def clip_poly(jsonpath, task_id, search_time, res_path):
start = time()
set_conf(jsonpath, task_id, search_time, res_path)
# os.mkdir(conf.sRslPath)
pWGSLT, pWGSRB = BaseProcesses.read_json_area(conf.jsonpath)
unitblock_list = get_unitblock_list(pWGSLT, pWGSRB)
grid_dic = {}
for unitblock in unitblock_list:
lsGridcode = GridCalculate.GridCodeToGridlist_iPCSType(unitblock['sGridCodeLT'],\
unitblock['sGridCodeRB'], unitblock['iPCSType'])
for sGridCode in lsGridcode:
lbds10kmIn = SearchEngine.SearchByRgDttmDtpd(sGridCode, conf.sDatahomePath, conf.search_time,
conf.iDataProduct, conf.iCloulLevel)
for lbd_time in lbds10kmIn:
if lbd_time not in grid_dic.keys():
grid_dic[lbd_time] = [lbd.sPathName for lbd in lbds10kmIn[lbd_time]]
else:
grid_dic[lbd_time] += [lbd.sPathName for lbd in lbds10kmIn[lbd_time]]
for lbd_time in grid_dic:
clip_dataset_list_groupby_time(grid_dic[lbd_time], lbd_time)
grid_dic = None
end = time()
print("任务{1}耗时{0}，涉及{2}个条带".format(end-start, task_id, len(unitblock_list)))
def DealIn10km(sGridCode, sDateTime, iDataProduct, iModelId, iCloulLevel,
sDatahomePath, sRslPath):
'''根据 格网编码 日期 类型， 处理单个10km格网内的业务 ——以基本结构表示的某景影像
1 根据格网序编号、日期、数据类型得到该网格内待处理数据列表 —Lbds
2 2 根据待处理数据列表，完成该格网的业务处理 —bds
'''
lbds10kmIn = SearchEngine.SearchByRgDttmDtpd(sGridCode, sDatahomePath,
sDateTime, iDataProduct,
iCloulLevel)
if (len(lbds10kmIn) >= 1):
bdsRlt = Stitching.StichingIn10km(lbds10kmIn, iDataProduct, iModelId,
sRslPath)
else:
bdsRlt = basic_data_struct()
bdsRlt.sPathName = "0"
return bdsRlt
if __name__ == "__main__":
start = time()
set_conf()
os.mkdir(conf.sRslPath)
pWGSLT, pWGSRB = BaseProcesses.read_json_area(conf.jsonpath)
unitblock_list = get_unitblock_list(pWGSLT, pWGSRB)
grid_dic = {}
for unitblock in unitblock_list:
lsGridcode = GridCalculate.GridCodeToGridlist_iPCSType(unitblock['sGridCodeLT'],\
unitblock['sGridCodeRB'], unitblock['iPCSType'])
for sGridCode in lsGridcode:
lbds10kmIn = SearchEngine.SearchByRgDttmDtpd(
sGridCode, conf.sDatahomePath, conf.search_time,
conf.iDataProduct, conf.iCloulLevel)
for lbd_time in lbds10kmIn:
if lbd_time not in grid_dic.keys():
grid_dic[lbd_time] = [
gdal.Open(lbd.sPathName)
for lbd in lbds10kmIn[lbd_time]
]
else:
grid_dic[lbd_time] += [
gdal.Open(lbd.sPathName)
for lbd in lbds10kmIn[lbd_time]
]
for lbd_time in grid_dic:
clip_dataset_list_groupby_time(grid_dic[lbd_time], lbd_time)
