def test_networkx_roundtrip(self):
print("\n---------- NetworkX Data Roundtrip Test Start -----------\n")
g = nx.newman_watts_strogatz_graph(100, 3, 0.5)
nodes = g.nodes()
edges = g.edges()
# Add some attributes
g.graph["name"] = "original"
g.graph["density"] = nx.density(g)
nx.set_node_attributes(g, "betweenness", nx.betweenness_centrality(g))
nx.set_node_attributes(g, "degree", nx.degree(g))
nx.set_node_attributes(g, "closeness", nx.closeness_centrality(g))
nx.set_edge_attributes(g, "eb", nx.edge_betweenness(g))
cyjs1 = util.from_networkx(g)
g2 = util.to_networkx(cyjs1)
self.assertEqual(len(g2.nodes()), len(nodes))
self.assertEqual(len(g2.edges()), len(edges))
edge_set = set(list(map(lambda x: (int(x[0]), int(x[1])), g2.edges())))
self.assertEqual(0, len(edge_set.difference(set(edges))))
node_original = g.node[1]
node_generated = g2.node["1"]
print(node_original)
print(node_generated)
self.assertEqual(node_original["degree"], node_generated["degree"])
self.assertEqual(node_original["betweenness"], node_generated["betweenness"])
self.assertEqual(node_original["closeness"], node_generated["closeness"])
def test_networkx_roundtrip(self):
print('\n---------- NetworkX Data Roundtrip Test Start -----------\n')
g = nx.newman_watts_strogatz_graph(100, 3, 0.5)
nodes = g.nodes()
edges = g.edges()
# Add some attributes
g.graph['name'] = 'original'
g.graph['density'] = nx.density(g)
nx.set_node_attributes(g, 'betweenness', nx.betweenness_centrality(g))
nx.set_node_attributes(g, 'degree', nx.degree(g))
nx.set_node_attributes(g, 'closeness', nx.closeness_centrality(g))
nx.set_edge_attributes(g, 'eb', nx.edge_betweenness(g))
cyjs1 = util.from_networkx(g)
g2 = util.to_networkx(cyjs1)
self.assertEqual(len(g2.nodes()), len(nodes))
self.assertEqual(len(g2.edges()), len(edges))
edge_set = set(list(map(lambda x: (int(x[0]), int(x[1])), g2.edges())))
self.assertEqual(0, len(edge_set.difference(set(edges))))
node_original = g.node[1]
node_generated = g2.node['1']
print(node_original)
print(node_generated)
self.assertEqual(node_original['degree'], node_generated['degree'])
self.assertEqual(node_original['betweenness'], node_generated['betweenness'])
self.assertEqual(node_original['closeness'], node_generated['closeness'])
def test_networkx_roundtrip(self):
print('\n---------- NetworkX Data Roundtrip Test Start -----------\n')
g = nx.newman_watts_strogatz_graph(100, 3, 0.5)
nodes = g.nodes()
edges = g.edges()
# Add some attributes
g.graph['name'] = 'original'
g.graph['density'] = nx.density(g)
nx.set_node_attributes(g, 'betweenness', nx.betweenness_centrality(g))
nx.set_node_attributes(g, 'degree', nx.degree(g))
nx.set_node_attributes(g, 'closeness', nx.closeness_centrality(g))
nx.set_edge_attributes(g, 'eb', nx.edge_betweenness(g))
cyjs1 = util.from_networkx(g)
g2 = util.to_networkx(cyjs1)
self.assertEqual(len(g2.nodes()), len(nodes))
self.assertEqual(len(g2.edges()), len(edges))
edge_set = set(list(map(lambda x: (int(x[0]), int(x[1])), g2.edges())))
self.assertEqual(0, len(edge_set.difference(set(edges))))
node_original = g.node[1]
node_generated = g2.node['1']
print(node_original)
print(node_generated)
self.assertEqual(node_original['degree'], node_generated['degree'])
