Improved drag'n'drop of data into scatter plots so that it no longer requires

matching identifiers along dimensions.

fluents/lib/blmplots.py

@@ -65,39 +65,6 @@ class BlmScatterPlot(plots.ScatterPlot):
         self.sc = self._mappable
         self.add_pc_spin_buttons(self._T.shape[1], absi, ordi)
 
-    def _update_color_from_dataset(self, data):
-        """Overriding scatter for testing of colormaps.
-        """
-        is_category = False
-        array = data.asarray()
-        #only support for 2d-arrays:
-        try:
-            m, n = array.shape
-        except:
-            raise ValueError, "No support for more than 2 dimensions."
-        # is dataset a vector or matrix?
-        if not n==1:
-            # we have a category dataset
-            if isinstance(data, fluents.dataset.CategoryDataset):
-                is_category = True
-                map_vec = scipy.dot(array, scipy.diag(scipy.arange(n))).sum(1)
-            else:
-                map_vec = array.sum(1)
-        else:
-            map_vec = array.ravel()
-
-        # update facecolors
-        self.sc.set_array(map_vec)
-        self.sc.set_clim(map_vec.min(), map_vec.max())
-        if is_category:
-            cmap = cm.Paired
-        else:
-            cmap = cm.jet
-
-        self.sc.set_cmap(cmap)
-        self.sc.update_scalarmappable() #sets facecolors from array
-        self.canvas.draw()
-        
     def set_facecolor(self, colors):
         """Set patch facecolors.
         """