Exemple #1
0
def main(args=None):
    """Run the hveto command-line interface
    """
    # declare global variables
    # this is needed for multiprocessing utilities
    global acache, analysis, areadkw, atrigfindkw, auxiliary, auxetg
    global auxfreq, counter, livetime, minsnr, naux, pchannel, primary
    global rnd, snrs, windows

    # parse command-line
    parser = create_parser()
    args = parser.parse_args(args=args)
    ifo = args.ifo
    start = int(args.gpsstart)
    end = int(args.gpsend)
    duration = end - start

    # log startup
    LOGGER.info("-- Welcome to Hveto --")
    LOGGER.info("GPS start time: %d" % start)
    LOGGER.info("GPS end time: %d" % end)
    LOGGER.info("Interferometer: %s" % ifo)

    # -- initialisation -------------------------

    # read configuration
    cp = config.HvetoConfigParser(ifo=ifo)
    cp.read(args.config_file)
    LOGGER.info("Parsed configuration file(s)")

    # format output directory
    outdir = _abs_path(args.output_directory)
    if not os.path.isdir(outdir):
        os.makedirs(outdir)
    os.chdir(outdir)
    LOGGER.info("Working directory: %s" % outdir)
    segdir = 'segments'
    plotdir = 'plots'
    trigdir = 'triggers'
    omegadir = 'scans'
    for d in [segdir, plotdir, trigdir, omegadir]:
        if not os.path.isdir(d):
            os.makedirs(d)

    # prepare html variables
    htmlv = {
        'title': '%s Hveto | %d-%d' % (ifo, start, end),
        'config': None,
        'prog': PROG,
        'context': ifo.lower(),
    }

    # get segments
    aflag = cp.get('segments', 'analysis-flag')
    url = cp.get('segments', 'url')
    padding = tuple(cp.getfloats('segments', 'padding'))
    if args.analysis_segments:
        segs_ = DataQualityDict.read(args.analysis_segments, gpstype=float)
        analysis = segs_[aflag]
        span = SegmentList([Segment(start, end)])
        analysis.active &= span
        analysis.known &= span
        analysis.coalesce()
        LOGGER.debug("Segments read from disk")
    else:
        analysis = DataQualityFlag.query(aflag, start, end, url=url)
        LOGGER.debug("Segments recovered from %s" % url)
    if padding != (0, 0):
        mindur = padding[0] - padding[1]
        analysis.active = type(analysis.active)([s for s in analysis.active if
                                                 abs(s) >= mindur])
        analysis.pad(*padding, inplace=True)
        LOGGER.debug("Padding %s applied" % str(padding))
    livetime = int(abs(analysis.active))
    livetimepc = livetime / duration * 100.
    LOGGER.info("Retrieved %d segments for %s with %ss (%.2f%%) livetime"
                % (len(analysis.active), aflag, livetime, livetimepc))

    # apply vetoes from veto-definer file
    try:
        vetofile = cp.get('segments', 'veto-definer-file')
    except configparser.NoOptionError:
        vetofile = None
    else:
        try:
            categories = cp.getfloats('segments', 'veto-definer-categories')
        except configparser.NoOptionError:
            categories = None
        # read file
        vdf = read_veto_definer_file(vetofile, start=start, end=end, ifo=ifo)
        LOGGER.debug("Read veto-definer file from %s" % vetofile)
        # get vetoes from segdb
        vdf.populate(source=url, segments=analysis.active, on_error='warn')
        # coalesce flags from chosen categories
        vetoes = DataQualityFlag('%s:VDF-VETOES:1' % ifo)
        nflags = 0
        for flag in vdf:
            if not categories or vdf[flag].category in categories:
                vetoes += vdf[flag]
                nflags += 1
        try:
            deadtime = int(abs(vetoes.active)) / int(abs(vetoes.known)) * 100
        except ZeroDivisionError:
            deadtime = 0
        LOGGER.debug("Coalesced %ss (%.2f%%) of deadtime from %d veto flags"
                     % (abs(vetoes.active), deadtime, nflags))
        # apply to analysis segments
        analysis -= vetoes
        LOGGER.debug("Applied vetoes from veto-definer file")
        livetime = int(abs(analysis.active))
        livetimepc = livetime / duration * 100.
        LOGGER.info("%ss (%.2f%%) livetime remaining after vetoes"
                    % (livetime, livetimepc))

