Python Data._raw_filename方法代码示例

# 需要导入模块: from pycmbs.data import Data [as 别名]
# 或者: from pycmbs.data.Data import _raw_filename [as 别名]
    def get_model_data_generic(self, interval="season", **kwargs):
        """
        unique parameters are:
            filename - file basename
            variable - name of the variable as the short_name in the netcdf file

            kwargs is a dictionary with keys for each model. Then a dictionary with properties follows

        """

        if not self.type in kwargs.keys():
            print ""
            print "WARNING: it is not possible to get data using generic function, as method missing: ", self.type, kwargs.keys()
            assert False

        locdict = kwargs[self.type]

        # read settings and details from the keyword arguments
        # no defaults; everything should be explicitely specified in either the config file or the dictionaries
        varname = locdict.pop("variable", None)
        # ~ print self.type
        # ~ print locdict.keys()
        assert varname is not None, "ERROR: provide varname!"

        units = locdict.pop("unit", None)
        assert units is not None, "ERROR: provide unit!"

        lat_name = locdict.pop("lat_name", "lat")
        lon_name = locdict.pop("lon_name", "lon")
        model_suffix = locdict.pop("model_suffix", None)
        model_prefix = locdict.pop("model_prefix", None)
        file_format = locdict.pop("file_format")
        scf = locdict.pop("scale_factor")
        valid_mask = locdict.pop("valid_mask")
        custom_path = locdict.pop("custom_path", None)
        thelevel = locdict.pop("level", None)

        target_grid = self._actplot_options["targetgrid"]
        interpolation = self._actplot_options["interpolation"]

        if custom_path is None:
            filename1 = self.get_raw_filename(varname, **kwargs)  # routine needs to be implemented by each subclass
        else:
            filename1 = custom_path + self.get_raw_filename(varname, **kwargs)

        if filename1 is None:
            print_log(WARNING, "No valid model input data")
            return None

        force_calc = False

        if self.start_time is None:
            raise ValueError("Start time needs to be specified")
        if self.stop_time is None:
            raise ValueError("Stop time needs to be specified")

        # /// PREPROCESSING ///
        cdo = Cdo()
        s_start_time = str(self.start_time)[0:10]
        s_stop_time = str(self.stop_time)[0:10]

        # 1) select timeperiod and generate monthly mean file
        if target_grid == "t63grid":
            gridtok = "T63"
        else:
            gridtok = "SPECIAL_GRID"

        file_monthly = (
            filename1[:-3] + "_" + s_start_time + "_" + s_stop_time + "_" + gridtok + "_monmean.nc"
        )  # target filename
        file_monthly = get_temporary_directory() + os.path.basename(file_monthly)

        sys.stdout.write("\n *** Model file monthly: %s\n" % file_monthly)

        if not os.path.exists(filename1):
            print "WARNING: File not existing: " + filename1
            return None

        cdo.monmean(
            options="-f nc",
            output=file_monthly,
            input="-"
            + interpolation
            + ","
            + target_grid
            + " -seldate,"
            + s_start_time
            + ","
            + s_stop_time
            + " "
            + filename1,
            force=force_calc,
        )

        sys.stdout.write("\n *** Reading model data... \n")
        sys.stdout.write("     Interval: " + interval + "\n")

        # 2) calculate monthly or seasonal climatology
        if interval == "monthly":
            mdata_clim_file = file_monthly[:-3] + "_ymonmean.nc"
#.........这里部分代码省略.........