Added information content drag'n'drop to z loadings plot.
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@@ -559,119 +559,16 @@ class VolcanoPlot(plots.ScatterPlot):
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sel_dim_2='_p', **kw)
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class PlotThresholder:
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"""Mixin class for plots that needs to filter nodes within a threshold
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range.
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"""
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def __init__(self, text="x"):
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"""Constructor.
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@param text: Name of the variable the threshold is on.
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"""
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self._threshold_ds = None
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self._add_spin_buttons(text)
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self._sb_min.set_sensitive(False)
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self._sb_max.set_sensitive(False)
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def set_threshold_dataset(self, ds):
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"""Sets the dataset to threshold on.
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@param ds: A dataset where one dimension corresponds to the select dimension
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in the plot, and any other dimensions have length 1
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"""
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self._threshold_ds = ds
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self._sb_min.set_sensitive(True)
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self._sb_max.set_sensitive(True)
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def _add_spin_buttons(self, text):
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"""Adds spin buttons to the toolbar for selecting minimum and maximum
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threshold values on information content."""
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sb_min = gtk.SpinButton(digits=2)
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sb_min.set_range(0, 100)
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sb_min.set_value(0)
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sb_min.set_increments(.1, 1.)
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sb_min.connect('value-changed', self._on_value_changed)
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self._sb_min = sb_min
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sb_max = gtk.SpinButton(digits=2)
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sb_max.set_range(0, 100)
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sb_max.set_value(1)
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sb_max.set_increments(.1, 1.)
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sb_max.connect('value-changed', self._on_value_changed)
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self._sb_max = sb_max
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label = gtk.Label(" < %s < " % text)
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hbox = gtk.HBox()
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hbox.pack_start(sb_min)
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hbox.pack_start(label)
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hbox.pack_start(sb_max)
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ti = gtk.ToolItem()
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ti.set_expand(False)
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ti.add(hbox)
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sb_min.show()
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sb_max.show()
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label.show()
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hbox.show()
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ti.show()
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self._toolbar.insert(ti, -1)
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ti.set_tooltip(self._toolbar.tooltips, "Set threshold")
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def set_threshold(self, min, max):
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"""Sets min and max to the given values.
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Updates the plot accordingly to show only values that have a
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value within the boundaries. Other values are
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also excluded from being selected from the plot.
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@param ic_min Do not show nodes with IC below this value.
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@param ic_max Do not show nodes with IC above this value.
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"""
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ds = self._threshold_ds
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if ds == None:
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return
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icnodes = ds.existing_identifiers('go-terms', self.nodes)
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icindices = ds.get_indices('go-terms', icnodes)
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a = ravel(ds.asarray()[icindices])
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good = set(array(icnodes)[(a>=min) & (a<=max)])
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sizes = zeros(len(self.nodes))
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visible = set()
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for i, n in enumerate(self.nodes):
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if n in good:
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sizes[i] = 50
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visible.add(n)
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else:
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sizes[i] = 0
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self.visible = visible
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self.node_collection._sizes = sizes
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self.canvas.draw()
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def get_nodes_within_bounds(self):
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"""Get a list of all nodes within the bounds of the selection in the
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seleted dataset.
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"""
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pass
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def filter_nodes(self, nodes):
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"""Filter a list of nodes and return only those that are within the
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threshold boundaries."""
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pass
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def _on_value_changed(self, sb):
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"""Callback on spin button value changes."""
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min = self._sb_min.get_value()
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max = self._sb_max.get_value()
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self.set_threshold(min, max)
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class DagPlot(plots.Plot):
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def __init__(self, graph, dim='go-terms', pos=None, nodecolor='b', nodesize=40,
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with_labels=False, name='DAG Plot'):
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plots.Plot.__init__(self, name)
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self.nodes = graph.nodes()
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self._map_ids = self.nodes
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self.graph = graph
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self._pos = pos
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self._cmap = matplotlib.cm.summer
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self._nodesize = nodesize
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self._nodecolor = nodecolor
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self._with_labels = with_labels
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@@ -700,6 +597,7 @@ class DagPlot(plots.Plot):
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linewidth=lw,
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zorder=3)
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self._mappable = self.node_collection
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self._mappable.set_cmap(self._cmap)
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# selected nodes is a transparent graph that adjust node-edge visibility
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# according to the current selection needed to get get the selected
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@@ -850,13 +748,13 @@ class DagPlot(plots.Plot):
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self.canvas.draw()
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class ThresholdDagPlot(DagPlot, PlotThresholder):
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class ThresholdDagPlot(DagPlot, plots.PlotThresholder):
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def __init__(self, graph, dim='go-terms', pos=None, nodecolor='b', nodesize=40,
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with_labels=False, name='DAG Plot'):
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DagPlot.__init__(self, graph, dim='go-terms', pos=None,
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nodecolor='b', nodesize=40,
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with_labels=False, name='DAG Plot')
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PlotThresholder.__init__(self, "IC")
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plots.PlotThresholder.__init__(self, "IC")
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def rectangle_select_callback(self, x1, y1, x2, y2, key):
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ids = self.points_in_rect(x1, y1, x2, y2, key)
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