    snrs = cp.getfloats('hveto', 'snr-thresholds')
    minsnr = min(snrs)
    windows = cp.getfloats('hveto', 'time-windows')

    # record all segments
    segments = DataQualityDict()
    segments[analysis.name] = analysis

    # -- load channels --------------------------

    # get primary channel name
    pchannel = cp.get('primary', 'channel')

    # read auxiliary cache
    if args.auxiliary_cache is not None:
        acache = read_cache(args.auxiliary_cache)
    else:
        acache = None

    # load auxiliary channels
    auxetg = cp.get('auxiliary', 'trigger-generator')
    auxfreq = cp.getfloats('auxiliary', 'frequency-range')
    try:
        auxchannels = cp.get('auxiliary', 'channels').strip('\n').split('\n')
    except config.configparser.NoOptionError:
        auxchannels = find_auxiliary_channels(auxetg, (start, end), ifo=ifo,
                                              cache=acache)
        cp.set('auxiliary', 'channels', '\n'.join(auxchannels))
        LOGGER.debug("Auto-discovered %d "
                     "auxiliary channels" % len(auxchannels))
    else:
        auxchannels = sorted(set(auxchannels))
        LOGGER.debug("Read list of %d auxiliary channels" % len(auxchannels))

    # load unsafe channels list
    _unsafe = cp.get('safety', 'unsafe-channels')
    if os.path.isfile(_unsafe):  # from file
        unsafe = set()
        with open(_unsafe, 'rb') as f:
            for c in f.read().rstrip('\n').split('\n'):
                if c.startswith('%(IFO)s'):
                    unsafe.add(c.replace('%(IFO)s', ifo))
                elif not c.startswith('%s:' % ifo):
                    unsafe.add('%s:%s' % (ifo, c))
                else:
                    unsafe.add(c)
    else:  # or from line-seprated list
        unsafe = set(_unsafe.strip('\n').split('\n'))
    unsafe.add(pchannel)
    cp.set('safety', 'unsafe-channels', '\n'.join(sorted(unsafe)))
    LOGGER.debug("Read list of %d unsafe channels" % len(unsafe))

    # remove unsafe channels
    nunsafe = 0
    for i in range(len(auxchannels) - 1, -1, -1):
        if auxchannels[i] in unsafe:
            LOGGER.warning("Auxiliary channel %r identified as unsafe and has "
                           "been removed" % auxchannels[i])
            auxchannels.pop(i)
            nunsafe += 1
    LOGGER.debug("%d auxiliary channels identified as unsafe" % nunsafe)
    naux = len(auxchannels)
    LOGGER.info("Identified %d auxiliary channels to process" % naux)

    # record INI file in output HTML directory
    inifile = '%s-HVETO_CONFIGURATION-%d-%d.ini' % (ifo, start, duration)
    if os.path.isfile(inifile) and any(
            os.path.samefile(inifile, x) for x in args.config_file):
        LOGGER.debug("Cannot write INI file to %s, file was given as input")
    else:
        with open(inifile, 'w') as f:
            cp.write(f)
        LOGGER.info("Configuration recorded as %s" % inifile)
    htmlv['config'] = inifile

    # -- load primary triggers ------------------

    # read primary cache
    if args.primary_cache is not None:
        pcache = read_cache(args.primary_cache)
    else:
        pcache = None

