#!/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/>.
"""Vaisala Global Lightning Dataset 360 reader.
Vaisala Global Lightning Dataset GLD360 is data as a service
that provides real-time lightning data for accurate and early
detection and tracking of severe weather. The data provided is
generated by a Vaisala owned and operated world-wide lightning
detection sensor network.
References:
- [GLD360] https://www.vaisala.com/en/products/data-subscriptions-and-reports/data-sets/gld360
"""
import logging
import dask.array as da
import pandas as pd
import xarray as xr
from satpy import CHUNK_SIZE
from satpy.readers.file_handlers import BaseFileHandler
logger = logging.getLogger(__name__)
[docs]class VaisalaGLD360TextFileHandler(BaseFileHandler):
"""ASCII reader for Vaisala GDL360 data."""
def __init__(self, filename, filename_info, filetype_info):
"""Initialize VaisalaGLD360TextFileHandler."""
super(VaisalaGLD360TextFileHandler, self).__init__(filename, filename_info, filetype_info)
names = ['gld360_date', 'gld360_time', 'latitude', 'longitude', 'power', 'unit']
types = ['str', 'str', 'float', 'float', 'float', 'str']
dtypes = dict(zip(names, types))
# Combine 'date' and 'time' into a datetime object
parse_dates = {'time': ['gld360_date', 'gld360_time']}
self.data = pd.read_csv(filename, delim_whitespace=True, header=None,
names=names, dtype=dtypes, parse_dates=parse_dates)
@property
def start_time(self):
"""Get start time."""
return self.data['time'].iloc[0]
@property
def end_time(self):
"""Get end time."""
return self.data['time'].iloc[-1]
[docs] def get_dataset(self, dataset_id, dataset_info):
"""Load a dataset."""
xarr = xr.DataArray(da.from_array(self.data[dataset_id['name']],
chunks=CHUNK_SIZE), dims=["y"])
# Add time, longitude, and latitude as non-dimensional y-coordinates
xarr['time'] = ('y', self.data['time'])
xarr['longitude'] = ('y', self.data['longitude'])
xarr['latitude'] = ('y', self.data['latitude'])
if dataset_id['name'] == 'power':
# Check that units in the file match the unit specified in the
# reader yaml-file
if not (self.data.unit == dataset_info['units']).all():
raise ValueError('Inconsistent units found in file!')
xarr.attrs.update(dataset_info)
return xarr