add modular for calculating the climatorlogy

video_prediction_tools/data_preprocess/calc_climatology.py

+
+__email__ = "b.gong@fz-juelich.de"
+__author__ = "Yan Ji, Bing Gong"
+__date__ = "2021-05-26"
+"""
+Use the monthly average vaules to calculate the climitological values from the datas sources that donwload from ECMWF : /p/fastdata/slmet/slmet111/met_data/ecmwf/era5/grib/monthly
+"""
+
+import os
+import time
+import glob
+import json
+
+
+class Calc_climatology(object):
+    def __init__(self, input_dir="/p/fastdata/slmet/slmet111/met_data/ecmwf/era5/grib/monthly", output_clim=None, region:list=[10,20], json_path=None):
+        self.input_dir = input_dir
+        self.output_clim = output_clim
+        self.region = region
+        self.lats = None
+        self.lons = None
+        self.json_path = json_path
+
+    @staticmethod
+    def calc_avg_per_year(grib_fl: str=None):
+        """
+        :param grib_fl: the relative path of the monthly average values
+        :return: None
+        """
+        return None
+
+    def cal_avg_all_files(self):
+
+        """
+        Average by time for all the grib files
+        :return: None
+        """
+
+        method = Calc_climatology.cal_avg_all_files.__name__
+
+        multiyears_path = os.path.join(self.output_clim,"multiyears.grb")
+        climatology_path = os.path.join(self.output_clim,"climatology.grb")
+        grib_files = glob.glob(os.path.join(self.input_dir,"*t2m.grb"))
+        if grib_files:
+            print ("{0}: There are {1} monthly years grib files".format(method,len(grib_files)))
+            # merge all the files into one grib file
+            os.system("cdo mergetime {0} {1}".format(grib_files,multiyears_path))
+            # average by time
+            os.system("cdo timavg {0} {1}".format(multiyears_path,climatology_path))
+
+        else:
+            FileExistsError("%{0}: The monthly years grib files do not exit in the input directory %{1}".format(method,self.input_dir))
+
+        return None
+
+
+    def get_lat_lon_from_json(self):
+        """
+        Get lons and lats from json file
+        :return: list of lats, and lons
+        """
+        method = Calc_climatology.get_lat_lon_from_json.__name__
+
+        if not os.path.exists(self.json_path):
+            raise FileExistsError("{0}: The json file {1} does not exist".format(method,self.json_path))
+
+        with open(self.json_path) as fl:
+            meta_data = json.load(fl)
+
+        if "coordinates" not in list(meta_data.keys()):
+            raise KeyError("{0}: 'coordinates' is not one of the keys for metadata,json".format(method))
+        else:
+            meta_coords = meta_data["coordinates"]
+            self.lats = meta_coords["lat"]
+            self.lons = meta_coords["lon"]
+        return self.lats, self.lons
+
+
+    def get_region_climate(self):
+        """
+        Get the climitollgical values from the selected regions
+        :return: None
+        """
+        pass
+
+
+    def __call__(self, *args, **kwargs):
+
+        if os.path.exists(os.path.join(self.output_clim,"climatology.grb")):
+            pass
+        else:
+            self.cal_avg_all_files()
+            self.get_lat_lon_from_json()
+            self.get_region_climate()
+
+
+
+
+
+if __name__ == '__main__':
+    exp = Calc_climatology(json_path="/p/project/deepacf/deeprain/video_prediction_shared_folder/preprocessedData/era5-Y2007-2019M01to12-92x56-3840N0000E-2t_tcc_t_850/metadata.json")
+    exp()
+
+