def process_fcn(g):
print "now processing"
input_stats = geo_stats(g)
geo_check_for_isolated(g)
geo_filter_nones(g)
geo_check_for_isolated(g)
filtered_stats = geo_stats(g)
node_map = geo_cluster(g, cities=[], restrict=False)
#r = nx.DiGraph()
g = geo_reduce(g, node_map)
node_map = geo_cluster(g, cities=city_list, restrict=False)
first_pass_stats = geo_stats(g)
if self.options.filter_cities:
g = geo_reduce(g, node_map)
output_stats = geo_stats(g)
elif self.options.geo_filter:
print "Geo filtering..."
g = geo_box_reduce(g, GEO_FILTERS[self.options.geo_filter])
output_stats = geo_stats(g)
print "input stats: \n" + input_stats
print "filtered stats: \n" + filtered_stats
print "first pass (no city filtering): \n" + first_pass_stats
if self.options.filter_cities or self.options.geo_filter:
print "output stats (after city filter): \n" + output_stats
return g
def __init__(self, post_fcn = None):
self.parse_args()
options = self.options
input = options.input
# Input graph
input_path = os.path.join(input, input + '.gpk')
self.g = nx.read_gpickle(input_path)
if not self.g:
raise Exception("null input file for input path %s" % input_path)
# Output (reduced) graph.
# Nodes: (lat, long) tuples w/ list of associated users & location strings
# Edges: weight: number of links in this direction
self.r = nx.DiGraph()
conn = Connection()
self.input_db = conn[self.options.input_db]
self.input_coll = self.input_db[self.options.input_coll]
print "now processing"
self.reduce()
print geo_stats(self.r)
if options.write:
geo_path = os.path.join(input, input + '.grg')
nx.write_gpickle(self.r, geo_path)
def process_fcn(g):
print "now processing"
input_stats = geo_stats(g)
geo_check_for_isolated(g)
geo_filter_nones(g)
geo_check_for_isolated(g)
filtered_stats = geo_stats(g)
node_map = geo_cluster(g, cities = [], restrict = False)
#r = nx.DiGraph()
g = geo_reduce(g, node_map)
node_map = geo_cluster(g, cities = city_list, restrict = False)
first_pass_stats = geo_stats(g)
if self.options.filter_cities:
g = geo_reduce(g, node_map)
output_stats = geo_stats(g)
elif self.options.geo_filter:
print "Geo filtering..."
g = geo_box_reduce(g, GEO_FILTERS[self.options.geo_filter])
output_stats = geo_stats(g)
print "input stats: \n" + input_stats
print "filtered stats: \n" + filtered_stats
print "first pass (no city filtering): \n"+ first_pass_stats
if self.options.filter_cities or self.options.geo_filter:
print "output stats (after city filter): \n" + output_stats
return g
def __init__(self, post_fcn=None):
self.parse_args()
options = self.options
input = options.input
# Input graph
input_path = os.path.join(input, input + '.gpk')
self.g = nx.read_gpickle(input_path)
if not self.g:
raise Exception("null input file for input path %s" % input_path)
# Output (reduced) graph.
# Nodes: (lat, long) tuples w/ list of associated users & location strings
# Edges: weight: number of links in this direction
self.r = nx.DiGraph()
conn = Connection()
self.input_db = conn[self.options.input_db]
self.input_coll = self.input_db[self.options.input_coll]
print "now processing"
self.reduce()
print geo_stats(self.r)
if options.write:
geo_path = os.path.join(input, input + '.grg')
nx.write_gpickle(self.r, geo_path)
