diff --git a/GPy/plotting/matplot_dep/models_plots.py b/GPy/plotting/matplot_dep/models_plots.py
index 16568c7d..77c42825 100644
--- a/GPy/plotting/matplot_dep/models_plots.py
+++ b/GPy/plotting/matplot_dep/models_plots.py
@@ -11,6 +11,7 @@ from base_plots import gpplot, x_frame1D, x_frame2D
 from ...models.gp_coregionalized_regression import GPCoregionalizedRegression
 from ...models.sparse_gp_coregionalized_regression import SparseGPCoregionalizedRegression
 from scipy import sparse
+from ...core.parameterization.variational import VariationalPosterior
 
 def plot_fit(model, plot_limits=None, which_data_rows='all',
         which_data_ycols='all', fixed_inputs=[],
@@ -78,7 +79,7 @@ def plot_fit(model, plot_limits=None, which_data_rows='all',
 
     if predict_kw is None:
         predict_kw = {}
-    
+
     #work out what the inputs are for plotting (1D or 2D)
     fixed_dims = np.array([i for i,v in fixed_inputs])
     free_dims = np.setdiff1d(np.arange(model.input_dim),fixed_dims)
@@ -219,7 +220,7 @@ def plot_fit_f(model, *args, **kwargs):
     kwargs['plot_raw'] = True
     plot_fit(model,*args, **kwargs)
 
-def fixed_inputs(model, non_fixed_inputs, fix_routine='median', as_list=True):
+def fixed_inputs(model, non_fixed_inputs, fix_routine='median', as_list=True, X_all=False):
     """
     Convenience function for returning back fixed_inputs where the other inputs
     are fixed using fix_routine
@@ -235,8 +236,13 @@ def fixed_inputs(model, non_fixed_inputs, fix_routine='median', as_list=True):
     f_inputs = []
     if hasattr(model, 'has_uncertain_inputs') and model.has_uncertain_inputs():
         X = model.X.mean.values.copy()
-    else:
+    elif isinstance(model.X, VariationalPosterior):
         X = model.X.values.copy()
+    else:
+        if X_all:
+            X = model.X_all.copy()
+        else:
+            X = model.X.copy()
     for i in range(X.shape[1]):
         if i not in non_fixed_inputs:
             if fix_routine == 'mean':