Source code for satpy.readers.scmi

#!/usr/bin/env python
# -*- coding: utf-8 -*-
# Copyright (c) 2018 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 <>.
"""SCMI NetCDF4 Reader.

SCMI files are typically used for data for the ABI instrument onboard the
GOES-16/17 satellites. It is the primary format used for providing ABI data
to the AWIPS visualization clients used by the US National Weather Service
forecasters. The python code for this reader may be reused by other readers
as NetCDF schemes/metadata change for different products. The initial reader
using this code is the "scmi_abi" reader (see `abi_l1b_scmi.yaml` for more

There are two forms of these files that this reader supports:

1. Official SCMI format: NetCDF4 files where the main data variable is stored
    in a variable called "Sectorized_CMI". This variable name can be
    configured in the YAML configuration file.
2. Satpy/Polar2Grid SCMI format: NetCDF4 files based on the official SCMI
    format created for the Polar2Grid project. This format was migrated to
    Satpy as part of Polar2Grid's adoption of Satpy for the majority of its
    features. This format is what is produced by Satpy's `scmi` writer.
    This format can be identified by a single variable named "data" and a
    global attribute named ``"awips_id"`` that is set to a string starting with


import logging
import os
from datetime import datetime

import numpy as np
import xarray as xr
from pyresample import geometry

from satpy import CHUNK_SIZE
from satpy.readers.file_handlers import BaseFileHandler

# NetCDF doesn't support multi-threaded reading, trick it by opening
# as one whole chunk then split it up before we do any calculations
logger = logging.getLogger(__name__)

