grouped_weighted_pauli_operator
       test.aqua.operators.test_weighted_pauli_operator
       test.aqua.test_custom_circuit_oracle
       test.aqua.test_entangler_map
       test.aqua.test_eoh
-      test.aqua.test_exact_eigen_solver
-      test.aqua.test_exact_ls_solver
       test.aqua.test_fixed_value_comparator
       test.aqua.test_hhl
       test.aqua.test_initial_state_custom
       test.aqua.test_initial_state_zero
-      test.aqua.test_input_parser
       test.aqua.test_iqpe
       test.aqua.test_logical_expression_oracle
       test.aqua.test_lookup_rotation
-      test.aqua.test_mct
-      test.aqua.test_mcu1
       test.aqua.test_measure_error_mitigation
       test.aqua.test_nlopt_optimizers
+      test.aqua.test_numpy_eigen_solver
+      test.aqua.test_numpy_ls_solver
       test.aqua.test_optimizers
       test.aqua.test_qgan
       test.aqua.test_qpe

qiskit/aqua/algorithms/amplitude_amplifiers/grover.py

@@ -15,15 +15,16 @@
 The Grover's Search algorithm.
 """
 
-from typing import Optional
+from typing import Optional, Union
 import logging
 import operator
 import numpy as np
 
 from qiskit import ClassicalRegister, QuantumCircuit, QuantumRegister
 from qiskit.qasm import pi
+from qiskit.providers import BaseBackend
 
-from qiskit.aqua import AquaError
+from qiskit.aqua import QuantumInstance, AquaError
 from qiskit.aqua.utils import get_subsystem_density_matrix
 from qiskit.aqua.utils.validation import validate_min, validate_in_set
 from qiskit.aqua.algorithms import QuantumAlgorithm
@@ -76,9 +77,12 @@ class Grover(QuantumAlgorithm):
     and be used with Grover algorithm to find a satisfiable assignment.
     """
 
-    def __init__(self, oracle: Oracle, init_state: Optional[InitialState] = None,
-                 incremental: bool = False, num_iterations: int = 1,
-                 mct_mode: str = 'basic') -> None:
+    def __init__(self,
+                 oracle: Oracle, init_state: Optional[InitialState] = None,
+                 incremental: bool = False,
+                 num_iterations: int = 1,
+                 mct_mode: str = 'basic',
+                 quantum_instance: Optional[Union[QuantumInstance, BaseBackend]] = None) -> None:
         r"""
         Args:
             oracle: The oracle component
@@ -98,6 +102,7 @@ def __init__(self, oracle: Oracle, init_state: Optional[InitialState] = None,
                 repeated to amplify the amplitude(s) of the target(s). Has a minimum value of 1.
             mct_mode: Multi-Control Toffoli mode ('basic' | 'basic-dirty-ancilla' |
                 'advanced' | 'noancilla')
+            quantum_instance: Quantum Instance or Backend
 
         Raises:
             AquaError: evaluate_classically() missing from the input oracle
@@ -106,7 +111,7 @@ def __init__(self, oracle: Oracle, init_state: Optional[InitialState] = None,
         validate_in_set('mct_mode', mct_mode,
                         {'basic', 'basic-dirty-ancilla',
                          'advanced', 'noancilla'})
-        super().__init__()
+        super().__init__(quantum_instance)
 
         if not callable(getattr(oracle, "evaluate_classically", None)):
             raise AquaError(

