Пример #1
0
def main_mpi(args, comm=None):

    psf_file = args.psf
    input_file = args.input

    # these parameters are interpreted as the *global* spec range,
    # to be divided among processes.
    specmin = args.specmin
    nspec = args.nspec

    #- Load input files and broadcast

    # FIXME: after we have fixed the serialization
    # of the PSF, read and broadcast here, to reduce
    # disk contention.

    img = None
    if comm is None:
        img = io.read_image(input_file)
    else:
        if comm.rank == 0:
            img = io.read_image(input_file)
        img = comm.bcast(img, root=0)

    psf = load_psf(psf_file)

    # get spectral range

    if nspec is None:
        nspec = psf.nspec
    specmax = specmin + nspec

    camera = img.meta['CAMERA'].lower()     #- b0, r1, .. z9
    spectrograph = int(camera[1])
    fibermin = spectrograph * psf.nspec + specmin

    if args.fibermap is not None:
        fibermap = io.read_fibermap(args.fibermap)
        fibermap = fibermap[fibermin:fibermin+nspec]
        fibers = fibermap['FIBER']
    else:
        fibermap = None
        fibers = np.arange(fibermin, fibermin+nspec, dtype='i4')

    #- Get wavelength grid from options

    if args.wavelength is not None:
        wstart, wstop, dw = map(float, args.wavelength.split(','))
    else:
        wstart = np.ceil(psf.wmin_all)
        wstop = np.floor(psf.wmax_all)
        dw = 0.5
        
    wave = np.arange(wstart, wstop+dw/2.0, dw)
    nwave = len(wave)

    #- Confirm that this PSF covers these wavelengths for these spectra
    
    psf_wavemin = np.max(psf.wavelength(range(specmin, specmax), y=0))
    psf_wavemax = np.min(psf.wavelength(range(specmin, specmax), y=psf.npix_y-1))
    if psf_wavemin > wstart:
        raise ValueError, 'Start wavelength {:.2f} < min wavelength {:.2f} for these fibers'.format(wstart, psf_wavemin)
    if psf_wavemax < wstop:
        raise ValueError, 'Stop wavelength {:.2f} > max wavelength {:.2f} for these fibers'.format(wstop, psf_wavemax)

    # Now we divide our spectra into bundles

    bundlesize = args.bundlesize
    checkbundles = set()
    checkbundles.update(np.floor_divide(np.arange(specmin, specmax), bundlesize*np.ones(nspec)).astype(int))
    bundles = sorted(list(checkbundles))
    nbundle = len(bundles)

    bspecmin = {}
    bnspec = {}
    for b in bundles:
        if specmin > b * bundlesize:
            bspecmin[b] = specmin
        else:
            bspecmin[b] = b * bundlesize
        if (b+1) * bundlesize > specmax:
            bnspec[b] = specmax - bspecmin[b]
        else:
            bnspec[b] = bundlesize

    # Now we assign bundles to processes

    nproc = 1
    rank = 0
    if comm is not None:
        nproc = comm.size
        rank = comm.rank

    mynbundle = int(nbundle // nproc)
    myfirstbundle = 0
    leftover = nbundle % nproc
    if rank < leftover:
        mynbundle += 1
        myfirstbundle = rank * mynbundle
    else:
        myfirstbundle = ((mynbundle + 1) * leftover) + (mynbundle * (rank - leftover))

    if rank == 0:
        #- Print parameters
        print "extract:  input = {}".format(input_file)
        print "extract:  psf = {}".format(psf_file)
        print "extract:  specmin = {}".format(specmin)
        print "extract:  nspec = {}".format(nspec)
        print "extract:  wavelength = {},{},{}".format(wstart, wstop, dw)
        print "extract:  nwavestep = {}".format(args.nwavestep)
        print "extract:  regularize = {}".format(args.regularize)

    # get the root output file

    outpat = re.compile(r'(.*)\.fits')
    outmat = outpat.match(args.output)
    if outmat is None:
        raise RuntimeError("extraction output file should have .fits extension")
    outroot = outmat.group(1)

    outdir = os.path.normpath(os.path.dirname(outroot))
    if rank == 0:
        if not os.path.isdir(outdir):
            os.makedirs(outdir)

    if comm is not None:
        comm.barrier()

    failcount = 0

    for b in range(myfirstbundle, myfirstbundle+mynbundle):
        outbundle = "{}_{:02d}.fits".format(outroot, b)
        outmodel = "{}_model_{:02d}.fits".format(outroot, b)

        print('extract:  Rank {} starting {} spectra {}:{} at {}'.format(
            rank, os.path.basename(input_file),
            bspecmin[b], bspecmin[b]+bnspec[b], time.asctime(),
            ) )

