#!/usr/bin/env python
# -*- coding: utf-8 -*-
# Copyright (c) 2017 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/>.
"""ACSPO SST Reader.
See the following page for more information:
https://podaac.jpl.nasa.gov/dataset/VIIRS_NPP-OSPO-L2P-v2.3
"""
import logging
from datetime import datetime
import numpy as np
from satpy.readers.netcdf_utils import NetCDF4FileHandler
LOG = logging.getLogger(__name__)
ROWS_PER_SCAN = {
'modis': 10,
'viirs': 16,
'avhrr': None,
}
[docs]class ACSPOFileHandler(NetCDF4FileHandler):
"""ACSPO L2P SST File Reader."""
@property
def platform_name(self):
"""Get satellite name for this file's data."""
res = self['/attr/platform']
if isinstance(res, np.ndarray):
return str(res.astype(str))
return res
@property
def sensor_name(self):
"""Get instrument name for this file's data."""
res = self['/attr/sensor']
if isinstance(res, np.ndarray):
res = str(res.astype(str))
return res.lower()
[docs] def get_shape(self, ds_id, ds_info):
"""Get numpy array shape for the specified dataset.
Args:
ds_id (DataID): ID of dataset that will be loaded
ds_info (dict): Dictionary of dataset information from config file
Returns:
tuple: (rows, cols)
"""
var_path = ds_info.get('file_key', '{}'.format(ds_id['name']))
if var_path + '/shape' not in self:
# loading a scalar value
shape = 1
else:
shape = self[var_path + '/shape']
if len(shape) == 3:
if shape[0] != 1:
raise ValueError("Not sure how to load 3D Dataset with more than 1 time")
shape = shape[1:]
return shape
@staticmethod
def _parse_datetime(datestr):
return datetime.strptime(datestr, "%Y%m%dT%H%M%SZ")
@property
def start_time(self):
"""Get first observation time of data."""
return self._parse_datetime(self['/attr/time_coverage_start'])
@property
def end_time(self):
"""Get final observation time of data."""
return self._parse_datetime(self['/attr/time_coverage_end'])
[docs] def get_dataset(self, dataset_id, ds_info):
"""Load data array and metadata from file on disk."""
var_path = ds_info.get('file_key', '{}'.format(dataset_id['name']))
metadata = self.get_metadata(dataset_id, ds_info)
shape = metadata['shape']
file_shape = self[var_path + '/shape']
metadata['shape'] = shape
valid_min = self[var_path + '/attr/valid_min']
valid_max = self[var_path + '/attr/valid_max']
# no need to check fill value since we are using valid min/max
scale_factor = self.get(var_path + '/attr/scale_factor')
add_offset = self.get(var_path + '/attr/add_offset')
data = self[var_path]
data = data.rename({"ni": "x", "nj": "y"})
if isinstance(file_shape, tuple) and len(file_shape) == 3:
# can only read 3D arrays with size 1 in the first dimension
data = data[0]
data = data.where((data >= valid_min) & (data <= valid_max))
if scale_factor is not None:
data = data * scale_factor + add_offset
if ds_info.get('cloud_clear', False):
# clear-sky if bit 15-16 are 00
clear_sky_mask = (self['l2p_flags'][0] & 0b1100000000000000) != 0
clear_sky_mask = clear_sky_mask.rename({"ni": "x", "nj": "y"})
data = data.where(~clear_sky_mask)
data.attrs.update(metadata)
# Remove these attributes since they are no longer valid and can cause invalid value filling.
data.attrs.pop('_FillValue', None)
data.attrs.pop('valid_max', None)
data.attrs.pop('valid_min', None)
return data