def do_npath(self, line):
''' finds no-weighted path between two artists'''
start_name, end_name = line.split(',')
aid_start = self.asearch(start_name)
aid_end = self.asearch(end_name)
if aid_start and aid_end:
path = db.artist_path(aid_start, aid_end, weighted=False, skipset=self.skipset)
if path:
self.print_path(path)
else:
print "no path between", db.artist_name(aid_start), db.artist_name(aid_end)
def do_expand_neighbors(self, line):
''' expand the neighborhood of an artist '''
fields = line.split(',')
if len(fields) > 0:
aid = self.asearch(fields[0])
if aid:
if len(fields) > 1:
radius = int(fields[1])
else:
radius = 3
queue = []
queue.append( (0, aid) )
which = 0
visited = set()
while len(queue) > 0:
lvl, aid = queue.pop(0)
if aid not in visited and lvl < radius:
visited.add(aid)
which += 1
print which, lvl, aid, db.artist_name(aid)
aids = db.artist_raw_neighbors(aid)
for naid in aids:
queue.append( (lvl+1, naid) )
def do_random_path(self, line):
''' picks two artists at random and finds a path between them'''
count = 1
if len(line) > 0:
count = int(line)
paths = 0
no_path = 0
sum_time = 0
sum_length = 0
max_length = 0
max_time = 0
for i in xrange(count):
aid1 = db.artist_random()
aid2 = db.artist_random()
print "random path between", aid1, db.artist_name(aid1), 'and', aid2, db.artist_name(aid2)
start = time.time()
path = db.artist_path(aid1, aid2, skipset=self.skipset)
delta = time.time() - start
if path:
self.print_path(path, 0)
paths += 1.0
lpath = len(path['links'])
sum_length += lpath
sum_time += delta
if lpath > max_length:
max_length = lpath
if delta > max_time:
max_time = delta
else:
print "no path between", aid1, db.artist_name(aid1), aid2, db.artist_name(aid2)
no_path += 1
print
print 'paths:', paths
print 'no paths:', no_path
if paths > 0:
avg_time = sum_time / paths
avg_length = sum_length / paths
print 'avg length:', avg_length
print 'avg time:', avg_time
print 'max length:', max_length
print 'max time:', max_time
def do_neighbors(self, line):
''' finds the neighbors of an artist'''
aid = self.asearch(line)
if aid:
path = db.artist_neighbors(aid)
if path:
self.print_path(path)
else:
print "no neighbors for", db.artist_name(aid)
def do_skips(self, line):
''' add artists to the skip set, or show the skip set '''
if len(line) > 0:
names = line.split(',')
for name in names:
aid = self.asearch(name)
self.skipset.add(aid)
else:
for aid in self.skipset:
print aid, db.artist_name(aid)
def do_find_popular_crossroads(self, line):
''' creates random paths and find the most common
crossroads
'''
nodes = collections.defaultdict(int)
count = 100
if len(line) > 0:
count = int(line)
paths = 0
no_path = 0
sum_time = 0
sum_length = 0
sum_score = 0
max_length = 0
max_time = 0
max_score = 0
avg_score = 0
for i in xrange(count):
aid1 = db.artist_random()
aid2 = db.artist_random()
start = time.time()
score, aids = db.artist_raw_path(aid1, aid2, skipset=self.skipset)
delta = time.time() - start
if aids:
for aid in aids:
nodes[aid] += 1
paths += 1.0
lpath = len(aids)
sum_score += score
if score > max_score:
max_score = score
sum_length += lpath
sum_time += delta
if lpath > max_length:
max_length = lpath
if delta > max_time:
max_time = delta
else:
print "no path between", aid1, db.artist_name(aid1), aid2, db.artist_name(aid2)
no_path += 1
nlist = [ (v,k) for k,v in nodes.items()]
nlist.sort(reverse=True)
print
for count, aid in nlist[:40]:
print count, aid, db.artist_name(aid)
print
print 'paths:', paths
print 'no paths:', no_path
if paths > 0:
avg_time = sum_time / paths
avg_length = sum_length / paths
avg_score = sum_score / paths
print 'avg length:', avg_length
print 'avg time:', avg_time
print 'avg score:', avg_score
print 'max length:', max_length
print 'max time:', max_time
print 'max score:', max_score
