Пример #1
0
    def make_frameqa(self, make_plots=False, clobber=False):
        """ Work through the exposures and make QA for all frames

        Parameters:
            make_plots: bool, optional
              Remake the plots too?
            clobber: bool, optional
        Returns:

        """
        # imports
        from desispec.qa.qa_frame import qaframe_from_frame
        from desispec.io.qa import qafile_from_framefile

        # Loop on nights
        for night in self.mexp_dict.keys():
            for exposure in self.mexp_dict[night]:
                # Object only??
                for camera, frame_fil in self.mexp_dict[night][exposure].items(
                ):
                    # Load frame
                    qafile, _ = qafile_from_framefile(
                        frame_fil, qaprod_dir=self.qaprod_dir)
                    if os.path.isfile(qafile) and (not clobber) and (
                            not make_plots):
                        continue
                    qaframe_from_frame(frame_fil,
                                       make_plots=make_plots,
                                       qaprod_dir=self.qaprod_dir,
                                       clobber=clobber)
Пример #2
0
    def build_qa_data(self, rebuild=False):
        """
        Build or re-build QA data


        Args:
            rebuild: bool, optional

        :return:
            Data is loaded in self.data
        """
        frame_files = desiio.get_files(filetype='frame',
                                       night=self.night,
                                       expid=self.expid,
                                       specprod_dir=self.specprod_dir)
        # Load into frames
        for camera, frame_file in frame_files.items():
            if rebuild:
                qafile, qatype = qafile_from_framefile(frame_file)
                if os.path.isfile(qafile):
                    os.remove(qafile)
            # Generate qaframe (and figures?)
            _ = qaframe_from_frame(frame_file,
                                   specprod_dir=self.specprod_dir,
                                   make_plots=False)
        # Reload
        self.load_qa_data()
Пример #3
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    def make_frameqa(self, make_plots=False, clobber=False):
        """ Work through the exposures and make QA for all frames

        Parameters:
            make_plots: bool, optional
              Remake the plots too?
            clobber: bool, optional
        Returns:

        """
        # imports
        from desispec.qa.qa_frame import qaframe_from_frame
        from desispec.io.qa import qafile_from_framefile

        # Loop on nights
        for night in self.mexp_dict.keys():
            for exposure in self.mexp_dict[night]:
                # Object only??
                for camera,frame_fil in self.mexp_dict[night][exposure].items():
                    # Load frame
                    qafile, _ = qafile_from_framefile(frame_fil, qaprod_dir=self.qaprod_dir)
                    if os.path.isfile(qafile) and (not clobber) and (not make_plots):
                        continue
                    qaframe_from_frame(frame_fil, make_plots=make_plots, qaprod_dir=self.qaprod_dir,
                                       clobber=clobber)
Пример #4
0
    def make_frameqa(self,
                     make_plots=False,
                     clobber=False,
                     restrict_nights=None):
        """ Work through the exposures and make QA for all frames

        Parameters:
            make_plots: bool, optional
              Remake the plots too?
            clobber: bool, optional
            restrict_nights: list, optional
              Only perform QA on the input list of nights
        Returns:

        """
        # imports
        from desispec.qa.qa_frame import qaframe_from_frame
        from desispec.io.qa import qafile_from_framefile

        # Loop on nights
        for night in self.mexp_dict.keys():
            if restrict_nights is not None:
                if night not in restrict_nights:
                    continue
            for exposure in self.mexp_dict[night]:
                # Object only??
                for camera, frame_fil in self.mexp_dict[night][exposure].items(
                ):
                    # QA filename
                    qafile, _ = qafile_from_framefile(
                        frame_fil, qaprod_dir=self.qaprod_dir)
                    if os.path.isfile(qafile) and (not clobber) and (
                            not make_plots):
                        continue
                    # Make QA
                    qaframe_from_frame(frame_fil,
                                       make_plots=make_plots,
                                       qaprod_dir=self.qaprod_dir,
                                       clobber=clobber,
                                       specprod_dir=self.specprod_dir)
Пример #5
0
def qaframe_from_frame(frame_file,
                       specprod_dir=None,
                       make_plots=False,
                       qaprod_dir=None,
                       output_dir=None,
                       clobber=True):
    """  Generate a qaframe object from an input frame_file name (and night)

