Dataset to colour of dragndrop in dataset + minor addjustments in networkplot
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0b30aeac6f
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@ -221,6 +221,13 @@ class ViewFrame (gtk.Frame):
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self.set_view(obj)
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self.focus()
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elif isinstance(obj, fluents.dataset.Dataset):
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view = self.get_view()
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if view.is_mappable_with(obj):
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view._update_color_from_dataset(obj)
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# add selections below
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class MainView (gtk.Notebook):
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"""The MainView class displays the Views in Fluents.
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@ -381,6 +388,10 @@ class View (gtk.Frame):
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def get_toolbar(self):
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return None
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def is_mappable_with(self, dataset):
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"""Override in individual plots."""
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return False
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class EmptyView (View):
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"""EmptyView is shown in ViewFrames that are unused."""
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@ -654,12 +665,15 @@ class ScatterPlot(Plot):
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self.xaxis_data = dataset_1._array[:, x_index]
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self.yaxis_data = dataset_2._array[:, y_index]
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lw = scipy.zeros(self.xaxis_data.shape)
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sc = self.ax.scatter(self.xaxis_data, self.yaxis_data, s=s, c=c, linewidth=lw, edgecolor='k', alpha=.6, cmap = cm.jet)
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self.sc = sc = self.ax.scatter(self.xaxis_data, self.yaxis_data,
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s=s, c=c, linewidth=lw,
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edgecolor='k', alpha=.8,
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cmap=cm.jet)
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if len(c)>1:
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self.fig.colorbar(sc,ticks=[], fraction=.05)
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self.fig.colorbar(sc, fraction=.05)
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self.ax.axhline(0, color='k', lw=1., zorder=1)
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self.ax.axvline(0, color='k', lw=1., zorder=1)
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#self.ax.set_title(self.get_title())
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# collection
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self.coll = self.ax.collections[0]
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@ -667,6 +681,41 @@ class ScatterPlot(Plot):
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self.add(self.canvas)
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self.canvas.show()
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def is_mappable_with(self, dataset):
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"""Returns True if dataset is mappable with this plot.
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"""
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if self.current_dim in dataset.get_dim_name() and dataset.asarray().shape[0] == self.xaxis_data.shape[0]:
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return True
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def _update_color_from_dataset(self, data):
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"""Updates the facecolors from a dataset.
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"""
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array = data.asarray()
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#only support for 2d-arrays:
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try:
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m, n = array.shape
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except:
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raise ValueError, "No support for more tha 2 dimensions."
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# is dataset a vector or matrix?
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if not n==1:
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# we have a category dataset
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if isinstance(data, fluents.dataset.CategoryDataset):
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map_vec = scipy.dot(array, scipy.diag(scipy.arange(n))).sum(1)
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else:
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map_vec = array.sum(1)
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else:
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map_vec = array.ravel()
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# normalise mapping vector
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map_vec = map_vec - map_vec.min()
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map_vec = map_vec/map_vec.max()
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# update facecolors
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self.sc._facecolors = self.sc.to_rgba(map_vec, self.sc._alpha)
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# draw
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self.sc._A = None # mean hack
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self.ax.draw_artist(self.sc)
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self.canvas.draw()
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def rectangle_select_callback(self, x1, y1, x2, y2):
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ydata = self.yaxis_data
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xdata = self.xaxis_data
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@ -714,7 +763,9 @@ class NetworkPlot(Plot):
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self.dataset = dataset
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self.keywords = kw
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self.dim_name = self.dataset.get_dim_name(0)
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self.current_dim = self.dim_name
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if not kw.has_key('with_labels'):
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k w['with_labels'] = False
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if not kw.has_key('name'):
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kw['name'] = self.dataset.get_name()
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if not kw.has_key('prog'):
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@ -722,6 +773,7 @@ class NetworkPlot(Plot):
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if not kw.has_key('pos') or kw['pos']:
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kw['pos'] = networkx.pygraphviz_layout(self.graph, kw['prog'])
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Plot.__init__(self, kw['name'])
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self.current_dim = self.dim_name
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# Keep node size and color as dicts for fast lookup
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self.node_size = {}
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@ -731,7 +783,7 @@ class NetworkPlot(Plot):
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self.node_size[id] = size
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else:
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for id in dataset[self.dim_name]:
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self.node_size[id] = 40
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self.node_size[id] = 30
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self.node_color = {}
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if kw.has_key('node_color') and cb.iterable(kw['node_color']):
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@ -747,9 +799,9 @@ class NetworkPlot(Plot):
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kw.pop('node_color')
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self.ax = self.fig.add_subplot(111)
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self.ax.set_position([0.01,0.01,.99,.99])
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self.ax.set_xticks([])
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self.ax.set_yticks([])
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self.ax.grid(False)
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# FIXME: ax shouldn't be in kw at all
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if kw.has_key('ax'):
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kw.pop('ax')
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@ -760,11 +812,13 @@ class NetworkPlot(Plot):
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# Initial draw
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networkx.draw_networkx(self.graph, ax=self.ax, **kw)
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print "Current dim is now: %s" %self.current_dim
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def get_toolbar(self):
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return self._toolbar
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def rectangle_select_callback(self, x1, y1, x2, y2):
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print "In select callbak, current dim is now: %s" %self.current_dim
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pos = self.keywords['pos']
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ydata = scipy.zeros((len(pos),), 'l')
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xdata = scipy.zeros((len(pos),), 'l')
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@ -782,9 +836,10 @@ class NetworkPlot(Plot):
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if y1 > y2:
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y1, y2 = y2, y1
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index = scipy.nonzero((xdata>x1) & (xdata<x2) & (ydata>y1) & (ydata<y2))[0]
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ids = [node_ids[i] for i in index]
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print "Updating listener from network with dim: %s" %self.current_dim
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print "ids: "
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print ids
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self.selection_listener(self.current_dim, ids)
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def set_current_selection(self, selection):
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@ -797,23 +852,28 @@ class NetworkPlot(Plot):
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if self.node_color:
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unselected_colors = [self.node_color[x] for x in unselected_nodes]
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else:
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unselected_colors = 'red'
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unselected_colors = 'gray'
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if self.node_size:
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unselected_sizes = [self.node_size[x] for x in unselected_nodes]
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selected_sizes = [self.node_size[x] for x in selected_nodes]
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self.ax.clear()
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networkx.draw_networkx_edges(self.graph, edge_list=self.graph.edges(), \
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ax=self.ax, **self.keywords)
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self.ax.collections=[]
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networkx.draw_networkx_edges(self.graph,
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edge_list=self.graph.edges(),
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ax=self.ax,
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**self.keywords)
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networkx.draw_networkx_labels(self.graph,**self.keywords)
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if unselected_nodes:
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networkx.draw_networkx_nodes(self.graph, nodelist=unselected_nodes, \
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node_color='r', node_size=unselected_sizes, ax=self.ax, **self.keywords)
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node_color='gray', node_size=unselected_sizes, ax=self.ax, **self.keywords)
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if selected_nodes:
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networkx.draw_networkx_nodes(self.graph, nodelist=selected_nodes, \
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node_color='k', node_size=selected_sizes, ax=self.ax, **self.keywords)
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node_color='r', node_size=selected_sizes, ax=self.ax, **self.keywords)
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self.ax.collections[-1].set_zorder(3)
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self.canvas.draw()
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