    # load primary triggers
    petg = cp.get('primary', 'trigger-generator')
    psnr = cp.getfloat('primary', 'snr-threshold')
    pfreq = cp.getfloats('primary', 'frequency-range')
    preadkw = cp.getparams('primary', 'read-')
    if pcache is not None:  # auto-detect the file format
        LOGGER.debug('Unsetting the primary trigger file format')
        preadkw['format'] = None
        preadkw['path'] = 'triggers'
    ptrigfindkw = cp.getparams('primary', 'trigfind-')
    primary = get_triggers(pchannel, petg, analysis.active, snr=psnr,
                           frange=pfreq, cache=pcache, nproc=args.nproc,
                           trigfind_kwargs=ptrigfindkw, **preadkw)
    fcol, scol = primary.dtype.names[1:3]

    if len(primary):
        LOGGER.info("Read %d events for %s" % (len(primary), pchannel))
    else:
        message = "No events found for %r in %d seconds of livetime" % (
           pchannel, livetime)
        LOGGER.critical(message)

    # cluster primary triggers
    clusterkwargs = cp.getparams('primary', 'cluster-')
    if clusterkwargs:
        primary = primary.cluster(**clusterkwargs)
        LOGGER.info("%d primary events remain after clustering over %s" %
                    (len(primary), clusterkwargs['rank']))

    # -- bail out early -------------------------
    # the bail out is done here so that we can at least generate the eventual
    # configuration file, mainly for HTML purposes

    # no segments
    if livetime == 0:
        message = ("No active segments found for analysis flag %r in interval "
                   "[%d, %d)" % (aflag, start, end))
        LOGGER.critical(message)
        htmlv['context'] = 'info'
        index = html.write_null_page(ifo, start, end, message, **htmlv)
        LOGGER.info("HTML report written to %s" % index)
        sys.exit(0)

    # no primary triggers
    if len(primary) == 0:
        htmlv['context'] = 'danger'
        index = html.write_null_page(ifo, start, end, message, **htmlv)
        LOGGER.info("HTML report written to %s" % index)
        sys.exit(0)

    # otherwise write all primary triggers to ASCII
    trigfile = os.path.join(
        trigdir,
        '%s-HVETO_RAW_TRIGS_ROUND_0-%d-%d.txt' % (ifo, start, duration),
    )
    primary.write(trigfile, format='ascii', overwrite=True)

    # -- load auxiliary triggers ----------------

    LOGGER.info("Reading triggers for aux channels...")
    counter = multiprocessing.Value('i', 0)

    areadkw = cp.getparams('auxiliary', 'read-')
    if acache is not None:  # auto-detect the file format
        LOGGER.debug('Unsetting the auxiliary trigger file format')
        areadkw['format'] = None
        areadkw['path'] = 'triggers'
    atrigfindkw = cp.getparams('auxiliary', 'trigfind-')

    # map with multiprocessing
    if args.nproc > 1:
        pool = multiprocessing.Pool(processes=args.nproc)
        results = pool.map(_get_aux_triggers, auxchannels)
        pool.close()
    # map without multiprocessing
    else:
        results = map(_get_aux_triggers, auxchannels)

    LOGGER.info("All aux events loaded")

    auxiliary = dict(x for x in results if x is not None)
    auxchannels = sorted(auxiliary.keys())
    chanfile = '%s-HVETO_CHANNEL_LIST-%d-%d.txt' % (ifo, start, duration)
    with open(chanfile, 'w') as f:
        for chan in auxchannels:
            print(chan, file=f)
    LOGGER.info("Recorded list of valid auxiliary channels in %s" % chanfile)

