docstring update

Author: brendan

bayes_opt/bayesian_optimization.py

@@ -262,27 +262,9 @@ def maximize(self,
             Number of iterations where the method attempts to find the maximum
             value.
 
-        acq: {'ucb', 'ei', 'poi'}
-            The acquisition method used.
-                * 'ucb' stands for the Upper Confidence Bounds method
-                * 'ei' is the Expected Improvement method
-                * 'poi' is the Probability Of Improvement criterion.
-
-        kappa: float, optional(default=2.576)
-            Parameter to indicate how closed are the next parameters sampled.
-                Higher value = favors spaces that are least explored.
-                Lower value = favors spaces where the regression function is
-                the highest.
-
-        kappa_decay: float, optional(default=1)
-            `kappa` is multiplied by this factor every iteration.
-
-        kappa_decay_delay: int, optional(default=0)
-            Number of iterations that must have passed before applying the
-            decay to `kappa`.
-
-        xi: float, optional(default=0.0)
-            [unused]
+        acquisition_function: object, optional
+            An instance of bayes_opt.util.UtilityFunction.
+            If nothing is passed, a default using ucb is used
         """
         self._prime_subscriptions()
         self.dispatch(Events.OPTIMIZATION_START)

bayes_opt/util.py

@@ -96,6 +96,26 @@ def to_minimize(x):
 class UtilityFunction(object):
     """
     An object to compute the acquisition functions.
+
+    kind: {'ucb', 'ei', 'poi'}
+        * 'ucb' stands for the Upper Confidence Bounds method
+        * 'ei' is the Expected Improvement method
+        * 'poi' is the Probability Of Improvement criterion.
+
+    kappa: float, optional(default=2.576)
+            Parameter to indicate how closed are the next parameters sampled.
+            Higher value = favors spaces that are least explored.
+            Lower value = favors spaces where the regression function is
+            the highest.
+
+    kappa_decay: float, optional(default=1)
+        `kappa` is multiplied by this factor every iteration.
+
+    kappa_decay_delay: int, optional(default=0)
+        Number of iterations that must have passed before applying the
+        decay to `kappa`.
+
+    xi: float, optional(default=0.0)
     """
 
     def __init__(self, kind='ucb', kappa=2.576, xi=0, kappa_decay=1, kappa_decay_delay=0):