        #- The actual extraction
        try:
            results = ex2d(img.pix, img.ivar*(img.mask==0), psf, bspecmin[b], 
                bnspec[b], wave, regularize=args.regularize, ndecorr=True,
                bundlesize=bundlesize, wavesize=args.nwavestep, verbose=args.verbose,
                full_output=True)

            flux = results['flux']
            ivar = results['ivar']
            Rdata = results['resolution_data']
            chi2pix = results['chi2pix']

            mask = np.zeros(flux.shape, dtype=np.uint32)
            mask[results['pixmask_fraction']>0.5] |= specmask.SOMEBADPIX
            mask[results['pixmask_fraction']==1.0] |= specmask.ALLBADPIX
            mask[chi2pix>100.0] |= specmask.BAD2DFIT

            #- Augment input image header for output
            img.meta['NSPEC']   = (nspec, 'Number of spectra')
            img.meta['WAVEMIN'] = (wstart, 'First wavelength [Angstroms]')
            img.meta['WAVEMAX'] = (wstop, 'Last wavelength [Angstroms]')
            img.meta['WAVESTEP']= (dw, 'Wavelength step size [Angstroms]')
            img.meta['SPECTER'] = (specter.__version__, 'https://github.com/desihub/specter')
            img.meta['IN_PSF']  = (_trim(psf_file), 'Input spectral PSF')
            img.meta['IN_IMG']  = (_trim(input_file), 'Input image')

            if fibermap is not None:
                bfibermap = fibermap[bspecmin[b]-specmin:bspecmin[b]+bnspec[b]-specmin]
            else:
                bfibermap = None

            bfibers = fibers[bspecmin[b]-specmin:bspecmin[b]+bnspec[b]-specmin]

            frame = Frame(wave, flux, ivar, mask=mask, resolution_data=Rdata,
                        fibers=bfibers, meta=img.meta, fibermap=bfibermap,
                        chi2pix=chi2pix)

            #- Write output
            io.write_frame(outbundle, frame)

            if args.model is not None:
                from astropy.io import fits
                fits.writeto(outmodel, results['modelimage'], header=frame.meta)

            print('extract:  Done {} spectra {}:{} at {}'.format(os.path.basename(input_file),
                bspecmin[b], bspecmin[b]+bnspec[b], time.asctime()))
        except:
            failcount += 1

    if comm is not None:
        failcount = comm.allreduce(failcount)

    if failcount > 0:
        # all processes throw
        raise RuntimeError("some extraction bundles failed")

    if rank == 0:
        mergeopts = [
            '--output', args.output,
            '--force',
            '--delete'
        ]
        mergeopts.extend([ "{}_{:02d}.fits".format(outroot, b) for b in bundles ])
        mergeargs = mergebundles.parse(mergeopts)
        mergebundles.main(mergeargs)

        if args.model is not None:
            model = None
            for b in bundles:
                outmodel = "{}_model_{:02d}.fits".format(outroot, b)
                if model is None:
                    model = fits.getdata(outmodel)
                else:
                    #- TODO: test and warn if models overlap for pixels with
                    #- non-zero values
                    model += fits.getdata(outmodel)

                os.remove(outmodel)

            fits.writeto(args.model, model)
Пример #2
0
def main_mpi(args, comm=None, timing=None):
    freeze_iers()
    nproc = 1
    rank = 0
    if comm is not None:
        nproc = comm.size
        rank = comm.rank

    mark_start = time.time()

    log = get_logger()

    psf_file = args.psf
    input_file = args.input

    # these parameters are interpreted as the *global* spec range,
    # to be divided among processes.
    specmin = args.specmin
    nspec = args.nspec

    #- Load input files and broadcast

    # FIXME: after we have fixed the serialization
    # of the PSF, read and broadcast here, to reduce
    # disk contention.

