Addresses issue #25

Author: fmfn

bayes_opt/bayesian_optimization.py

@@ -157,15 +157,9 @@ def initialize(self, points_dict):
         :return:
         """
 
-        for target in points_dict:
-
-            self.y_init.append(target)
-
-            all_points = []
-            for key in self.keys:
-                all_points.append(points_dict[target][key])
-
-            self.x_init.append(all_points)
+        for points in zip(*(points_dict[k] for k in sorted(points_dict))):
+            self.y_init.append(points[0])
+            self.x_init.append(list(points[1:]))
 
     def initialize_df(self, points_df):
         """

examples/usage.py

@@ -20,12 +20,18 @@
 # tell that to the optimizer.
 # Here we pass a dictionary with target values as keys of another
 # dictionary with parameters names and their corresponding value.
-bo.initialize({-2: {'x': 1, 'y': 0}, -1.251: {'x': 1, 'y': 1.5}})
+bo.initialize(
+    {
+        'target': [-1, -1],
+        'x': [1, 1],
+        'y': [0, 2]
+    }
+)
 
 # Once we are satisfied with the initialization conditions
 # we let the algorithm do its magic by calling the maximize()
 # method.
-bo.maximize(init_points=5, n_iter=15, kappa=3.29)
+bo.maximize(init_points=5, n_iter=15, kappa=2)
 
 # The output values can be accessed with self.res
 print(bo.res['max'])