Add Himawari-8 AHI L2 reader

satpy/etc/readers/ahi_l2_nc.yaml

@@ -0,0 +1,30 @@
+reader:
+    description: Himawari-8 AHI Level 2 NetCDF reader
+    name: ahi_l2_nc
+    reader: !!python/name:satpy.readers.yaml_reader.FileYAMLReader
+    sensors: [ahi]
+
+file_types:
+    ahi_l2_arp:
+        # Ex: NC_H08_20190807_0600_L2ARP021_FLDK.02401_02401.nc
+        file_reader: !!python/name:satpy.readers.ahi_l2_nc.AHIL2FileHandler
+        file_patterns:
+            - 'NC_{platform_shortname:3s}_{start_time:%Y%m%d_%H%M}_L2ARP{version:s}_{observation_type:s}.{pixel_number:s}_{line_number:s}.nc'
+    ahi_l2_clp:
+        # Ex: NC_H08_20190807_0600_L2CLP010_FLDK.02401_02401.nc
+        file_reader: !!python/name:satpy.readers.ahi_l2_nc.AHIL2FileHandler
+        file_patterns:
+            - 'NC_{platform_shortname:3s}_{start_time:%Y%m%d_%H%M}_L2CLP{version:s}_{observation_type:s}.{pixel_number:s}_{line_number:s}.nc'
+    ahi_l2_rfl:
+        # Ex: H08_20190807_0600_rFL010_FLDK.02701_02601.nc
+        file_reader: !!python/name:satpy.readers.ahi_l2_nc.AHIL2FileHandler
+        file_patterns:
+            ['{platform_shortname:3s}_{start_time:%Y%m%d_%H%M}_rFL{version:s}_{observation_type:s}.{pixel_number:s}_{line_number:s}.nc',
+             '{platform_shortname:3s}_{start_time:%Y%m%d_%H%M}_RFL{version:s}_{observation_type:s}.{pixel_number:s}_{line_number:s}.nc']
+    ahi_l2_sst:
+        # Ex: 20190807060000-JAXA-L2P_GHRSST-SSTskin-H08_AHI-v1.2-v02.0-fv01.0.nc
+        file_reader: !!python/name:satpy.readers.ahi_l2_nc.AHIL2FileHandler
+        file_patterns:
+            - '{start_time:%Y%m%d%H%M%S}-JAXA-L2P_GHRSST-SSTskin-{platform_shortname:3s}_{sensor:s}-{version:s}-v02.0-{file_version:s}.nc'
+
+datasets: {}

satpy/readers/ahi_l2_nc.py

@@ -0,0 +1,145 @@
+#!/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 <http://www.gnu.org/licenses/>.
+
+"""Advanced Himawari Imager (AHI) reader for the Level 2 NC format
+
+Ref:
+    ftp://ftp.ptree.jaxa.jp/pub/README_HimawariGeo_en.txt
+"""
+
+from satpy.readers.netcdf_utils import NetCDF4FileHandler, netCDF4
+import logging
+import numpy as np
+
+logger = logging.getLogger(__name__)
+
+
+class AHIL2FileHandler(NetCDF4FileHandler):
+    """File handler for AHI L2 netCDF files."""
+    def available_datasets(self, configured_datasets=None):
+        """Automatically determine datasets provided by this file."""
+        logger.debug('Available_datasets begin...')
+        handled_variables = set()
+
+        for is_avail, ds_info in (configured_datasets or []):
+            # some other file handler knows how to load this
+            if is_avail is not None:
+                yield is_avail, ds_info
+
+            var_name = ds_info.get('file_key', ds_info['name'])
+            logger.debug("Evaluating previously configured variable: %s", var_name)
+            matches = self.file_type_matches(ds_info['file_type'])
+
+            if (matches and var_name in self):
+                logger.debug('Handling previously configured variable: %s', var_name)
+                handled_variables.add(var_name)
+                new_info = ds_info.copy()  # don't mess up the above yielded
+                yield True, new_info
+            elif is_avail is None:
+                # if we didn't know how to handle this dataset and no one else did
+                # then we should keep it going down the chain
+                yield is_avail, ds_info
+
+        # Iterate over dataset contents
+        for var_name, val in self.file_content.items():
+            # Only evaluate variables
+            if isinstance(val, netCDF4.Variable):
+                logger.debug('Found valid additional dataset: %s', var_name)
+
+                # Skip anything we have already configured
+                if (var_name in handled_variables):
+                    logger.debug('Already handled, skipping: %s', var_name)
+                    continue
+                handled_variables.add(var_name)
+
+                # Create new ds_info object
+                new_info = {
+                    'name': var_name,
+                    'file_key': var_name,
+                    'file_type': self.filetype_info['file_type'],
+                    'resolution': None,
+                }
+                yield True, new_info
+
+    def get_metadata(self, data, ds_info):
+        """Get metadata."""
+        metadata = {}
+        metadata.update(data.attrs)
+        metadata.update(ds_info)
+        metadata.update({
+            'platform_shortname': self.platform_shortname,
+            'sensor': 'ahi',
+            'start_time': self.start_time,
+        })
+
+        return metadata
+
+    def get_dataset(self, ds_id, ds_info):
+        """Get dataset."""
+        logger.debug('Getting data for: %s', ds_id.name)
+        file_key = ds_info.get('file_key', ds_id.name)
+
+        # read data and attributes
+        data = self[file_key]
+        data.attrs = self.get_metadata(data, ds_info)
+
+        scale_factor = data.attrs.get('scale_factor')
+        add_offset = data.attrs.get('add_offset')
+        valid_min = data.attrs.get('valid_min')
+        valid_max = data.attrs.get('valid_max')
+        fill_value = data.attrs.get('missing_value', np.float32(np.nan))
+        data = data.squeeze()
+
+        # preserve integer data types if possible
+        if np.issubdtype(data.dtype, np.integer):
+            new_fill = fill_value
+        else:
+            new_fill = np.float32(np.nan)
+            data.attrs.pop('missing_value', None)
+        good_mask = data != fill_value
+
+        # scale data
+        if scale_factor is not None:
+            data.data = data.data * scale_factor + add_offset
+
+        # mask data
+        data = data.where(good_mask, new_fill)
+        data = data.where((data >= valid_min) &
+                          (data <= valid_max))
+
+        return data
+
+    @property
+    def start_time(self):
+        """Get start time."""
+        return self.filename_info['start_time']
+
+    @property
+    def platform_shortname(self):
+        """Get platform shortname."""
+        return self.filename_info['platform_shortname']
+
+    @property
+    def sensor(self):
+        """Assign sensor."""
+        return 'ahi'
+
+    @property
+    def sensor_names(self):
+        """Assign sensor set."""
+        return 'ahi'