先输入，后 np.column_stack的一个奇怪错误
作者：互联网
我前面尝试使用以下代码创建路网上的乘客，但是在使用时候发现，部分乘客不在对应的线上（‘O_wgs_lng’, ‘O_wgs_lat’ 不在线段’起点路段节点1编号’, ‘起点路段节点2编号’），尝试多次未找到原因
def generate_customer_data(**kwargs):
p_num = kwargs['p_num']
run_times = kwargs['run_times']
columns_cus_name = np.zeros(shape=(p_num, 1), dtype=object)
columns_O_wgs_lng = np.zeros(shape=(p_num, 1), dtype=np.float32)
columns_O_wgs_lat = np.zeros(shape=(p_num, 1), dtype=np.float32)
columns_O_point_name1 = np.zeros(shape=(p_num, 1), dtype=object)
columns_O_point_name2 = np.zeros(shape=(p_num, 1), dtype=object)
columns_D_wgs_lng = np.zeros(shape=(p_num, 1), dtype=np.float32)
columns_D_wgs_lat = np.zeros(shape=(p_num, 1), dtype=np.float32)
columns_D_point_name1 = np.zeros(shape=(p_num, 1), dtype=object)
columns_D_point_name2 = np.zeros(shape=(p_num, 1), dtype=object)
columns_appear_time = np.zeros(shape=(p_num, 1), dtype=int)
columns_state = np.zeros(shape=(p_num, 1), dtype=object)
columns_car_name = np.zeros(shape=(p_num, 1), dtype=object)
columns_get_car_time = np.zeros(shape=(p_num, 1), dtype=int)
columns_on_car_time = np.zeros(shape=(p_num, 1), dtype=int)
columns_off_car_time = np.zeros(shape=(p_num, 1), dtype=int)
adjacent_data = pd.read_csv(r'..\Map\adjacent_inf.csv')
for i in range(p_num):
order_time = random.randint(1, run_times + 1)
road_row_1 = random.randint(0, len(adjacent_data) - 1)
O_point_name1 = adjacent_data.loc[road_row_1, 'fir_point_name']
O_point_name2 = adjacent_data.loc[road_row_1, 'lst_point_name']
A1 = [adjacent_data.loc[road_row_1, 'start_x'], adjacent_data.loc[road_row_1, 'start_y']]
B1 = [adjacent_data.loc[road_row_1, 'end_x'], adjacent_data.loc[road_row_1, 'end_y']]
P1 = sub_way.Get_Mid_Point(fir_point=A1, lst_point=B1)
road_row_2 = random.randint(0, len(adjacent_data) - 1)
D_point_name1 = adjacent_data.loc[road_row_2, 'fir_point_name']
D_point_name2 = adjacent_data.loc[road_row_2, 'lst_point_name']
A2 = [adjacent_data.loc[road_row_2, 'start_x'], adjacent_data.loc[road_row_2, 'start_y']]
B2 = [adjacent_data.loc[road_row_2, 'end_x'], adjacent_data.loc[road_row_2, 'end_y']]
P2 = sub_way.Get_Mid_Point(fir_point=A2, lst_point=B2)
columns_cus_name[i, 0] = 'cus_' + str(i + 1)
columns_O_wgs_lng[i, 0] = P1[0]
columns_O_wgs_lat[i, 0] = P1[1]
columns_O_point_name1[i, 0] = O_point_name1
columns_O_point_name2[i, 0] = O_point_name2
columns_D_wgs_lng[i, 0] = P2[0]
columns_D_wgs_lat[i, 0] = P2[1]
columns_D_point_name1[i, 0] = D_point_name1
columns_D_point_name2[i, 0] = D_point_name2
columns_appear_time[i, 0] = order_time
columns_state[i, 0] = '未出现'
customer_data = np.column_stack((
columns_cus_name,
columns_O_wgs_lng, columns_O_wgs_lat, columns_O_point_name1, columns_O_point_name2,
columns_D_wgs_lng, columns_D_wgs_lat, columns_D_point_name1, columns_D_point_name2,
columns_appear_time, columns_state, columns_car_name,
columns_get_car_time, columns_on_car_time, columns_off_car_time
))
# np.save(r'..\Data\config\customer_data.npy', customer_data)
fi_customer_data = pd.DataFrame(customer_data)
fi_customer_data.columns = [
'乘客编号',
'O_wgs_lng', 'O_wgs_lat', '起点路段节点1编号', '起点路段节点2编号',
'D_wgs_lng', 'D_wgs_lat', '终点路段节点1编号', '终点路段节点2编号',
'出现时间', '状态', '搭乘车的车牌号',
'打车时间', '搭车时间', '下车时间'
]
fi_customer_data.to_csv(r'..\Data\config\customer_data.csv', index=False, encoding='utf_8_sig')
而后我尝试先拼接，再输入数据，错误就解决了
def generate_customer_data(**kwargs):
f = open(r'..\Data\config\Graph_layer.pkl', 'rb')
G = pickle.load(f)
p_num = kwargs['p_num']
run_times = kwargs['run_times']
columns_cus_name = np.zeros(shape=(p_num, 1), dtype=object)
columns_O_wgs_lng = np.zeros(shape=(p_num, 1), dtype=np.float32)
