def sta_value_ensemble_near_by_sta(sta_to,
nearNum=100,
sta_from=None,
drop_frist=False):
if (sta_to is None):
return None
if (sta_from is None):
sta_from = copy.deepcopy(sta_to)
xyz_sta0 = lon_lat_to_cartesian(sta_to['lon'].values[:],
sta_to['lat'].values[:],
R=meteva.base.basicdata.ER)
xyz_sta1 = lon_lat_to_cartesian(sta_from['lon'].values[:],
sta_from['lat'].values[:],
R=meteva.base.basicdata.ER)
tree = cKDTree(xyz_sta0)
_, indexs = tree.query(xyz_sta1, k=nearNum)
data_name = meteva.base.get_stadata_names(sta_from)[0]
input_dat = sta_from[data_name].values
sta_ensemble = sta_to[meteva.base.get_coord_names()]
for i in range(nearNum):
data_name = "data" + str(i)
sta_ensemble[data_name] = input_dat[indexs[:, i]]
if drop_frist:
sta_ensemble = sta_ensemble.drop(columns=['data0'])
return sta_ensemble
def get_nearby_sta_dis_ensemble(sta_to,nearNum = 100,sta_from = None,drop_frist = False):
if(sta_to is None):
return None
if(sta_from is None):
sta_from = copy.deepcopy(sta_to)
xyz_sta0 = lon_lat_to_cartesian(sta_to['lon'].values[:], sta_to['lat'].values[:],R = meteva.base.basicdata.ER)
xyz_sta1 = lon_lat_to_cartesian(sta_from['lon'].values[:], sta_from['lat'].values[:],R = meteva.base.basicdata.ER)
tree = cKDTree(xyz_sta0)
d,_ = tree.query(xyz_sta1, k=nearNum)
sta_ensemble = sta_to[meteva.base.get_coord_names()]
for i in range(nearNum):
data_name = "data" + str(i)
sta_ensemble[data_name] = d[:,i]
if drop_frist:
sta_ensemble = sta_ensemble.drop(columns=['data0'])
return sta_ensemble
def values_list_list_in_r_of_sta(sta_to,
r=40,
sta_from=None,
drop_first=False):
'''
:param sta_to:
:param r:
:param sta_from:
:param drop_first:
:return: 返回的站点将会和sta_to 一致
'''
if (sta_to is None):
return None
if (sta_from is None):
sta_from = copy.deepcopy(sta_to)
sta_from = meteva.base.not_IV(sta_from)
#print(sta_from)
xyz_sta0 = lon_lat_to_cartesian(sta_to['lon'].values[:],
sta_to['lat'].values[:],
R=meteva.base.basicdata.ER)
xyz_sta1 = lon_lat_to_cartesian(sta_from['lon'].values[:],
sta_from['lat'].values[:],
R=meteva.base.basicdata.ER)
tree = cKDTree(xyz_sta1)
data_name = meteva.base.get_stadata_names(sta_from)[0]
input_dat = sta_from[data_name].values
indexs_list = tree.query_ball_point(xyz_sta0, r=r)
values_list = []
if drop_first:
for indexs in indexs_list:
if len(indexs) > 1:
values = input_dat[indexs[1:]]
values_list.append(values)
else:
values_list.append([meteva.base.IV])
else:
for indexs in indexs_list:
values = input_dat[indexs]
values_list.append(values)
return values_list