laydi/fluents/navigator.py

import gtk
import gobject
import plots
import time
import fluents
from logger import logger
import dataset, plots, project, workflow, main
import scipy

class NavigatorView (gtk.TreeView):
    """The NavigatorView is a tree view of the project.

    There is always one NavigatorView, that shows the functions, plots and
    datasets in the current project.
    """

    def __init__(self):
        if main.project:
            self.data_tree = main.project.data_tree
        else:
            self.data_tree = None
        
        gtk.TreeView.__init__(self) 

        # Various properties
        self.set_enable_tree_lines(True)
        self.set_headers_visible(False)
        self.get_hadjustment().set_value(0)

        # Selection Mode
        self.get_selection().set_mode(gtk.SELECTION_MULTIPLE)
        self.get_selection().connect('changed',self.on_selection_changed)
        self._previous_selection = []

        # Setting up TextRenderers etc
        self.connect('row_activated', self.on_row_activated)
        self.connect('cursor_changed', self.on_cursor_changed)

        # Activate context menu
        self.menu = NavigatorMenu(self)
        self.connect('popup_menu', self.popup_menu)
        self.connect('button_press_event', self.on_mouse_event)

        self.textrenderer = textrenderer = gtk.CellRendererText()
        pixbufrenderer = gtk.CellRendererPixbuf()
        self.object_col = gtk.TreeViewColumn('Object')
        self.object_col.pack_start(pixbufrenderer,expand=False)
        self.object_col.pack_start(textrenderer,expand=False)
        self.object_col.set_attributes(textrenderer, cell_background=3, 
                                       foreground=4, text=0)
        self.object_col.set_attributes(pixbufrenderer, pixbuf=5)
        self.append_column(self.object_col)

        # send events to plots / itself
        self.enable_model_drag_source(gtk.gdk.BUTTON1_MASK,
            [("GTK_TREE_MODEL_ROW", gtk.TARGET_SAME_APP, 7)],
            gtk.gdk.ACTION_LINK | gtk.gdk.ACTION_MOVE)
    
        self.connect("drag-data-get",self.slot_drag_data)

        logger.debug('Initializing navigator window.')
   
    def slot_drag_data(self, treeview, context, selection, target_id, etime):
        """Sets the data for a drag event."""
        treeselection = treeview.get_selection()
        model, paths = treeselection.get_selected_rows()
        if paths:
            self.data_tree.drag_data_get(paths[0], selection)

    def add_project(self, project):
        """Dependency injection."""
        self.data_tree = project.data_tree
        self.set_model(project.data_tree)
        self.data_tree.connect('row-changed',self.on_row_changed)
    
    def on_selection_changed(self, selection):
        """Update the list of currently selected datasets."""

        # update prev selection right away in case of multiple events
        model, paths = selection.get_selected_rows()
        if not paths: # a plot is marked: do nothing
            return

        tmp = self._previous_selection
        self._previous_selection = paths
        tree = self.data_tree

        # set timestamp on newly selected objects
        [tree.set_value(tree.get_iter(path), 6, time.time()) 
         for path in paths if path not in tmp]

        objs = [tree.get_iter(path) for path in paths]
        objs = [(tree[iter][6], tree[iter][2]) for iter in objs]

        objs.sort()
        objs = [obj for timestamp, obj in objs]

        if objs and isinstance(objs[0], dataset.Dataset):
            logger.debug('Selecting dataset')
            main.project.current_data = objs
        else:
            logger.debug('Deselecting dataset')
            main.project.current_data = []

    def on_row_changed(self, treestore, pos, iter):
        """Set correct focus and colours when rows have changed."""
        obj = treestore[iter][2]
        obj_type = treestore[iter][1]

        if not (obj or obj_type):
            return
        self.expand_to_path(pos)        

        if isinstance(obj, dataset.Dataset):
            self.set_cursor(pos)
            self.grab_focus()
        
    def on_row_activated(self, widget, path, column):
        tree_iter = self.data_tree.get_iter(path)
        obj = self.data_tree.get_value(tree_iter, 2)
        
        if isinstance(obj, plots.Plot):
            logger.debug('Activating plot')
            main.application.change_plot(obj)
        elif isinstance(obj, dataset.Dataset):
            pass
        elif obj == None:
            children = []
            i = self.data_tree.iter_children(tree_iter)
            while i:
                child = self.data_tree.get(i, 2)[0]
                if isinstance(child, plots.Plot):
                    children.append(child)
                i = self.data_tree.iter_next(i)
            main.application.change_plots(children)
        else:
            t = type(obj)
            logger.notice('Activated datatype was %s. Don\'t know what to do.' % t)

    def popup_menu(self, *rest):
        self.menu.popup(None, None, None, 0, 0)

    def on_mouse_event(self, widget, event):
        path = widget.get_path_at_pos(int(event.x), int(event.y))

        if path:
            iter = self.data_tree.get_iter(path[0])
            obj = self.data_tree.get_value(iter, 2)
        else:
            iter = None
            obj = None

        if isinstance(obj, dataset.Dataset):
            self.menu.set_dataset(obj, iter)
        else:
            self.menu.set_dataset(None, iter)

        if event.button == 3:
            self.menu.popup(None, None, None, event.button, event.time)

    def on_cursor_changed(self, widget):
        """Update statusbar to contain dataset information.

