get_dim_names and get_identifiers added in dataset

system/dataset.py

@@ -157,19 +157,25 @@ class Dataset:
             self.has_array = True
 
     def get_name(self):
+        """Returns dataset name"""
         return self._name
+
     def get_all_dims(self):
+        """Returns all dimensions in project"""
         return self._all_dims
 
-    def get_identifiers(self):
+    def get_dim_names(self):
-        #return [n for n in self._map.iteritems()]
+        """Returns dim names""" 
+        return [dim for dim in self._dims]
+
+    def get_identifiers(self,dim):
+        """Returns identifiers aling dim, sorted by position (index)"""
+        items = self._map[dim].items()
+        backitems=[ [v[1],v[0]] for v in items]
+        backitems.sort()
+        sorted_ids=[ backitems[i][1] for i in range(0,len(backitems))]
+        return tuple(sorted_ids)
      
-        # ensure correct order
-        # this has correct dims but not identifiers
-        ids = []
-        for dim in self._dims:
-            ids.append((dim,self._map[dim].keys()))
-        return ids
 
 class CategoryDataset(Dataset):
     """The category dataset class.

workflows/pca_workflow.py

@@ -93,13 +93,12 @@ class PCAFunction(Function):
         singel_def = ('1',('s'))
 
         # pull out input identifiers:
-        data_ids = []
+        row_ids = data.get_identifiers('genes')
-        for dim in data:
+        col_ids = data.get_identifiers('samples')
-            data_ids.append((dim,data[dim].keys()))
         
-        T = dataset.Dataset(T,(data_ids[0],comp_def))
+        T = dataset.Dataset(T,[('samples',col_ids) ,comp_def])
-        P = dataset.Dataset(P,[data_ids[1],comp_def])
+        P = dataset.Dataset(P,[('genes',row_ids),comp_def])
-        E = dataset.Dataset(E,data_ids)
+        E = dataset.Dataset(E,[('samples',col_ids),'genes',(row_ids)])
         #tsq = dataset.Dataset(tsq,[singel_def,data_ids[1])
         
         ## plots