def extract(output_path, input_path, data_name):
df = {"id": ["1701"], "lon": [115.8136], "lat": [40.55861], "data0": [0]}
df = pd.DataFrame(df)
sta = nvb.sta_data(df)
time0 = datetime.datetime(2020, 1, 7, 8, 0)
end_time = datetime.datetime.now()
sta_speed_all = nvb.read_stadata_from_csv(output_path)
while time0 < end_time:
sta_t = nvb.in_time_list(sta_speed_all, [time0])
if len(sta_t.index) == 0:
for dh in range(0, 241, 3):
sta_dt = nvb.in_dtime_list(sta_t, [dh])
if len(sta_dt.index) == 0:
path_speed = nvb.get_path(input_path, time0, dh)
if os.path.exists(path_speed):
grd_speed = nvb.read_griddata_from_nc(path_speed)
print(path_speed)
if grd_speed is not None:
sta1 = nvb.interp_gs_linear(grd_speed, sta)
nvb.set_stadata_coords(sta1,
level=0,
time=time0,
dtime=dh)
sta_speed_all = nvb.combine_join(
sta_speed_all, sta1)
#print(sta_speed_all)
time0 = time0 + datetime.timedelta(hours=12)
nvb.set_stadata_names(sta_speed_all, [data_name])
sta_speed_all.to_csv(output_path)
def extract_ob(output_path, input_dir, station, data_name):
ids = station["id"].values.tolist()
now = datetime.datetime.now()
end_time = datetime.datetime(now.year, now.month, now.day, now.hour, 0)
time0 = end_time - datetime.timedelta(hours=240)
sta_speed_all = nvb.read_stadata_from_csv(output_path)
while time0 < end_time:
sta_t = nvb.in_time_list(sta_speed_all, [time0])
if len(sta_t.index) == 0:
path_in = nvb.get_path(input_dir, time0)
if os.path.exists(path_in):
sta = nvb.read_stadata_from_micaps3(path_in)
print(path_in)
if sta is not None:
#print(sta)
sta1 = nvb.put_stadata_on_station(sta, station)
print(sta1)
#sta1 = nvb.in_id_list(sta,ids)
nvb.set_stadata_coords(sta1, level=0, time=time0)
sta_speed_all = nvb.combine_join(sta_speed_all, sta1)
# print(sta_speed_all)
time0 = time0 + datetime.timedelta(hours=1)
nvb.set_stadata_names(sta_speed_all, [data_name])
sta_speed_all.to_csv(output_path)
def extract_fo(output_path, input_dir, station, data_name):
sta = copy.deepcopy(station)
now = datetime.datetime.now()
end_time = datetime.datetime(now.year, now.month, now.day, 20, 0)
time0 = end_time - datetime.timedelta(hours=240)
if os.path.exists(output_path):
sta_speed_all = nvb.read_stadata_from_csv(output_path)
else:
sta_speed_all = None
while time0 < end_time:
if sta_speed_all is not None:
sta_t = nvb.in_time_list(sta_speed_all, [time0])
else:
sta_t = None
if sta_t is None or len(sta_t.index) == 0:
for dh in range(0, 241, 3):
if sta_t is not None:
sta_dt = nvb.in_dtime_list(sta_t, [dh])
else:
sta_dt = None
if sta_dt is None or len(sta_dt.index) == 0:
path_speed = nvb.get_path(input_dir, time0, dh)
print(path_speed)
if os.path.exists(path_speed):
grd_speed = nvb.read_griddata_from_nc(path_speed)
print(path_speed)
if grd_speed is not None:
#print(grd_speed)
sta1 = nvb.interp_gs_linear(grd_speed, sta)
nvb.set_stadata_coords(sta1,
level=0,
time=time0,
dtime=dh)
sta_speed_all = nvb.combine_join(
sta_speed_all, sta1)
#print(sta_speed_all)
time0 = time0 + datetime.timedelta(hours=12)
nvb.set_stadata_names(sta_speed_all, [data_name])
sta_speed_all.to_csv(output_path)
def merge1():
time0 = datetime.datetime(2020, 1, 7, 0, 0)
dir = r"H:\task\other\201911-预报司-冬奥会检验\冬奥观测数据\延庆赛区\10分钟数据集\A1701\YYYYMM\YYYYMMDD.csv"
end_time = datetime.datetime.now()
sta_ob_all = None
while time0 < end_time:
filename = nvb.get_path(dir, time0, 0)
if os.path.exists(filename):
file = open(filename, 'r')
sta = pd.read_csv(file, parse_dates=['观测时间'])
sta = sta[["观测时间", "2分钟平均风速"]]
sta.columns = ["time", "ob"]
sta["id"] = 1701
sta = nvb.sta_data(sta)
nvb.set_stadata_coords(sta,
level=0,
dtime=0,
lon=115.8136,
lat=40.55861)
sta_ob_all = nvb.combine_join(sta_ob_all, sta)
#print(sta_ob_all)
time0 = time0 + datetime.timedelta(hours=24)
sta_ob_all.to_csv(r"H:\task\other\201911-预报司-冬奥会检验\冬奥观测数据\ob\speed_ob.txt")
def ob_multi_time_fo(para):
begin = time.time()
now = datetime.datetime.now()
now = datetime.datetime(now.year, now.month, now.day, now.hour, 0)