    img = None
    if rank == 0:
        img = io.read_image(input_file)
    if comm is not None:
        img = comm.bcast(img, root=0)

    psf = load_psf(psf_file)

    mark_read_input = time.time()

    # get spectral range
    if nspec is None:
        nspec = psf.nspec

    if args.fibermap is not None:
        fibermap = io.read_fibermap(args.fibermap)
    else:
        try:
            fibermap = io.read_fibermap(args.input)
        except (AttributeError, IOError, KeyError):
            fibermap = None

    if fibermap is not None:
        fibermap = fibermap[specmin:specmin + nspec]
        if nspec > len(fibermap):
            log.warning(
                "nspec {} > len(fibermap) {}; reducing nspec to {}".format(
                    nspec, len(fibermap), len(fibermap)))
            nspec = len(fibermap)
        fibers = fibermap['FIBER']
    else:
        fibers = np.arange(specmin, specmin + nspec)

    specmax = specmin + nspec

    #- Get wavelength grid from options
    if args.wavelength is not None:
        raw_wstart, raw_wstop, raw_dw = [
            float(tmp) for tmp in args.wavelength.split(',')
        ]
    else:
        raw_wstart = np.ceil(psf.wmin_all)
        raw_wstop = np.floor(psf.wmax_all)
        raw_dw = 0.7

    raw_wave = np.arange(raw_wstart, raw_wstop + raw_dw / 2.0, raw_dw)
    nwave = len(raw_wave)
    bundlesize = args.bundlesize

    if args.barycentric_correction:
        if ('RA' in img.meta) or ('TARGTRA' in img.meta):
            barycentric_correction_factor = \
                    barycentric_correction_multiplicative_factor(img.meta)
        #- Early commissioning has RA/TARGTRA in fibermap but not HDU 0
        elif fibermap is not None and \
                (('RA' in fibermap.meta) or ('TARGTRA' in fibermap.meta)):
            barycentric_correction_factor = \
                    barycentric_correction_multiplicative_factor(fibermap.meta)
        else:
            msg = 'Barycentric corr requires (TARGT)RA in HDU 0 or fibermap'
            log.critical(msg)
            raise KeyError(msg)
    else:
        barycentric_correction_factor = 1.

    # Explictly define the correct wavelength values to avoid confusion of reference frame
    # If correction applied, otherwise divide by 1 and use the same raw values
    wstart = raw_wstart / barycentric_correction_factor
    wstop = raw_wstop / barycentric_correction_factor
    dw = raw_dw / barycentric_correction_factor
    wave = raw_wave / barycentric_correction_factor

    #- Confirm that this PSF covers these wavelengths for these spectra
    psf_wavemin = np.max(psf.wavelength(list(range(specmin, specmax)), y=-0.5))
    psf_wavemax = np.min(
        psf.wavelength(list(range(specmin, specmax)), y=psf.npix_y - 0.5))
    if psf_wavemin - 5 > wstart:
        raise ValueError(
            'Start wavelength {:.2f} < min wavelength {:.2f} for these fibers'.
            format(wstart, psf_wavemin))
    if psf_wavemax + 5 < wstop:
        raise ValueError(
            'Stop wavelength {:.2f} > max wavelength {:.2f} for these fibers'.
            format(wstop, psf_wavemax))

    if rank == 0:
        #- Print parameters
        log.info("extract:  input = {}".format(input_file))
        log.info("extract:  psf = {}".format(psf_file))
        log.info("extract:  specmin = {}".format(specmin))
        log.info("extract:  nspec = {}".format(nspec))
        log.info("extract:  wavelength = {},{},{}".format(wstart, wstop, dw))
        log.info("extract:  nwavestep = {}".format(args.nwavestep))
        log.info("extract:  regularize = {}".format(args.regularize))

    if barycentric_correction_factor != 1.:
        img.meta['HELIOCOR'] = barycentric_correction_factor

    #- Augment input image header for output
    img.meta['NSPEC'] = (nspec, 'Number of spectra')
    img.meta['WAVEMIN'] = (raw_wstart, 'First wavelength [Angstroms]')
    img.meta['WAVEMAX'] = (raw_wstop, 'Last wavelength [Angstroms]')
    img.meta['WAVESTEP'] = (raw_dw, 'Wavelength step size [Angstroms]')
    img.meta['SPECTER'] = (specter.__version__,
                           'https://github.com/desihub/specter')
    img.meta['IN_PSF'] = (io.shorten_filename(psf_file), 'Input spectral PSF')
    img.meta['IN_IMG'] = io.shorten_filename(input_file)
    depend.add_dependencies(img.meta)

