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# -*- coding: utf-8 -*- |
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# vim:fileencoding=utf-8 |
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# |
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# Copyright (c) 2014-2017 Stefan Bender |
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# |
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# This file is part of sciapy. |
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# sciapy is free software: you can redistribute it or modify it |
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# under the terms of the GNU General Public License as published by |
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# the Free Software Foundation, version 2. |
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# See accompanying LICENSE file or http://www.gnu.org/licenses/gpl-2.0.html. |
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"""SCIAMACHY level 1c limb spectra netcdf interface |
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""" |
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from __future__ import absolute_import, division, print_function |
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import numpy as np |
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try: |
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from netCDF4 import Dataset as netcdf_file |
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_fmtargs = {"format": "NETCDF4"} |
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except ImportError: |
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try: |
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from scipy.io.netcdf import netcdf_file |
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_fmtargs = {"version": 1} |
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except ImportError: |
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from pupynere import netcdf_file |
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_fmtargs = {"version": 1} |
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from ._types import _limb_data_dtype |
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View Code Duplication |
def read_from_netcdf(self, filename): |
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"""SCIAMACHY level 1c limb scan netcdf import |
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Parameters |
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---------- |
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filename : str |
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The netcdf filename to read the data from. |
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Returns |
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------- |
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nothing |
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""" |
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import numpy.lib.recfunctions as rfn |
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ncf = netcdf_file(filename, 'r') |
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self.textheader_length = ncf.textheader_length |
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self.textheader = ncf.textheader |
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self.orbit_state = ncf.orbit_state |
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(self.orbit, self.state_in_orbit, self.state_id, |
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self.profiles_per_state, self.profile_in_state) = self.orbit_state |
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self.date = ncf.date |
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self.cent_lat_lon = ncf.cent_lat_lon |
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self.orbit_phase = ncf.orbit_phase |
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try: |
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self.nalt = ncf.dimensions['limb'].size |
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self.npix = ncf.dimensions['wavelength'].size |
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except: |
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self.nalt = ncf.dimensions['limb'] |
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self.npix = ncf.dimensions['wavelength'] |
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self.wls = ncf.variables['wavelength'][:] |
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# pre-set the limb_data |
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if self._limb_data_dtype is None: |
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self._limb_data_dtype = _limb_data_dtype.copy() |
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self.limb_data = np.zeros((self.nalt), dtype=self._limb_data_dtype) |
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self.limb_data["sub_sat_lat"] = ncf.variables['sub_sat_lat'][:] |
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self.limb_data["sub_sat_lon"] = ncf.variables['sub_sat_lon'][:] |
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self.limb_data["tp_lat"] = ncf.variables['TP latitude'][:] |
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self.limb_data["tp_lon"] = ncf.variables['TP longitude'][:] |
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self.limb_data["tp_alt"] = ncf.variables['TP altitude'][:] |
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self.limb_data["tp_sza"] = ncf.variables['TP SZA'][:] |
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self.limb_data["tp_saa"] = ncf.variables['TP SAA'][:] |
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self.limb_data["tp_los"] = ncf.variables['TP LOS Zenith'][:] |
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self.limb_data["toa_sza"] = ncf.variables['TOA SZA'][:] |
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self.limb_data["toa_saa"] = ncf.variables['TOA SAA'][:] |
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self.limb_data["toa_los"] = ncf.variables['TOA LOS Zenith'][:] |
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self.limb_data["sat_sza"] = ncf.variables['SAT SZA'][:] |
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self.limb_data["sat_saa"] = ncf.variables['SAT SAA'][:] |
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self.limb_data["sat_los"] = ncf.variables['SAT LOS Zenith'][:] |
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self.limb_data["sat_alt"] = ncf.variables['SAT altitude'][:] |
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self.limb_data["earth_rad"] = ncf.variables['earthradius'][:] |
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tmp_rad_arr = list(ncf.variables['radiance'][:]) |
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tmp_err_arr = list(ncf.variables['radiance errors'][:]) |
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# save to limb_data recarray |
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rads = np.rec.fromarrays([tmp_rad_arr], |
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dtype=np.dtype([("rad", 'f4', (self.npix,))])) |
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errs = np.rec.fromarrays([tmp_err_arr], |
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dtype=np.dtype([("err", 'f4', (self.npix,))])) |
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self.limb_data = rfn.merge_arrays([self.limb_data, rads, errs], |
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usemask=False, asrecarray=True, flatten=True) |
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self._limb_data_dtype = self.limb_data.dtype |
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ncf.close() |
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View Code Duplication |
def write_to_netcdf(self, filename): |
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"""SCIAMACHY level 1c limb scan netcdf export |
