def run_Kd_standard(self, param):
logging.debug('building Kd_standard...')
tree = Kd_standard(self.data, param)
start = time.clock()
tree.buildIndex()
end = time.clock()
logging.info('[T] Kd-standard building time: %.2f' % (end - start))
return self.query(tree)
def run_Kd_standard(self, param):
logging.debug('building Kd_standard...')
tree = Kd_standard(self.data, param)
start = time.clock()
tree.buildIndex()
# tree.adjustConsistency()
end = time.clock()
logging.info('[T] Kd-standard building time: %.2f' % (end - start))
return self.query(tree)
def eval_partition(data, param):
# tree = Grid_standard(data, param)
# tree = Quad_standard(data, param)
tree = Kd_standard(data, param)
tree.buildIndex()
seed = 1000
fov_count = 200
print optimization(tree, fov_count, seed, param)
def run_Kd_noisymean(self, param):
logging.debug('building Kd_noisymean...')
param.splitScheme = 'noisyMean'
tree = Kd_standard(self.data, param)
start = time.clock()
tree.buildIndex()
tree.adjustConsistency()
end = time.clock()
logging.info('[T] Kd-noisymean building time: %.2f' % (end - start))
return self.query(tree)
def eval_partition(data, param):
# tree = Grid_standard(data, param)
# tree = Quad_standard(data, param)
tree = Kd_standard(data, param)
tree.buildIndex()
seed = 1000
bandwidth = 1000
answer = optimization(tree, bandwidth, seed, param)
print "\n if my knapsack can hold %d bandwidth, i can get %f profit." % (bandwidth,answer[0])
print "\tby taking item(s): ",
for i in range(len(answer[1])):
if (answer[1][i] != 0):
print i+1,
def run_Kd_noisymean(self, param):
logging.debug('building Kd_noisymean...')
param.splitScheme = 'noisyMean'
tree = Kd_standard(self.data, param)
start = time.clock()
tree.buildIndex()
tree.adjustConsistency()
end = time.clock()
logging.info('[T] Kd-noisymean building time: %.2f' % (end - start))
return self.query(tree)
def __init__(self, data, param):
Kd_standard.__init__(self, data, param)
def __init__(self, data, param):
Kd_standard.__init__(self, data, param)