columns_O_wgs_lat = np.zeros(shape=(p_num, 1), dtype=np.float32)
columns_O_point_name1 = np.zeros(shape=(p_num, 1), dtype=object)
columns_O_point_name2 = np.zeros(shape=(p_num, 1), dtype=object)
columns_D_wgs_lng = np.zeros(shape=(p_num, 1), dtype=np.float32)
columns_D_wgs_lat = np.zeros(shape=(p_num, 1), dtype=np.float32)
columns_D_point_name1 = np.zeros(shape=(p_num, 1), dtype=object)
columns_D_point_name2 = np.zeros(shape=(p_num, 1), dtype=object)
columns_appear_time = np.zeros(shape=(p_num, 1), dtype=int)
columns_state = np.zeros(shape=(p_num, 1), dtype=object)
columns_car_name = np.zeros(shape=(p_num, 1), dtype=object)
columns_get_car_time = np.zeros(shape=(p_num, 1), dtype=int)
columns_on_car_time = np.zeros(shape=(p_num, 1), dtype=int)
columns_off_car_time = np.zeros(shape=(p_num, 1), dtype=int)
adjacent_data = pd.read_csv(r'..\Map\adjacent_inf.csv')
customer_data = np.column_stack((
columns_cus_name,
columns_O_wgs_lng, columns_O_wgs_lat, columns_O_point_name1, columns_O_point_name2,
columns_D_wgs_lng, columns_D_wgs_lat, columns_D_point_name1, columns_D_point_name2,
columns_appear_time, columns_state, columns_car_name,
columns_get_car_time, columns_on_car_time, columns_off_car_time
))
# np.save(r'..\Data\config\customer_data.npy', customer_data)
fi_customer_data = pd.DataFrame(customer_data)
fi_customer_data.columns = [
'乘客编号',
'O_wgs_lng', 'O_wgs_lat', '起点路段节点1编号', '起点路段节点2编号',
'D_wgs_lng', 'D_wgs_lat', '终点路段节点1编号', '终点路段节点2编号',
'出现时间', '状态', '搭乘车的车牌号',
'打车时间', '搭车时间', '下车时间'
]
for customer_index in fi_customer_data.index:
order_time = random.randint(1, run_times + 1)
road_row_1 = random.randint(0, len(adjacent_data) - 1)
O_point_name1 = adjacent_data.loc[road_row_1, 'fir_point_name']
O_point_name2 = adjacent_data.loc[road_row_1, 'lst_point_name']
A1 = [adjacent_data.loc[road_row_1, 'start_x'], adjacent_data.loc[road_row_1, 'start_y']]
B1 = [adjacent_data.loc[road_row_1, 'end_x'], adjacent_data.loc[road_row_1, 'end_y']]
P1 = sub_way.Get_Mid_Point(fir_point=A1, lst_point=B1)
sub_way.Get_Pro(fir_point=A1, lst_point=B1, mid_point=P1, accuracy=7)
road_row_2 = random.randint(0, len(adjacent_data) - 1)
D_point_name1 = adjacent_data.loc[road_row_2, 'fir_point_name']
D_point_name2 = adjacent_data.loc[road_row_2, 'lst_point_name']
A2 = [adjacent_data.loc[road_row_2, 'start_x'], adjacent_data.loc[road_row_2, 'start_y']]
B2 = [adjacent_data.loc[road_row_2, 'end_x'], adjacent_data.loc[road_row_2, 'end_y']]
P2 = sub_way.Get_Mid_Point(fir_point=A2, lst_point=B2)
sub_way.Get_Pro(fir_point=A2, lst_point=B2, mid_point=P2, accuracy=7)
fi_customer_data.loc[customer_index, '乘客编号'] = 'cus_' + str(int(customer_index) + 1)
fi_customer_data.loc[customer_index, ['O_wgs_lng', 'O_wgs_lat', '起点路段节点1编号', '起点路段节点2编号']] = \
P1[0], P1[1], O_point_name1, O_point_name2
fi_customer_data.loc[customer_index, ['D_wgs_lng', 'D_wgs_lat', '终点路段节点1编号', '终点路段节点2编号']] = \
P2[0], P2[1], D_point_name1, D_point_name2
fi_customer_data.loc[customer_index, ['出现时间', '状态']] = order_time, '未出现'
# columns_cus_name[i, 0] = 'cus_' + str(i + 1)
# columns_O_wgs_lng[i, 0] = P1[0]
# columns_O_wgs_lat[i, 0] = P1[1]
# columns_O_point_name1[i, 0] = O_point_name1
# columns_O_point_name2[i, 0] = O_point_name2
# columns_D_wgs_lng[i, 0] = P2[0]
# columns_D_wgs_lat[i, 0] = P2[1]
# columns_D_point_name1[i, 0] = D_point_name1
# columns_D_point_name2[i, 0] = D_point_name2
# columns_appear_time[i, 0] = order_time
# columns_state[i, 0] = '未出现'
fi_customer_data.to_csv(r'..\Data\config\customer_data.csv', index=False, encoding='utf_8_sig')
我只能说，阿巴巴
标签：point,column,num,wgs,np,data,stack,columns 来源： https://blog.csdn.net/needtry/article/details/121186115