#!/usr/bin/env python
# -*- coding: utf-8 -*-
# Copyright (c) 2017-2023 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 <http://www.gnu.org/licenses/>.
"""Nowcasting SAF common PPS&MSG NetCDF/CF format reader.
References:
- The NWCSAF GEO 2018 products documentation: http://www.nwcsaf.org/web/guest/archive
"""
import functools
import logging
import os
from contextlib import suppress
from datetime import datetime
import dask.array as da
import numpy as np
import xarray as xr
from pyproj import CRS
from pyresample.geometry import AreaDefinition
from satpy.readers.file_handlers import BaseFileHandler
from satpy.readers.utils import unzip_file
from satpy.utils import get_chunk_size_limit
logger = logging.getLogger(__name__)
CHUNK_SIZE = get_chunk_size_limit()
SENSOR = {"NOAA-19": "avhrr-3",
"NOAA-18": "avhrr-3",
"NOAA-15": "avhrr-3",
"Metop-A": "avhrr-3",
"Metop-B": "avhrr-3",
"Metop-C": "avhrr-3",
"EOS-Aqua": "modis",
"EOS-Terra": "modis",
"Suomi-NPP": "viirs",
"NOAA-20": "viirs",
"NOAA-21": "viirs",
"NOAA-22": "viirs",
"NOAA-23": "viirs",
"JPSS-1": "viirs",
"Metop-SG-A1": "metimage",
"Metop-SG-A2": "metimage",
"Metop-SG-A3": "metimage",
"GOES-16": "abi",
"GOES-17": "abi",
"Himawari-8": "ahi",
"Himawari-9": "ahi",
}
PLATFORM_NAMES = {"MSG1": "Meteosat-8",
"MSG2": "Meteosat-9",
"MSG3": "Meteosat-10",
"MSG4": "Meteosat-11",
"GOES16": "GOES-16",
"GOES17": "GOES-17",
}
[docs]
class NcNWCSAF(BaseFileHandler):
"""NWCSAF PPS&MSG NetCDF reader."""
def __init__(self, filename, filename_info, filetype_info):
"""Init method."""
super(NcNWCSAF, self).__init__(filename, filename_info,
filetype_info)
self._unzipped = unzip_file(self.filename)
if self._unzipped:
self.filename = self._unzipped
self.cache = {}
self.nc = xr.open_dataset(self.filename,
decode_cf=True,
mask_and_scale=False,
chunks=CHUNK_SIZE)
self.nc = self.nc.rename({"nx": "x", "ny": "y"})
self.sw_version = self.nc.attrs["source"]
self.pps = False
self.platform_name = None
self.sensor = None
self.file_key_prefix = filetype_info.get("file_key_prefix", "")
try:
# NWCSAF/Geo:
try:
kwrgs = {"sat_id": self.nc.attrs["satellite_identifier"]}
except KeyError:
kwrgs = {"sat_id": self.nc.attrs["satellite_identifier"].astype(str)}
except KeyError:
# NWCSAF/PPS:
kwrgs = {"platform_name": self.nc.attrs["platform"]}
self.set_platform_and_sensor(**kwrgs)
self.upsample_geolocation = functools.lru_cache(maxsize=1)(
self._upsample_geolocation_uncached
)
[docs]
def remove_timedim(self, var):
"""Remove time dimension from dataset."""
if self.pps and var.dims[0] == "time":
data = var[0, :, :]
data.attrs = var.attrs
var = data
return var
[docs]
def drop_xycoords(self, variable):
"""Drop x, y coords when y is scan line number."""
try:
if variable.coords["y"].attrs["long_name"] == "scan line number":
return variable.drop_vars(["y", "x"])
except KeyError:
pass
return variable
[docs]
def get_dataset(self, dsid, info):
"""Load a dataset."""
dsid_name = dsid["name"]
if dsid_name in self.cache:
logger.debug("Get the data set from cache: %s.", dsid_name)
return self.cache[dsid_name]
if dsid_name in ["lon", "lat"] and dsid_name not in self.nc:
# Get full resolution lon,lat from the reduced (tie points) grid
lon, lat = self.upsample_geolocation()
if dsid_name == "lon":
return lon
else:
return lat
logger.debug("Reading %s.", dsid_name)
file_key = self._get_filekeys(dsid_name, info)
variable = self.nc[file_key]
variable = self.remove_timedim(variable)
variable = self.scale_dataset(variable, info)
variable = self.drop_xycoords(variable)
self.get_orbital_parameters(variable)
variable.attrs["start_time"] = self.start_time
variable.attrs["end_time"] = self.end_time
return variable
[docs]
def get_orbital_parameters(self, variable):
"""Get the orbital parameters from the file if possible (geo)."""
