From 53dcd3f9fa272aeef2d6d556c19d0ae9aa4b1784 Mon Sep 17 00:00:00 2001
From: Max Zwiessele <ibinbei@gmail.com>
Date: Tue, 13 Jan 2015 13:53:28 +0000
Subject: [PATCH] [objective grads] undid the change, as this would lead to
 dramatic problems in reloading old models using the pickle module

---
 GPy/core/model.py                |  6 +++---
 GPy/core/verbose_optimization.py | 18 +++++++++---------
 2 files changed, 12 insertions(+), 12 deletions(-)

diff --git a/GPy/core/model.py b/GPy/core/model.py
index 107ecf85..05a514e8 100644
--- a/GPy/core/model.py
+++ b/GPy/core/model.py
@@ -257,7 +257,7 @@ class Model(Parameterized):
             opt = optimizer(start, model=self, max_iters=max_iters, **kwargs)
 
         with VerboseOptimization(self, opt, maxiters=max_iters, verbose=messages, ipython_notebook=ipython_notebook):
-            opt.run(f_fp=self._objective_and_grads, f=self._objective, fp=self._objective_grads)
+            opt.run(f_fp=self._objective_grads, f=self._objective, fp=self._grads)
 
         self.optimization_runs.append(opt)
 
@@ -314,7 +314,7 @@ class Model(Parameterized):
             # evaulate around the point x
             f1 = self._objective(x + dx)
             f2 = self._objective(x - dx)
-            gradient = self._objective_grads(x)
+            gradient = self._grads(x)
 
             dx = dx[transformed_index]
             gradient = gradient[transformed_index]
@@ -360,7 +360,7 @@ class Model(Parameterized):
                     print "No free parameters to check"
                     return
 
-            gradient = self._objective_grads(x).copy()
+            gradient = self._grads(x).copy()
             np.where(gradient == 0, 1e-312, gradient)
             ret = True
             for nind, xind in itertools.izip(param_index, transformed_index):
diff --git a/GPy/core/verbose_optimization.py b/GPy/core/verbose_optimization.py
index eab62d60..b718a0cd 100644
--- a/GPy/core/verbose_optimization.py
+++ b/GPy/core/verbose_optimization.py
@@ -12,8 +12,9 @@ def exponents(fnow, current_grad):
 
 class VerboseOptimization(object):
     def __init__(self, model, opt, maxiters, verbose=True, current_iteration=0, ipython_notebook=False):
-        self.verbose = verbose
-        if self.verbose or ipython_notebook:
+        self.verbose = verbose or ipython_notebook
+        self.ipython_notebook = ipython_notebook
+        if self.verbose:
             self.model = model
             self.iteration = current_iteration
             self.ipython_notebook = ipython_notebook
@@ -130,12 +131,11 @@ class VerboseOptimization(object):
 
     def __exit__(self, type, value, traceback):
         if self.verbose or self.ipython_notebook:
+            self.stop = time.time()
             self.model.remove_observer(self)
-        self.stop = time.time()
+            self.print_out()
 
-        self.print_out()
-
-        if not self.ipython_notebook:
-            print
-            print 'Optimization finished in {0:.5g} Seconds'.format(self.stop-self.start)
-            print
+            if not self.ipython_notebook:
+                print
+                print 'Optimization finished in {0:.5g} Seconds'.format(self.stop-self.start)
+                print