Added existing_identifiers function to Dataset.

Added colouring drag'n'drop to DAGPlot in gobrowser module.

fluents/dataset.py

@@ -194,6 +194,12 @@ class Dataset:
                      for key in idents if self._map[dim].has_key(key)]
         return asarray(index)        
 
+    def existing_identifiers(self, dim, idents):
+        if not isinstance(idents, list) and not isinstance(idents, set):
+            raise ValueError("idents needs to be a list/set got: %s" %type(idents))
+
+        return [key for key in idents if self._map[dim].has_key(key)]
+
     def copy(self):
         """ Returns deepcopy of dataset.
         """

workflows/gobrowser.py

@@ -477,7 +477,6 @@ class PlotDagFunction(workflow.Function):
 
     def run(self, selection):
         g = self.get_network(list(selection['go-terms']))
-#        print g.edges()
         ds = dataset.GraphDataset(networkx.adj_matrix(g),
                                   [('go-terms', g.nodes()), ('_go-terms', g.nodes())],
                                   name="DAG")
@@ -674,3 +673,47 @@ class DagPlot(plots.Plot):
         self.selected_nodes.set_linewidth(linewidth)
         self.canvas.draw()
 
+    def is_mappable_with(self, obj):
+        """Returns True if dataset/selection is mappable with this plot.
+        """
+        if isinstance(obj, fluents.dataset.Dataset):
+            if self.current_dim in obj.get_dim_name():
+                return True
+        return False
+
+    def _update_color_from_dataset(self, ds):
+        """Updates the facecolors from a dataset.
+        """
+
+        array = ds.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(ds, fluents.dataset.CategoryDataset):
+                vec = dot(array, diag(arange(n))).sum(1)
+            else:
+                vec = array.sum(1)
+        else:
+            vec = array.ravel()
+
+        indices = ds.get_indices(self.current_dim, self.nodes)
+        nodes = ds.existing_identifiers(self.current_dim, self.nodes)
+        v = vec.take(indices, 0)
+        d = dict(zip(nodes, list(v))) 
+
+        map_vec = zeros(len(self.nodes))
+        for i, n in enumerate(self.nodes):
+            map_vec[i] = d.get(n, -1)
+
+        # update facecolors
+        self.node_collection.set_array(map_vec)
+        self.node_collection.set_clim(map_vec.min(), map_vec.max())
+        self.node_collection.update_scalarmappable() #sets facecolors from array
+        self.canvas.draw()
+