self.assertEqual(node_original['betweenness'], node_generated['betweenness'])
self.assertEqual(node_original['closeness'], node_generated['closeness'])
def test_networkx_parse_network(self):
f = open(self.cur_dir + '/data/galFiltered.json', 'r')
jsonData = json.load(f)
j_nodes = jsonData['elements']['nodes']
j_edges = jsonData['elements']['edges']
print('\n---------- JSON Loading Test Start -----------\n')
# print(json.dumps(jsonData, indent=4))
g = util.to_networkx(jsonData)
nodes = g.nodes()
edges = g.edges()
self.assertEqual('Yeast Network Sample', g.graph['name'])
self.assertEqual('Sample network created by JSON export.', g.graph['description'])
self.assertEqual(4, len(g.graph['numberList']))
self.assertEqual(len(j_nodes), len(nodes))
self.assertEqual(len(j_edges), len(edges))
edge_set = set(list(map(lambda x: (int(x[0]), int(x[1])), edges)))
self.assertEqual(0, len(compare_edge_sets(edge_set, j_edges)))
def test_networkx_parse_network(self):
f = open(self.cur_dir + '/data/galFiltered.json', 'r')
jsonData = json.load(f)
j_nodes = jsonData['elements']['nodes']
j_edges = jsonData['elements']['edges']
print('\n---------- JSON Loading Test Start -----------\n')
# print(json.dumps(jsonData, indent=4))
g = util.to_networkx(jsonData)
nodes = g.nodes()
edges = g.edges()
self.assertEqual('Yeast Network Sample', g.graph['name'])
self.assertEqual('Sample network created by JSON export.', g.graph['description'])
self.assertEqual(4, len(g.graph['numberList']))
self.assertEqual(len(j_nodes), len(nodes))
self.assertEqual(len(j_edges), len(edges))
edge_set = set(list(map(lambda x: (int(x[0]), int(x[1])), edges)))
self.assertEqual(0, len(compare_edge_sets(edge_set, j_edges)))
def test_networkx_parse_network(self):
f = open(self.cur_dir + "/data/galFiltered.json", "r")
jsonData = json.load(f)
j_nodes = jsonData["elements"]["nodes"]
j_edges = jsonData["elements"]["edges"]
print("\n---------- JSON Loading Test Start -----------\n")
# print(json.dumps(jsonData, indent=4))
g = util.to_networkx(jsonData)
nodes = g.nodes()
edges = g.edges()
self.assertEqual("Yeast Network Sample", g.graph["name"])
self.assertEqual("Sample network created by JSON export.", g.graph["description"])
self.assertEqual(4, len(g.graph["numberList"]))
self.assertEqual(len(j_nodes), len(nodes))
self.assertEqual(len(j_edges), len(edges))
edge_set = set(list(map(lambda x: (int(x[0]), int(x[1])), edges)))
self.assertEqual(0, len(compare_edge_sets(edge_set, j_edges)))
def single_otu_result():
if request.method == 'POST':
if request.form['name']:
try:
genome = session.query(Genome).filter_by(
name=request.form['name']).one()
except NoResultFound:
flash("OTU ID %s not in database." % request.form['name'])
return redirect(url_for('welcome_page'))
metab_net_json = json.loads(genome.metab_net)
metab_net = cy.to_networkx(metab_net_json)
metab_net, ss = mna.determine_seed_set(metab_net)
seeds = [j for i in list(ss.values()) for j in i]
return render_template('singleOTUResult.html',
genome=genome,
taxa_str=pretty_taxa(genome.taxonomy),
seeds=sorted(seeds),
eles=json.dumps(metab_net_json['elements']))
else:
flash("No OTU ID entered for single analysis.")
return redirect(url_for('welcome_page'))
else:
flash("How did you get here to single?")
