def gencountryscatter(self):
info = [self.ccode, self.scode, self.scode2]
#print (info)
self.f.clf()
self.f = Figure(figsize=(8, 6), dpi=100)
self.a = self.f.add_subplot(111)
generate("scattercountry", info, self.a)
self.canvas = FigureCanvasTkAgg(self.f, master=self.master)
self.canvas.show()
self.canvas._tkcanvas.grid(row=0, column=1, rowspan=3)
def gencountryscatter(self):
info = [self.ccode, self.scode, self.scode2]
#print (info)
self.f.clf()
self.f = Figure(figsize=(8, 6), dpi=100)
self.a = self.f.add_subplot(111)
generate("scattercountry", info, self.a)
self.canvas = FigureCanvasTkAgg(self.f, master=self.master)
self.canvas.show()
self.canvas._tkcanvas.grid(row=0, column=1, rowspan=3)
def gengraph(self):
b = self.beginscale
e = self.endscale
info = [b.get(), e.get(), self.ccode, self.scode]
#print(info)
self.f.clf()
self.f = Figure(figsize=(8, 6), dpi=100)
self.a = self.f.add_subplot(111)
generate("line", info, self.a)
self.canvas = FigureCanvasTkAgg(self.f, master=self.master)
self.canvas.show()
self.canvas.get_tk_widget().pack(side=TOP, fill=BOTH, expand=1)
self.canvas._tkcanvas.grid(row=0, column=1, rowspan=3)
def gengraph(self):
b = self.beginscale
e = self.endscale
info = [b.get(), e.get(), self.ccode, self.scode]
#print(info)
self.f.clf()
self.f = Figure(figsize=(8, 6), dpi=100)
self.a = self.f.add_subplot(111)
generate("line", info, self.a)
self.canvas = FigureCanvasTkAgg(self.f, master=self.master)
self.canvas.show()
self.canvas.get_tk_widget().pack(side=TOP, fill=BOTH, expand=1)
self.canvas._tkcanvas.grid(row=0, column=1, rowspan=3)
def index(request):
graph.generate()
# Request the context of the request.
# The context contains information such as the client's machine details, for example.
context = RequestContext(request)
# Construct a dictionary to pass to the template engine as its context.
# Note the key boldmessage is the same as {{ boldmessage }} in the template!
context_dict = {'boldmessage': "I am bold font from the context"}
# Return a rendered response to send to the client.
# We make use of the shortcut function to make our lives easier.
# Note that the first parameter is the template we wish to use.
return render_to_response('index.html', context_dict, context)
def execute(db,db2,name, pkg_structure):
root = ET.Element("project")
root.set("name",name)
file_set1 = get_filenames(db,'.java',pkg_structure)
file_set2 = get_filenames(db2, '.java',pkg_structure)
filenames = set.intersection(file_set1,file_set2)
file_deleted=file_set1.difference(file_set2)
file_added=file_set2.difference(file_set1)
for file in file_added:
file2 = db2.lookup(file,"file")[0]
class10 = [sel_class for sel_class in db2.lookup(file.split(".")[0],"class") if sel_class.parent() == file2][0]
class_elem = ET.SubElement(root, "class")
class_elem.set("name",class10.simplename())
class_elem.set("type","Added")
class_elem.set("name","class")
for file in file_deleted:
file1 = db.lookup(file,"file")[0]
class10 = [sel_class for sel_class in db.lookup(file.split(".")[0],"class") if sel_class.parent() == file1][0]
class_elem = ET.SubElement(root, "class")
class_elem.set("name",class10.simplename())
class_elem.set("type","deleted")
class_elem.set("name","class")
if(not (bool(filenames))):
print('No changes done')
for file in filenames:
class_elem = ET.SubElement(root, "class")
class_elem.set("name",file)
g.generate(db,db2,file, class_elem)
analyze(db,db2,name,file,class_elem)
tree = ET.ElementTree(root)
