NC Forecast Extract Grid To Weather Data Model

ECMWFExtractGridToWeatherDataModel

Bases: ECMWFExtractBaseToWeatherDataModel

Extract a grid from a local .nc file downloaded from ECMWF via MARS

Parameters:

Name	Type	Description	Default
lat_min	float	Minimum latitude of grid to extract	required
lat_max	float	Maximum latitude of grid to extract	required
lon_min	float	Minimum longitude of grid to extract	required
lon_max	float	Maximum longitude of grid to extract	required
grid_step	float	The grid length to use to define the grid, e.g. 0.1.	required
load_path	str	Path to local directory with nc files downloaded in format "yyyy-mm-dd_HH.nc"	required
date_start	str	Start date of extraction in "YYYY-MM-DD HH:MM:SS" format	required
date_end	str	End date of extraction in "YYYY-MM-DD HH:MM:SS" format	required
run_frequency	str	Frequency format of runs to download, e.g. "H"	required
run_interval	str	Interval of runs, e.g. a run_frequency of "H" and run_interval of "12" will extract the data of the 00 and 12 run for each day.	required
utc	bool	Add utc to the datetime indexes? Defaults to True.	True

Source code in src/sdk/python/rtdip_sdk/pipelines/transformers/spark/ecmwf/nc_extractgrid_to_weather_data_model.py

class ECMWFExtractGridToWeatherDataModel(ECMWFExtractBaseToWeatherDataModel):
    """Extract a grid from a local .nc file downloaded from ECMWF via MARS

    Args:
        lat_min (float): Minimum latitude of grid to extract
        lat_max (float): Maximum latitude of grid to extract
        lon_min (float): Minimum longitude of grid to extract
        lon_max (float): Maximum longitude of grid to extract
        grid_step (float): The grid length to use to define the grid, e.g. 0.1.
        load_path (str): Path to local directory with nc files downloaded in format "yyyy-mm-dd_HH.nc"
        date_start (str): Start date of extraction in "YYYY-MM-DD HH:MM:SS" format
        date_end (str): End date of extraction in "YYYY-MM-DD HH:MM:SS" format
        run_frequency (str): Frequency format of runs to download, e.g. "H"
        run_interval (str): Interval of runs, e.g. a run_frequency of "H" and run_interval of "12" will extract the data of the 00 and 12 run for each day.
        utc (bool, optional): Add utc to the datetime indexes? Defaults to True.

    """

    def __init__(
        self,
        lat_min: float,
        lat_max: float,
        lon_min: float,
        lon_max: float,
        grid_step: float,
        load_path: str,
        date_start: str,
        date_end: str,
        run_interval: str,
        run_frequency: str,
        utc: bool = True,
    ):
        # hmm careful with floating points, this seems to work ok...
        lat_xr = xr.DataArray(
            np.linspace(
                lat_min, lat_max, int(np.round((lat_max - lat_min) / grid_step)) + 1
            ),
            dims=["latitude"],
        )
        lon_xr = xr.DataArray(
            np.linspace(
                lon_min, lon_max, int(np.round((lon_max - lon_min) / grid_step)) + 1
            ),
            dims=["longitude"],
        )

        self.load_path = load_path
        self.lat_min = lat_min
        self.lat_max = lat_max
        self.lon_min = lon_min
        self.lon_max = lon_max
        self.grid_step = grid_step
        self.lat = lat_xr
        self.lon = lon_xr
        self.date_start = date_start
        self.date_end = date_end
        self.run_frequency = run_frequency
        self.run_interval = run_interval
        self.utc = utc

        super(ECMWFExtractGridToWeatherDataModel, self).__init__(
            lat=lat_xr,
            lon=lon_xr,
            load_path=load_path,
            date_start=date_start,
            date_end=date_end,
            run_interval=run_interval,
            run_frequency=run_frequency,
            utc=utc,
        )