[docs]class SCMIFileHandler(BaseFileHandler): """Handle a single SCMI NetCDF4 file.""" def __init__(self, filename, filename_info, filetype_info): """Set up the SCMI file handler.""" super(SCMIFileHandler, self).__init__(filename, filename_info, filetype_info) # xarray's default netcdf4 engine = xr.open_dataset(self.filename, decode_cf=True, mask_and_scale=False, chunks={'x': LOAD_CHUNK_SIZE, 'y': LOAD_CHUNK_SIZE}) self.platform_name =['satellite_id'] self.sensor = self._get_sensor() self.nlines =['y'] self.ncols =['x'] self.coords = {} def _get_sensor(self): """Determine the sensor for this file.""" # sometimes Himawari-8 (or 9) data is stored in SCMI format is_h8 = 'H8' in self.platform_name is_h9 = 'H9' in self.platform_name is_ahi = is_h8 or is_h9 return 'ahi' if is_ahi else 'abi' @property def sensor_names(self): """Get the sensor names.""" return [self.sensor] def __getitem__(self, item): """Wrap around `[item]`. Some datasets use a 32-bit float scaling factor like the 'x' and 'y' variables which causes inaccurate unscaled data values. This method forces the scale factor to a 64-bit float first. """ data =[item] attrs = data.attrs factor = data.attrs.get('scale_factor') offset = data.attrs.get('add_offset') fill = data.attrs.get('_FillValue') if fill is not None: data = data.where(data != fill) if factor is not None: # make sure the factor is a 64-bit float # can't do this in place since data is most likely uint16 # and we are making it a 64-bit float data = data * float(factor) + offset data.attrs = attrs # handle coordinates (and recursive fun) new_coords = {} # 'time' dimension causes issues in other processing if 'time' in data.coords: data = data.drop_vars('time') if item in data.coords: self.coords[item] = data for coord_name in data.coords.keys(): if coord_name not in self.coords: self.coords[coord_name] = self[coord_name] new_coords[coord_name] = self.coords[coord_name] data.coords.update(new_coords) return data
[docs] def get_shape(self, key, info): """Get the shape of the data.""" return self.nlines, self.ncols
[docs] def get_dataset(self, key, info): """Load a dataset.""" logger.debug('Reading in get_dataset %s.', key['name']) var_name = info.get('file_key', self.filetype_info.get('file_key')) if var_name: data = self[var_name] elif 'Sectorized_CMI' in data = self['Sectorized_CMI'] elif 'data' in data = self['data'] # NetCDF doesn't support multi-threaded reading, trick it by opening # as one whole chunk then split it up before we do any calculations data = data.chunk({'x': CHUNK_SIZE, 'y': CHUNK_SIZE}) # convert to satpy standard units factor = data.attrs.pop('scale_factor', 1) offset = data.attrs.pop('add_offset', 0) units = data.attrs.get('units', 1) # the '*1' unit is some weird convention added/needed by AWIPS if units in ['1', '*1'] and key['calibration'] == 'reflectance': data *= 100 factor *= 100 # used for valid_min/max data.attrs['units'] = '%' # set up all the attributes that might be useful to the user/satpy data.attrs.update({'platform_name': self.platform_name, 'sensor': data.attrs.get('sensor', self.sensor), }) if 'satellite_longitude' in data.attrs['orbital_parameters'] = { 'projection_longitude':['satellite_longitude'], 'projection_latitude':['satellite_latitude'], 'projection_altitude':['satellite_altitude'], } scene_id ='scene_id') if scene_id is not None: data.attrs['scene_id'] = scene_id data.attrs.update(key.to_dict()) data.attrs.pop('_FillValue', None) if 'valid_min' in data.attrs: vmin = data.attrs.pop('valid_min') vmax = data.attrs.pop('valid_max') vmin = vmin * factor + offset vmax = vmax * factor + offset data.attrs['valid_min'] = vmin data.attrs['valid_max'] = vmax return data
def _get_cf_grid_mapping_var(self): """Figure out which grid mapping should be used.""" gmaps = ['fixedgrid_projection', 'goes_imager_projection', 'lambert_projection', 'polar_projection', 'mercator_projection'] if 'grid_mapping' in self.filename_info: gmaps = [self.filename_info.get('grid_mapping')] + gmaps for grid_mapping in gmaps: if grid_mapping in return[grid_mapping] raise KeyError("Can't find grid mapping variable in SCMI file") def _get_proj4_name(self, projection): """Map CF projection name to PROJ.4 name.""" gmap_name = projection.attrs['grid_mapping_name'] proj = { 'geostationary': 'geos', 'lambert_conformal_conic': 'lcc', 'polar_stereographic': 'stere', 'mercator': 'merc', }.get(gmap_name, gmap_name) return proj def _get_proj_specific_params(self, projection): """Convert CF projection parameters to PROJ.4 dict.""" proj = self._get_proj4_name(projection) proj_dict = { 'proj': proj, 'a': float(projection.attrs['semi_major_axis']), 'b': float(projection.attrs['semi_minor_axis']), 'units': 'm', } if proj == 'geos': proj_dict['h'] = float(projection.attrs['perspective_point_height']) proj_dict['sweep'] = projection.attrs.get('sweep_angle_axis', 'y') proj_dict['lon_0'] = float(projection.attrs['longitude_of_projection_origin']) proj_dict['lat_0'] = float(projection.attrs.get('latitude_of_projection_origin', 0.0)) elif proj == 'lcc': proj_dict['lat_0'] = float(projection.attrs['standard_parallel']) proj_dict['lon_0'] = float(projection.attrs['longitude_of_central_meridian']) proj_dict['lat_1'] = float(projection.attrs['latitude_of_projection_origin']) elif proj == 'stere': proj_dict['lat_ts'] = float(projection.attrs['standard_parallel']) proj_dict['lon_0'] = float(projection.attrs['straight_vertical_longitude_from_pole']) proj_dict['lat_0'] = float(projection.attrs['latitude_of_projection_origin']) elif proj == 'merc': proj_dict['lat_ts'] = float(projection.attrs['standard_parallel']) proj_dict['lat_0'] = proj_dict['lat_ts'] proj_dict['lon_0'] = float(projection.attrs['longitude_of_projection_origin']) else: raise ValueError("Can't handle projection '{}'".format(proj)) return proj_dict def _calc_extents(self, proj_dict): """Calculate area extents from x/y variables.""" h = float(proj_dict.get('h', 1.)) # force to 64-bit float x = self['x'] y = self['y'] x_units = x.attrs.get('units', 'rad') if x_units == 'meters': h_factor = 1. factor = 1. elif x_units == 'microradian': h_factor = h factor = 1e6 else: # radians h_factor = h factor = 1. x_l = h_factor * x[0] / factor x_r = h_factor * x[-1] / factor y_l = h_factor * y[-1] / factor y_u = h_factor * y[0] / factor x_half = (x_r - x_l) / (self.ncols - 1) / 2. y_half = (y_u - y_l) / (self.nlines - 1) / 2. return x_l - x_half, y_l - y_half, x_r + x_half, y_u + y_half
[docs] def get_area_def(self, key): """Get the area definition of the data at hand.""" # FIXME: Can't we pass dataset info to the get_area_def? projection = self._get_cf_grid_mapping_var() proj_dict = self._get_proj_specific_params(projection) area_extent = self._calc_extents(proj_dict) area_name = '{}_{}'.format(self.sensor, proj_dict['proj']) return geometry.AreaDefinition( area_name, "SCMI file area", area_name, proj_dict, self.ncols, self.nlines, np.asarray(area_extent))
@property def start_time(self): """Get the start time.""" return datetime.strptime(['start_date_time'], '%Y%j%H%M%S') @property def end_time(self): """Get the end time.""" return self.start_time def __del__(self): """Delete the instance.""" try: except OSError: pass