def test_quadtreeOpt(data, queryShape, all_queries):
global method_list, exp_name
exp_name = 'quadtreeOpt'
method_list = ['quad-geo']
# method_list = ['quad-baseline', 'quad-geo', 'quad-baseline-localness', 'quad-geo-localness']
res_cube_abs = np.zeros((len(eps_list), len(seed_list), len(method_list)))
res_cube_rel = np.zeros((len(eps_list), len(seed_list), len(method_list)))
for j in range(len(seed_list)):
queryList = all_queries[j]
kexp = GKExp(data, queryList)
p = Params(seed_list[j])
for i in range(len(eps_list)):
p.Eps = eps_list[i]
for k in range(len(method_list)):
if method_list[k] == 'quad-baseline':
res_cube_abs[i, j, k], res_cube_rel[i, j, k] = kexp.run_Quad_baseline(p)
elif method_list[k] == 'quad-baseline-localness':
res_cube_abs[i, j, k], res_cube_rel[i, j, k] = kexp.run_Quad_baseline_localness(p)
elif method_list[k] == 'quad-geo':
res_cube_abs[i, j, k], res_cube_rel[i, j, k] = kexp.run_Quad_geo(p)
elif method_list[k] == 'quad-geo-localness':
res_cube_abs[i, j, k], res_cube_rel[i, j, k] = kexp.run_Quad_geo_localness(p)
else:
logging.error('No such index structure!')
sys.exit(1)
res_abs_summary = np.average(res_cube_abs, axis=1)
res_rel_summary = np.average(res_cube_rel, axis=1)
#np.savetxt(Params.resdir+exp_name+'_abs_'+`int(queryShape[0]*10)`+'_'+`int(queryShape[1]*10)`, res_abs_summary, fmt='%.4f\t')
np.savetxt(Params.resdir + exp_name + '_rel_' + `int(queryShape[0] * 10)` + '_' + `int(queryShape[1] * 10)`,
res_rel_summary, fmt='%.4f\t')