    Write QA to disk
    Will also make plots if directed
    Args:
        frame_file: str
        specprod_dir: str, optional
        qa_dir: str, optional -- Location of QA
        make_plots: bool, optional
        output_dir: str, optional

    Returns:

    """
    import glob
    import os

    from desispec.io import read_frame
    from desispec.io import meta
    from desispec.io.qa import load_qa_frame, write_qa_frame
    from desispec.io.qa import qafile_from_framefile
    from desispec.io.frame import search_for_framefile
    from desispec.io.fiberflat import read_fiberflat
    from desispec.fiberflat import apply_fiberflat
    from desispec.qa import qa_plots
    from desispec.io.sky import read_sky
    from desispec.io.fluxcalibration import read_flux_calibration
    from desispec.qa import qa_plots_ql

    if '/' in frame_file:  # If present, assume full path is used here
        pass
    else:  # Find the frame file in the desispec hierarchy?
        frame_file = search_for_framefile(frame_file)

    # Load frame
    frame = read_frame(frame_file)
    frame_meta = frame.meta
    night = frame_meta['NIGHT'].strip()
    camera = frame_meta['CAMERA'].strip()
    expid = frame_meta['EXPID']
    spectro = int(frame_meta['CAMERA'][-1])

    # Filename
    qafile, qatype = qafile_from_framefile(frame_file,
                                           qaprod_dir=qaprod_dir,
                                           output_dir=output_dir)
    if os.path.isfile(qafile) and (not clobber):
        write = False
    else:
        write = True
    qaframe = load_qa_frame(qafile, frame, flavor=frame.meta['FLAVOR'])
    # Flat QA
    if frame_meta['FLAVOR'] in ['flat']:
        fiberflat_fil = meta.findfile('fiberflat',
                                      night=night,
                                      camera=camera,
                                      expid=expid,
                                      specprod_dir=specprod_dir)
        try:  # Backwards compatibility
            fiberflat = read_fiberflat(fiberflat_fil)
        except FileNotFoundError:
            fiberflat_fil = fiberflat_fil.replace('exposures', 'calib2d')
            path, basen = os.path.split(fiberflat_fil)
            path, _ = os.path.split(path)
            fiberflat_fil = os.path.join(path, basen)
            fiberflat = read_fiberflat(fiberflat_fil)
        if qaframe.run_qa('FIBERFLAT', (frame, fiberflat), clobber=clobber):
            write = True
        if make_plots:
            # Do it
            qafig = meta.findfile('qa_flat_fig',
                                  night=night,
                                  camera=camera,
                                  expid=expid,
                                  qaprod_dir=qaprod_dir,
                                  specprod_dir=specprod_dir,
                                  outdir=output_dir)
            if (not os.path.isfile(qafig)) or clobber:
                qa_plots.frame_fiberflat(qafig, qaframe, frame, fiberflat)
    # SkySub QA
    if qatype == 'qa_data':
        sky_fil = meta.findfile('sky',
                                night=night,
                                camera=camera,
                                expid=expid,
                                specprod_dir=specprod_dir)

        fiberflat_fil = meta.findfile('fiberflatnight',
                                      night=night,
                                      camera=camera)
        if not os.path.exists(fiberflat_fil):
            # Backwards compatibility (for now)
            dummy_fiberflat_fil = meta.findfile(
                'fiberflat',
                night=night,
                camera=camera,
                expid=expid,
                specprod_dir=specprod_dir)  # This is dummy
            path = os.path.dirname(os.path.dirname(dummy_fiberflat_fil))
            fiberflat_files = glob.glob(
                os.path.join(path, '*', 'fiberflat-' + camera + '*.fits'))
            if len(fiberflat_files) == 0:
                path = path.replace('exposures', 'calib2d')
                path, _ = os.path.split(path)  # Remove night
                fiberflat_files = glob.glob(
                    os.path.join(path, 'fiberflat-' + camera + '*.fits'))