    # -- execute hveto analysis -----------------

    minsig = cp.getfloat('hveto', 'minimum-significance')

    pevents = [primary]
    pvetoed = []

    auxfcol, auxscol = auxiliary[auxchannels[0]].dtype.names[1:3]
    slabel = plot.get_column_label(scol)
    flabel = plot.get_column_label(fcol)
    auxslabel = plot.get_column_label(auxscol)
    auxflabel = plot.get_column_label(auxfcol)

    rounds = []
    rnd = core.HvetoRound(1, pchannel, rank=scol)
    rnd.segments = analysis.active

    while True:
        LOGGER.info("-- Processing round %d --" % rnd.n)

        # write segments for this round
        segfile = os.path.join(
            segdir, '%s-HVETO_ANALYSIS_SEGS_ROUND_%d-%d-%d.txt'
                    % (ifo, rnd.n, start, duration))
        write_ascii_segments(segfile, rnd.segments)

        # calculate significances for this round
        if args.nproc > 1:  # multiprocessing
            # separate channel list into chunks and process each chunk
            pool = multiprocessing.Pool(
                processes=min(args.nproc, len(auxiliary.keys())))
            chunks = utils.channel_groups(list(auxiliary.keys()), args.nproc)
            results = pool.map(_find_max_significance, chunks)
            pool.close()
            winners, sigsets = zip(*results)
            # find winner of chunk winners
            winner = sorted(winners, key=lambda w: w.significance)[-1]
            # flatten sets of significances into one list
            newsignificances = sigsets[0]
            for subdict in sigsets[1:]:
                newsignificances.update(subdict)
        else:  # single process
            winner, newsignificances = core.find_max_significance(
                primary, auxiliary, pchannel, snrs, windows, rnd.livetime)

        LOGGER.info("Round %d winner: %s" % (rnd.n, winner.name))

        # plot significance drop here for the last round
        #   only now do we actually have the new data to
        #   calculate significance drop
        if rnd.n > 1:
            svg = (pngname % 'SIG_DROP').replace('.png', '.svg')  # noqa: F821
            plot.significance_drop(
                svg, oldsignificances, newsignificances,  # noqa: F821
                title=' | '.join([title, subtitle]),  # noqa: F821
                bbox_inches='tight')
            LOGGER.debug("Figure written to %s" % svg)
            svg = FancyPlot(svg, caption=plot.ROUND_CAPTION['SIG_DROP'])
            rounds[-1].plots.append(svg)
        oldsignificances = newsignificances  # noqa: F841

        # break out of the loop if the significance is below stopping point
        if winner.significance < minsig:
            LOGGER.info("Maximum signifiance below stopping point")
            LOGGER.debug("    (%.2f < %.2f)" % (winner.significance, minsig))
            LOGGER.info("-- Rounds complete! --")
            break

        # work out the vetoes for this round
        allaux = auxiliary[winner.name][
            auxiliary[winner.name][auxscol] >= winner.snr]
        winner.events = allaux
        coincs = allaux[core.find_coincidences(allaux['time'], primary['time'],
                                               dt=winner.window)]
        rnd.vetoes = winner.get_segments(allaux['time'])
        flag = DataQualityFlag(
            '%s:HVT-ROUND_%d:1' % (ifo, rnd.n), active=rnd.vetoes,
            known=rnd.segments,
            description="winner=%s, window=%s, snr=%s" % (
                winner.name, winner.window, winner.snr))
        segments[flag.name] = flag
        LOGGER.debug("Generated veto segments for round %d" % rnd.n)

        # link events before veto for plotting
        before = primary
        beforeaux = auxiliary[winner.name]

        # apply vetoes to primary
        primary, vetoed = core.veto(primary, rnd.vetoes)
        pevents.append(primary)
        pvetoed.append(vetoed)
        LOGGER.debug("Applied vetoes to primary")

        # record results
        rnd.winner = winner
        rnd.efficiency = (len(vetoed), len(primary) + len(vetoed))
        rnd.use_percentage = (len(coincs), len(winner.events))
        if rnd.n > 1:
            rnd.cum_efficiency = (
                len(vetoed) + rounds[-1].cum_efficiency[0],
                rounds[0].efficiency[1])
            rnd.cum_deadtime = (
                rnd.deadtime[0] + rounds[-1].cum_deadtime[0],
                livetime)
        else:
            rnd.cum_efficiency = rnd.efficiency
            rnd.cum_deadtime = rnd.deadtime