return redirect(url_for('welcome_page'))
def calculate(self, graph, params):
nx_graph = util.to_networkx(graph)
return nx.betweenness_centrality(nx_graph)
def cyjs_to_networkx(cyjs):
return util.to_networkx(cyjs)
def calculate(self, graph, params):
nx_graph = util.to_networkx(graph)
return nx.clustering(nx_graph)
def calculate(self, graph, params):
nx_graph = util.to_networkx(graph)
return nx.pagerank_scipy(nx_graph)
def calculate(self, graph, params):
nx_graph = util.to_networkx(graph)
return nx.betweenness_centrality(nx_graph)
def cyjs_to_networkx(cyjs):
return util.to_networkx(cyjs)
def calculate(self, graph, params):
nx_graph = util.to_networkx(graph)
return nx.clustering(nx_graph)
def calculate(self, graph, params):
nx_graph = util.to_networkx(graph)
return nx.pagerank_scipy(nx_graph)
def calculate(self, graph, params):
nx_graph = util.to_networkx(graph)
return util.from_networkx(nx_graph)
def pair_otu_result():
if request.method == 'POST':
if request.form['name1'] and request.form['name2']:
# get genomes from database
exception = False
genome1 = None
try:
genome1 = session.query(Genome).filter_by(
name=request.form['name1']).one()
except NoResultFound:
flash("OTU %s not found in the database." %
request.form['name1'])
exception = True
genome2 = None
try:
genome2 = session.query(Genome).filter_by(
name=request.form['name2']).one()
except NoResultFound:
flash("OTU %s not found in the database." %
request.form['name2'])
exception = True
if exception:
return redirect(url_for('welcome_page'))
# get tree data
tip2tip = get_tip2tip(genome1.name, genome2.name)
# get data and determine seeds
metab_net1_json = json.loads(genome1.metab_net)
metab_net1 = cy.to_networkx(metab_net1_json)
metab_net2_json = json.loads(genome2.metab_net)
metab_net2 = cy.to_networkx(metab_net2_json)
metab_net1, ss1 = mna.determine_seed_set(metab_net1)
metab_net2, ss2 = mna.determine_seed_set(metab_net2)
seeds1 = set([j for i in list(ss1.values()) for j in i])
seeds2 = set([j for i in list(ss2.values()) for j in i])
# analyze seeds and determine metabolic characteristics
seeds1_only = seeds1 - seeds2
if seeds1_only == set():
seeds1_only = [None]
seeds2_only = seeds2 - seeds1
if seeds2_only == set():
seeds2_only = [None]
shared_seeds = seeds1 & seeds2
otu1_seeds_otu2_complement = seeds1_only & set(metab_net2.nodes())
otu2_seeds_otu1_complement = seeds2_only & set(metab_net1.nodes())
net1net2_bss, net2net1_bss = mna.calculate_bss(
metab_net1, ss1, metab_net2, ss2)
net1net2_mci, net2net1_mci = mna.calculate_mci(
metab_net1, ss1, metab_net2, ss2)
# render page
return render_template(
'pairOTUResult.html',
genome1=genome1,
taxa_str1=pretty_taxa(genome1.taxonomy),
seeds1=sorted(seeds1_only),
eles1=json.dumps(metab_net1_json['elements']),
genome2=genome2,
taxa_str2=pretty_taxa(genome2.taxonomy),
seeds2=sorted(seeds2_only),
eles2=json.dumps(metab_net2_json['elements']),
tip2tip=round(tip2tip, 2),
shared_seeds=sorted(shared_seeds),
net1net2_bss=round(net1net2_bss, 2),
net2net1_bss=round(net2net1_bss, 2),
net1net2_mci=round(net1net2_mci, 2),
net2net1_mci=round(net2net1_mci, 2),
otu1_seeds_otu2_complement=otu1_seeds_otu2_complement,
otu2_seeds_otu1_complement=otu2_seeds_otu1_complement)
else:
flash("Need to enter two OTU ID's to compare OTUs")
return redirect(url_for('welcome_page'))
else:
flash("How did you get to pairs then?")
return redirect(url_for('welcome_page'))
