Added spline kernel (from P. Hennig) to GPy

Had to modify the base_plots and model_plots.py, since I had troubles
installing GPy in anaconda on debian linux due to the dependency on
Tango. Why is Tango needed to represent colors that can also be typed in
Hex format thus eliminating further dependencies.

GPy/plotting/matplot_dep/base_plots.py

@@ -3,7 +3,7 @@
 
 
 try:
-    import Tango
+    #import Tango
     import pylab as pb
 except:
     pass
@@ -17,11 +17,11 @@ def ax_default(fignum, ax):
         fig = ax.figure
     return fig, ax
 
-def meanplot(x, mu, color=Tango.colorsHex['darkBlue'], ax=None, fignum=None, linewidth=2,**kw):
+def meanplot(x, mu, color='#3300FF', ax=None, fignum=None, linewidth=2,**kw):
     _, axes = ax_default(fignum, ax)
     return axes.plot(x,mu,color=color,linewidth=linewidth,**kw)
 
-def gpplot(x, mu, lower, upper, edgecol=Tango.colorsHex['darkBlue'], fillcol=Tango.colorsHex['lightBlue'], ax=None, fignum=None, **kwargs):
+def gpplot(x, mu, lower, upper, edgecol='#3300FF', fillcol='#33CCFF', ax=None, fignum=None, **kwargs):
     _, axes = ax_default(fignum, ax)
 
     mu = mu.flatten()

GPy/plotting/matplot_dep/models_plots.py

@@ -2,7 +2,7 @@
 # Licensed under the BSD 3-clause license (see LICENSE.txt)
 
 try:
-    import Tango
+#    import Tango
     import pylab as pb
 except:
     pass
@@ -16,7 +16,7 @@ def plot_fit(model, plot_limits=None, which_data_rows='all',
         which_data_ycols='all', fixed_inputs=[],
         levels=20, samples=0, fignum=None, ax=None, resolution=None,
         plot_raw=False,
-        linecol=Tango.colorsHex['darkBlue'],fillcol=Tango.colorsHex['lightBlue'], Y_metadata=None, data_symbol='kx'):
+        linecol='#3300FF',fillcol='#00FFFF', Y_metadata=None, data_symbol='kx'):
     """
     Plot the posterior of the GP.
       - In one dimension, the function is plotted with a shaded region identifying two standard deviations.
@@ -107,7 +107,7 @@ def plot_fit(model, plot_limits=None, which_data_rows='all',
         if samples: #NOTE not tested with fixed_inputs
             Ysim = model.posterior_samples(Xgrid, samples)
             for yi in Ysim.T:
-                plots['posterior_samples'] = ax.plot(Xnew, yi[:,None], Tango.colorsHex['darkBlue'], linewidth=0.25)
+                plots['posterior_samples'] = ax.plot(Xnew, yi[:,None], '#3300FF', linewidth=0.25)
                 #ax.plot(Xnew, yi[:,None], marker='x', linestyle='--',color=Tango.colorsHex['darkBlue']) #TODO apply this line for discrete outputs.