with suppress(KeyError):
gdal_params = dict(elt.strip("+").split("=") for elt in self.nc.attrs["gdal_projection"].split())
variable.attrs["orbital_parameters"] = dict(
satellite_nominal_altitude=float(gdal_params["h"]),
satellite_nominal_longitude=float(self.nc.attrs["sub-satellite_longitude"]),
satellite_nominal_latitude=0)
[docs]
def _get_varname_in_file(self, info, info_type="file_key"):
if isinstance(info[info_type], list):
for key in info[info_type]:
file_key = self.file_key_prefix + key
if file_key in self.nc:
return file_key
return self.file_key_prefix + info[info_type]
[docs]
def _get_filekeys(self, dsid_name, info):
try:
file_key = self._get_varname_in_file(info, info_type="file_key")
except KeyError:
file_key = dsid_name
return file_key
[docs]
def scale_dataset(self, variable, info):
"""Scale the data set, applying the attributes from the netCDF file.
The scale and offset attributes will then be removed from the resulting variable.
"""
variable = remove_empties(variable)
scale = variable.attrs.get("scale_factor", np.array(1))
offset = variable.attrs.get("add_offset", np.array(0))
if "_FillValue" in variable.attrs:
variable.attrs["scaled_FillValue"] = variable.attrs["_FillValue"] * scale + offset
if np.issubdtype((scale + offset).dtype, np.floating) or np.issubdtype(variable.dtype, np.floating):
variable = self._mask_variable(variable)
attrs = variable.attrs.copy()
variable = variable * scale + offset
variable.attrs = attrs
if "valid_range" in variable.attrs:
variable.attrs["valid_range"] = variable.attrs["valid_range"] * scale + offset
variable.attrs.pop("add_offset", None)
variable.attrs.pop("scale_factor", None)
variable.attrs.update({"platform_name": self.platform_name,
"sensor": self.sensor})
if not variable.attrs.get("standard_name", "").endswith("status_flag"):
# TODO: do we really need to add units to everything ?
variable.attrs.setdefault("units", "1")
ancillary_names = variable.attrs.get("ancillary_variables", "")
try:
variable.attrs["ancillary_variables"] = ancillary_names.split()
except AttributeError:
pass
if "palette_meanings" in variable.attrs:
variable = self._prepare_variable_for_palette(variable, info)
if "standard_name" in info:
variable.attrs.setdefault("standard_name", info["standard_name"])
variable = self._adjust_variable_for_legacy_software(variable)
return variable
[docs]
@staticmethod
def _mask_variable(variable):
if "_FillValue" in variable.attrs:
variable = variable.where(
variable != variable.attrs["_FillValue"])
variable.attrs["_FillValue"] = np.nan
if "valid_range" in variable.attrs:
variable = variable.where(
variable <= variable.attrs["valid_range"][1])
variable = variable.where(
variable >= variable.attrs["valid_range"][0])
if "valid_max" in variable.attrs:
variable = variable.where(
variable <= variable.attrs["valid_max"])
if "valid_min" in variable.attrs:
variable = variable.where(
variable >= variable.attrs["valid_min"])
return variable
[docs]
def _prepare_variable_for_palette(self, variable, info):
try:
so_dataset = self.nc[self._get_varname_in_file(info, info_type="scale_offset_dataset")]
except KeyError:
scale = 1
offset = 0
fill_value = 255
else:
scale = so_dataset.attrs["scale_factor"]
offset = so_dataset.attrs["add_offset"]
fill_value = so_dataset.attrs["_FillValue"]
variable.attrs["palette_meanings"] = [int(val)
for val in variable.attrs["palette_meanings"].split()]
if fill_value not in variable.attrs["palette_meanings"] and "fill_value_color" in variable.attrs:
variable.attrs["palette_meanings"] = [fill_value] + variable.attrs["palette_meanings"]
variable = xr.DataArray(da.vstack((np.array(variable.attrs["fill_value_color"]), variable.data)),
coords=variable.coords, dims=variable.dims, attrs=variable.attrs)
val, idx = np.unique(variable.attrs["palette_meanings"], return_index=True)
variable.attrs["palette_meanings"] = val * scale + offset
variable = variable[idx]
return variable
[docs]
def _adjust_variable_for_legacy_software(self, variable):
if self.sw_version == "NWC/PPS version v2014" and variable.attrs.get("standard_name") == "cloud_top_altitude":
# pps 2014 valid range and palette don't match
variable.attrs["valid_range"] = (0., 9000.)
if (self.sw_version == "NWC/PPS version v2014" and
variable.attrs.get("long_name") == "RGB Palette for ctth_alti"):
# pps 2014 palette has the nodata color (black) first
variable = variable[1:, :]
return variable
[docs]
def _upsample_geolocation_uncached(self):
"""Upsample the geolocation (lon,lat) from the tiepoint grid."""
