* system/plots.py: Added NetworkPlot, which may or may not work correctly.
* system/dataset.py: Removed a few lines of obsolete code.
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@ -113,9 +113,6 @@ class Dataset:
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def asarray(self):
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"""Returns the numeric array (data) of dataset"""
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if not self.has_array:
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raise ValueError, "Dataset is empty"
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else:
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return self._array
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def add_array(self,array):
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@ -199,13 +196,6 @@ class CategoryDataset(Dataset):
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def __init__(self):
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Dataset.__init__(self)
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self.has_collection = False
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def as_array(self):
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"""Returns data as binary matrix"""
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if not self.has_array and self.has_collection:
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#build numeric array
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pass
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def as_collection(self,dim):
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"""Returns data as collection along dim"""
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@ -236,7 +226,7 @@ class GraphDataset(Dataset):
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self.has_graph = False
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def asnetworkx(self,nx_type='graph'):
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dim = self.get_dim_names()[0]
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dim = self.get_dim_name()[0]
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ids = self.get_identifiers(dim)
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adj_mat = self.asarray()
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G = self._graph_from_adj_matrix(adj_mat,labels=ids)
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@ -270,6 +260,7 @@ class GraphDataset(Dataset):
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tail = labels[i]
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G.add_edge(head,tail)
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return G
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Dataset._all_dims=set()
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class Selection:
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111
system/plots.py
111
system/plots.py
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@ -11,6 +11,7 @@ from matplotlib.figure import Figure
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from matplotlib.numerix import arange, sin, pi
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from matplotlib.widgets import RectangleSelector
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from matplotlib import cm
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import networkx
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from system import logger
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@ -471,24 +472,23 @@ class ScatterPlot(Plot):
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# find indices of selected area
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if x1>x2:
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if y1<y2:
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index =scipy.nonzero((xdata<x1) & (xdata>x2) & (ydata>y1) & (ydata<y2))
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else:
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index =scipy.nonzero((xdata<x1) & (xdata>x2) & (ydata<y1) & (ydata>y2))
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else:
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#logger.log('debug','Selection x_start less than x_end')
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if y1<y2:
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#logger.log('debug','Selection y_start less than y_end')
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x1, x2 = x2, x1
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if y1>y2:
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y1, y2 = y2, y1
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assert x1<=x2
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assert y1<=y2
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index = scipy.nonzero((xdata>x1) & (xdata<x2) & (ydata>y1) & (ydata<y2))
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else:
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#logger.log('debug','Selection y_start bigger than y_end')
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index =scipy.nonzero((xdata>x1) & (xdata<x2) & (ydata<y1) & (ydata>y2))
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print 'index:', index
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print 'current_dim', self.current_dim
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ids = self.dataset_1.get_identifiers(self.current_dim, index)
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print 'ids', ids
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self.selection_listener(self.current_dim, ids)
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def selection_changed(self, selection):
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ids = selection[self.current_dim] # current identifiers
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print 'ids: ', ids
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index = self.dataset_1.get_indices(self.current_dim, ids)
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xdata_new = scipy.take(self.xaxis_data, index) #take data
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@ -499,16 +499,52 @@ class ScatterPlot(Plot):
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self.canvas.draw()
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class NetworkPlot(Plot):
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def __init__(self, dataset, name='Network Plot'):
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Plot.__init__(self)
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def __init__(self, graph, **kw):
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# Set member variables and call superclass' constructor
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self.graph = graph.asnetworkx()
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self.dataset = graph
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self.keywords = kw
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self.dim_name = self.dataset.get_dim_name(0)
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fig = Figure(figsize=(5,4), dpi=72)
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self.ax = ax = fig.add_subplot(111)
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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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kw['prog'] = 'neato'
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if not kw.has_key('pos') or kw['pos']:
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print 'graph: ', self.graph, type(self.graph)
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print 'prog:', kw['prog']
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kw['pos'] = networkx.drawing.nx_pydot.graphviz_layout(self.graph, kw['prog'])
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Plot.__init__(self, kw['name'])
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self.canvas = FigureCanvas(fig)
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# Keep node size and color as dicts for fast lookup
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if kw.has_key('node_size') and cb.iterable(kw['node_size']):
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kw.remove('node_size')
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self.node_size = {}
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for id, size in zip(self.dataset[self.dim_name], kw['node_size']):
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self.node_size[id] = size
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if kw.has_key('node_color') and cb.iterable(kw['node_color']):
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kw.remove('node_color')
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self.node_color = {}
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for id, color in zip(self.dataset[self.dim_name], kw['node_color']):
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self.node_color[id] = color
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# FIXME: What is figsize?
