Revert "Update to 1.9.4 (#330)"

This reverts commit c57ad61.

requirements.txt

@@ -20,6 +20,7 @@ qulacs # default simulator (best integration), remove if the installation gives
 #qibo <= 0.1.1 # can not be installed in the same environment as gpyopt
 
 #optional optimizers
+#phoenics # version on PyPi  isc urrently broken, we recommend to install from source (AAG github)
 #gpyopt # not in combination with qibo as quantum backend
 
 #optional third party libraries

src/tequila/apps/adapt/adapt.py

@@ -21,7 +21,7 @@ class AdaptParameters:
     degeneracy_threshold: float = 5.e-4
     silent: bool = False
 
-    def __post_init__(self):
+    def __post__init__(self):
         # avoid stacking of same operator-types in a row
         if "method_options" in self.optimizer_args:
             if "gtol" in self.optimizer_args["method_options"]:

src/tequila/optimizers/__init__.py

@@ -16,7 +16,7 @@ class _Optimizers:
     methods: list = None
 
 
-SUPPORTED_OPTIMIZERS = ['scipy', 'gpyopt', 'gd']
+SUPPORTED_OPTIMIZERS = ['scipy', 'phoenics', 'gpyopt', 'gd']
 INSTALLED_OPTIMIZERS = {}
 INSTALLED_OPTIMIZERS['scipy'] = _Optimizers(cls=OptimizerSciPy,
                                             minimize=minimize_scipy,
@@ -37,6 +37,19 @@ class _Optimizers:
 except ImportError:
     has_gpyopt = False
 
+has_phoenics = False
+try:
+    from tequila.optimizers.optimizer_phoenics import OptimizerPhoenics
+    from tequila.optimizers.optimizer_phoenics import minimize as minimize_phoenics
+
+    INSTALLED_OPTIMIZERS['phoenics'] = _Optimizers(cls=OptimizerPhoenics,
+                                                   minimize=minimize_phoenics,
+                                                   methods=OptimizerPhoenics.available_methods())
+    has_phoenics = True
+except ImportError:
+    has_phoenics = False
+
+
 def show_available_optimizers(module=None):
     """
     Returns

src/tequila/optimizers/optimizer_gpyopt.py

@@ -4,6 +4,8 @@
 import numbers
 from tequila.objective.objective import Variable
 import warnings
+
+warnings.simplefilter("ignore")
 import GPyOpt
 from GPyOpt.methods import BayesianOptimization
 import numpy as np