def get_sens_from_file(std1dfile=None,
                       instrument='GNIRS',
                       star_type=None,
                       star_mag=None,
                       star_ra=None,
                       star_dec=None,
                       sens_polyorder=8,
                       mask_abs_lines=True,
                       disp=True,
                       show=True,
                       debug=False):

    # sensfunction output file name
    if '.sens.fits' in std1dfile:
        sensfile = std1dfile
    else:
        sensfile = std1dfile.replace('.fits', '.sens.fits')

    # get the pca pickle file and atmosphere model grid
    pca_file = os.path.join(basedir,
                            'Dropbox/PypeIt_Redux/qso_pca_1200_3100.pckl')

    if (instrument == 'GNIRS') or (instrument == 'NIRES') or (instrument
                                                              == 'MOSFIRE'):
        telgridfile = os.path.join(
            basedir,
            'Dropbox/PypeIt_Redux/TelFit_MaunaKea_3100_26100_R20000.fits')
    elif (instrument == 'XSHOOTER_VIS') or (instrument == 'GMOS-S'):
        telgridfile = os.path.join(
            basedir,
            'Dropbox/PypeIt_Redux/XSHOOTER/TelFit_Paranal_VIS_4900_11100_R25000.fits'
        )
    elif instrument == 'XSHOOTER_NIR':
        telgridfile = os.path.join(
            basedir,
            'Dropbox/PypeIt_Redux/XSHOOTER/TelFit_Paranal_NIR_9800_25000_R25000.fits'
        )
    else:
        telgridfile = os.path.join(
            basedir,
            'Dropbox/PypeIt_Redux/TelFit_MaunaKea_3100_26100_R20000.fits')
        msgs.warn('No telluric grid is found. Using MaunaKea!')
    msgs.info('Using {:}'.format(telgridfile))

    # run telluric.sensfunc_telluric to get the sensfile
    TelSens = telluric.sensfunc_telluric(std1dfile,
                                         telgridfile,
                                         sensfile,
                                         star_type=star_type,
                                         star_mag=star_mag,
                                         star_ra=star_ra,
                                         star_dec=star_dec,
                                         mask_abs_lines=mask_abs_lines,
                                         polyorder=sens_polyorder,
                                         disp=show,
                                         debug=debug)
    return sensfile, telgridfile
Exemple #2
0
    def compute_sensfunc(self):
        """
        Calls routine to compute the sensitivity function.

        Returns
        -------
        meta_table: astropy table
               Table containing sensfunc meta data
        out_table: astropy table
               Table containing sensfunc information.
        """

        meta_table, out_table = telluric.sensfunc_telluric(
            self.wave,
            self.counts,
            self.counts_ivar,
            self.counts_mask,
            self.meta_spec['EXPTIME'],
            self.meta_spec['AIRMASS'],
            self.std_dict,
            self.par['IR']['telgridfile'],
            polyorder=self.par['polyorder'],
            ech_orders=self.meta_spec['ECH_ORDERS'],
            sn_clip=self.par['IR']['sn_clip'],
            mask_abs_lines=self.par['mask_abs_lines'],
            # JFH Implement thease in parset?
            #delta_coeff_bounds=self.par['IR']['delta_coeff_bounds'],
            #minmax_coeff_bounds=self.par['IR']['min_max_coeff_bounds'],
            tol=self.par['IR']['tol'],
            popsize=self.par['IR']['popsize'],
            recombination=self.par['IR']['recombination'],
            polish=self.par['IR']['polish'],
            disp=self.par['IR']['disp'],
            debug=self.debug)
        # Add the algorithm to the meta_table
        meta_table['ALGORITHM'] = self.par['algorithm']
        self.steps.append(inspect.stack()[0][3])

        return meta_table, out_table
                        'Dropbox/PypeIt_Redux/qso_pca_1200_3100.pckl')
telgridfile = os.path.join(
    os.getenv('HOME'),
    'Dropbox/PypeIt_Redux/TelFit_MaunaKea_3100_26100_R20000.fits')

# TODO: set sensfile=None if you want to derive sensfunc from std1dfile
sensfile = os.path.join(
    os.getenv('HOME'), 'Dropbox/PypeIt_Redux/NIRES/GD153_sens_tell_nires.fits')
if do_sens:
    if std1dfile is None:
        msgs.error('You need either give a std1dfile to derive sensfunc')
    else:
        # run telluric.sensfunc_telluric to get the sensfile
        TelSens = telluric.sensfunc_telluric(std1dfile,
                                             telgridfile,
                                             sensfile,
                                             mask_abs_lines=True,
                                             debug=debug)

## Apply the sensfunc to all spectra (only sensfunc but not tellluric)
# TODO: change show=False to show=show
apply_sensfunc(fnames,
               sensfile,
               extinct_correct=False,
               tell_correct=False,
               debug=debug,
               show=show)

fnames_flux = [f.replace('.fits', '_flux.fits') for f in fnames]

## Let's coadd all the fluxed spectra
    dev_suite_path,
    'spec1d_cN20170331S0206-HIP62745_GNIRS_2017Mar31T083351.681.fits')
#According to Simbad HIP62745 is an A0 star with V=8.86
star_type = 'A0'
Vmag = 8.86
sensfile = os.path.join(mpia_path, 'HIP62745_sens_tell_gnirs.fits')
# telgridfile is a large grid of atmosphere models
telgridfile = os.path.join(mpia_path, 'TelFit_MaunaKea_3100_26100_R20000.fits')

# TODO: set sensfile=None if you want to derive sensfunc from std1dfile
if not os.path.exists(sensfile) or clobber:
    # Run sensfun_teluric to get the sensitivity function
    TelSens = telluric.sensfunc_telluric(std1dfile,
                                         telgridfile,
                                         sensfile,
                                         star_type=star_type,
                                         star_mag=Vmag,
                                         mask_abs_lines=True,
                                         debug=True)

## Apply the sensfunc to all spectra. This is flux calibration only, but not telluric correction.
spec1dfiles_flux = [f.replace('.fits', '_flux.fits') for f in spec1dfiles]
if not os.path.exists(spec1dfiles_flux[0]):
    apply_sensfunc(spec1dfiles,
                   sensfile,
                   extinct_correct=False,
                   tell_correct=False,
                   debug=False,
                   show=False)

# Now let's coadd the spectrum
Exemple #5
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    def compute_zeropoint(self):
        """
        Calls routine to compute the sensitivity function.