        # apply vetoes to auxiliary
        if args.nproc > 1:  # multiprocess
            # separate channel list into chunks and process each chunk
            pool = multiprocessing.Pool(
                processes=min(args.nproc, len(auxiliary.keys())))
            chunks = utils.channel_groups(list(auxiliary.keys()), args.nproc)
            results = pool.map(_veto, chunks)
            pool.close()
            auxiliary = results[0]
            for subdict in results[1:]:
                auxiliary.update(subdict)
        else:  # single process
            auxiliary = core.veto_all(auxiliary, rnd.vetoes)
        LOGGER.debug("Applied vetoes to auxiliary channels")

        # log results
        LOGGER.info("""Results for round %d:\n\n
    winner :          %s
    significance :    %s
    mu :              %s
    snr :             %s
    dt :              %s
    use_percentage :  %s
    efficiency :      %s
    deadtime :        %s
    cum. efficiency : %s
    cum. deadtime :   %s\n\n""" % (
            rnd.n, rnd.winner.name, rnd.winner.significance,
            rnd.winner.mu, rnd.winner.snr, rnd.winner.window,
            rnd.use_percentage, rnd.efficiency, rnd.deadtime,
            rnd.cum_efficiency, rnd.cum_deadtime))

        # write segments
        segfile = os.path.join(
            segdir,
            '%s-HVETO_VETO_SEGS_ROUND_%d-%d-%d.txt' % (
                ifo, rnd.n, start, duration))
        write_ascii_segments(segfile, rnd.vetoes)
        LOGGER.debug("Round %d vetoes written to %s" % (rnd.n, segfile))
        rnd.files['VETO_SEGS'] = (segfile,)
        # write triggers
        trigfile = os.path.join(
            trigdir,
            '%s-HVETO_%%s_TRIGS_ROUND_%d-%d-%d.txt' % (
                ifo, rnd.n, start, duration))
        for tag, arr in zip(
                ['WINNER', 'VETOED', 'RAW'],
                [winner.events, vetoed, primary]):
            f = trigfile % tag
            arr.write(f, format='ascii', overwrite=True)
            LOGGER.debug("Round %d %s events written to %s"
                         % (rnd.n, tag.lower(), f))
            rnd.files[tag] = f

        # record times to omega scan
        if args.omega_scans:
            N = len(vetoed)
            ind = random.sample(range(0, N), min(args.omega_scans, N))
            rnd.scans = vetoed[ind]
            LOGGER.debug("Collected %d events to omega scan:\n\n%s\n\n"
                         % (len(rnd.scans), rnd.scans))

        # -- make some plots --

        pngname = os.path.join(plotdir, '%s-HVETO_%%s_ROUND_%d-%d-%d.png' % (
            ifo, rnd.n, start, duration))
        wname = texify(rnd.winner.name)
        beforel = 'Before\n[%d]' % len(before)
        afterl = 'After\n[%d]' % len(primary)
        vetoedl = 'Vetoed\n(primary)\n[%d]' % len(vetoed)
        beforeauxl = 'All\n[%d]' % len(beforeaux)
        usedl = 'Used\n(aux)\n[%d]' % len(winner.events)
        coincl = 'Coinc.\n[%d]' % len(coincs)
        title = '%s Hveto round %d' % (ifo, rnd.n)
        ptitle = '%s: primary impact' % title
        atitle = '%s: auxiliary use' % title
        subtitle = 'winner: %s [%d-%d]' % (wname, start, end)

