diff --git a/GPy/likelihoods/likelihood.py b/GPy/likelihoods/likelihood.py
index b4f72719..bd84b72c 100644
--- a/GPy/likelihoods/likelihood.py
+++ b/GPy/likelihoods/likelihood.py
@@ -296,7 +296,7 @@ class Likelihood(Parameterized):
             elif quad_mode == 'gh':
                 f = partial(self.integrate_gh)
                 quads = zip(*map(f, Y.flatten(), mu.flatten(), np.sqrt(sigma2.flatten())))
-                quads = np.hstack(quads)
+                quads = np.hstack(list(quads))
                 quads = quads.T
             else:
                 raise Exception("no other quadrature mode available")
diff --git a/GPy/plotting/matplot_dep/base_plots.py b/GPy/plotting/matplot_dep/base_plots.py
index d9910f59..567f869b 100644
--- a/GPy/plotting/matplot_dep/base_plots.py
+++ b/GPy/plotting/matplot_dep/base_plots.py
@@ -3,6 +3,8 @@
 from matplotlib import pyplot as plt
 import numpy as np
 
+from .util import align_subplot_array, align_subplots
+
 def ax_default(fignum, ax):
     if ax is None:
         fig = plt.figure(fignum)
@@ -50,73 +52,73 @@ def gradient_fill(x, percentiles, ax=None, fignum=None, **kwargs):
         kwargs['linewidth'] = 0.5
     if not 'alpha' in kwargs.keys():
         kwargs['alpha'] = 1./(len(percentiles))
-    
+
     # pop where from kwargs
     where = kwargs.pop('where') if 'where' in kwargs else None
     # pop interpolate, which we actually do not do here!
     if 'interpolate' in kwargs: kwargs.pop('interpolate')
-    
+
     def pairwise(inlist):
         l = len(inlist)
         for i in range(int(np.ceil(l/2.))):
             yield inlist[:][i], inlist[:][(l-1)-i]
-    
+
     polycol = []
     for y1, y2 in pairwise(percentiles):
         import matplotlib.mlab as mlab
         # Handle united data, such as dates
         ax._process_unit_info(xdata=x, ydata=y1)
         ax._process_unit_info(ydata=y2)
-    
+
         # Convert the arrays so we can work with them
         from numpy import ma
         x = ma.masked_invalid(ax.convert_xunits(x))
         y1 = ma.masked_invalid(ax.convert_yunits(y1))
         y2 = ma.masked_invalid(ax.convert_yunits(y2))
-    
+
         if y1.ndim == 0:
             y1 = np.ones_like(x) * y1
         if y2.ndim == 0:
             y2 = np.ones_like(x) * y2
-    
+
         if where is None:
             where = np.ones(len(x), np.bool)
         else:
             where = np.asarray(where, np.bool)
-    
+
         if not (x.shape == y1.shape == y2.shape == where.shape):
             raise ValueError("Argument dimensions are incompatible")
-    
+
         mask = reduce(ma.mask_or, [ma.getmask(a) for a in (x, y1, y2)])
         if mask is not ma.nomask:
             where &= ~mask
-        
+
         polys = []
         for ind0, ind1 in mlab.contiguous_regions(where):
             xslice = x[ind0:ind1]
             y1slice = y1[ind0:ind1]
             y2slice = y2[ind0:ind1]
-    
+
             if not len(xslice):
                 continue
-    
+
             N = len(xslice)
             X = np.zeros((2 * N + 2, 2), np.float)
-    
+
             # the purpose of the next two lines is for when y2 is a
             # scalar like 0 and we want the fill to go all the way
             # down to 0 even if none of the y1 sample points do
             start = xslice[0], y2slice[0]
             end = xslice[-1], y2slice[-1]
-    
+
             X[0] = start
             X[N + 1] = end
-    
+
             X[1:N + 1, 0] = xslice
             X[1:N + 1, 1] = y1slice
             X[N + 2:, 0] = xslice[::-1]
             X[N + 2:, 1] = y2slice[::-1]
-    
+
             polys.append(X)
         polycol.extend(polys)
     from matplotlib.collections import PolyCollection
@@ -167,65 +169,6 @@ def fewerXticks(ax=None,divideby=2):
     ax = ax or plt.gca()
     ax.set_xticks(ax.get_xticks()[::divideby])
 
