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 __init__(self, data, param): Kd_standard.__init__(self, data, param)