            # Sort and take the first (same as old pipeline)
            fiberflat_files.sort()
            fiberflat_fil = fiberflat_files[0]

        fiberflat = read_fiberflat(fiberflat_fil)
        apply_fiberflat(frame, fiberflat)
        # Load sky model and run
        try:
            skymodel = read_sky(sky_fil)
        except FileNotFoundError:
            warnings.warn(
                "Sky file {:s} not found.  Skipping..".format(sky_fil))
        else:
            if qaframe.run_qa('SKYSUB', (frame, skymodel), clobber=clobber):
                write = True
            if make_plots:
                qafig = meta.findfile('qa_sky_fig',
                                      night=night,
                                      camera=camera,
                                      expid=expid,
                                      specprod_dir=specprod_dir,
                                      outdir=output_dir,
                                      qaprod_dir=qaprod_dir)
                qafig2 = meta.findfile('qa_skychi_fig',
                                       night=night,
                                       camera=camera,
                                       expid=expid,
                                       specprod_dir=specprod_dir,
                                       outdir=output_dir,
                                       qaprod_dir=qaprod_dir)
                if (not os.path.isfile(qafig)) or clobber:
                    qa_plots.frame_skyres(qafig, frame, skymodel, qaframe)
                #qa_plots.frame_skychi(qafig2, frame, skymodel, qaframe)

    # S/N QA on cframe
    if qatype == 'qa_data':
        # cframe
        cframe_file = frame_file.replace('frame-', 'cframe-')
        cframe = read_frame(cframe_file)
        if qaframe.run_qa('S2N', (cframe, ), clobber=clobber):
            write = True
        # Figure?
        if make_plots:
            s2n_dict = copy.deepcopy(qaframe.qa_data['S2N'])
            qafig = meta.findfile('qa_s2n_fig',
                                  night=night,
                                  camera=camera,
                                  expid=expid,
                                  specprod_dir=specprod_dir,
                                  outdir=output_dir,
                                  qaprod_dir=qaprod_dir)
            #badfibs = np.where(np.isnan(s2n_dict['METRICS']['MEDIAN_SNR']))[0].tolist()
            #sci_idx = s2n_dict['METRICS']['OBJLIST'].index('SCIENCE')
            coeff = s2n_dict['METRICS']['FITCOEFF_TGT']  #[sci_idx]
            # Add an item or two for the QL method
            s2n_dict['CAMERA'] = camera
            s2n_dict['EXPID'] = expid
            s2n_dict['PANAME'] = 'SNRFit'
            s2n_dict['METRICS']['RA'] = frame.fibermap['FIBER_RA']
            s2n_dict['METRICS']['DEC'] = frame.fibermap['FIBER_DEC']
            objlist = s2n_dict['METRICS']['OBJLIST']
            # Deal with YAML list instead of ndarray
            s2n_dict['METRICS']['MEDIAN_SNR'] = np.array(
                s2n_dict['METRICS']['MEDIAN_SNR'])
            # Generate
            if (not os.path.isfile(qafig)) or clobber:
                qa_plots_ql.plot_SNR(s2n_dict, qafig, objlist,
                                     [[]] * len(objlist), coeff)