qiskit/aqua/algorithms/amplitude_estimators/ae.py

@@ -21,7 +21,8 @@
 from scipy.optimize import bisect
 
 from qiskit import QuantumCircuit
-from qiskit.aqua import AquaError
+from qiskit.providers import BaseBackend
+from qiskit.aqua import QuantumInstance, AquaError
 from qiskit.aqua.utils import CircuitFactory
 from qiskit.aqua.circuits import PhaseEstimationCircuit
 from qiskit.aqua.components.iqfts import IQFT, Standard
@@ -53,7 +54,8 @@ def __init__(self, num_eval_qubits: int,
                  a_factory: Optional[CircuitFactory] = None,
                  q_factory: Optional[CircuitFactory] = None,
                  i_objective: Optional[int] = None,
-                 iqft: Optional[IQFT] = None) -> None:
+                 iqft: Optional[IQFT] = None,
+                 quantum_instance: Optional[Union[QuantumInstance, BaseBackend]] = None) -> None:
         r"""
         Args:
             num_eval_qubits: Number of evaluation qubits, has a min. value of 1.
@@ -64,9 +66,10 @@ def __init__(self, num_eval_qubits: int,
                 with the state \|1> and 'bad' solutions with the state \|0>.
             iqft: The Inverse Quantum Fourier Transform component, defaults to using a standard IQFT
                 when None
+            quantum_instance: Quantum Instance or Backend
         """
         validate_min('num_eval_qubits', num_eval_qubits, 1)
-        super().__init__(a_factory, q_factory, i_objective)
+        super().__init__(a_factory, q_factory, i_objective, quantum_instance)
 
         # get parameters
         self._m = num_eval_qubits

qiskit/aqua/algorithms/amplitude_estimators/ae_algorithm.py

@@ -15,11 +15,14 @@
 The Amplitude Estimation Algorithm.
 """
 
+from typing import Optional, Union
 import logging
 from abc import abstractmethod
 
+from qiskit.providers import BaseBackend
+from qiskit.aqua import QuantumInstance
 from qiskit.aqua.algorithms import QuantumAlgorithm
-
+from qiskit.aqua.utils import CircuitFactory
 from .q_factory import QFactory
 
 logger = logging.getLogger(__name__)
@@ -46,12 +49,24 @@ class AmplitudeEstimationAlgorithm(QuantumAlgorithm):
     """
 
     @abstractmethod
-    def __init__(self, a_factory=None, q_factory=None, i_objective=None):
+    def __init__(self,
+                 a_factory: Optional[CircuitFactory] = None,
+                 q_factory: Optional[CircuitFactory] = None,
+                 i_objective: Optional[int] = None,
+                 quantum_instance: Optional[Union[QuantumInstance, BaseBackend]] = None) -> None:
+        """
+        Args:
+            a_factory: The A operator, specifying the QAE problem
+            q_factory: The Q operator (Grover operator), constructed from the
+                A operator
+            i_objective: Index of the objective qubit, that marks the 'good/bad' states
+            quantum_instance: Quantum Instance or Backend
+        """
         self._a_factory = a_factory
         self._q_factory = q_factory
         self._i_objective = i_objective
 
-        super().__init__()
+        super().__init__(quantum_instance)
 
     @property
     def a_factory(self):

qiskit/aqua/algorithms/amplitude_estimators/iqae.py

@@ -20,7 +20,8 @@
 from scipy.stats import beta
 
 from qiskit import ClassicalRegister, QuantumRegister, QuantumCircuit
-from qiskit.aqua import AquaError
+from qiskit.providers import BaseBackend
+from qiskit.aqua import QuantumInstance, AquaError
 from qiskit.aqua.utils.circuit_factory import CircuitFactory
 from qiskit.aqua.utils.validation import validate_range, validate_in_set
 
@@ -47,7 +48,8 @@ def __init__(self, epsilon: float, alpha: float,
                  confint_method: str = 'beta', min_ratio: float = 2,
                  a_factory: Optional[CircuitFactory] = None,
                  q_factory: Optional[CircuitFactory] = None,
-                 i_objective: Optional[int] = None) -> None:
+                 i_objective: Optional[int] = None,
+                 quantum_instance: Optional[Union[QuantumInstance, BaseBackend]] = None) -> None:
         """
         The output of the algorithm is an estimate for the amplitude `a`, that with at least
         probability 1 - alpha has an error of epsilon. The number of A operator calls scales
@@ -64,6 +66,7 @@ def __init__(self, epsilon: float, alpha: float,
             q_factory: The Q operator (Grover operator), constructed from the
                 A operator
             i_objective: Index of the objective qubit, that marks the 'good/bad' states
+            quantum_instance: Quantum Instance or Backend
 
