Added log transform, support for multi selections in navigator-scatter, removed get_project-nonsense

fluents/navigator.py

@@ -97,10 +97,10 @@ class NavigatorView (gtk.TreeView):
 
         if objs and isinstance(objs[0], dataset.Dataset):
             logger.debug('Selecting dataset')
-            main.project.set_current_data(objs)
+            main.project.current_data = objs
         else:
             logger.debug('Deselecting dataset')
-            main.project.set_current_data([])
+            main.project.current_data = []
 
     def on_row_changed(self, treestore, pos, iter):
         """Set correct focus and colours when rows have changed."""
@@ -217,6 +217,11 @@ class NavigatorMenu(gtk.Menu):
         self.trans_menu.append(self.trans_stdc_item)
         self.trans_stdc_item.show()
 
+        self.trans_log_item = gtk.MenuItem('Log')
+        self.trans_log_item.connect('activate', self.on_log, navigator)
+        self.trans_menu.append(self.trans_log_item)
+        self.trans_log_item.show()
+
         self.trans_item = gtk.MenuItem("Transformation")
         self.append(self.trans_item)
         self.trans_item.set_submenu(self.trans_menu)
@@ -339,14 +344,26 @@ class NavigatorMenu(gtk.Menu):
 
     def on_plot_scatter(self, item, navigator):
         project = main.project
-        ds = self.dataset
+        datasets = main.project.current_data
-        dims = ds.get_dim_name()
+        ds_major = datasets[0]
-        ids = ds.get_identifiers(dims[1])
+        dims_major = ds_major.get_dim_name()
-        plot = plots.ScatterPlot(ds, ds, 
+        ids_major = ds_major.get_identifiers(dims_major[1])
-                                 dims[0], dims[1], 
+        if len(datasets)>1:
-                                 ids[0], ids[1],
+            # If there is more than one active dataset -> try to use the two first
-                                 name='Scatter (%s)' % ds.get_name())
+            ds_minor = datasets[1]
-        plot.add_axes_spin_buttons(len(ids), 0, 1)
+            dims_minor = ds_minor.get_dim_name()
+            if dims_minor != dims_major or ds_minor.shape[0] != ds_major.shape[0]:
+                # the selected datasets are not matched -> use initial selected
+                ds_minor = ds_major
+        else:
+            #Only one dataset selected
+            ds_minor = ds_major
+        
+        plot = plots.ScatterPlot(ds_major, ds_minor, 
+                                 dims_major[0], dims_major[1], 
+                                 ids_major[0], ids_major[1],
+                                 name='Scatter (%s)' % ds_major.get_name())
+        plot.add_axes_spin_buttons(len(ids_major), 0, 1)
         icon = fluents.icon_factory.get("line_plot")
         project.data_tree_insert(self.tree_iter, 'Scatter', plot, None, "black", icon)
         plot.set_selection_listener(project.set_selection)
@@ -372,16 +389,32 @@ class NavigatorMenu(gtk.Menu):
     def on_standardise_rows(self, item, navigator):
         project = main.project
         ds = self.dataset.copy()
+        ds._name = self.dataset._name + ".rsc"
         axis = 1
         ds._array = ds._array/scipy.expand_dims(ds._array.std(axis), axis)
         icon = fluents.icon_factory.get("dataset")
-        project.data_tree_insert(self.tree_iter, self.dataset.get_name()+".rsc", ds, None, "black", icon)
+        project.data_tree_insert(self.tree_iter, ds._name, ds, None, "black", icon)
 
     def on_standardise_cols(self, item, navigator):
         project = main.project
         ds = self.dataset.copy()
+        ds._name = self.dataset._name + ".csc"
         axis = 0
         ds._array = ds._array/scipy.expand_dims(ds._array.std(axis), axis)
         icon = fluents.icon_factory.get("dataset")
-        project.data_tree_insert(self.tree_iter, self.dataset.get_name()+".csc", ds, None, "black", icon)
+        project.data_tree_insert(self.tree_iter, ds._name, ds, None, "black", icon)
 
+    def on_log(self, item, navigator):
+        project = main.project
+        try:
+            if not scipy.all(self.dataset._array>0):
+                raise ValueError
+        except:
+            logger.log('warning', 'Datasets needs to be strictly positive for a log transform')
+            return
+        
+        ds = self.dataset.copy()
+        ds._array = scipy.log(ds._array)
+        icon = fluents.icon_factory.get("dataset")
+        ds._name = self.dataset.get_name()+".log"
+        project.data_tree_insert(self.tree_iter, ds._name, ds, None, "black", icon)