        Lists the dimensions of a dataset in the statusbar of the program
        if a dataset is focused in the navigator.
        """
        path = widget.get_cursor()[0]
        tree_iter = self.data_tree.get_iter(path)
        obj = self.data_tree.get_value(tree_iter, 2)

        if isinstance(obj, dataset.Dataset):
            dims = zip(obj.get_dim_name(), obj.shape)
            dim_text = ", ".join(["%s (%d)" % dim for dim in dims])
        else:
            dim_text = ""
        main.application['appbar1'].push(dim_text)
        

class NavigatorMenu(gtk.Menu):
    def __init__(self, navigator):
        gtk.Menu.__init__(self)
        self.navigator = navigator
        self.dataset = None
        self.tree_iter = None        

        # Populate main menu
        self.load_item = gtk.MenuItem('Load dataset')
        self.load_item.connect('activate', self.on_load_dataset, navigator)
        self.append(self.load_item)
        self.load_item.show()

        self.save_item = gtk.MenuItem('Save dataset')
        self.save_item.connect('activate', self.on_save_dataset, navigator)
        self.append(self.save_item)
        self.save_item.show()

        self.delete_item = gtk.MenuItem('Delete')
        self.delete_item.connect('activate', self.on_delete, navigator)
        self.append(self.delete_item)
        self.delete_item.show()

        # Build transform sub menu
        self.trans_menu = gtk.Menu()
        
        self.trans_tr_item = gtk.MenuItem('Transpose')
        self.trans_tr_item.connect('activate', self.on_transpose, navigator)
        self.trans_menu.append(self.trans_tr_item)
        self.trans_tr_item.show()

        self.trans_stdr_item = gtk.MenuItem('Std. rows')
        self.trans_stdr_item.connect('activate', self.on_standardise_rows, navigator)
        self.trans_menu.append(self.trans_stdr_item)
        self.trans_stdr_item.show()
        
        self.trans_stdc_item = gtk.MenuItem('Std. cols')
        self.trans_stdc_item.connect('activate', self.on_standardise_cols, navigator)
        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)
        self.trans_item.show()
        
        # Build plot sub menu
        self.plot_menu = gtk.Menu()

        self.plot_image_item = gtk.MenuItem('Image Plot')
        self.plot_image_item.connect('activate', self.on_plot_image, navigator)
        self.plot_menu.append(self.plot_image_item)
        self.plot_image_item.show()

        self.plot_hist_item = gtk.MenuItem('Histogram')
        self.plot_hist_item.connect('activate', self.on_plot_hist, navigator)
        self.plot_menu.append(self.plot_hist_item)
        self.plot_hist_item.show()
        
        self.plot_scatter_item = gtk.MenuItem('Scatter')
        self.plot_scatter_item.connect('activate', self.on_plot_scatter, navigator)
        self.plot_menu.append(self.plot_scatter_item)
        self.plot_scatter_item.show()
        
        self.plot_line_item = gtk.MenuItem('Line view')
        self.plot_line_item.connect('activate', self.on_plot_line, navigator)
        self.plot_menu.append(self.plot_line_item)
        self.plot_line_item.show()
        
        self.plot_item = gtk.MenuItem('Plot')
        self.append(self.plot_item)
        self.plot_item.set_submenu(self.plot_menu)
        self.plot_item.show()

    def set_dataset(self, ds, it):
        self.dataset = ds
        self.tree_iter = it

        if ds == None:
            self.save_item.set_property('sensitive', False)
            self.plot_item.set_property('sensitive', False)
            self.trans_item.set_property('sensitive', False)
        else:
            self.save_item.set_property('sensitive', True)
            self.plot_item.set_property('sensitive', True)
            self.trans_item.set_property('sensitive', True)

    def load_dataset(self, filename):
        """Load the dataset from the given file and add it to the project."""
        ds = dataset.read_ftsv(filename)

        if isinstance(ds, dataset.GraphDataset):
            icon = fluents.icon_factory.get("graph_dataset")
        elif isinstance(ds, dataset.CategoryDataset):
            icon = fluents.icon_factory.get("category_dataset")
        else:
            icon = fluents.icon_factory.get("dataset")