    #- Check if input PSF was itself a traceshifted version of another PSF
    orig_psf = None
    if rank == 0:
        try:
            psfhdr = fits.getheader(psf_file, 'PSF')
            orig_psf = psfhdr['IN_PSF']
        except KeyError:
            #- could happen due to PSF format not having "PSF" extension,
            #- or due to PSF header not having 'IN_PSF' keyword.  Either is OK
            pass

    if comm is not None:
        orig_psf = comm.bcast(orig_psf, root=0)

    if orig_psf is not None:
        img.meta['ORIG_PSF'] = orig_psf

    #- If not using MPI, use a single call to each of these and then end this function call
    #  Otherwise, continue on to splitting things up for the different ranks
    if comm is None:
        _extract_and_save(img, psf, specmin, nspec, specmin, wave, raw_wave,
                          fibers, fibermap, args.output, args.model,
                          bundlesize, args, log)

        #- This is it if we aren't running MPI, so return
        return
    #else:
    #    # Continue to the MPI section, which could go under this else statment
    #    # But to save on indentation we'll just pass on to the rest of the function
    #    # since the alternative has already returned
    #    pass

    # Now we divide our spectra into bundles
    checkbundles = set()
    checkbundles.update(
        np.floor_divide(np.arange(specmin, specmax),
                        bundlesize * np.ones(nspec)).astype(int))
    bundles = sorted(checkbundles)
    nbundle = len(bundles)

    bspecmin = {}
    bnspec = {}

    for b in bundles:
        if specmin > b * bundlesize:
            bspecmin[b] = specmin
        else:
            bspecmin[b] = b * bundlesize
        if (b + 1) * bundlesize > specmax:
            bnspec[b] = specmax - bspecmin[b]
        else:
            bnspec[b] = bundlesize

    # Now we assign bundles to processes
    mynbundle = int(nbundle // nproc)
    myfirstbundle = 0
    leftover = nbundle % nproc
    if rank < leftover:
        mynbundle += 1
        myfirstbundle = rank * mynbundle
    else:
        myfirstbundle = ((mynbundle + 1) * leftover) + (mynbundle *
                                                        (rank - leftover))

    # get the root output file
    outpat = re.compile(r'(.*)\.fits')
    outmat = outpat.match(args.output)
    if outmat is None:
        raise RuntimeError(
            "extraction output file should have .fits extension")
    outroot = outmat.group(1)

    outdir = os.path.normpath(os.path.dirname(outroot))

    if rank == 0:
        if not os.path.isdir(outdir):
            os.makedirs(outdir)

    if comm is not None:
        comm.barrier()

    mark_preparation = time.time()
    time_total_extraction = 0.0
    time_total_write_output = 0.0
    failcount = 0

    for b in range(myfirstbundle, myfirstbundle + mynbundle):
        mark_iteration_start = time.time()
        outbundle = "{}_{:02d}.fits".format(outroot, b)
        outmodel = "{}_model_{:02d}.fits".format(outroot, b)

        log.info('extract:  Rank {} extracting {} spectra {}:{} at {}'.format(
            rank,
            os.path.basename(input_file),
            bspecmin[b],
            bspecmin[b] + bnspec[b],
            time.asctime(),
        ))
        sys.stdout.flush()

        #- The actual extraction
        try:
            mark_extraction = _extract_and_save(img, psf, bspecmin[b],
                                                bnspec[b], specmin, wave,
                                                raw_wave, fibers, fibermap,
                                                outbundle, outmodel,
                                                bundlesize, args, log)

            mark_write_output = time.time()

            time_total_extraction += mark_extraction - mark_iteration_start
            time_total_write_output += mark_write_output - mark_extraction
        except:
            # Log the error and increment the number of failures
            log.error(
                "extract:  FAILED bundle {}, spectrum range {}:{}".format(
                    b, bspecmin[b], bspecmin[b] + bnspec[b]))
            exc_type, exc_value, exc_traceback = sys.exc_info()
            lines = traceback.format_exception(exc_type, exc_value,
                                               exc_traceback)
            log.error(''.join(lines))
            failcount += 1
            sys.stdout.flush()

