def cluster_newsitems(qs, radius=26):
"""
A convenience function for clustering a newsitem queryset.
Returns: a mapping of scale -> list of clusters for that scale.
"""
return clustering.cluster_scales(
dict([(ni.id, (ni.location.centroid.x, ni.location.centroid.y))
for ni in qs if ni.location]),
radius)
start = time.time()
ret_val = f(*args, **kwargs)
print >> sys.stderr, "%s took %.4f seconds" % (label, time.time()-start)
return ret_val
def randomize(L):
import copy, random
Lprime = copy.copy(L)
random.shuffle(Lprime)
return Lprime
def main():
buffer = 20
objs = gen_test_objs(rand_seed="foo")
bunches = timeit("cluster", cluster.buffer_cluster, objs, buffer)
display(bunches, buffer=buffer, f=print_bunches)
if __name__ == "__main__":
print "main:"
main()
print "cluster_by_scale:"
for bunch in cluster_by_scale(sample.sample_pts, 51, 19200):
print "%3d objects: center (%.4f, %.4f)" % (len(bunch.objects), bunch.x, bunch.y)
print "cluster_scales:"
clusters_by_scale = cluster_scales(sample.sample_pts, 26)
from django.utils.simplejson import dumps
print dumps(clusters_by_scale, cls=json.ClusterJSON,
sort_keys=True, indent=2)
#import pprint
#pprint.pprint(clusters_by_scale)
def randomize(L):
import copy, random
Lprime = copy.copy(L)
random.shuffle(Lprime)
return Lprime
def main():
buffer = 20
objs = _gen_test_objs(rand_seed="foo")
bunches = timeit("cluster", cluster.buffer_cluster, objs, buffer)
display(bunches, buffer=buffer, f=print_bunches)
if __name__ == "__main__":
print "main:"
main()
print "cluster_by_scale:"
for bunch in cluster_by_scale(sample.sample_pts, 51, 19200):
print "%3d objects: center (%.4f, %.4f)" % (len(
bunch.objects), bunch.x, bunch.y)
print "cluster_scales:"
clusters_by_scale = cluster_scales(sample.sample_pts, 26)
from django.utils.simplejson import dumps
print dumps(clusters_by_scale,
cls=json.ClusterJSON,
sort_keys=True,
indent=2)
#import pprint
#pprint.pprint(clusters_by_scale)