    # FluxCalib QA
    if qatype == 'qa_data':
        # Standard stars
        stdstar_fil = meta.findfile('stdstars',
                                    night=night,
                                    camera=camera,
                                    expid=expid,
                                    specprod_dir=specprod_dir,
                                    spectrograph=spectro)
        # try:
        #    model_tuple=read_stdstar_models(stdstar_fil)
        # except FileNotFoundError:
        #    warnings.warn("Standard star file {:s} not found.  Skipping..".format(stdstar_fil))
        # else:
        flux_fil = meta.findfile('calib',
                                 night=night,
                                 camera=camera,
                                 expid=expid,
                                 specprod_dir=specprod_dir)
        try:
            fluxcalib = read_flux_calibration(flux_fil)
        except FileNotFoundError:
            warnings.warn(
                "Flux file {:s} not found.  Skipping..".format(flux_fil))
        else:
            if qaframe.run_qa(
                    'FLUXCALIB', (frame, fluxcalib),
                    clobber=clobber):  # , model_tuple))#, indiv_stars))
                write = True
            if make_plots:
                qafig = meta.findfile('qa_flux_fig',
                                      night=night,
                                      camera=camera,
                                      expid=expid,
                                      specprod_dir=specprod_dir,
                                      outdir=output_dir,
                                      qaprod_dir=qaprod_dir)
                if (not os.path.isfile(qafig)) or clobber:
                    qa_plots.frame_fluxcalib(qafig, qaframe, frame,
                                             fluxcalib)  # , model_tuple)
    # Write
    if write:
        write_qa_frame(qafile, qaframe, verbose=True)
    return qaframe
Пример #6
0
def qaframe_from_frame(frame_file,
                       specprod_dir=None,
                       make_plots=False,
                       qaprod_dir=None,
                       output_dir=None,
                       clobber=True):
    """  Generate a qaframe object from an input frame_file name (and night)

    Write QA to disk
    Will also make plots if directed
    Args:
        frame_file: str
        specprod_dir: str, optional
        qa_dir: str, optional -- Location of QA
        make_plots: bool, optional
        output_dir: str, optional

    Returns:

    """
    import glob
    import os

    from desispec.io import read_frame
    from desispec.io import meta
    from desispec.io.qa import load_qa_frame, write_qa_frame
    from desispec.io.qa import qafile_from_framefile
    from desispec.io.frame import search_for_framefile
    from desispec.io.fiberflat import read_fiberflat
    from desispec.fiberflat import apply_fiberflat
    from desispec.qa import qa_plots
    from desispec.io.sky import read_sky
    from desispec.io.fluxcalibration import read_flux_calibration

    if '/' in frame_file:  # If present, assume full path is used here
        pass
    else:  # Find the frame file in the desispec hierarchy?
        frame_file = search_for_framefile(frame_file)

    # Load frame
    frame = read_frame(frame_file)
    frame_meta = frame.meta
    night = frame_meta['NIGHT'].strip()
    camera = frame_meta['CAMERA'].strip()
    expid = frame_meta['EXPID']
    spectro = int(frame_meta['CAMERA'][-1])

    # Filename
    qafile, qatype = qafile_from_framefile(frame_file,
                                           qaprod_dir=qaprod_dir,
                                           output_dir=output_dir)
    qaframe = load_qa_frame(qafile, frame, flavor=frame.meta['FLAVOR'])
    # Flat QA
    if frame_meta['FLAVOR'] in ['flat']:
        fiberflat_fil = meta.findfile('fiberflat',
                                      night=night,
                                      camera=camera,
                                      expid=expid,
                                      specprod_dir=specprod_dir)
        try:  # Backwards compatibility
            fiberflat = read_fiberflat(fiberflat_fil)
        except FileNotFoundError:
            fiberflat_fil = fiberflat_fil.replace('exposures', 'calib2d')
            path, basen = os.path.split(fiberflat_fil)
            path, _ = os.path.split(path)
            fiberflat_fil = os.path.join(path, basen)
            fiberflat = read_fiberflat(fiberflat_fil)
        qaframe.run_qa('FIBERFLAT', (frame, fiberflat), clobber=clobber)
        if make_plots:
            # Do it
            qafig = meta.findfile('qa_flat_fig',
                                  night=night,
                                  camera=camera,
                                  expid=expid,
                                  specprod_dir=specprod_dir,
                                  outdir=output_dir)
            qa_plots.frame_fiberflat(qafig, qaframe, frame, fiberflat)
    # SkySub QA
    if qatype == 'qa_data':
        sky_fil = meta.findfile('sky',
                                night=night,
                                camera=camera,
                                expid=expid,
                                specprod_dir=specprod_dir)