    if comm is not None:
        failcount = comm.allreduce(failcount)

    if failcount > 0:
        # all processes throw
        raise RuntimeError("some extraction bundles failed")

    time_merge = None
    if rank == 0:
        mark_merge_start = time.time()
        mergeopts = ['--output', args.output, '--force', '--delete']
        mergeopts.extend(
            ["{}_{:02d}.fits".format(outroot, b) for b in bundles])
        mergeargs = mergebundles.parse(mergeopts)
        mergebundles.main(mergeargs)

        if args.model is not None:
            model = None
            for b in bundles:
                outmodel = "{}_model_{:02d}.fits".format(outroot, b)
                if model is None:
                    model = fits.getdata(outmodel)
                else:
                    #- TODO: test and warn if models overlap for pixels with
                    #- non-zero values
                    model += fits.getdata(outmodel)

                os.remove(outmodel)

            fits.writeto(args.model, model)
        mark_merge_end = time.time()
        time_merge = mark_merge_end - mark_merge_start

    # Resolve difference timer data

    if type(timing) is dict:
        timing["read_input"] = mark_read_input - mark_start
        timing["preparation"] = mark_preparation - mark_read_input
        timing["total_extraction"] = time_total_extraction
        timing["total_write_output"] = time_total_write_output
        timing["merge"] = time_merge
Пример #3
0
def main_mpi(args, comm=None):

    log = get_logger()

    psf_file = args.psf
    input_file = args.input

    # these parameters are interpreted as the *global* spec range,
    # to be divided among processes.
    specmin = args.specmin
    nspec = args.nspec

    #- Load input files and broadcast

    # FIXME: after we have fixed the serialization
    # of the PSF, read and broadcast here, to reduce
    # disk contention.

    img = None
    if comm is None:
        img = io.read_image(input_file)
    else:
        if comm.rank == 0:
            img = io.read_image(input_file)
        img = comm.bcast(img, root=0)

    psf = load_psf(psf_file)

    # get spectral range

    if nspec is None:
        nspec = psf.nspec
    specmax = specmin + nspec

    camera = img.meta['CAMERA'].lower()  #- b0, r1, .. z9
    spectrograph = int(camera[1])
    fibermin = spectrograph * psf.nspec + specmin

    if args.fibermap is not None:
        fibermap = io.read_fibermap(args.fibermap)
        fibermap = fibermap[fibermin:fibermin + nspec]
        fibers = fibermap['FIBER']
    else:
        fibermap = None
        fibers = np.arange(fibermin, fibermin + nspec, dtype='i4')

    #- Get wavelength grid from options

    if args.wavelength is not None:
        wstart, wstop, dw = [float(tmp) for tmp in args.wavelength.split(',')]
    else:
        wstart = np.ceil(psf.wmin_all)
        wstop = np.floor(psf.wmax_all)
        dw = 0.5

    wave = np.arange(wstart, wstop + dw / 2.0, dw)
    nwave = len(wave)

    #- Confirm that this PSF covers these wavelengths for these spectra

    psf_wavemin = np.max(psf.wavelength(list(range(specmin, specmax)), y=0))
    psf_wavemax = np.min(
        psf.wavelength(list(range(specmin, specmax)), y=psf.npix_y - 1))
    if psf_wavemin > wstart:
        raise ValueError(
            'Start wavelength {:.2f} < min wavelength {:.2f} for these fibers'.
            format(wstart, psf_wavemin))
    if psf_wavemax < wstop:
        raise ValueError(
            'Stop wavelength {:.2f} > max wavelength {:.2f} for these fibers'.
            format(wstop, psf_wavemax))

    # Now we divide our spectra into bundles

    bundlesize = args.bundlesize
    checkbundles = set()
    checkbundles.update(
        np.floor_divide(np.arange(specmin, specmax),
                        bundlesize * np.ones(nspec)).astype(int))
    bundles = sorted(checkbundles)
    nbundle = len(bundles)

    bspecmin = {}
    bnspec = {}
    for b in bundles:
        if specmin > b * bundlesize:
            bspecmin[b] = specmin
        else:
            bspecmin[b] = b * bundlesize
        if (b + 1) * bundlesize > specmax:
            bnspec[b] = specmax - bspecmin[b]
        else:
            bnspec[b] = bundlesize

