import random as rd
import pylab as pl
import mpl_toolkits.basemap as bm
from numpy import sqrt
#import community as cm
#New Modules
sys.path.append('/Users/Eyota/projects/thesis/code/python/modules')
from rowtodict import *
from drawnetworks import netplot
from importnetworks import importnetwork
import com2 as cm
os.chdir("/Users/Eyota/projects/thesis")
year = '0910'
width = 4700000
height = 3100000
metros, mg, nodedata = importnetwork(year)
#formal communities based on redoing com detection on 100-runs
comsform = pd.io.parsers.read_csv('output/comsformal.csv')
comsform.set_index('id',inplace = True)
comsform = comsform[['pop','lat','lon','MSAName','formalcom']]
comsformdict = comsform['formalcom'].to_dict()
print cm.modularity(comsformdict, mg)
nx.draw(mgdraw, pos,with_labels = False,alpha = 1, linewidths = 0.5, width = 0,
nodelist = list(comsdraw.sort(['pop']).index),node_size = 40, node_color = comsdraw.sort(['pop'])['com'])
'''
comnet = nx.Graph()
comnet.add_nodes_from(nodedata)
comsdraw = coms[(metros['lon'] < -60) & (metros['lon'] >-125)]
comlist = []
modularities = []
for i in range(100):
partition = cm.best_partition(mg)
modularities.append(cm.modularity(partition, mg))
#I think it's ok to use the full network including AKHI
comsdraw = dict2column(comsdraw, partition,'com%s'%i)
#'part%s' %i)
netplot('output/commaps/maps_com_%s_%s.jpeg'%(i,year),width, height, mgdraw,pos,with_labels = False,alpha = 1, linewidths = 0.5, width = 0,
nodelist = list(comsdraw.sort(['pop']).index),
node_size = sqrt(comsdraw.sort(['pop'])['pop']),
node_color = comsdraw.sort(['pop'])['com%s'%i])
for n in mg.nodes():
for m in mg.nodes(): #[find(mg.nodes() == n):len(mg.nodes())]:
if m == n:
continue
else:
if partition[m] == partition[n]:
#comnet.add_edge(m,n)