        # before/after histogram
        png = pngname % 'HISTOGRAM'
        plot.before_after_histogram(
            png, before[scol], primary[scol],
            label1=beforel, label2=afterl, xlabel=slabel,
            title=ptitle, subtitle=subtitle)
        LOGGER.debug("Figure written to %s" % png)
        png = FancyPlot(png, caption=plot.ROUND_CAPTION['HISTOGRAM'])
        rnd.plots.append(png)

        # snr versus time
        png = pngname % 'SNR_TIME'
        plot.veto_scatter(
            png, before, vetoed, x='time', y=scol, label1=beforel,
            label2=vetoedl, epoch=start, xlim=[start, end], ylabel=slabel,
            title=ptitle, subtitle=subtitle, legend_title="Primary:")
        LOGGER.debug("Figure written to %s" % png)
        png = FancyPlot(png, caption=plot.ROUND_CAPTION['SNR_TIME'])
        rnd.plots.append(png)

        # snr versus frequency
        png = pngname % 'SNR_%s' % fcol.upper()
        plot.veto_scatter(
            png, before, vetoed, x=fcol, y=scol, label1=beforel,
            label2=vetoedl, xlabel=flabel, ylabel=slabel, xlim=pfreq,
            title=ptitle, subtitle=subtitle, legend_title="Primary:")
        LOGGER.debug("Figure written to %s" % png)
        png = FancyPlot(png, caption=plot.ROUND_CAPTION['SNR'])
        rnd.plots.append(png)

        # frequency versus time coloured by SNR
        png = pngname % '%s_TIME' % fcol.upper()
        plot.veto_scatter(
            png, before, vetoed, x='time', y=fcol, color=scol,
            label1=None, label2=None, ylabel=flabel,
            clabel=slabel, clim=[3, 100], cmap='YlGnBu',
            epoch=start, xlim=[start, end], ylim=pfreq,
            title=ptitle, subtitle=subtitle)
        LOGGER.debug("Figure written to %s" % png)
        png = FancyPlot(png, caption=plot.ROUND_CAPTION['TIME'])
        rnd.plots.append(png)

        # aux used versus frequency
        png = pngname % 'USED_SNR_TIME'
        plot.veto_scatter(
            png, winner.events, vetoed, x='time', y=[auxscol, scol],
            label1=usedl, label2=vetoedl, ylabel=slabel, epoch=start,
            xlim=[start, end], title=atitle, subtitle=subtitle)
        LOGGER.debug("Figure written to %s" % png)
        png = FancyPlot(png, caption=plot.ROUND_CAPTION['USED_SNR_TIME'])
        rnd.plots.append(png)

        # snr versus time
        png = pngname % 'AUX_SNR_TIME'
        plot.veto_scatter(
            png, beforeaux, (winner.events, coincs), x='time', y=auxscol,
            label1=beforeauxl, label2=(usedl, coincl), epoch=start,
            xlim=[start, end], ylabel=auxslabel, title=atitle,
            subtitle=subtitle)
        LOGGER.debug("Figure written to %s" % png)
        png = FancyPlot(png, caption=plot.ROUND_CAPTION['AUX_SNR_TIME'])
        rnd.plots.append(png)

        # snr versus frequency
        png = pngname % 'AUX_SNR_FREQUENCY'
        plot.veto_scatter(
            png, beforeaux, (winner.events, coincs), x=auxfcol, y=auxscol,
            label1=beforeauxl, label2=(usedl, coincl), xlabel=auxflabel,
            ylabel=auxslabel, title=atitle, subtitle=subtitle,
            legend_title="Aux:")
        LOGGER.debug("Figure written to %s" % png)
        png = FancyPlot(png, caption=plot.ROUND_CAPTION['AUX_SNR_FREQUENCY'])
        rnd.plots.append(png)

