if __name__ == '__main__':
time_slice = 4
train = 0.5
# beijing = (39.433333, 41.05, 115.416667, 117.5)
# haidian = (39.883333, 40.15, 116.05, 116.383333)
# region = (39.88, 40.03, 116.05, 116.25)
# region = (39.88, 40.05, 116.05, 116.26)
region = (39.88, 40.05, 116.05, 116.26)
cluster_radius = 0.00
filter_count = 30
order = 2
top_k = 1
length, height, top_left = get_length_height(region)
print "区域（长度，宽度）：", length, height
x_values = []
y_values1 = []
y_values2 = []
y_values3 = []
y_values4 = []
y_values5 = []
while cluster_radius <= 4.0:
temp_data, time_slice, train, cluster_radius = init_data(
time_slice, train, region, cluster_radius, filter_count)
axis_pois, axis_users, train_structure_data, poi_adjacent_list, recommends, unknow_poi_set = preprocess(
temp_data, time_slice, train, cluster_radius, order)
print "train_structure_data: ", train_structure_data
# 2.Tersor Factorization（TF）：基于用户-时间-地点的频数张量进行hosvd分解，没有用户的转移信息（地点对地点的评分）
if __name__ == '__main__':
time_slice = 2
train = 0.6
# beijing = (39.433333, 41.05, 115.416667, 117.5)
# haidian = (39.883333, 40.15, 116.05, 116.383333)
# region = (39.88, 40.03, 116.05, 116.25)
# region = (39.88, 40.05, 116.05, 116.26)
region = (39.88, 40.05, 116.05, 116.26)
cluster_radius = 1
filter_count = 30
order = 2
top_k = 1
length, height, top_left = get_length_height(region)
print "区域（长度，宽度）：", length, height
# pmpt
temp_data, time_slice, train, cluster_radius = init_data(time_slice, train, region, cluster_radius, filter_count)
axis_pois, axis_users, train_structure_data, poi_adjacent_list, recommends, unknow_poi_set = preprocess(temp_data, time_slice, train, cluster_radius, order)
tensor = trans(train_structure_data, poi_adjacent_list, order, len(axis_pois), len(axis_users), time_slice)
U, S, D = HOSVD(numpy.array(tensor), 0.7)
A = reconstruct(S, U)
# factorized markov chain
temp_data2, time_slice, train2 = init_data2(region, train, time_slice, filter_count)
axis_pois2, axis_users2, train_structure_data2, recommends2, unknow_poi_set2 = preprocess2(temp_data2, time_slice, train2, order)
A2 = trans2(train_structure_data2, order, len(axis_pois2), time_slice, 0.7)
# tensor factorization
