Source code for satpy.readers.fy4_base

#!/usr/bin/env python
# -*- coding: utf-8 -*-
# Copyright (c) 2019 Satpy developers
# This file is part of satpy.
# satpy is free software: you can redistribute it and/or modify it under the
# terms of the GNU General Public License as published by the Free Software
# Foundation, either version 3 of the License, or (at your option) any later
# version.
# satpy is distributed in the hope that it will be useful, but WITHOUT ANY
# WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR
# A PARTICULAR PURPOSE.  See the GNU General Public License for more details.
# You should have received a copy of the GNU General Public License along with
# satpy.  If not, see <>.
"""Base reader for the L1 HDF data from the AGRI and GHI instruments aboard the FengYun-4A/B satellites.

The files read by this reader are described in the official Real Time Data Service:


import logging
from datetime import datetime

import dask.array as da
import numpy as np
import numpy.typing as npt
import xarray as xr

from satpy._compat import cached_property
from satpy.readers._geos_area import get_area_definition, get_area_extent
from satpy.readers.hdf5_utils import HDF5FileHandler

logger = logging.getLogger(__name__)

RESOLUTION_LIST = [250, 500, 1000, 2000, 4000]

[docs] class FY4Base(HDF5FileHandler): """The base class for the FengYun4 AGRI and GHI readers.""" def __init__(self, filename, filename_info, filetype_info): """Init filehandler.""" super(FY4Base, self).__init__(filename, filename_info, filetype_info) self.sensor = filename_info["instrument"] # info of 250m, 500m, 1km, 2km and 4km data self._COFF_list = [21983.5, 10991.5, 5495.5, 2747.5, 1373.5] self._LOFF_list = [21983.5, 10991.5, 5495.5, 2747.5, 1373.5] self._CFAC_list = [163730199.0, 81865099.0, 40932549.0, 20466274.0, 10233137.0] self._LFAC_list = [163730199.0, 81865099.0, 40932549.0, 20466274.0, 10233137.0] self.PLATFORM_NAMES = {"FY4A": "FY-4A", "FY4B": "FY-4B", "FY4C": "FY-4C"} try: self.PLATFORM_ID = self.PLATFORM_NAMES[filename_info["platform_id"]] except KeyError: raise KeyError(f"Unsupported platform ID: {filename_info['platform_id']}") self.CHANS_ID = "NOMChannel" self.SAT_ID = "NOMSatellite" self.SUN_ID = "NOMSun"
[docs] @staticmethod def scale(dn, slope, offset): """Convert digital number (DN) to calibrated quantity through scaling. Args: dn: Raw detector digital number slope: Slope offset: Offset Returns: Scaled data """ ref = dn * slope + offset ref = ref.clip(min=0) ref.attrs = dn.attrs return ref
[docs] def _apply_lut(self, data: xr.DataArray, lut: npt.NDArray[np.float32]) -> xr.DataArray: """Calibrate digital number (DN) by applying a LUT. Args: data: Raw detector digital number lut: the look up table Returns: Calibrated quantity """ # append nan to the end of lut for fillvalue fill_value = data.attrs.get("FillValue") if fill_value is not None and fill_value.item() <= lut.shape[0] - 1: # If LUT includes the fill_value, remove that entry and everything # after it. # Ex. C07 has a LUT of 65536 elements, but fill value is 65535 # This is considered a bug in the input file format lut = lut[:fill_value.item()] lut = np.append(lut, np.nan) = da.where( >= lut.shape[0], lut.shape[0] - 1, res =, lut, dtype=lut.dtype) res = xr.DataArray(res, dims=data.dims, attrs=data.attrs, coords=data.coords) return res
[docs] @staticmethod def _getitem(block, lut): return lut[block]
@cached_property def reflectance_coeffs(self): """Retrieve the reflectance calibration coefficients from the HDF file.""" # using the corresponding SCALE and OFFSET if self.PLATFORM_ID == "FY-4A": cal_coef = "CALIBRATION_COEF(SCALE+OFFSET)" elif self.PLATFORM_ID == "FY-4B": cal_coef = "Calibration/CALIBRATION_COEF(SCALE+OFFSET)" else: raise KeyError(f"Unsupported platform ID for calibration: {self.PLATFORM_ID}") return self.get(cal_coef).values
[docs] def calibrate(self, data, ds_info, ds_name, file_key): """Calibrate the data.""" # Check if calibration is present, if not assume dataset is an angle calibration = ds_info.get("calibration") # Return raw data in case of counts or no calibration if calibration in ("counts", None): data.attrs["units"] = ds_info["units"] ds_info["valid_range"] = data.attrs["valid_range"] ds_info["fill_value"] = data.attrs["FillValue"].item() elif calibration == "reflectance": channel_index = int(file_key[-2:]) - 1 data = self.calibrate_to_reflectance(data, channel_index, ds_info) elif calibration == "brightness_temperature": data = self.calibrate_to_bt(data, ds_info, ds_name) elif calibration == "radiance": raise NotImplementedError("Calibration to radiance is not supported.") # Apply range limits, but not for counts or we convert to float! if calibration != "counts": data = data.where((data >= min(ds_info["valid_range"])) & (data <= max(ds_info["valid_range"]))) else: data.attrs["_FillValue"] = data.attrs["FillValue"].item() return data