tree.write("changes.xml")
def kafka_acl_graph():
include_pattern = unquote(request.args.get('include-pattern', ''))
exclude_user_pattern = unquote(request.args.get('exclude-user-pattern',
''))
exclude_topic_pattern = unquote(
request.args.get('exclude-topic-pattern', ''))
acls = aiven.get_aiven_acls()
nodes, edges = graph.generate(
acls,
graph.SearchConditions(include_pattern, exclude_user_pattern,
exclude_topic_pattern))
rendered, content = graph.render(
nodes, edges,
graph.LinkGenerator(generate_self_link, generate_topic_download_link,
get_static_resource))
os.remove(rendered)
logger.info(f'File {rendered} deleted')
response = Response(response=content, status=200, mimetype="image/svg+xml")
response.headers["Content-Type"] = "image/svg+xml; charset=utf-8"
return response
def Bay_psa(t0):
Adj, E, edgno = graph.generate(100, 20)
sum = 0
for _ in range(10):
sum+= sa(100, E, 25, edgno, t0, 1000, P, 1)[0]
return -sum
def Bay_ba(t0):
Adj, E, edgno = graph.generate(100, 20)
sum = 0
for _ in range(10):
sum+= sa(100, E, 25, edgno, t0, 1000, 1, P)[0]
return -sum
#FOR BAYESIAN OPTIMIZATION
bo = BayesianOptimization(FUNCTION TO OPTIMIZE,{'t0': (0.00000000001, 1), 'g0': (0.0000000001, 10)})
bo.maximize(init_points=15, n_iter=45, kappa=2)
print(bo.res['max'])
'''
#Toggle below to compare time taken or numbe of iterations (Figure 2 and 3)
#B = 0 #FOR TIME TAKEN
#B = 1 #FOR NUMBER OF ITERATIONS
#QA vs SA vs PSA vs BA
for _ in range(100):
Adj, E, edgno = graph.generate(100, 20)
print qa(100, Adj, 25, edgno, 0.35, 0.75, 100, P,
1.0)[B], sa(100, E, 25, edgno, 0.35, 1000, 1,
1)[B], sa(100, E, 25, edgno, 0.35, 1000, P,
1)[B], sa(100, E, 25, edgno, 0.35, 1000, 1,
P)[B]
P = 10
'''
#Functions for Bayesian optimization
def Bay_qaw(t0, g0):
Adj, E, edgno = graph.generate(100, 20)
sum = 0
for _ in range(10):
sum+= qa(100, Adj, 25, edgno, t0, g0, 100, P, 1.0)[0]
return -sum
def Bay_qaw0(t0, g0):
Adj, E, edgno = graph.generate(100, 20)
sum = 0
for _ in range(10):
sum+= qa(100, Adj, 25, edgno, t0, g0, 100, P, 0.00)[0]
return -sum
#FOR BAYESIAN OPTIMIZATION
bo = BayesianOptimization(Bay_qaw,{'t0': (0.00000000001, 1), 'g0': (0.0000000001, 10)})
bo.maximize(init_points=15, n_iter=45, kappa=2)
print(bo.res['max'])
'''
B = 0 #FOR TIME TAKEN
#QA forward vs QA backward
for _ in range(100):
Adj, E, edgno = graph.generate(500, 200)
print qa(500, Adj, 250, edgno, 0.62, 1.2, 1000, P,
1.0)[B], qarev(500, Adj, 250, edgno, 0.62, 1.2, 1000, P, 1.0)[B]
#should get similar results for both
def Bay_SA(t0, x): Adj, E, edgno = graph.generate(100, 20) sum = 0 for _ in range(3): sum+= sa(100, E, 25, edgno, t0, 100, 1+int(floor(x)), 1+10-int(floor(x)))[0] return -sum
def main():
img = graph.generate(data=test_data, title="Test Stock")
print(img)
for e in next_node.edges:
frontier.add(e)
graph.remove(next_node)
ret.add(next_node)
return ret
if __name__ == '__main__':
if len(sys.argv) < 2:
print "Usage ./dijkstra <start-node> [<input-file>]"
sys.exit(0)
start_node = sys.argv[1]
if len(sys.argv) < 3:
import cities
nodenames = ["{}, {}".format(city, state) for city, state in cities.CITIES]
nodes = generate(100, nodenames)
filename = "a.txt"
else:
filename = sys.argv[2]
nodes = parse(filename)
print "Looking for %s" % start_node
assert start_node in nodes
result = dijkstra(nodes[start_node], set(nodes.values()))
for node in result:
print "{}: {}".format(node.name, node.cost)
graphviz(filename.replace('.txt', '.dot'), nodes.values())
