[Stable] Prepare 0.9.5 release (#1630)

* Fix QubitConverter import in Migration Tutorial (#1625)

* Fix lint errors (#1626)

* Remove jaxlib pin from CI (#1628)

* Handle new yfinance, fix bugs in provider (#1629)

* Prepare 0.9.5 release

Author: manoelmarques

.github/workflows/main.yml

@@ -130,13 +130,6 @@ jobs:
       - uses: ./.github/actions/install-main-dependencies
         if: ${{ !startsWith(github.ref, 'refs/heads/stable') && !startsWith(github.base_ref, 'stable/') }}
       - uses: ./.github/actions/install-aqua
-      - name: Install Dependencies
-        run: |
-          # pin jax and jaxlib as the latest jaxlib 0.1.60 forces
-          # numpy 1.19.5 to be installed which causes cvxpy failure to load
-          # with 'numpy.core.multiarray failed to import.' error.
-          pip install -U jax==0.2.9 jaxlib==0.1.59
-        shell: bash
       - name: Aqua Unit Tests under Python ${{ matrix.python-version }}
         uses: ./.github/actions/run-tests
         with:

docs/tutorials/Qiskit Algorithms Migration Guide.ipynb

@@ -1 +1 @@
-0.9.4
+0.9.5

qiskit/aqua/VERSION.txt

@@ -279,7 +279,8 @@ def get_rel_entr(self) -> float:
         return rel_entr
 
     def _store_params(self, e, d_loss, g_loss, rel_entr):
-        with open(os.path.join(self._snapshot_dir, 'output.csv'), mode='a') as csv_file:
+        with open(os.path.join(self._snapshot_dir, 'output.csv'),
+                  mode='a', encoding="utf8") as csv_file:
             fieldnames = ['epoch', 'loss_discriminator',
                           'loss_generator', 'params_generator', 'rel_entropy']
             writer = csv.DictWriter(csv_file, fieldnames=fieldnames)
@@ -296,7 +297,8 @@ def train(self):
             AquaError: Batch size bigger than the number of items in the truncated data set
         """
         if self._snapshot_dir is not None:
-            with open(os.path.join(self._snapshot_dir, 'output.csv'), mode='w') as csv_file:
+            with open(os.path.join(self._snapshot_dir, 'output.csv'),
+                      mode='w', encoding="utf8") as csv_file:
                 fieldnames = ['epoch', 'loss_discriminator', 'loss_generator', 'params_generator',
                               'rel_entropy']
                 writer = csv.DictWriter(csv_file, fieldnames=fieldnames)

qiskit/aqua/algorithms/distribution_learners/qgan.py

@@ -394,7 +394,7 @@ def _run(self) -> AlgorithmResult:
                 )
                 up_qreg_density_mat_diag = np.diag(up_qreg_density_mat)
 
-                counts = dict()
+                counts = {}
                 for i, v in enumerate(up_qreg_density_mat_diag):
                     if not v == 0:
                         counts[bin(int(i))[2:].zfill(2 * self._n)] = v ** 2

qiskit/aqua/algorithms/factorizers/shor.py

@@ -288,7 +288,7 @@ def z_sol(self):
 
     def dump(self, filename):
         """ dump """
-        with open(filename, 'w') as outfile:
+        with open(filename, 'w', encoding="utf8") as outfile:
             outfile.write('# objective {}\n'.format(self.objective))
             outfile.write('# elapsed time {}\n'.format(self._elapsed))
             writer = csv.writer(outfile, delimiter=self.delimiter)

qiskit/aqua/algorithms/minimum_eigen_solvers/cplex/classical_cplex.py

@@ -33,7 +33,7 @@ def __init__(self) -> None:
         super().__init__()
         self._num_parameters = 0
         self._num_qubits = 0
-        self._bounds = list()  # type: List[object]
+        self._bounds = []  # type: List[object]
         warn_package('aqua.components.neural_networks',
                      'qiskit_machine_learning.algorithms.distribution_learners.qgan',
                      'qiskit-machine-learning')