from geotiepoints import SatelliteInterpolator
# Read the fields needed:
col_indices = self.nc["nx_reduced"].values
row_indices = self.nc["ny_reduced"].values
lat_reduced = self.scale_dataset(self.nc["lat_reduced"], {})
lon_reduced = self.scale_dataset(self.nc["lon_reduced"], {})
shape = (self.nc["y"].shape[0], self.nc["x"].shape[0])
cols_full = np.arange(shape[1])
rows_full = np.arange(shape[0])
satint = SatelliteInterpolator((lon_reduced.values, lat_reduced.values),
(row_indices,
col_indices),
(rows_full, cols_full))
lons, lats = satint.interpolate()
lon = xr.DataArray(lons, attrs=lon_reduced.attrs, dims=["y", "x"])
lat = xr.DataArray(lats, attrs=lat_reduced.attrs, dims=["y", "x"])
lat = self.drop_xycoords(lat)
lon = self.drop_xycoords(lon)
return lon, lat
[docs]
def get_area_def(self, dsid):
"""Get the area definition of the datasets in the file.
Only applicable for MSG products!
"""
if self.pps:
# PPS:
raise NotImplementedError
if dsid["name"].endswith("_pal"):
raise NotImplementedError
crs, area_extent = self._get_projection()
crs, area_extent = self._ensure_crs_extents_in_meters(crs, area_extent)
nlines, ncols = self.nc[dsid["name"]].shape
area = AreaDefinition("some_area_name",
"On-the-fly area",
"geosmsg",
crs,
ncols,
nlines,
area_extent)
return area
[docs]
@staticmethod
def _ensure_crs_extents_in_meters(crs, area_extent):
"""Fix units in Earth shape, satellite altitude and 'units' attribute."""
import warnings
if "kilo" in crs.axis_info[0].unit_name:
with warnings.catch_warnings():
# The proj dict route is the only feasible way to modify the area, suppress the warning it causes
warnings.filterwarnings("ignore", category=UserWarning,
message="You will likely lose important projection information")
proj_dict = crs.to_dict()
proj_dict["units"] = "m"
if "a" in proj_dict:
proj_dict["a"] *= 1000.
if "b" in proj_dict:
proj_dict["b"] *= 1000.
if "R" in proj_dict:
proj_dict["R"] *= 1000.
proj_dict["h"] *= 1000.
area_extent = tuple([val * 1000. for val in area_extent])
crs = CRS.from_dict(proj_dict)
return crs, area_extent
def __del__(self):
"""Delete the instance."""
if self._unzipped:
try:
os.remove(self._unzipped)
except OSError:
pass
@property
def start_time(self):
"""Return the start time of the object."""
try:
return read_nwcsaf_time(self.nc.attrs["nominal_product_time"])
except KeyError:
return read_nwcsaf_time(self.nc.attrs["time_coverage_start"])
@property
def end_time(self):
"""Return the end time of the object."""
return read_nwcsaf_time(self.nc.attrs["time_coverage_end"])
@property
def sensor_names(self):
"""List of sensors represented in this file."""
return self.sensor
[docs]
def _get_projection(self):
"""Get projection from the NetCDF4 attributes."""
try:
proj_str = self.nc.attrs["gdal_projection"]
except TypeError:
proj_str = self.nc.attrs["gdal_projection"].decode()
# Check the a/b/h units
radius_a = proj_str.split("+a=")[-1].split()[0]
if float(radius_a) > 10e3:
units = "m"
scale = 1.0
else:
units = "km"
scale = 1e3
if "units" not in proj_str:
proj_str = proj_str + " +units=" + units
area_extent = (float(self.nc.attrs["gdal_xgeo_up_left"]) / scale,
float(self.nc.attrs["gdal_ygeo_low_right"]) / scale,
float(self.nc.attrs["gdal_xgeo_low_right"]) / scale,
float(self.nc.attrs["gdal_ygeo_up_left"]) / scale)
crs = CRS.from_string(proj_str)
return crs, area_extent
[docs]
def remove_empties(variable):
"""Remove empty objects from the *variable*'s attrs."""
import h5py
for key, val in variable.attrs.items():
if isinstance(val, h5py._hl.base.Empty):
variable.attrs.pop(key)
return variable
[docs]
def read_nwcsaf_time(time_value):
"""Read the time, nwcsaf-style."""
try:
# MSG:
try:
return datetime.strptime(time_value, "%Y-%m-%dT%H:%M:%SZ")
except TypeError: # Remove this in summer 2024 (this is not needed since h5netcdf 0.14)
return datetime.strptime(time_value.astype(str), "%Y-%m-%dT%H:%M:%SZ")
except ValueError:
# PPS:
return datetime.strptime(time_value, "%Y%m%dT%H%M%S%fZ")