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#!/usr/bin/env python
# -*- coding: utf-8 -*-
#
# Copyright (c) 2023 Pytroll developers
#
#
# This program 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.
#
# This program 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 this program. If not, see <http://www.gnu.org/licenses/>.
"""Read the DSCOVR-EPIC spectral response functions.
Data from the NASA Goddard website:
https://avdc.gsfc.nasa.gov/pub/DSCOVR/EPIC_Filter_Data/
"""
import logging
import os
import numpy as np
import pandas as pd
from pyspectral.raw_reader import InstrumentRSR
from pyspectral.utils import convert2hdf5 as tohdf5
LOG = logging.getLogger(__name__)
EPIC_BAND_NAMES = {'B317': 'T(317.5) %',
'B325': 'T(325) %',
'B340': 'T(340) %',
'B388': 'T(388) %',
'B443': 'T(443) %',
'B551': 'T(551) %',
'B680': 'T(680) %',
'B688': 'T(687.75) %',
'B764': 'T(764) %',
'B780': 'T(779.5) %'}
#: Default time format
_DEFAULT_TIME_FORMAT = '%Y-%m-%d %H:%M:%S'
#: Default log format
_DEFAULT_LOG_FORMAT = '[%(levelname)s: %(asctime)s : %(name)s] %(message)s'
class EpicRSR(InstrumentRSR):
"""Container for the DSCOVR EPIC relative spectral response data."""
def __init__(self, bandname, platform_name):
"""Initialize the EPIC RSR class."""
super(EpicRSR, self).__init__(
bandname, platform_name, EPIC_BAND_NAMES.keys())
self.instrument = 'epic'
self._get_options_from_config()
LOG.debug("Filename: %s", str(self.path))
if os.path.exists(self.path):
self._load()
else:
LOG.warning("Couldn't find an existing file for this band: %s",
str(self.bandname))
# To be compatible with VIIRS....
self.filename = self.requested_band_filename
self.unit = 'micrometer'
self.wavespace = 'wavelength'
def _load(self, scale=10000.0):
"""Load the EPIC relative spectral responses."""
df1 = pd.read_excel(self.path,
sheet_name='Data',
skiprows=4,
engine='openpyxl')
# Remove empty row from the data
df1.drop(df1.index[0], inplace=True)
# Column names don't match band names - so we use a dict to find correct
# columns. We also need to find the column with the wavelength data.
# This is the column before the actual RSR data for each band.
col_pos = df1.columns.get_loc(EPIC_BAND_NAMES[self.bandname])
wvl_data = df1.iloc[:, col_pos - 1]
srf_data = df1.iloc[:, col_pos]
# Not all bands have an identical number of RSR points, so we need to
# remove NaNs from the data.
wvl_data.dropna(inplace=True)
srf_data.dropna(inplace=True)
# Data is in nanometers, so we need to convert to micrometers.
self.rsr = {'wavelength': np.array(wvl_data) / 1000,
'response': np.array(srf_data) / np.nanmax(srf_data)}
if __name__ == "__main__":
import sys
LOG = logging.getLogger('epic_rsr')
handler = logging.StreamHandler(sys.stderr)
formatter = logging.Formatter(fmt=_DEFAULT_LOG_FORMAT,
datefmt=_DEFAULT_TIME_FORMAT)
handler.setFormatter(formatter)
handler.setLevel(logging.DEBUG)
LOG.setLevel(logging.DEBUG)
LOG.addHandler(handler)
for platform_name in ['DSCOVR', ]:
tohdf5(EpicRSR, platform_name, list(EPIC_BAND_NAMES.keys()))
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