         Raises:
             AquaError: if the method to compute the confidence intervals is not supported
@@ -73,7 +76,7 @@ def __init__(self, epsilon: float, alpha: float,
         validate_range('alpha', alpha, 0, 1)
         validate_in_set('confint_method', confint_method, {'chernoff', 'beta'})
 
-        super().__init__(a_factory, q_factory, i_objective)
+        super().__init__(a_factory, q_factory, i_objective, quantum_instance)
 
         # store parameters
         self._epsilon = epsilon

qiskit/aqua/algorithms/amplitude_estimators/mlae.py

@@ -19,8 +19,9 @@
 from scipy.optimize import brute
 from scipy.stats import norm, chi2
 
+from qiskit.providers import BaseBackend
 from qiskit import ClassicalRegister, QuantumRegister, QuantumCircuit
-from qiskit.aqua import AquaError
+from qiskit.aqua import QuantumInstance, AquaError
 from qiskit.aqua.utils.circuit_factory import CircuitFactory
 from qiskit.aqua.utils.validation import validate_min
 from .ae_algorithm import AmplitudeEstimationAlgorithm
@@ -45,7 +46,8 @@ def __init__(self, num_oracle_circuits: int,
                  a_factory: Optional[CircuitFactory] = None,
                  q_factory: Optional[CircuitFactory] = None,
                  i_objective: Optional[int] = None,
-                 likelihood_evals: Optional[int] = None) -> None:
+                 likelihood_evals: Optional[int] = None,
+                 quantum_instance: Optional[Union[QuantumInstance, BaseBackend]] = None) -> None:
         r"""
         Args:
             num_oracle_circuits: The number of circuits applying different powers of the Grover
@@ -60,9 +62,10 @@ def __init__(self, num_oracle_circuits: int,
                 with the state \|1> and 'bad' solutions with the state \|0>
             likelihood_evals: The number of gridpoints for the maximum search of the likelihood
                 function
+            quantum_instance: Quantum Instance or Backend
         """
         validate_min('num_oracle_circuits', num_oracle_circuits, 1)
-        super().__init__(a_factory, q_factory, i_objective)
+        super().__init__(a_factory, q_factory, i_objective, quantum_instance)
 
         # get parameters
         self._evaluation_schedule = [0] + [2**j for j in range(num_oracle_circuits)]

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

@@ -14,7 +14,7 @@
 
 """Quantum SVM algorithm."""
 
-from typing import Dict, Optional
+from typing import Dict, Optional, Union
 import logging
 import sys
 
@@ -23,8 +23,8 @@
 from qiskit.tools import parallel_map
 from qiskit.tools.events import TextProgressBar
 from qiskit.circuit import ParameterVector
-
-from qiskit.aqua import aqua_globals
+from qiskit.providers import BaseBackend
+from qiskit.aqua import QuantumInstance, aqua_globals
 from qiskit.aqua.algorithms import QuantumAlgorithm
 from qiskit.aqua import AquaError
 from qiskit.aqua.utils.dataset_helper import get_num_classes
@@ -80,7 +80,8 @@ def __init__(self, feature_map: FeatureMap,
                  training_dataset: Optional[Dict[str, np.ndarray]] = None,
                  test_dataset: Optional[Dict[str, np.ndarray]] = None,
                  datapoints: Optional[np.ndarray] = None,
-                 multiclass_extension: Optional[MulticlassExtension] = None) -> None:
+                 multiclass_extension: Optional[MulticlassExtension] = None,
+                 quantum_instance: Optional[Union[QuantumInstance, BaseBackend]] = None) -> None:
         """
         Args:
             feature_map: Feature map module, used to transform data
@@ -89,11 +90,12 @@ def __init__(self, feature_map: 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.
+            quantum_instance: Quantum Instance or Backend
 
         Raises:
             AquaError: Multiclass extension not supplied when number of classes > 2
         """
-        super().__init__()
+        super().__init__(quantum_instance)
         # check the validity of provided arguments if possible
         if training_dataset is not None:
             is_multiclass = get_num_classes(training_dataset) > 2

qiskit/aqua/algorithms/classifiers/vqc.py

@@ -14,7 +14,7 @@
 
 """ The Variational Quantum Classifier algorithm """
 
