added m['ard'] gives all parameters matching 'ard', as well as setting m['ard'] = x to set all mrd parameters

GPy/core/model.py

@@ -83,6 +83,12 @@ class model(parameterised):
         for w in which:
             self.priors[w] = what
 
+    def __getitem__(self, name):
+        return self.get(name)
+
+    def __setitem(self, name, val):
+        return self.set(name, val)
+
     def get(self, name, return_names=False):
         """
         Get a model parameter by name. The name is applied as a regular expression and all parameters that match that regular expression are returned.

GPy/models/mrd.py

@@ -287,29 +287,6 @@ class MRD(model):
         else:
             return pylab.gcf()
 
-    def plot_X_1d(self, fig_num="MRD X 1d", axes=None, colors=None):
-        fig = pylab.figure(num=fig_num, figsize=(min(8, (3 * len(self.bgplvms))), min(12, (2 * self.X.shape[1]))))
-        if colors is None:
-            colors = pylab.gca()._get_lines.color_cycle
-            pylab.clf()
-        plots = []
-        for i in range(self.X.shape[1]):
-            if axes is None:
-                ax = fig.add_subplot(self.X.shape[1], 1, i + 1)
-            ax.plot(self.X, c='k', alpha=.3)
-            plots.extend(ax.plot(self.X.T[i], c=colors.next(), label=r"$\mathbf{{X_{}}}$".format(i)))
-            ax.fill_between(numpy.arange(self.X.shape[0]),
-                            self.X.T[i] - 2 * numpy.sqrt(self.gref.X_variance.T[i]),
-                            self.X.T[i] + 2 * numpy.sqrt(self.gref.X_variance.T[i]),
-                            facecolor=plots[-1].get_color(),
-                            alpha=.3)
-            ax.legend(borderaxespad=0.)
-            if i < self.X.shape[1] - 1:
-                ax.set_xticklabels('')
-        pylab.draw()
-        fig.tight_layout(h_pad=.01)  # , rect=(0, 0, 1, .95))
-        return fig
-
     def plot_X(self, fig_num="MRD Predictions", axes=None):
         fig = self._handle_plotting(fig_num, axes, lambda i, g, ax: ax.imshow(g.X))
         return fig