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Parameters |
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---------- |
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filename : str |
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The netcdf filename to write the data to. |
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Returns |
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------- |
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nothing |
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""" |
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ncf = netcdf_file(filename, 'w', **_fmtargs) |
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ncf.textheader_length = self.textheader_length |
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ncf.textheader = self.textheader |
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ncf.orbit_state = self.orbit_state |
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ncf.date = self.date |
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ncf.cent_lat_lon = self.cent_lat_lon |
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ncf.orbit_phase = self.orbit_phase |
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ncf.createDimension('limb', self.nalt) |
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ncf.createDimension('wavelength', self.npix) |
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wavs = ncf.createVariable('wavelength', np.dtype('float32').char, ('wavelength',)) |
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wavs.units = 'nm' |
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wavs[:] = np.asarray(self.wls) |
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sslat = ncf.createVariable('sub_sat_lat', np.dtype('float32').char, ('limb',)) |
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sslat.units = 'deg' |
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sslat[:] = np.asarray(self.limb_data["sub_sat_lat"]) |
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sslon = ncf.createVariable('sub_sat_lon', np.dtype('float32').char, ('limb',)) |
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sslon.units = 'deg' |
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sslon[:] = np.asarray(self.limb_data["sub_sat_lon"]) |
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tp_lats = ncf.createVariable('TP latitude', np.dtype('float32').char, ('limb',)) |
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tp_lats.units = 'deg' |
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tp_lats[:] = np.asarray(self.limb_data["tp_lat"]) |
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tp_lons = ncf.createVariable('TP longitude', np.dtype('float32').char, ('limb',)) |
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tp_lons.units = 'deg' |
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tp_lons[:] = np.asarray(self.limb_data["tp_lon"]) |
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tp_alts = ncf.createVariable('TP altitude', np.dtype('float32').char, ('limb',)) |
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tp_alts.units = 'km' |
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tp_alts[:] = np.asarray(self.limb_data["tp_alt"]) |
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tp_szas = ncf.createVariable('TP SZA', np.dtype('float32').char, ('limb',)) |
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tp_szas.units = 'deg' |
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tp_szas[:] = np.asarray(self.limb_data["tp_sza"]) |
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tp_saas = ncf.createVariable('TP SAA', np.dtype('float32').char, ('limb',)) |
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tp_saas.units = 'deg' |
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tp_saas[:] = np.asarray(self.limb_data["tp_saa"]) |
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tp_los_zeniths = ncf.createVariable('TP LOS Zenith', np.dtype('float32').char, ('limb',)) |
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tp_los_zeniths.units = 'deg' |
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tp_los_zeniths[:] = np.asarray(self.limb_data["tp_los"]) |
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toa_szas = ncf.createVariable('TOA SZA', np.dtype('float32').char, ('limb',)) |
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toa_szas.units = 'deg' |
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toa_szas[:] = np.asarray(self.limb_data["toa_sza"]) |
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toa_saas = ncf.createVariable('TOA SAA', np.dtype('float32').char, ('limb',)) |
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toa_saas.units = 'deg' |
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toa_saas[:] = np.asarray(self.limb_data["toa_saa"]) |
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toa_los_zeniths = ncf.createVariable('TOA LOS Zenith', np.dtype('float32').char, ('limb',)) |
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toa_los_zeniths.units = 'deg' |
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toa_los_zeniths[:] = np.asarray(self.limb_data["toa_los"]) |
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sat_szas = ncf.createVariable('SAT SZA', np.dtype('float32').char, ('limb',)) |
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sat_szas.units = 'deg' |
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sat_szas[:] = np.asarray(self.limb_data["sat_sza"]) |
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sat_saas = ncf.createVariable('SAT SAA', np.dtype('float32').char, ('limb',)) |
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sat_saas.units = 'deg' |
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sat_saas[:] = np.asarray(self.limb_data["sat_saa"]) |
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sat_los_zeniths = ncf.createVariable('SAT LOS Zenith', np.dtype('float32').char, ('limb',)) |
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sat_los_zeniths.units = 'deg' |
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sat_los_zeniths[:] = np.asarray(self.limb_data["sat_los"]) |
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sat_alts = ncf.createVariable('SAT altitude', np.dtype('float32').char, ('limb',)) |
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sat_alts.units = 'km' |
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sat_alts[:] = np.asarray(self.limb_data["sat_alt"]) |
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eradii_alts = ncf.createVariable('earthradius', np.dtype('float32').char, ('limb',)) |
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eradii_alts.units = 'km' |
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eradii_alts[:] = np.asarray(self.limb_data["earth_rad"]) |
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rads = ncf.createVariable('radiance', np.dtype('float32').char, |
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('limb', 'wavelength'), zlib=True, complevel=1) |
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errs = ncf.createVariable('radiance errors', np.dtype('float32').char, |
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('limb', 'wavelength'), zlib=True, complevel=1) |
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rads.units = 'ph / s / cm^2 / nm' |
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errs.units = 'ph / s / cm^2 / nm' |
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rads[:] = np.asarray(self.limb_data["rad"]).reshape(self.nalt, self.npix) |
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errs[:] = np.asarray(self.limb_data["err"]).reshape(self.nalt, self.npix) |
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ncf.close() |
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st-bender /
sciapy
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