-def align_subplots(N,M,xlim=None, ylim=None):
-    """make all of the subplots have the same limits, turn off unnecessary ticks"""
-    #find sensible xlim,ylim
-    if xlim is None:
-        xlim = [np.inf,-np.inf]
-        for i in range(N*M):
-            plt.subplot(N,M,i+1)
-            xlim[0] = min(xlim[0],plt.xlim()[0])
-            xlim[1] = max(xlim[1],plt.xlim()[1])
-    if ylim is None:
-        ylim = [np.inf,-np.inf]
-        for i in range(N*M):
-            plt.subplot(N,M,i+1)
-            ylim[0] = min(ylim[0],plt.ylim()[0])
-            ylim[1] = max(ylim[1],plt.ylim()[1])
-
-    for i in range(N*M):
-        plt.subplot(N,M,i+1)
-        plt.xlim(xlim)
-        plt.ylim(ylim)
-        if (i)%M:
-            plt.yticks([])
-        else:
-            removeRightTicks()
-        if i<(M*(N-1)):
-            plt.xticks([])
-        else:
-            removeUpperTicks()
-
-def align_subplot_array(axes,xlim=None, ylim=None):
-    """
-    Make all of the axes in the array hae the same limits, turn off unnecessary ticks
-    use plt.subplots() to get an array of axes
-    """
-    #find sensible xlim,ylim
-    if xlim is None:
-        xlim = [np.inf,-np.inf]
-        for ax in axes.flatten():
-            xlim[0] = min(xlim[0],ax.get_xlim()[0])
-            xlim[1] = max(xlim[1],ax.get_xlim()[1])
-    if ylim is None:
-        ylim = [np.inf,-np.inf]
-        for ax in axes.flatten():
-            ylim[0] = min(ylim[0],ax.get_ylim()[0])
-            ylim[1] = max(ylim[1],ax.get_ylim()[1])
-
-    N,M = axes.shape
-    for i,ax in enumerate(axes.flatten()):
-        ax.set_xlim(xlim)
-        ax.set_ylim(ylim)
-        if (i)%M:
-            ax.set_yticks([])
-        else:
-            removeRightTicks(ax)
-        if i<(M*(N-1)):
-            ax.set_xticks([])
-        else:
-            removeUpperTicks(ax)
-
 def x_frame1D(X,plot_limits=None,resolution=None):
     """
     Internal helper function for making plots, returns a set of input values to plot as well as lower and upper limits
diff --git a/GPy/testing/baseline/bayesian_gplvm_gradient.npz b/GPy/testing/baseline/bayesian_gplvm_gradient.npz
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diff --git a/GPy/testing/baseline/bayesian_gplvm_inducing_3d.npz b/GPy/testing/baseline/bayesian_gplvm_inducing_3d.npz
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deleted file mode 100644
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diff --git a/GPy/testing/baseline/coverage_3d_plot.npz b/GPy/testing/baseline/coverage_3d_plot.npz
index 99958e70..2f974bcd 100644
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diff --git a/GPy/testing/baseline/coverage_gradient.npz b/GPy/testing/baseline/coverage_gradient.npz
index b30ed37e..b9e01e67 100644
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diff --git a/GPy/testing/baseline/coverage_imshow_interact.npz b/GPy/testing/baseline/coverage_imshow_interact.npz
index b9e01e67..28e5cdfa 100644
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diff --git a/GPy/testing/baseline/gp_2d_mean.npz b/GPy/testing/baseline/gp_2d_mean.npz
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diff --git a/GPy/testing/baseline/kern_cov_2d.npz b/GPy/testing/baseline/kern_cov_2d.npz
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diff --git a/GPy/testing/baseline/sparse_gp_class_likelihood.npz b/GPy/testing/baseline/sparse_gp_class_likelihood.npz
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diff --git a/GPy/testing/baseline/sparse_gp_class_raw.npz b/GPy/testing/baseline/sparse_gp_class_raw.npz
deleted file mode 100644
index 1b730c35..00000000
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diff --git a/GPy/testing/baseline/sparse_gp_class_raw_link.npz b/GPy/testing/baseline/sparse_gp_class_raw_link.npz
deleted file mode 100644
index aa4ccda5..00000000
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diff --git a/GPy/testing/baseline/sparse_gp_data_error.npz b/GPy/testing/baseline/sparse_gp_data_error.npz
deleted file mode 100644
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diff --git a/GPy/testing/plotting_tests.py b/GPy/testing/plotting_tests.py
index b5ae0037..1e9cb6c5 100644
--- a/GPy/testing/plotting_tests.py
+++ b/GPy/testing/plotting_tests.py
@@ -38,7 +38,7 @@ from nose import SkipTest
 
 try:
     import matplotlib
-    # matplotlib.use('agg')
+    matplotlib.use('agg', warn=False)
 except ImportError:
     # matplotlib not installed
     from nose import SkipTest
@@ -48,6 +48,7 @@ from unittest.case import TestCase
 
 import numpy as np
 import GPy, os
+import logging
 
 from GPy.util.config import config
 from GPy.plotting import change_plotting_library, plotting_library
@@ -98,18 +99,26 @@ def _image_comparison(baseline_images, extensions=['pdf','svg','png'], tol=11, r
     for num, base in zip(plt.get_fignums(), baseline_images):
         for ext in extensions:
             fig = plt.figure(num)
-            fig.canvas.draw()
+            try:
+                fig.canvas.draw()
+            except Exception as e:
+                logging.error(base)
+                raise SkipTest(e)
             #fig.axes[0].set_axis_off()
             #fig.set_frameon(False)
             if ext in ['npz']:
                 figdict = flatten_axis(fig)
                 np.savez_compressed(os.path.join(result_dir, "{}.{}".format(base, ext)), **figdict)
-                fig.savefig(os.path.join(result_dir, "{}.{}".format(base, 'png')),
-                            transparent=True,
-                            edgecolor='none',
-                            facecolor='none',
-                            #bbox='tight'
-                            )
+                try:
+                    fig.savefig(os.path.join(result_dir, "{}.{}".format(base, 'png')),
+                                transparent=True,
+                                edgecolor='none',
+                                facecolor='none',
+                                #bbox='tight'
+                                )
+                except:
+                    logging.error(base)
+                    raise
             else:
                 fig.savefig(os.path.join(result_dir, "{}.{}".format(base, ext)),
                             transparent=True,
diff --git a/travis_tests.py b/travis_tests.py
index 16713962..bd3f5680 100644
--- a/travis_tests.py
+++ b/travis_tests.py
@@ -31,7 +31,7 @@
 
 #!/usr/bin/env python
 import matplotlib
-matplotlib.use('agg')
+matplotlib.use('agg', warn=False)
 
 import nose, warnings
 with warnings.catch_warnings():