    # Now we assign bundles to processes

    nproc = 1
    rank = 0
    if comm is not None:
        nproc = comm.size
        rank = comm.rank

    mynbundle = int(nbundle // nproc)
    myfirstbundle = 0
    leftover = nbundle % nproc
    if rank < leftover:
        mynbundle += 1
        myfirstbundle = rank * mynbundle
    else:
        myfirstbundle = ((mynbundle + 1) * leftover) + (mynbundle *
                                                        (rank - leftover))

    if rank == 0:
        #- Print parameters
        log.info("extract:  input = {}".format(input_file))
        log.info("extract:  psf = {}".format(psf_file))
        log.info("extract:  specmin = {}".format(specmin))
        log.info("extract:  nspec = {}".format(nspec))
        log.info("extract:  wavelength = {},{},{}".format(wstart, wstop, dw))
        log.info("extract:  nwavestep = {}".format(args.nwavestep))
        log.info("extract:  regularize = {}".format(args.regularize))

    # get the root output file

    outpat = re.compile(r'(.*)\.fits')
    outmat = outpat.match(args.output)
    if outmat is None:
        raise RuntimeError(
            "extraction output file should have .fits extension")
    outroot = outmat.group(1)

    outdir = os.path.normpath(os.path.dirname(outroot))
    if rank == 0:
        if not os.path.isdir(outdir):
            os.makedirs(outdir)

    if comm is not None:
        comm.barrier()

    failcount = 0

    for b in range(myfirstbundle, myfirstbundle + mynbundle):
        outbundle = "{}_{:02d}.fits".format(outroot, b)
        outmodel = "{}_model_{:02d}.fits".format(outroot, b)

        log.info('extract:  Rank {} starting {} spectra {}:{} at {}'.format(
            rank,
            os.path.basename(input_file),
            bspecmin[b],
            bspecmin[b] + bnspec[b],
            time.asctime(),
        ))
        sys.stdout.flush()

        #- The actual extraction
        try:
            results = ex2d(img.pix,
                           img.ivar * (img.mask == 0),
                           psf,
                           bspecmin[b],
                           bnspec[b],
                           wave,
                           regularize=args.regularize,
                           ndecorr=True,
                           bundlesize=bundlesize,
                           wavesize=args.nwavestep,
                           verbose=args.verbose,
                           full_output=True)

            flux = results['flux']
            ivar = results['ivar']
            Rdata = results['resolution_data']
            chi2pix = results['chi2pix']

            mask = np.zeros(flux.shape, dtype=np.uint32)
            mask[results['pixmask_fraction'] > 0.5] |= specmask.SOMEBADPIX
            mask[results['pixmask_fraction'] == 1.0] |= specmask.ALLBADPIX
            mask[chi2pix > 100.0] |= specmask.BAD2DFIT

            #- Augment input image header for output
            img.meta['NSPEC'] = (nspec, 'Number of spectra')
            img.meta['WAVEMIN'] = (wstart, 'First wavelength [Angstroms]')
            img.meta['WAVEMAX'] = (wstop, 'Last wavelength [Angstroms]')
            img.meta['WAVESTEP'] = (dw, 'Wavelength step size [Angstroms]')
            img.meta['SPECTER'] = (specter.__version__,
                                   'https://github.com/desihub/specter')
            img.meta['IN_PSF'] = (_trim(psf_file), 'Input spectral PSF')
            img.meta['IN_IMG'] = (_trim(input_file), 'Input image')

            if fibermap is not None:
                bfibermap = fibermap[bspecmin[b] - specmin:bspecmin[b] +
                                     bnspec[b] - specmin]
            else:
                bfibermap = None

            bfibers = fibers[bspecmin[b] - specmin:bspecmin[b] + bnspec[b] -
                             specmin]

            frame = Frame(wave,
                          flux,
                          ivar,
                          mask=mask,
                          resolution_data=Rdata,
                          fibers=bfibers,
                          meta=img.meta,
                          fibermap=bfibermap,
                          chi2pix=chi2pix)