        fiberflat_fil = meta.findfile('fiberflatnight',
                                      night=night,
                                      camera=camera)
        if not os.path.exists(fiberflat_fil):
            # Backwards compatibility (for now)
            dummy_fiberflat_fil = meta.findfile(
                'fiberflat',
                night=night,
                camera=camera,
                expid=expid,
                specprod_dir=specprod_dir)  # This is dummy
            path = os.path.dirname(os.path.dirname(dummy_fiberflat_fil))
            fiberflat_files = glob.glob(
                os.path.join(path, '*', 'fiberflat-' + camera + '*.fits'))
            if len(fiberflat_files) == 0:
                path = path.replace('exposures', 'calib2d')
                path, _ = os.path.split(path)  # Remove night
                fiberflat_files = glob.glob(
                    os.path.join(path, 'fiberflat-' + camera + '*.fits'))

            # Sort and take the first (same as old pipeline)
            fiberflat_files.sort()
            fiberflat_fil = fiberflat_files[0]

        fiberflat = read_fiberflat(fiberflat_fil)
        apply_fiberflat(frame, fiberflat)
        # Load sky model and run
        try:
            skymodel = read_sky(sky_fil)
        except FileNotFoundError:
            warnings.warn(
                "Sky file {:s} not found.  Skipping..".format(sky_fil))
        else:
            qaframe.run_qa('SKYSUB', (frame, skymodel), clobber=clobber)
            if make_plots:
                qafig = meta.findfile('qa_sky_fig',
                                      night=night,
                                      camera=camera,
                                      expid=expid,
                                      specprod_dir=specprod_dir,
                                      outdir=output_dir)
                qafig2 = meta.findfile('qa_skychi_fig',
                                       night=night,
                                       camera=camera,
                                       expid=expid,
                                       specprod_dir=specprod_dir,
                                       outdir=output_dir)
                qa_plots.frame_skyres(qafig, frame, skymodel, qaframe)
                #qa_plots.frame_skychi(qafig2, frame, skymodel, qaframe)
    # FluxCalib QA
    if qatype == 'qa_data':
        # Standard stars
        stdstar_fil = meta.findfile('stdstars',
                                    night=night,
                                    camera=camera,
                                    expid=expid,
                                    specprod_dir=specprod_dir,
                                    spectrograph=spectro)
        # try:
        #    model_tuple=read_stdstar_models(stdstar_fil)
        # except FileNotFoundError:
        #    warnings.warn("Standard star file {:s} not found.  Skipping..".format(stdstar_fil))
        # else:
        flux_fil = meta.findfile('calib',
                                 night=night,
                                 camera=camera,
                                 expid=expid,
                                 specprod_dir=specprod_dir)
        try:
            fluxcalib = read_flux_calibration(flux_fil)
        except FileNotFoundError:
            warnings.warn(
                "Flux file {:s} not found.  Skipping..".format(flux_fil))
        else:
            qaframe.run_qa(
                'FLUXCALIB',
                (frame, fluxcalib))  # , model_tuple))#, indiv_stars))
            if make_plots:
                qafig = meta.findfile('qa_flux_fig',
                                      night=night,
                                      camera=camera,
                                      expid=expid,
                                      specprod_dir=specprod_dir,
                                      outdir=output_dir)
                qa_plots.frame_fluxcalib(qafig, qaframe, frame,
                                         fluxcalib)  # , model_tuple)
    # Write
    write_qa_frame(qafile, qaframe, verbose=True)
    return qaframe
Пример #7
0
def qaframe_from_frame(frame_file, specprod_dir=None, make_plots=False, qaprod_dir=None,
                       output_dir=None, clobber=True):
    """  Generate a qaframe object from an input frame_file name (and night)

    Write QA to disk
    Will also make plots if directed
    Args:
        frame_file: str
        specprod_dir: str, optional
        qa_dir: str, optional -- Location of QA
        make_plots: bool, optional
        output_dir: str, optional

