def drawGraph(genes_names_list, network_as_list):
G = nx.MultiDiGraph()
G.add_nodes_from(genes_names_list)
val_map = {'ARR23': 1.0, 'CRF2': 0.5714285714285714}
values = [val_map.get(node, 0.85) for node in G.nodes()]
#ajout des aretes et des noeuds
for i in range(len(network_as_list)):
gene_source = network_as_list[i][0]
gene_target = network_as_list[i][2]
interaction = network_as_list[i][1]
G.add_edge(gene_source, gene_target, arrowstyle=interaction)
# if gene_source not in G.nodes :
# if gene_target == gene_source :
# G.add_node(gene_source, regulation = "auto")
# else:
# G.add_node(gene_source, regulation = "none")
print(G.adj)
pos = nx.circular_layout(G)
nx.draw_networkx_nodes(G, pos, node_size=1500, node_color=values)
nx.draw_networkx_labels(G, pos)
for edge in G.edges(data=True):
if edge[2]['arrowstyle'] == "-1":
arrowstyle = "-["
else:
arrowstyle = "-|>"
nx.draw_networkx_edges(G,
pos,
edgelist=[(edge[0], edge[1])],
arrowstyle=arrowstyle,
node_size=1900)
# plt.show()
plt.gca().yaxis.set_minor_formatter(NullFormatter())
plt.subplots_adjust(top=1,
bottom=0,
left=0,
right=1,
hspace=0.25,
wspace=0.35)
fig = plt.gcf()
art = plot_network(G,
node_style=use_attributes(),
edge_style=use_attributes())
art.set_picker(10) # if using Pyplot then get the figure from the plot
return fig
def draw_workflow(dol, simulations):
graph = nx.from_dict_of_lists(dol, create_using=None)
fig, ax = plt.subplots()
art = plot_network(graph, ax=ax, node_style=use_attributes(),
edge_style=use_attributes(),
#layout="kamada_kawai",
#node_label_style = {'font_weight': 'bold', 'font_size': 15}
)
art.set_picker(10)
ax.set_title('workflow simulations, click on the nodes to see structure')
fig.canvas.mpl_connect('pick_event', hilighter)
plt.show()
plt.close()
return
def test_use_style_attributes_default(style_key, barbell_network):
for node, node_attr in barbell_network.nodes.data():
node_attr[style_key] = 'TEST'
node_styles = generate_node_styles(barbell_network,
use_attributes())
for node, style in node_styles.items():
assert node in barbell_network
assert style[style_key] == 'TEST'
def test_use_style_attributes_filter_single(barbell_network):
for node, node_attr in barbell_network.nodes.data():
for style_key in _ALL_STYLE_KEYS:
node_attr[style_key] = 'TEST'
node_styles = generate_node_styles(barbell_network,
use_attributes('color'))
expected = default_node_style()
expected['color'] = 'TEST'
for node, style in node_styles.items():
assert node in barbell_network
assert style == expected
def plotGraph(self):
G = self.graph[0]
largest_node = self.graph[1]
G.add_edge(largest_node, largest_node)
for node in G.nodes:
G.nodes[node]["size"] = 200
G.nodes[node]["color"] = 'C0'
G.nodes[largest_node]["size"] = 400
G.nodes[largest_node]["color"] = "red"
self.app.axes.clear()
self.app.selectedDocument.setText("")
graph = plot_network(G,
layout="spring",
ax=self.app.axes,
node_style=use_attributes(),
edge_style=use_attributes())
graph.set_picker(10)
self.app.canvas.mpl_connect('pick_event', self.app.selectNode)
self.app.update_graph.emit()
def set_graph(self):
"""
Draws current graph on canvas
"""
# add dummy edge if no edges
# circumvent the fact that drawing graph with no edges is not supported
if self.graph.number_of_edges() == 0:
for n in self.graph.nodes:
self.graph.add_edge(n, n)
if args.dataset == "clevr":
layout = "circular"
else:
layout = self.g_layout
self._static_ax.clear()
self.art = plot_network(
self.graph,
layout=layout,
ax=self._static_ax, #self.g_layout, "spring"
node_style=use_attributes(
), # use_attributes(), #node_options, #dict(node_size=50),
edge_style=use_attributes(), # ) #edge_options) # #,
node_label_style={
'font_size': '10',
'font_weight': 'bold'
}) # layout=self.g_layout
self.art.set_picker(10)
self._static_ax.figure.canvas.draw_idle()
# reset combobox for node choices and update with new object list
for i in range(self.comboBox_obj2.count()):
self.comboBox_obj2.removeItem(0)
for obj in self.graph.nodes:
if obj.split(".")[0] in objs:
self.comboBox_obj2.addItem(obj)
# clear any non-default color on nodes
for node, attributes in graph.nodes.data():
attributes.pop('color', None)
for u, v, attributes in graph.edges.data():
attributes.pop('width', None)
for node in event.nodes:
graph.nodes[node]['color'] = 'C1'
for edge_attribute in graph[node].values():
edge_attribute['width'] = 3
# update the screen
event.artist.stale = True
event.artist.figure.canvas.draw_idle()
graph = nx.barbell_graph(10, 14)
fig, ax = plt.subplots()
art = plot_network(graph,
ax=ax,
node_style=use_attributes(),
edge_style=use_attributes())
art.set_picker(10)
ax.set_title('Click on the nodes!')
fig.canvas.mpl_connect('pick_event', hilighter)
plt.show()
# clear any non-default color on nodes
for node, attributes in graph.nodes.data():
attributes.pop('color', None)
for u, v, attributes in graph.edges.data():
attributes.pop('width', None)
for node in event.nodes:
graph.nodes[node]['color'] = 'C1'
for edge_attribute in graph[node].values():
edge_attribute['width'] = 3
# update the screen
event.artist.stale = True
event.artist.figure.canvas.draw_idle()
graph = nx.barbell_graph(10, 14)
pos = nx.circular_layout(graph)
fig, ax = plt.subplots()
art = plot_network(graph, ax=ax,node_style=use_attributes(),
edge_style=use_attributes(), node_size = 500)
art.set_picker(10)
ax.set_title('Click on the nodes!')
fig.canvas.mpl_connect('pick_event', hilighter)
plt.show()