print 'new connectance = ', net.connectance()
else:
net = obtain_interactions_network()
net_to_save = net.copy()
nx.write_graphml(net_to_save, network_file)
ecosystem = Ecosystem(net, drawing=False)
ecosystem.initialise_world(True)
#ecosystem.draw_species_distribution()
out_row = get_out_row(0, net, '', 0, '', '')
out.writerow(out_row)
# iteration_to_reset = (int) (math.ceil(ITERATIONS*NETWORK_RESET))
out_row_eco = get_eco_state_row(0, ecosystem)
out_eco.writerow(out_row_eco)
# print ecosystem.get_groups_counts()
# plot_series = []
# plot_prods = []
# plot_mut_prods = []
# plot_herbs = []
# plot_muts = []
# plot_prim = []
# plot_sec = []
#
# plot_prods_rep = []
# plot_mut_prods_rep = []
# plot_herbs_rep = []
# plot_muts_rep = []
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)
##############################################
ecosystem = Ecosystem(net, drawing=False)
ecosystem.initialise_world(True)
# here it works out the inital populations
series_counts = dict()
dict_stats = get_eco_state_row(0, ecosystem)
series_counts[0] = ecosystem.populations
# we don't this to store data, just for its keys
cumulative_sps_stats = dict.fromkeys(net.nodes(), None)
##############################################
for i in range(1, ITERATIONS+1):
print i
ecosystem.update_world()
dict_stats = get_eco_state_row(ITERATIONS, ecosystem)
series_counts[i] = ecosystem.populations
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)
##################################################################################################################
ecosystem = Ecosystem(net, drawing=False)
ecosystem.initialise_world(True)
out_row = get_out_row(0, net, '', 0, '', '')
out.writerow(out_row)
out_row_eco = get_eco_state_row(0, ecosystem)
out_eco.writerow(out_row_eco)
series_counts = dict()
if SPATIAL_VARIATION:
centroids_counts = dict()
areas_counts = dict()
##this structure holds the numbers of immigration, birth and dead of individuals
##for each species during the last ITERATIONS_TO_RECORD iterations
cumulative_sps_stats = dict.fromkeys(net.nodes(), None)
stats = ['immigrants', 'born', 'dead', 'tps']
for sp in cumulative_sps_stats.keys():
cumulative_sps_stats[sp] = dict.fromkeys(stats, 0)
threshold_iter = math.ceil(ITERATIONS - (ITERATIONS*ITERATIONS_TO_RECORD))