###this is for python < 2.7
# headers_dict = dict()
# for n in header_names:
# headers_dict[n] = n
#
# out_eco.writerow(headers_dict)
### for python >= 2.7 comment the above block and uncomment the following line
out_eco.writeheader()
network_file = output_dir + '/' + SRC_NET_FILE
if READ_FILE_NETWORK:
graph = nx.read_graphml(network_file)
net = Network(graph)
print 'connectance = ', net.connectance()
tls = net.get_trophic_levels()
top, top_preds = net.top_predators()
basal, basal_sps = net.basal()
for u, v in net.edges():
if u in basal_sps and v in top_preds and tls[v] == 3:
net.remove_edge(u, v)
print 'new connectance = ', net.connectance()
else:
net = obtain_interactions_network()
net_to_save = net.copy()
nx.write_graphml(net_to_save, network_file)
# we now make sure that links between TL 0 and 3 are removed for any network, both those read from file and those created on the fly.
network_file = output_dir+'/'+SRC_NET_FILE ## use this when generating niche modle networks and want to save in output directory
#network_file = SRC_NET_FILE ## use this when running with networks saved locally in src
#network_file = output_dir + '/new_network_%d.graphml' %(int(task)-1)
if READ_FILE_NETWORK:
graph = nx.read_graphml(network_file)
net = Network(graph)
else:
net = obtain_interactions_network()
print 'connectance = ', net.connectance()
tls = net.get_trophic_levels()
top, top_preds = net.top_predators()
basal, basal_sps = net.basal()
for u,v in net.edges():
if u in basal_sps and v in top_preds and tls[v] == 3:
net.remove_edge(u,v)
print 'new connectance = ', net.connectance()
if not READ_FILE_NETWORK:
net_to_save = net.copy()
nx.write_graphml(net_to_save, network_file)
if not os.path.exists(output_dir):
os.makedirs(output_dir)
if os.path.isfile("./output/" + SRC_NET_FILE):
shutil.copy("./output/" + SRC_NET_FILE, output_dir)
##############################################
# network_file = output_dir+'/'+SRC_NET_FILE
network_file = output_dir + "/new_network_%d.graphml" % (int(task) - 1)
# if True:
if READ_FILE_NETWORK:
graph = nx.read_graphml(network_file)
net = Network(graph)
print "connectance = ", net.connectance()
tls = net.get_trophic_levels()
top, top_preds = net.top_predators()
basal, basal_sps = net.basal()
for u, v in net.edges():
if u in basal_sps and v in top_preds and tls[v] == 3:
net.remove_edge(u, v)
print "new connectance = ", net.connectance()
else:
net = obtain_interactions_network()
net_to_save = net.copy()
nx.write_graphml(net_to_save, network_file)
###this is for python < 2.7
# headers_dict = dict()
# for n in header_names:
# headers_dict[n] = n
#
# out_eco.writerow(headers_dict)
### for python >= 2.7 comment the above block and uncomment the following line
out_eco.writeheader()
network_file = output_dir + '/' + SRC_NET_FILE
if READ_FILE_NETWORK:
graph = nx.read_graphml(network_file)
net = Network(graph)
print('connectance = ', net.connectance())
tls = net.get_trophic_levels()
top, top_preds = net.top_predators()
basal, basal_sps = net.basal()
for u, v in net.edges():
if u in basal_sps and v in top_preds and tls[v] == 3:
net.remove_edge(u, v)
print('new connectance = ', net.connectance())
else:
net = obtain_interactions_network()
net_to_save = net.copy()
#nx.write_graphml(net_to_save, network_file) ## new networkx doesn't like numpy floats
###this is for python < 2.7
# headers_dict = dict()
# for n in header_names:
# headers_dict[n] = n
#
# out_eco.writerow(headers_dict)
### for python >= 2.7 comment the above block and uncomment the following line
out_eco.writeheader()
network_file = output_dir + '/' + SRC_NET_FILE
if READ_FILE_NETWORK:
graph = nx.read_graphml(network_file)
net = Network(graph)
print('connectance = ', net.connectance())
tls = net.get_trophic_levels()
top, top_preds = net.top_predators()
basal, basal_sps = net.basal()
for u, v in net.edges():
if u in basal_sps and v in top_preds and tls[v] == 3:
net.remove_edge(u, v)
print('new connectance = ', net.connectance())
else:
net = obtain_interactions_network()
net_to_save = net.copy()
nx.write_graphml(net_to_save, network_file)
###this is for python < 2.7
# headers_dict = dict()
# for n in header_names:
# headers_dict[n] = n
#
# out_eco.writerow(headers_dict)
### for python >= 2.7 comment the above block and uncomment the following line
out_eco.writeheader()
network_file = output_dir+'/'+SRC_NET_FILE
if READ_FILE_NETWORK:
graph = nx.read_graphml(network_file)
net = Network(graph)
print 'connectance = ', net.connectance()
tls = net.get_trophic_levels()
top, top_preds = net.top_predators()
basal, basal_sps = net.basal()
for u,v in net.edges():
if u in basal_sps and v in top_preds and tls[v] == 3:
net.remove_edge(u,v)
print 'new connectance = ', net.connectance()
else:
net = obtain_interactions_network()
net_to_save = net.copy()
#nx.write_graphml(net_to_save, network_file) ## new networkx doesn't like numpy floats
G = nx.Graph(G)
#find modularity
#net = Network(G)
#tls = net.get_trophic_levels()
#part = community.best_partition(G)
#IG = igr.read_graphml(graphml_file)
IG = igr.load(graphml_file)
IG.to_undirected() # = IG0.to_undirected()
membs = IG.community_multilevel()
mod = IG.modularity(membs)
#mod = modularity(part, G)
print("Modularity:")
print(mod)
print(IG.transitivity_undirected())
print(Net.connectance())
Net.get_trophic_levels()
Net.find_trophic_positions()
#print(Net.omnivory())
print(Net.generality_vulnerability_sd())
print(Net.maximum_similarity())
gsd, vsd = Net.generality_vulnerability_sd()
all_results[0,0] = G.number_of_nodes() #/ 120.0 Now normalising all elements
all_results[0,1] = Net.connectance()
all_results[0,2] = mod
all_results[0,3] = IG.transitivity_undirected()
all_results[0,4] = gsd
all_results[0,5] = vsd
all_results[0,6] = Net.maximum_similarity()