        Returns
        -------
        TelObj : :class:`~pypeit.core.telluric.Telluric`
            Best-fitting telluric model
        """
        self.telluric = telluric.sensfunc_telluric(
            self.wave_cnts,
            self.counts,
            self.counts_ivar,
            self.counts_mask,
            self.meta_spec['EXPTIME'],
            self.meta_spec['AIRMASS'],
            self.std_dict,
            self.par['IR']['telgridfile'],
            polyorder=self.par['polyorder'],
            ech_orders=self.meta_spec['ECH_ORDERS'],
            resln_guess=self.par['IR']['resln_guess'],
            resln_frac_bounds=self.par['IR']['resln_frac_bounds'],
            sn_clip=self.par['IR']['sn_clip'],
            mask_abs_lines=self.par['mask_abs_lines'],
            maxiter=self.par['IR']['maxiter'],
            lower=self.par['IR']['lower'],
            upper=self.par['IR']['upper'],
            delta_coeff_bounds=self.par['IR']['delta_coeff_bounds'],
            minmax_coeff_bounds=self.par['IR']['minmax_coeff_bounds'],
            tol=self.par['IR']['tol'],
            popsize=self.par['IR']['popsize'],
            recombination=self.par['IR']['recombination'],
            polish=self.par['IR']['polish'],
            disp=self.par['IR']['disp'],
            debug=self.debug,
            debug_init=self.debug)

        # Copy the relevant metadata
        self.std_name = self.telluric.std_name
        self.std_cal = self.telluric.std_cal
        self.std_ra = self.telluric.std_ra
        self.std_dec = self.telluric.std_dec
        self.airmass = self.telluric.airmass
        self.exptime = self.telluric.exptime

        # Instantiate the main output data table
        self.sens = self.empty_sensfunc_table(
            self.telluric.norders,
            self.telluric.wave_grid.size,
            ncoeff=self.telluric.max_ntheta_obj)

        # For stupid reasons related to how astropy tables will let me store
        # this data I have to redundantly write out the wavelength grid for each
        # order.  In actuality a variable length wavelength grid is needed which
        # is a subset of the original fixed grid, but there is no way to write
        # this to disk.  Perhaps the better solution would be a list of of
        # astropy tables, one for each order, that would save some space, since
        # we could then write out only the subset used to the table column. I'm
        # going with this inefficient approach for now, since eventually we will
        # want to create a data container for these outputs. That said, coming
        # up with that standarized model is a bit tedious given the somewhat
        # heterogenous outputs of the two different fluxing algorithms.

        # Extract and construct the relevant data using the telluric model
        self.sens['SENS_COEFF'] = self.telluric.model['OBJ_THETA']
        self.sens['WAVE_MIN'] = self.telluric.model['WAVE_MIN']
        self.sens['WAVE_MAX'] = self.telluric.model['WAVE_MAX']
        self.sens['ECH_ORDERS'] = self.telluric.model['ECH_ORDERS']
        s = self.telluric.model['IND_LOWER']
        e = self.telluric.model['IND_UPPER'] + 1
        self.sens['POLYORDER_VEC'] = self.telluric.model['POLYORDER_VEC']
        for i in range(self.norderdet):
            # Compute and assign the zeropint_data from the input data and the
            # best-fit telluric model
            self.sens['SENS_WAVE'][
                i, s[i]:e[i]] = self.telluric.wave_grid[s[i]:e[i]]
            self.sens['SENS_ZEROPOINT_GPM'][
                i, s[i]:e[i]] = self.telluric.mask_arr[s[i]:e[i], i]
            self.sens['SENS_COUNTS_PER_ANG'][
                i, s[i]:e[i]] = self.telluric.flux_arr[s[i]:e[i], i]
            N_lam = self.sens['SENS_COUNTS_PER_ANG'][i,
                                                     s[i]:e[i]] / self.exptime
            self.sens['SENS_ZEROPOINT'][i,s[i]:e[i]] \
                    = flux_calib.compute_zeropoint(self.sens['SENS_WAVE'][i,s[i]:e[i]], N_lam,
                                                   self.sens['SENS_ZEROPOINT_GPM'][i,s[i]:e[i]],
                                                   self.telluric.obj_dict_list[i]['flam_true'],
                                                   tellmodel=self.telluric.tellmodel_list[i])[0]
            # TODO: func is always 'legendre' because that is what's set by
            # sensfunc_telluric
            self.sens['SENS_ZEROPOINT_FIT'][i,s[i]:e[i]] \
                    = fitting.evaluate_fit(self.sens['SENS_COEFF'][
                                                i,:self.sens['POLYORDER_VEC'][i]+2],
                                           self.telluric.func, self.sens['SENS_WAVE'][i,s[i]:e[i]],
                                           minx=self.sens['WAVE_MIN'][i],
                                           maxx=self.sens['WAVE_MAX'][i])
            self.sens['SENS_ZEROPOINT_FIT_GPM'][
                i, s[i]:e[i]] = self.telluric.outmask_list[i]