[Stable] Release 0.6.5 - Remove cvxopt from install, backport fix for issue #768

CHANGELOG.md

@@ -15,9 +15,22 @@ Changelog](http://keepachangelog.com/en/1.0.0/).
 > -   **Fixed**: for any bug fixes.
 > -   **Security**: in case of vulnerabilities.
 
-[UNRELEASED](https://github.com/Qiskit/qiskit-aqua/compare/0.6.4...HEAD)
+[UNRELEASED](https://github.com/Qiskit/qiskit-aqua/compare/0.6.5...HEAD)
 ========================================================================
 
+[0.6.5](https://github.com/Qiskit/qiskit-aqua/compare/0.6.4...0.6.5) - 2020-03-16
+=================================================================================
+
+Removed
+-------
+
+-  Removed cvxopt from installation. (#858)
+
+Fixed
+-----
+
+-  Fixes issue #768. The AQGD optimizer if condition in func converged was ignored. That kept breaking the while loop for training. (#858)
+
 [0.6.4](https://github.com/Qiskit/qiskit-aqua/compare/0.6.3...0.6.4) - 2020-02-06
 =================================================================================
 

qiskit/aqua/VERSION.txt

@@ -1 +1 @@
-0.6.4
+0.6.5

qiskit/aqua/components/optimizers/aqgd.py

@@ -156,7 +156,7 @@ def converged(self, objval, n=2):
         Returns:
             bool: Whether or not the optimization has converged.
         """
-        if not hasattr(self, '_previous_loss'):
+        if self._previous_loss is None:
             self._previous_loss = [objval + 2 * self._tol] * n
 
         if all([absolute(objval - prev) < self._tol for prev in self._previous_loss]):

requirements.txt

@@ -6,7 +6,6 @@ numpy>=1.13
 psutil>=5
 jsonschema>=2.6
 scikit-learn>=0.20.0
-cvxopt; python_version < '3.8' or sys_platform != 'win32'
 dlx
 docplex
 fastdtw

setup.py

@@ -34,7 +34,6 @@
     "psutil>=5",
     "jsonschema>=2.6",
     "scikit-learn>=0.20.0",
-    "cvxopt; python_version < '3.8' or sys_platform != 'win32'",
     "dlx",
     "docplex",
     "fastdtw",

test/aqua/test_qsvm.py

@@ -73,12 +73,15 @@ def test_qsvm_binary_via_run_algorithm(self):
                 'name': 'QSVM'
             }
         }
-        backend = BasicAer.get_backend('qasm_simulator')
-        algo_input = ClassificationInput(training_input, test_input, total_array)
-        result = run_algorithm(params, algo_input, backend=backend)
-        self.assertEqual(result['testing_accuracy'], 0.6)
-        self.assertEqual(result['predicted_classes'], ['A', 'A', 'A', 'A', 'A',
-                                                       'A', 'B', 'A', 'A', 'A'])
+        try:
+            backend = BasicAer.get_backend('qasm_simulator')
+            algo_input = ClassificationInput(training_input, test_input, total_array)
+            result = run_algorithm(params, algo_input, backend=backend)
+            self.assertEqual(result['testing_accuracy'], 0.6)
+            self.assertEqual(result['predicted_classes'], ['A', 'A', 'A', 'A', 'A',
+                                                           'A', 'B', 'A', 'A', 'A'])
+        except NameError as ex:
+            self.skipTest(str(ex))
 
     def test_qsvm_binary_directly(self):
         """ QSVM Binary Directly test """