Factored out a mixin class for IC thresholding.
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0523ebab05
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3f7215bc35
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@ -491,7 +491,7 @@ class PlotDagFunction(workflow.Function):
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ds = dataset.GraphDataset(networkx.adj_matrix(g),
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ds = dataset.GraphDataset(networkx.adj_matrix(g),
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[('go-terms', g.nodes()), ('_go-terms', g.nodes())],
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[('go-terms', g.nodes()), ('_go-terms', g.nodes())],
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name="DAG")
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name="DAG")
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return [DagPlot(g)]
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return [ThresholdDagPlot(g)]
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def get_network(self, terms, subtree='bp'):
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def get_network(self, terms, subtree='bp'):
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"""Returns a DAG connecting the given terms by including their parents
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"""Returns a DAG connecting the given terms by including their parents
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@ -559,12 +559,116 @@ class VolcanoPlot(plots.ScatterPlot):
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sel_dim_2='_p', **kw)
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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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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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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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with_labels=False, name='DAG Plot'):
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plots.Plot.__init__(self, name)
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plots.Plot.__init__(self, name)
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self._add_ic_spin_buttons()
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self.nodes = graph.nodes()
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self.nodes = graph.nodes()
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self.graph = graph
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self.graph = graph
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self._pos = pos
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self._pos = pos
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@ -630,39 +734,6 @@ class DagPlot(plots.Plot):
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self.axes.set_frame_on(False)
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self.axes.set_frame_on(False)
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self.fig.subplots_adjust(left=0, right=1, bottom=0, top=1)
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self.fig.subplots_adjust(left=0, right=1, bottom=0, top=1)
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def _add_ic_spin_buttons(self):
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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_ic_value_changed)
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self._ic_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_ic_value_changed)
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self._ic_sb_max = sb_max
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label = gtk.Label(" < IC < ")
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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 information content threshold")
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def _calc_pos(self, graph):
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def _calc_pos(self, graph):
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"""Calculates position for graph nodes using 'dot' layout."""
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"""Calculates position for graph nodes using 'dot' layout."""
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gv_graph = networkx.DiGraph()
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gv_graph = networkx.DiGraph()
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@ -678,44 +749,7 @@ class DagPlot(plots.Plot):
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pos[k] = v
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pos[k] = v
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return pos
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return pos
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def set_ic_threshold(self, ic_min, ic_max):
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def points_in_rect(self, x1, y1, x2, y2, key):
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"""Sets Information Content min and max to the given values.
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Updates the plot accordingly to show only values that have an
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information content 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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ic = getattr(main.workflow, 'current_ic', None)
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if ic == None:
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print "no ic set"
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return
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icnodes = ic.existing_identifiers('go-terms', self.nodes)
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icindices = ic.get_indices('go-terms', icnodes)
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a = ravel(ic.asarray()[icindices])
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ic_good = set(array(icnodes)[(a>=ic_min) & (a<=ic_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 ic_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 _on_ic_value_changed(self, sb):
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"""Callback on spin button value changes."""
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ic_min = self._ic_sb_min.get_value()
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ic_max = self._ic_sb_max.get_value()
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self.set_ic_threshold(ic_min, ic_max)
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def rectangle_select_callback(self, x1, y1, x2, y2, key):
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ydata = self.yaxis_data
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ydata = self.yaxis_data
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xdata = self.xaxis_data
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xdata = self.xaxis_data
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@ -732,7 +766,12 @@ class DagPlot(plots.Plot):
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ids = self.visible.intersection([self.nodes[i] for i in index])
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ids = self.visible.intersection([self.nodes[i] for i in index])
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else:
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else:
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ids = set([self.nodes[i] for i in index])
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ids = set([self.nodes[i] for i in index])
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return ids
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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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ids = self.update_selection(ids, key)
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ids = self.update_selection(ids, key)
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self.selection_listener(self.current_dim, ids)
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self.selection_listener(self.current_dim, ids)
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def lasso_select_callback(self, verts, key=None):
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def lasso_select_callback(self, verts, key=None):
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@ -807,9 +846,34 @@ class DagPlot(plots.Plot):
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self.node_collection.set_array(map_vec)
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self.node_collection.set_array(map_vec)
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self.node_collection.set_clim(vec_min, vec_max)
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self.node_collection.set_clim(vec_min, vec_max)
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self.node_collection.update_scalarmappable() #sets facecolors from array
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self.node_collection.update_scalarmappable() #sets facecolors from array
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self._ic_sb_min.set_range(0, vec_max)
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self._ic_sb_min.set_value(vec_min)
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self._ic_sb_max.set_range(0, vec_max)
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self._ic_sb_max.set_value(vec_max)
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self.canvas.draw()
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self.canvas.draw()
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class ThresholdDagPlot(DagPlot, 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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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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ids = self.visible.intersection(ids)
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ids = self.update_selection(ids, key)
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self.selection_listener(self.current_dim, ids)
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def _update_color_from_dataset(self, ds):
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DagPlot._update_color_from_dataset(self, ds)
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self.set_threshold_dataset(ds)
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a = ds.asarray()
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a_max = max(a[a<inf])
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a_min = min(a[a>-inf])
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self._sb_min.set_range(0, a_max)
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self._sb_min.set_value(a_min)
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self._sb_max.set_range(0, a_max)
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self._sb_max.set_value(a_max)
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