def save_datamodel(data_model, num_str=None, **kwargs):
if num_str:
dir_temp = os.path.join(
data_model.data_source.data_config.data_path["Temp"], num_str)
else:
dir_temp = data_model.data_source.data_config.data_path["Temp"]
if not os.path.isdir(dir_temp):
os.makedirs(dir_temp)
data_source_file = os.path.join(dir_temp, kwargs['data_source_file_name'])
stat_file = os.path.join(dir_temp, kwargs['stat_file_name'])
flow_file = os.path.join(dir_temp, kwargs['flow_file_name'])
forcing_file = os.path.join(dir_temp, kwargs['forcing_file_name'])
attr_file = os.path.join(dir_temp, kwargs['attr_file_name'])
f_dict_file = os.path.join(dir_temp, kwargs['f_dict_file_name'])
var_dict_file = os.path.join(dir_temp, kwargs['var_dict_file_name'])
t_s_dict_file = os.path.join(dir_temp, kwargs['t_s_dict_file_name'])
serialize_pickle(data_model.data_source, data_source_file)
serialize_json(data_model.stat_dict, stat_file)
serialize_numpy(data_model.data_flow, flow_file)
serialize_numpy(data_model.data_forcing, forcing_file)
serialize_numpy(data_model.data_attr, attr_file)
# dictFactorize.json is the explanation of value of categorical variables
serialize_json(data_model.f_dict, f_dict_file)
serialize_json(data_model.var_dict, var_dict_file)
serialize_json(data_model.t_s_dict, t_s_dict_file)
def test_data_source_test(self):
config_data = CamelsConfig(self.config_file)
# 准备训练数据
source_data = CamelsSource(
config_data, config_data.model_dict["data"]["tRangeTest"])
# 序列化保存对象
serialize_pickle(source_data, self.data_source_test_file)
def test_data_source(self):
source_data = GagesSource(
self.config_data,
self.config_data.model_dict["data"]["tRangeTrain"],
screen_basin_area_huc4=False)
my_file = os.path.join(self.config_data.data_path["Temp"],
'data_source.txt')
serialize_pickle(source_data, my_file)
def save_nidinput(nid_model, data_path, num_str=None, **kwargs):
if num_str is not None:
data_path = os.path.join(data_path, num_str)
if not os.path.isdir(data_path):
os.makedirs(data_path)
nid_source_file = os.path.join(data_path, kwargs['nid_source_file_name'])
nid_data_file = os.path.join(data_path, kwargs['nid_data_file_name'])
serialize_pickle(nid_model.nid_source, nid_source_file)
serialize_geopandas(nid_model.nid_data, nid_data_file)