-from typing import Optional, Callable, Dict
+from typing import Optional, Callable, Dict, Union
 import logging
 import math
 import numpy as np
@@ -23,7 +23,8 @@
 from qiskit import ClassicalRegister, QuantumCircuit, QuantumRegister
 from qiskit.circuit import ParameterVector
 
-from qiskit.aqua import AquaError
+from qiskit.providers import BaseBackend
+from qiskit.aqua import QuantumInstance, AquaError
 from qiskit.aqua.utils import map_label_to_class_name
 from qiskit.aqua.utils import split_dataset_to_data_and_labels
 from qiskit.aqua.algorithms import VQAlgorithm
@@ -56,8 +57,8 @@ def __init__(
             datapoints: Optional[np.ndarray] = None,
             max_evals_grouped: int = 1,
             minibatch_size: int = -1,
-            callback: Optional[Callable[[int, np.ndarray, float, int], None]] = None
-    ) -> None:
+            callback: Optional[Callable[[int, np.ndarray, float, int], None]] = None,
+            quantum_instance: Optional[Union[QuantumInstance, BaseBackend]] = None) -> None:
         """
         Args:
             optimizer: The classical optimizer to use.
@@ -73,6 +74,7 @@ def __init__(
                 Four parameter values are passed to the callback as follows during each evaluation.
                 These are: the evaluation count, parameters of the variational form,
                 the evaluated value, the index of data batch.
+            quantum_instance: Quantum Instance or Backend
         Note:
             We use `label` to denotes numeric results and `class` the class names (str).
         Raises:
@@ -81,7 +83,8 @@ def __init__(
         super().__init__(
             var_form=var_form,
             optimizer=optimizer,
-            cost_fn=self._cost_function_wrapper
+            cost_fn=self._cost_function_wrapper,
+            quantum_instance=quantum_instance
         )
         self._batches = None
         self._label_batches = None

qiskit/aqua/algorithms/distribution_learners/qgan.py

@@ -18,15 +18,16 @@
     <https://www.nature.com/articles/s41534-019-0223-2>`_
 """
 
-from typing import Optional
+from typing import Optional, Union
 import csv
 import os
 import logging
 
 import numpy as np
 from scipy.stats import entropy
 
-from qiskit.aqua import AquaError, aqua_globals
+from qiskit.providers import BaseBackend
+from qiskit.aqua import QuantumInstance, AquaError, aqua_globals
 from qiskit.aqua.algorithms import QuantumAlgorithm
 from qiskit.aqua.components.neural_networks.discriminative_network import DiscriminativeNetwork
 from qiskit.aqua.components.neural_networks.generative_network import GenerativeNetwork
@@ -65,7 +66,8 @@ def __init__(self, data: np.ndarray, bounds: Optional[np.ndarray] = None,
                  num_epochs: int = 3000, seed: int = 7,
                  discriminator: Optional[DiscriminativeNetwork] = None,
                  generator: Optional[GenerativeNetwork] = None,
-                 tol_rel_ent: Optional[float] = None, snapshot_dir: Optional[str] = None) -> None:
+                 tol_rel_ent: Optional[float] = None, snapshot_dir: Optional[str] = None,
+                 quantum_instance: Optional[Union[QuantumInstance, BaseBackend]] = None) -> None:
         """
 
         Args:
@@ -84,11 +86,12 @@ def __init__(self, data: np.ndarray, bounds: Optional[np.ndarray] = None,
                 If the training achieves relative entropy equal or lower than tolerance it finishes.
             snapshot_dir: Directory in to which to store cvs file with parameters,
                 if None (default) then no cvs file is created.
+            quantum_instance: Quantum Instance or Backend
         Raises:
             AquaError: invalid input
         """
         validate_min('batch_size', batch_size, 1)
-        super().__init__()
+        super().__init__(quantum_instance)
         if data is None:
             raise AquaError('Training data not given.')
         self._data = np.array(data)