    Returns:

    """
    import glob
    import os

    from desispec.io import read_frame
    from desispec.io import meta
    from desispec.io.qa import load_qa_frame, write_qa_frame
    from desispec.io.qa import qafile_from_framefile
    from desispec.io.frame import search_for_framefile
    from desispec.io.fiberflat import read_fiberflat
    from desispec.fiberflat import apply_fiberflat
    from desispec.qa import qa_plots
    from desispec.io.sky import read_sky
    from desispec.io.fluxcalibration import read_flux_calibration
    from desispec.qa import qa_plots_ql

    if '/' in frame_file:  # If present, assume full path is used here
        pass
    else: # Find the frame file in the desispec hierarchy?
        frame_file = search_for_framefile(frame_file)

    # Load frame
    frame = read_frame(frame_file)
    frame_meta = frame.meta
    night = frame_meta['NIGHT'].strip()
    camera = frame_meta['CAMERA'].strip()
    expid = frame_meta['EXPID']
    spectro = int(frame_meta['CAMERA'][-1])

    # Filename
    qafile, qatype = qafile_from_framefile(frame_file, qaprod_dir=qaprod_dir, output_dir=output_dir)
    if os.path.isfile(qafile) and (not clobber):
        write = False
    else:
        write = True
    qaframe = load_qa_frame(qafile, frame, flavor=frame.meta['FLAVOR'])
    # Flat QA
    if frame_meta['FLAVOR'] in ['flat']:
        fiberflat_fil = meta.findfile('fiberflat', night=night, camera=camera, expid=expid,
                                      specprod_dir=specprod_dir)
        try: # Backwards compatibility
            fiberflat = read_fiberflat(fiberflat_fil)
        except FileNotFoundError:
            fiberflat_fil = fiberflat_fil.replace('exposures', 'calib2d')
            path, basen = os.path.split(fiberflat_fil)
            path,_ = os.path.split(path)
            fiberflat_fil = os.path.join(path, basen)
            fiberflat = read_fiberflat(fiberflat_fil)
        if qaframe.run_qa('FIBERFLAT', (frame, fiberflat), clobber=clobber):
            write = True
        if make_plots:
            # Do it
            qafig = meta.findfile('qa_flat_fig', night=night, camera=camera, expid=expid,
                                  qaprod_dir=qaprod_dir, specprod_dir=specprod_dir, outdir=output_dir)
            if (not os.path.isfile(qafig)) or clobber:
                qa_plots.frame_fiberflat(qafig, qaframe, frame, fiberflat)
    # SkySub QA
    if qatype == 'qa_data':
        sky_fil = meta.findfile('sky', night=night, camera=camera, expid=expid, specprod_dir=specprod_dir)

        fiberflat_fil = meta.findfile('fiberflatnight', night=night, camera=camera)
        if not os.path.exists(fiberflat_fil):
            # Backwards compatibility (for now)
            dummy_fiberflat_fil = meta.findfile('fiberflat', night=night, camera=camera, expid=expid,
                                            specprod_dir=specprod_dir) # This is dummy
            path = os.path.dirname(os.path.dirname(dummy_fiberflat_fil))
            fiberflat_files = glob.glob(os.path.join(path,'*','fiberflat-'+camera+'*.fits'))
            if len(fiberflat_files) == 0:
                path = path.replace('exposures', 'calib2d')
                path,_ = os.path.split(path) # Remove night
                fiberflat_files = glob.glob(os.path.join(path,'fiberflat-'+camera+'*.fits'))