[docs] def calibrate_to_reflectance(self, data, channel_index, ds_info): """Calibrate to reflectance [%].""" logger.debug("Calibrating to reflectances") # using the corresponding SCALE and OFFSET if self.sensor != "AGRI" and self.sensor != "GHI": raise ValueError(f"Unsupported sensor type: {self.sensor}") coeffs = self.reflectance_coeffs num_channel = coeffs.shape[0] if self.sensor == "AGRI" and num_channel == 1: # only channel_2, resolution = 500 m channel_index = 0 = da.where( == data.attrs["FillValue"].item(), np.nan, data.attrs["scale_factor"] = coeffs[channel_index, 0].item() data.attrs["add_offset"] = coeffs[channel_index, 1].item() data = self.scale(data, data.attrs["scale_factor"], data.attrs["add_offset"]) data *= 100 ds_info["valid_range"] = (data.attrs["valid_range"] * data.attrs["scale_factor"] + data.attrs["add_offset"]) ds_info["valid_range"] = ds_info["valid_range"] * 100 return data
[docs] def calibrate_to_bt(self, data, ds_info, ds_name): """Calibrate to Brightness Temperatures [K].""" logger.debug("Calibrating to brightness_temperature") if self.sensor not in ["GHI", "AGRI"]: raise ValueError("Error, sensor must be GHI or AGRI.") # The key is sometimes prefixes with `Calibration/` so we try both options here lut_key = ds_info.get("lut_key", ds_name) try: lut = self[lut_key] except KeyError: lut_key = f'Calibration/{ds_info.get("lut_key", ds_name)}' lut = self[lut_key] # the value of dn is the index of brightness_temperature data = self._apply_lut(data, lut.compute().data) ds_info["valid_range"] = lut.attrs["valid_range"] return data
@property def start_time(self): """Get the start time.""" start_time = self["/attr/Observing Beginning Date"] + "T" + self["/attr/Observing Beginning Time"] + "Z" try: return datetime.strptime(start_time, "%Y-%m-%dT%H:%M:%S.%fZ") except ValueError: # For some data there is no sub-second component return datetime.strptime(start_time, "%Y-%m-%dT%H:%M:%SZ") @property def end_time(self): """Get the end time.""" end_time = self["/attr/Observing Ending Date"] + "T" + self["/attr/Observing Ending Time"] + "Z" try: return datetime.strptime(end_time, "%Y-%m-%dT%H:%M:%S.%fZ") except ValueError: # For some data there is no sub-second component return datetime.strptime(end_time, "%Y-%m-%dT%H:%M:%SZ")
[docs] def get_area_def(self, key): """Get the area definition.""" # Coordination Group for Meteorological Satellites LRIT/HRIT Global Specification # res = key["resolution"] pdict = {} begin_cols = float(self.file_content["/attr/Begin Pixel Number"]) end_lines = float(self.file_content["/attr/End Line Number"]) pdict["coff"] = self._COFF_list[RESOLUTION_LIST.index(res)] - begin_cols + 1 pdict["loff"] = -self._LOFF_list[RESOLUTION_LIST.index(res)] + end_lines + 1 pdict["cfac"] = self._CFAC_list[RESOLUTION_LIST.index(res)] pdict["lfac"] = self._LFAC_list[RESOLUTION_LIST.index(res)] try: pdict["a"] = float(self.file_content["/attr/Semimajor axis of ellipsoid"]) except KeyError: pdict["a"] = float(self.file_content["/attr/dEA"]) if pdict["a"] < 10000: pdict["a"] = pdict["a"] * 1E3 # equator radius (m) try: pdict["b"] = float(self.file_content["/attr/Semiminor axis of ellipsoid"]) except KeyError: pdict["b"] = pdict["a"] * (1 - 1 / self.file_content["/attr/dObRecFlat"]) # polar radius (m) pdict["h"] = self.file_content["/attr/NOMSatHeight"] # the altitude of satellite (m) if pdict["h"] > 42000000.0: pdict["h"] = pdict["h"] - pdict["a"] pdict["ssp_lon"] = float(self.file_content["/attr/NOMCenterLon"]) pdict["nlines"] = float(self.file_content["/attr/RegLength"]) pdict["ncols"] = float(self.file_content["/attr/RegWidth"]) pdict["scandir"] = "N2S" pdict["a_desc"] = "FY-4 {} area".format(self.filename_info["observation_type"]) pdict["a_name"] = f'{self.filename_info["observation_type"]}_{res}m' pdict["p_id"] = f"FY-4, {res}m" area_extent = get_area_extent(pdict) area_extent = (area_extent[0], area_extent[1], area_extent[2], area_extent[3]) area = get_area_definition(pdict, area_extent) return area