            #- Write output
            io.write_frame(outbundle, frame, units='photon/bin')

            if args.model is not None:
                from astropy.io import fits
                fits.writeto(outmodel,
                             results['modelimage'],
                             header=frame.meta)

            log.info('extract:  Done {} spectra {}:{} at {}'.format(
                os.path.basename(input_file), bspecmin[b],
                bspecmin[b] + bnspec[b], time.asctime()))
            sys.stdout.flush()
        except:
            # Log the error and increment the number of failures
            log.error(
                "extract:  FAILED bundle {}, spectrum range {}:{}".format(
                    b, bspecmin[b], bspecmin[b] + bnspec[b]))
            exc_type, exc_value, exc_traceback = sys.exc_info()
            lines = traceback.format_exception(exc_type, exc_value,
                                               exc_traceback)
            log.error(''.join(lines))
            failcount += 1
            sys.stdout.flush()

    if comm is not None:
        failcount = comm.allreduce(failcount)

    if failcount > 0:
        # all processes throw
        raise RuntimeError("some extraction bundles failed")

    if rank == 0:
        mergeopts = ['--output', args.output, '--force', '--delete']
        mergeopts.extend(
            ["{}_{:02d}.fits".format(outroot, b) for b in bundles])
        mergeargs = mergebundles.parse(mergeopts)
        mergebundles.main(mergeargs)

        if args.model is not None:
            model = None
            for b in bundles:
                outmodel = "{}_model_{:02d}.fits".format(outroot, b)
                if model is None:
                    model = fits.getdata(outmodel)
                else:
                    #- TODO: test and warn if models overlap for pixels with
                    #- non-zero values
                    model += fits.getdata(outmodel)

                os.remove(outmodel)

            fits.writeto(args.model, model)
Пример #4
0
def main_mpi(args, comm=None):

    psf_file = args.psf
    input_file = args.input

    # these parameters are interpreted as the *global* spec range,
    # to be divided among processes.
    specmin = args.specmin
    nspec = args.nspec

    #- Load input files and broadcast

    # FIXME: after we have fixed the serialization
    # of the PSF, read and broadcast here, to reduce
    # disk contention.

    img = None
    if comm is None:
        img = io.read_image(input_file)
    else:
        if comm.rank == 0:
            img = io.read_image(input_file)
        img = comm.bcast(img, root=0)

    psf = load_psf(psf_file)

    # get spectral range

    if nspec is None:
        nspec = psf.nspec
    specmax = specmin + nspec

    camera = img.meta['CAMERA'].lower()  #- b0, r1, .. z9
    spectrograph = int(camera[1])
    fibermin = spectrograph * psf.nspec + specmin

    if args.fibermap is not None:
        fibermap = io.read_fibermap(args.fibermap)
        fibermap = fibermap[fibermin:fibermin + nspec]
        fibers = fibermap['FIBER']
    else:
        fibermap = None
        fibers = np.arange(fibermin, fibermin + nspec, dtype='i4')

    #- Get wavelength grid from options

    if args.wavelength is not None:
        wstart, wstop, dw = map(float, args.wavelength.split(','))
    else:
        wstart = np.ceil(psf.wmin_all)
        wstop = np.floor(psf.wmax_all)
        dw = 0.5

    wave = np.arange(wstart, wstop + dw / 2.0, dw)
    nwave = len(wave)

    #- Confirm that this PSF covers these wavelengths for these spectra

    psf_wavemin = np.max(psf.wavelength(range(specmin, specmax), y=0))
    psf_wavemax = np.min(
        psf.wavelength(range(specmin, specmax), y=psf.npix_y - 1))
    if psf_wavemin > wstart:
        raise ValueError, 'Start wavelength {:.2f} < min wavelength {:.2f} for these fibers'.format(
            wstart, psf_wavemin)
    if psf_wavemax < wstop:
        raise ValueError, 'Stop wavelength {:.2f} > max wavelength {:.2f} for these fibers'.format(
            wstop, psf_wavemax)