            # Sort and take the first (same as old pipeline)
            fiberflat_files.sort()
            fiberflat_fil = fiberflat_files[0]

        fiberflat = read_fiberflat(fiberflat_fil)
        apply_fiberflat(frame, fiberflat)
        # Load sky model and run
        try:
            skymodel = read_sky(sky_fil)
        except FileNotFoundError:
            warnings.warn("Sky file {:s} not found.  Skipping..".format(sky_fil))
        else:
            if qaframe.run_qa('SKYSUB', (frame, skymodel), clobber=clobber):
                write=True
            if make_plots:
                qafig = meta.findfile('qa_sky_fig', night=night, camera=camera, expid=expid,
                                      specprod_dir=specprod_dir, outdir=output_dir, qaprod_dir=qaprod_dir)
                qafig2 = meta.findfile('qa_skychi_fig', night=night, camera=camera, expid=expid,
                                      specprod_dir=specprod_dir, outdir=output_dir, qaprod_dir=qaprod_dir)
                if (not os.path.isfile(qafig)) or clobber:
                    qa_plots.frame_skyres(qafig, frame, skymodel, qaframe)
                #qa_plots.frame_skychi(qafig2, frame, skymodel, qaframe)

    # S/N QA on cframe
    if qatype == 'qa_data':
        # cframe
        cframe_file = frame_file.replace('frame-', 'cframe-')
        cframe = read_frame(cframe_file)
        if qaframe.run_qa('S2N', (cframe,), clobber=clobber):
            write=True
        # Figure?
        if make_plots:
            s2n_dict = copy.deepcopy(qaframe.qa_data['S2N'])
            qafig = meta.findfile('qa_s2n_fig', night=night, camera=camera, expid=expid,
                              specprod_dir=specprod_dir, outdir=output_dir, qaprod_dir=qaprod_dir)
            #badfibs = np.where(np.isnan(s2n_dict['METRICS']['MEDIAN_SNR']))[0].tolist()
            #sci_idx = s2n_dict['METRICS']['OBJLIST'].index('SCIENCE')
            coeff = s2n_dict['METRICS']['FITCOEFF_TGT']#[sci_idx]
            # Add an item or two for the QL method
            s2n_dict['CAMERA'] = camera
            s2n_dict['EXPID'] = expid
            s2n_dict['PANAME'] = 'SNRFit'
            s2n_dict['METRICS']['RA'] = frame.fibermap['FIBER_RA']
            s2n_dict['METRICS']['DEC'] = frame.fibermap['FIBER_DEC']
            objlist = s2n_dict['METRICS']['OBJLIST']
            # Deal with YAML list instead of ndarray
            s2n_dict['METRICS']['MEDIAN_SNR'] = np.array(s2n_dict['METRICS']['MEDIAN_SNR'])
            # Generate
            if (not os.path.isfile(qafig)) or clobber:
                qa_plots_ql.plot_SNR(s2n_dict, qafig, objlist, [[]]*len(objlist), coeff)

    # FluxCalib QA
    if qatype == 'qa_data':
        # Standard stars
        stdstar_fil = meta.findfile('stdstars', night=night, camera=camera, expid=expid, specprod_dir=specprod_dir,
                                    spectrograph=spectro)
        # try:
        #    model_tuple=read_stdstar_models(stdstar_fil)
        # except FileNotFoundError:
        #    warnings.warn("Standard star file {:s} not found.  Skipping..".format(stdstar_fil))
        # else:
        flux_fil = meta.findfile('calib', night=night, camera=camera, expid=expid, specprod_dir=specprod_dir)
        try:
            fluxcalib = read_flux_calibration(flux_fil)
        except FileNotFoundError:
            warnings.warn("Flux file {:s} not found.  Skipping..".format(flux_fil))
        else:
            if qaframe.run_qa('FLUXCALIB', (frame, fluxcalib), clobber=clobber):  # , model_tuple))#, indiv_stars))
                write = True
            if make_plots:
                qafig = meta.findfile('qa_flux_fig', night=night, camera=camera, expid=expid,
                                      specprod_dir=specprod_dir, outdir=output_dir, qaprod_dir=qaprod_dir)
                if (not os.path.isfile(qafig)) or clobber:
                    qa_plots.frame_fluxcalib(qafig, qaframe, frame, fluxcalib)  # , model_tuple)
    # Write
    if write:
        write_qa_frame(qafile, qaframe, verbose=True)
    return qaframe