station = nvb.read_stadata_from_micaps3(para["station_file"])
id_list = station["id"].values.tolist()
ip, port = nvb.read_gds_ip_port(r"H:\test_data\input\nvb\ip_port.txt")
if para["value_type"] == "wind":
sta_ob_s_all = None
sta_ob_d_all = None
for i in range(para["max_dh"] + 12):
time0 = now - datetime.timedelta(hours=i)
path = nvb.get_path(para["ob_dir"], time0)
sta_s = nvb.read_stadata_from_gds(
ip,
port,
filename=path,
element_id=nvb.gds_element_id.平均风速_2分钟)
if sta_s is None: continue
sta_ob_s_all = nvb.combine_join(sta_ob_s_all, sta_s)
sta_d = nvb.read_stadata_from_gds(
ip,
port,
filename=path,
element_id=nvb.gds_element_id.平均风向_2分钟)
if sta_d is None: continue
sta_ob_d_all = nvb.combine_join(sta_ob_s_all, sta_d)
sta_ob_all = nvb.diag.speed_angle_to_wind(sta_ob_s_all, sta_ob_d_all)
dir_u, file_u = os.path.split(para["fo_grd_dir_u"])
file_list_u = nvb.path_tools.get_gds_file_list_in_one_dir(
ip, port, dir_u)
dir_v, file_v = os.path.split(para["fo_grd_dir_v"])
file_list_v = nvb.path_tools.get_gds_file_list_in_one_dir(
ip, port, dir_v)
# 读取预报数据
sta_fo_all = None
for i in range(para["max_dh"] + 12):
time0 = now - datetime.timedelta(hours=i)
for dh in range(para["max_dh"]):
filename = nvb.get_path(file_u, time0, dh)
if not filename in file_list_u: continue
# grd = nvb.read_griddata_from_gds(ip,port,dir_u + "/"+filename)
# if(grd is None):continue
# sta_u = nvb.interp_gs_linear(grd,station)
sta_u = nvb.read_stadata_from_gds_griddata(
ip, port, dir_u + "/" + filename, station)
if (sta_u is None): continue
nvb.set_stadata_coords(sta_u, time=time0, dtime=dh)
path = nvb.get_path(file_v, time0, dh)
if not filename in file_list_v: continue
# grd = nvb.read_griddata_from_gds(ip,port,dir_v + "/" + filename)
# if (grd is None): continue
# sta_v = nvb.interp_gs_linear(grd,station)
sta_v = nvb.read_stadata_from_gds_griddata(
ip, port, dir_v + "/" + filename, station)
if sta_v is None: continue
nvb.set_stadata_coords(sta_v, time=time0, dtime=dh)
sta_uv = nvb.combine_on_all_coords(sta_u, sta_v)
nvb.set_stadata_names(
sta_uv,
data_name_list=["u" + para["title"], "v" + para["title"]])
sta_fo_all = nvb.combine_join(sta_fo_all, sta_uv)
for id in id_list:
output_path = para["output_dir"]
if (output_path is not None):
output_path = nvb.get_path(output_path, now)
output_path = output_path + "/" + str(id) + ".png"
sta_ob = nvb.in_id_list(sta_ob_all, [id])
sta_fo = nvb.in_id_list(sta_fo_all, [id])
nvp.continuous.wind_ob_and_multi_time_fo(sta_ob,
sta_fo,
pic_path=output_path,
max_dh=para["max_dh"],
plot_error=True)
else:
sta_ob_all = None
sta_ob_all = None
for i in range(para["max_dh"] + 12):
time0 = now - datetime.timedelta(hours=i)
path = nvb.get_path(para["ob_dir"], time0)
sta_s = nvb.read_stadata_from_gds(
ip,
port,
filename=path,
element_id=nvb.gds_element_id_dict[para["value_type"]])
if sta_s is None: continue
sta_ob_all = nvb.combine_join(sta_ob_all, sta_s)
dir_u, file_u = os.path.split(para["fo_grd_dir_u"])
file_list_u = nvb.path_tools.get_gds_file_list_in_one_dir(
ip, port, dir_u)
# 读取预报数据
sta_fo_all = None
for i in range(para["max_dh"] + 12):
time0 = now - datetime.timedelta(hours=i)
for dh in range(para["max_dh"]):
filename = nvb.get_path(file_u, time0, dh)
if not filename in file_list_u: continue
sta_u = nvb.read_stadata_from_gds_griddata(
ip, port, dir_u + "/" + filename, station)
if (sta_u is None): continue
nvb.set_stadata_names(sta_u, data_name_list=[para["title"]])
sta_fo_all = nvb.combine_join(sta_fo_all, sta_u)
for id in id_list:
output_path = para["output_dir"]
if (output_path is not None):
output_path = nvb.get_path(output_path, now)
output_path = output_path + "/" + str(id) + ".png"
sta_ob = nvb.in_id_list(sta_ob_all, [id])
sta_fo = nvb.in_id_list(sta_fo_all, [id])
if para["value_type"] == "温度":
nvp.continuous.temp_ob_and_multi_time_fo(sta_ob,
sta_fo,
pic_path=output_path,
max_dh=para["max_dh"],
plot_error=True)
elif para["value_type"] == "降水1h":
pass