    # Now we divide our spectra into bundles

    bundlesize = args.bundlesize
    checkbundles = set()
    checkbundles.update(
        np.floor_divide(np.arange(specmin, specmax),
                        bundlesize * np.ones(nspec)).astype(int))
    bundles = sorted(list(checkbundles))
    nbundle = len(bundles)

    bspecmin = {}
    bnspec = {}
    for b in bundles:
        if specmin > b * bundlesize:
            bspecmin[b] = specmin
        else:
            bspecmin[b] = b * bundlesize
        if (b + 1) * bundlesize > specmax:
            bnspec[b] = specmax - bspecmin[b]
        else:
            bnspec[b] = bundlesize

    # Now we assign bundles to processes

    nproc = 1
    rank = 0
    if comm is not None:
        nproc = comm.size
        rank = comm.rank

    mynbundle = int(nbundle / nproc)
    myfirstbundle = 0
    leftover = nbundle % nproc
    if rank < leftover:
        mynbundle += 1
        myfirstbundle = rank * mynbundle
    else:
        myfirstbundle = ((mynbundle + 1) * leftover) + (mynbundle *
                                                        (rank - leftover))

    if rank == 0:
        #- Print parameters
        print "extract:  input = {}".format(input_file)
        print "extract:  psf = {}".format(psf_file)
        print "extract:  specmin = {}".format(specmin)
        print "extract:  nspec = {}".format(nspec)
        print "extract:  wavelength = {},{},{}".format(wstart, wstop, dw)
        print "extract:  nwavestep = {}".format(args.nwavestep)
        print "extract:  regularize = {}".format(args.regularize)

    # get the root output file

    outpat = re.compile(r'(.*)\.fits')
    outmat = outpat.match(args.output)
    if outmat is None:
        raise RuntimeError(
            "extraction output file should have .fits extension")
    outroot = outmat.group(1)

    outdir = os.path.dirname(outroot)
    if rank == 0:
        if not os.path.isdir(outdir):
            os.makedirs(outdir)

    if comm is not None:
        comm.barrier()

    failcount = 0

    for b in range(myfirstbundle, myfirstbundle + mynbundle):
        outbundle = "{}_{:02d}.fits".format(outroot, b)

        print('extract:  Starting {} spectra {}:{} at {}'.format(
            os.path.basename(input_file), bspecmin[b], bspecmin[b] + bnspec[b],
            time.asctime()))

        #- The actual extraction
        try:
            flux, ivar, Rdata = ex2d(img.pix,
                                     img.ivar * (img.mask == 0),
                                     psf,
                                     bspecmin[b],
                                     bnspec[b],
                                     wave,
                                     regularize=args.regularize,
                                     ndecorr=True,
                                     bundlesize=bundlesize,
                                     wavesize=args.nwavestep,
                                     verbose=args.verbose)

            #- Augment input image header for output
            img.meta['NSPEC'] = (nspec, 'Number of spectra')
            img.meta['WAVEMIN'] = (wstart, 'First wavelength [Angstroms]')
            img.meta['WAVEMAX'] = (wstop, 'Last wavelength [Angstroms]')
            img.meta['WAVESTEP'] = (dw, 'Wavelength step size [Angstroms]')
            img.meta['SPECTER'] = (specter.__version__,
                                   'https://github.com/desihub/specter')
            img.meta['IN_PSF'] = (_trim(psf_file), 'Input spectral PSF')
            img.meta['IN_IMG'] = (_trim(input_file), 'Input image')

            bfibermap = fibermap[bspecmin[b] - specmin:bspecmin[b] +
                                 bnspec[b] - specmin]
            bfibers = fibers[bspecmin[b] - specmin:bspecmin[b] + bnspec[b] -
                             specmin]

            frame = Frame(wave,
                          flux,
                          ivar,
                          resolution_data=Rdata,
                          fibers=bfibers,
                          meta=img.meta,
                          fibermap=bfibermap)

            #- Write output
            io.write_frame(outbundle, frame)

            print('extract:  Done {} spectra {}:{} at {}'.format(
                os.path.basename(input_file), bspecmin[b],
                bspecmin[b] + bnspec[b], time.asctime()))
        except:
            failcount += 1

    if comm is not None:
        failcount = comm.allreduce(failcount)

    if failcount > 0:
        # all processes throw
        raise RuntimeError("some extraction bundles failed")

    if rank == 0:
        opts = ['--output', args.output, '--force', '--delete']
        opts.extend(["{}_{:02d}.fits".format(outroot, b) for b in bundles])
        args = merge.parse(opts)
        merge.main(args)