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#!/usr/bin/env python
# -*- coding: utf-8 -*-
#
# Copyright (c) 2018-2022 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/>.
"""Spitting original Metop-C AVHRR RSR data to one file per band.
Take the 'original' Metop-C AVHRR spectral responses from the file
AVHRR_A309_METOPC_SRF_PRELIMINARY.TXT and split it in one file per band and
convert the wavenumbers to wavelengths.
"""
import os
import numpy as np
DATAFILE = "/home/a000680/data/SpectralResponses/avhrr/AVHRR_A309_METOPC_SRF_PRELIMINARY.TXT"
OUTPUT_DIR = "/home/a000680/data/SpectralResponses/avhrr"
CH1_NAME = "Metop_C_A309C001.txt"
CH2_NAME = "Metop_C_A309C002.txt"
CH3A_NAME = "Metop_C_A309C03A.txt"
CH3B_NAME = "Metop_C_A309C03B.txt"
CH4_NAME = "Metop_C_A309C004.txt"
CH5_NAME = "Metop_C_A309C005.txt"
CH_FILES = {'ch1': CH1_NAME,
'ch2': CH2_NAME,
'ch3A': CH3A_NAME,
'ch3B': CH3B_NAME,
'ch4': CH4_NAME,
'ch5': CH5_NAME
}
HEADERLINE = "Wavelegth (um) Normalized RSF"
with open(DATAFILE) as fpt:
lines = fpt.readlines()
idx = 0
for counter, channel in enumerate(['ch1', 'ch2', 'ch3A', 'ch3B', 'ch4', 'ch5']):
for line in lines[idx::]:
if line.startswith('AVHRR'):
break
idx = idx + 1
# print(lines[idx+2])
wvn = []
response = []
for line in lines[idx+2:-1]:
try:
waven, resp = line.split()
except ValueError:
break
wvn.append(float(waven))
response.append(float(resp))
idx = idx + 1
# Convert from wavenumbers (cm-1) to wavelength (microns, um)
wvl = 1./np.array(wvn) * 10000.0
response = np.array(response)
filename = os.path.join(OUTPUT_DIR, CH_FILES[channel])
data = np.stack((wvl[::-1], response[::-1]), axis=-1)
print(counter, filename)
np.savetxt(filename, data, fmt="%8.6f %10.8f", header=HEADERLINE)
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