        main.project.add_dataset(ds)
        main.project.data_tree_insert(None, ds.get_name(), ds, None, "black", icon)

    def on_load_dataset(self, item, navigator):
        # Set up file chooser.
        dialog = gtk.FileChooserDialog('Load dataset')
        dialog.set_action(gtk.FILE_CHOOSER_ACTION_OPEN)
        dialog.add_buttons(gtk.STOCK_CANCEL, gtk.RESPONSE_CANCEL, 
                           gtk.STOCK_OPEN, gtk.RESPONSE_OK)
        dialog.set_select_multiple(True)
        dialog.set_current_folder(main.options.datadir)

        retval = dialog.run()
        if retval in [gtk.RESPONSE_CANCEL, gtk.RESPONSE_DELETE_EVENT]:
            pass
        elif retval == gtk.RESPONSE_OK:
            for filename in dialog.get_filenames():
                self.load_dataset(filename)
        else:
            print "unknown; ", retval 
        dialog.destroy()

    def on_save_dataset(self, item, navigator):
        dialog = gtk.FileChooserDialog('Save dataset')
        dialog.set_action(gtk.FILE_CHOOSER_ACTION_SAVE)
        dialog.add_buttons(gtk.STOCK_CANCEL, gtk.RESPONSE_CANCEL, gtk.STOCK_SAVE, gtk.RESPONSE_OK)
        dialog.set_current_name("%s.ftsv" % self.dataset.get_name())
        retval = dialog.run()
        if retval in [gtk.RESPONSE_CANCEL, gtk.RESPONSE_DELETE_EVENT]:
            logger.debug("Cancelled save dataset")
        elif retval == gtk.RESPONSE_OK:
            logger.debug("Saving dataset as: %s" % dialog.get_filename())
            fd = open(dialog.get_filename(), 'w')
            dataset.write_ftsv(fd, self.dataset)
            fd.close()
        else:
            print "unknown; ", retval 
        dialog.destroy()

    def on_delete(self, item, navigator):
        tm, rows = navigator.get_selection().get_selected_rows()
        iters = [tm.get_iter(r) for r in rows]
        iters.reverse()
        for i in iters:
            main.project.delete_data(i)
   #         tm.remove(i)
    
    def on_plot_image(self, item, navigator):
        plot = plots.ImagePlot(self.dataset, name='Image Plot')
        icon = fluents.icon_factory.get("line_plot")
        main.project.data_tree_insert(self.tree_iter, 'Image Plot', plot, None, "black", icon)
        # fixme: image plot selections are not well defined
        #plot.set_selection_listener(project.set_selection)
        #project._selection_observers.append(plot)

    def on_plot_hist(self, item, navigator):
        project = main.project
        plot = plots.HistogramPlot(self.dataset, name='Histogram')
        icon = fluents.icon_factory.get("line_plot")
        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_plot_scatter(self, item, navigator):
        project = main.project
        datasets = main.project.current_data
        ds_major = datasets[0]
        dims_major = ds_major.get_dim_name()
        ids_major = ds_major.get_identifiers(dims_major[1])
        if len(datasets)>1:
            # If there is more than one active dataset -> try to use the two first
            ds_minor = datasets[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)
        project._selection_observers.append(plot)
        
    def on_plot_line(self, item, navigator):
        project = main.project
        ds = self.dataset
        dims = ds.get_dim_name()
        ids = ds.get_identifiers(dims[1])
        plot = plots.LineViewPlot(ds, name='Line (%s)' % ds.get_name())
        icon = fluents.icon_factory.get("line_plot")
        project.data_tree_insert(self.tree_iter, 'Line view', 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()
        ds._name = ds._name + ".T"
        icon = fluents.icon_factory.get(ds)
        project.data_tree_insert(self.tree_iter, ds.get_name(), ds, None, "black", icon)

    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.asarray()/scipy.expand_dims(ds.asarray().std(axis), axis)
        icon = fluents.icon_factory.get(ds)
        project.data_tree_insert(self.tree_iter, ds.get_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.asarray()/scipy.expand_dims(ds.asarray().std(axis), axis)
        icon = fluents.icon_factory.get(ds)
        project.data_tree_insert(self.tree_iter, ds.get_name(), ds, None, "black", icon)

    def on_log(self, item, navigator):
        project = main.project
        try:
            if not scipy.all(self.dataset.asarray()>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.asarray())
        icon = fluents.icon_factory.get(ds)
        ds._name = ds._name + ".log"
        project.data_tree_insert(self.tree_iter, ds.get_name(), ds, None, "black", icon)