qiskit/aqua/components/neural_networks/discriminative_network.py

@@ -28,7 +28,7 @@ def __init__(self):
         super().__init__()
         self._num_parameters = 0
         self._num_qubits = 0
-        self._bounds = list()
+        self._bounds = []
         warn_package('aqua.components.neural_networks',
                      'qiskit_machine_learning.algorithms.distribution_learners.qgan',
                      'qiskit-machine-learning')

qiskit/aqua/components/neural_networks/generative_network.py

@@ -1,7 +1,6 @@
-
 # This code is part of Qiskit.
 #
-# (C) Copyright IBM 2019, 2020.
+# (C) Copyright IBM 2019, 2021.
 #
 # This code is licensed under the Apache License, Version 2.0. You may
 # obtain a copy of this license in the LICENSE.txt file in the root directory
@@ -99,7 +98,8 @@ def __init__(self,
 
         if self._snapshot_dir:
 
-            with open(os.path.join(self._snapshot_dir, 'adam_params.csv'), mode='w') as csv_file:
+            with open(os.path.join(self._snapshot_dir, 'adam_params.csv'),
+                      mode='w', encoding="utf8") as csv_file:
                 if self._amsgrad:
                     fieldnames = ['v', 'v_eff', 'm', 't']
                 else:
@@ -127,13 +127,15 @@ def save_params(self, snapshot_dir: str) -> None:
             snapshot_dir: The directory to store the file in.
         """
         if self._amsgrad:
-            with open(os.path.join(snapshot_dir, 'adam_params.csv'), mode='a') as csv_file:
+            with open(os.path.join(snapshot_dir, 'adam_params.csv'),
+                      mode='a', encoding="utf8") as csv_file:
                 fieldnames = ['v', 'v_eff', 'm', 't']
                 writer = csv.DictWriter(csv_file, fieldnames=fieldnames)
                 writer.writerow({'v': self._v, 'v_eff': self._v_eff,
                                  'm': self._m, 't': self._t})
         else:
-            with open(os.path.join(snapshot_dir, 'adam_params.csv'), mode='a') as csv_file:
+            with open(os.path.join(snapshot_dir, 'adam_params.csv'),
+                      mode='a', encoding="utf8") as csv_file:
                 fieldnames = ['v', 'm', 't']
                 writer = csv.DictWriter(csv_file, fieldnames=fieldnames)
                 writer.writerow({'v': self._v, 'm': self._m, 't': self._t})
@@ -144,7 +146,8 @@ def load_params(self, load_dir: str) -> None:
         Args:
             load_dir: The directory containing ``adam_params.csv``.
         """
-        with open(os.path.join(load_dir, 'adam_params.csv'), mode='r') as csv_file:
+        with open(os.path.join(load_dir, 'adam_params.csv'),
+                  mode='r', encoding="utf8") as csv_file:
             if self._amsgrad:
                 fieldnames = ['v', 'v_eff', 'm', 't']
             else:

qiskit/aqua/components/optimizers/adam_amsgrad.py

@@ -1,6 +1,6 @@
 # This code is part of Qiskit.
 #
-# (C) Copyright IBM 2019, 2020.
+# (C) Copyright IBM 2019, 2021.
 #
 # This code is licensed under the Apache License, Version 2.0. You may
 # obtain a copy of this license in the LICENSE.txt file in the root directory
@@ -223,7 +223,7 @@ def evaluate_classically(self, measurement):
         """ evaluate classically """
         assignment = [(var + 1) * (int(tf) * 2 - 1) for tf, var in zip(measurement[::-1],
                                                                        range(len(measurement)))]
-        assignment_dict = dict()
+        assignment_dict = {}
         for v in assignment:
             assignment_dict[self._lit_to_var[abs(v)]] = bool(v > 0)
         return self._expr.subs(assignment_dict), assignment