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self.fig = Figure(figsize=(5, 4), dpi=72)
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self.ax = self.fig.add_subplot(111)
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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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# Add canvas and show
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self.canvas = FigureCanvas(self.fig)
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self.add(self.canvas)
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self.canvas.show()
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# Initial draw
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networkx.draw_networkx(self.graph, ax=self.ax, **kw)
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# Setup toolbar
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self._toolbar = NavToolbar(self.canvas, None)
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self._toolbar.set_property('show-arrow', False)
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self._toolbar.set_select_callback(self.rectangle_select_callback)
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@ -516,8 +552,49 @@ class NetworkPlot(Plot):
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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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'event1 and event2 are the press and release events'
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pos = self.kw['pos']
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ydata = zeros((len(pos),),'l')
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xdata = zeros((len(pos),),'l')
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node_ids = []
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c = 0
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for name,(x,y) in pos.items():
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node_ids.append(name)
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xdata[c] = x
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ydata[c] = y
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c+=1
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# find indices of selected area
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if x1 > x2:
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x1, x2 = x2, x1
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if y1 > y2:
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y1, y2 = y2, y1
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index = nonzero((xdata<x1) & (xdata>x2) & (ydata>y1) & (ydata<y2))
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ids = [node_ids[i] for i in index]
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self.selection_listener(self.dataset.get_dim_name(0), ids)
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def selection_changed(self, selection):
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return None
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ids = selection[self.dataset.get_dim_name(0)] # current identifiers
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selected_nodes = list(ids.intersection(set(self.graph.nodes())))
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unselected_nodes = list(ids.difference(selected_nodes))
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unselected_colors = [self.node_color[x] for x in unselected_nodes]
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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, self.kw['pos'], edge_list=self.graph.edges(), \
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ax=self.ax, *kw)
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networkx.draw_networkx_nodes(self.graph, self.kw['pos'], node_list=unselected_nodes, \
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node_color=unselected_colors, node_size=unselected_sizes, ax=self.ax, *kw)
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networkx.draw_networkx_nodes(self.graph, self.kw['pos'], node_list=selected_nodes, \
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node_color='black', node_size=selected_sizes, ax=self.ax, *kw)
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self.canvas.draw()
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# Create a view-changed signal that should be emitted every time
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@ -4,6 +4,7 @@ from system import dataset, logger, plots, workflow
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#import gostat
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from scipy import array,randn,log
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import cPickle
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import networkx
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class TestWorkflow (workflow.Workflow):
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@ -103,7 +104,15 @@ class TestDataFunction(workflow.Function):
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x = randn(20,30)
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X = dataset.Dataset(x)
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p = plots.ScatterPlot(X, X, 'rows', 'rows', '0_1', '0_2')
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return [X, plots.SinePlot(), p]
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graph = networkx.XGraph()
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for x in 'ABCDEF':
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for y in 'ADE':
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graph.add_edge(x, y, 3)
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print networkx.adj_matrix(graph)
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ds = dataset.GraphDataset(array(networkx.adj_matrix(graph)))
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ds_plot = plots.NetworkPlot(ds)
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return [X, ds, plots.SinePlot(), p, ds_plot]
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class DatasetLog(workflow.Function):
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def __init__(self):
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