Added dataset transpose option

fluents/dataset.py

@@ -76,7 +76,7 @@ class Dataset:
         """Return the identifers along the dimension dim."""
         return self._map[dim]
 
-    def _create_identifiers(self,shape,all_dims):
+    def _create_identifiers(self, shape, all_dims):
         """Creates dimension names and identifier names, and returns
         identifiers."""
         
@@ -141,7 +141,7 @@ class Dataset:
         if type(axis)==int:
             return self._dims[axis]
         else:
-            return [dim for dim in self]
+            return [dim for dim in self._dims]
 
     def common_dims(self, ds):
         """Returns a list of the common dimensions in the two datasets."""
@@ -220,6 +220,19 @@ class Dataset:
         """
         return copy.deepcopy(self)
 
+    def transpose(self):
+        """Returns a copy of transpose of a dataset.
+
+        As for the moment: only support for 2D-arrays.
+        """
+        
+        #assert(self._array==ndarray)
+        ds = self.copy()
+        ds._array = ds._array.T
+        ds._dims.reverse()
+        ds.shape = ds._array.shape
+        return ds
+    
     def _validate_identifiers(self, identifiers):
         
         for dim_name, ids in identifiers: 

fluents/navigator.py

@@ -198,6 +198,11 @@ class NavigatorMenu(gtk.Menu):
         self.append(self.save_item)
         self.save_item.show()
 
+        self.trans_item = gtk.MenuItem('Transpose')
+        self.trans_item.connect('activate', self.on_transpose, navigator)
+        self.append(self.trans_item)
+        self.trans_item.show()
+        
         # Build plot menu
         self.plot_menu = gtk.Menu()
 
@@ -286,4 +291,9 @@ class NavigatorMenu(gtk.Menu):
         project.data_tree_insert(self.tree_iter, 'Histogram', plot, None, "black", icon)
         plot.set_selection_listener(project.set_selection)
         project._selection_observers.append(plot)
-        
+
+    def on_transpose(self, item, navigator):
+        project = main.project
+        ds = self.dataset.transpose()
+        icon = fluents.icon_factory.get("dataset")
+        project.data_tree_insert(self.tree_iter, self.dataset.get_name()+".T", ds, None, "black", icon)