        # frequency versus time coloured by SNR
        png = pngname % 'AUX_FREQUENCY_TIME'
        plot.veto_scatter(
            png, beforeaux, (winner.events, coincs), x='time', y=auxfcol,
            color=auxscol, label1=None, label2=[None, None], ylabel=auxflabel,
            clabel=auxslabel, clim=[3, 100], cmap='YlGnBu', epoch=start,
            xlim=[start, end], title=atitle, subtitle=subtitle)
        LOGGER.debug("Figure written to %s" % png)
        png = FancyPlot(png, caption=plot.ROUND_CAPTION['AUX_FREQUENCY_TIME'])
        rnd.plots.append(png)

        # move to the next round
        rounds.append(rnd)
        rnd = core.HvetoRound(rnd.n + 1, pchannel, rank=scol,
                              segments=rnd.segments-rnd.vetoes)

    # write file with all segments
    segfile = os.path.join(
        segdir, '%s-HVETO_SEGMENTS-%d-%d.h5' % (ifo, start, duration))
    segments.write(segfile, overwrite=True)
    LOGGER.debug("Segment summary written to %s" % segfile)

    LOGGER.debug("Making summary figures...")

    # -- exit early if no rounds above threshold

    if not rounds:
        message = ("No rounds completed above threshold. Analysis stopped "
                   "with %s achieving significance of %.2f"
                   % (winner.name, winner.significance))
        LOGGER.critical(message)
        message = message.replace(
            winner.name, cis_link(winner.name, class_='alert-link'))
        message += '<br>[T<sub>win</sub>: %ss, SNR: %s]' % (
            winner.window, winner.snr)
        htmlv['context'] = 'warning'
        index = html.write_null_page(ifo, start, end, message, **htmlv)
        LOGGER.info("HTML report written to %s" % index)
        sys.exit(0)

    # -- plot all rounds impact
    pngname = os.path.join(plotdir, '%s-HVETO_%%s_ALL_ROUNDS-%d-%d.png' % (
        ifo, start, duration))
    plots = []
    title = '%s Hveto all rounds' % args.ifo
    subtitle = '%d rounds | %d-%d' % (len(rounds), start, end)

    # before/after histogram
    png = pngname % 'HISTOGRAM'
    beforel = 'Before analysis [%d events]' % len(pevents[0])
    afterl = 'After %d rounds [%d]' % (len(pevents) - 1, len(pevents[-1]))
    plot.before_after_histogram(
        png, pevents[0][scol], pevents[-1][scol],
        label1=beforel, label2=afterl, xlabel=slabel,
        title=title, subtitle=subtitle)
    png = FancyPlot(png, caption=plot.HEADER_CAPTION['HISTOGRAM'])
    plots.append(png)
    LOGGER.debug("Figure written to %s" % png)

    # efficiency/deadtime curve
    png = pngname % 'ROC'
    plot.hveto_roc(png, rounds, title=title, subtitle=subtitle)
    png = FancyPlot(png, caption=plot.HEADER_CAPTION['ROC'])
    plots.append(png)
    LOGGER.debug("Figure written to %s" % png)

    # frequency versus time
    png = pngname % '%s_TIME' % fcol.upper()
    labels = [str(r.n) for r in rounds]
    legtitle = 'Vetoed at\nround'
    plot.veto_scatter(
        png, pevents[0], pvetoed,
        label1='', label2=labels, title=title,
        subtitle=subtitle, ylabel=flabel, x='time', y=fcol,
        epoch=start, xlim=[start, end], legend_title=legtitle)
    png = FancyPlot(png, caption=plot.HEADER_CAPTION['TIME'])
    plots.append(png)
    LOGGER.debug("Figure written to %s" % png)

    # snr versus time
    png = pngname % 'SNR_TIME'
    plot.veto_scatter(
        png, pevents[0], pvetoed, label1='', label2=labels, title=title,
        subtitle=subtitle, ylabel=slabel, x='time', y=scol,
        epoch=start, xlim=[start, end], legend_title=legtitle)
    png = FancyPlot(png, caption=plot.HEADER_CAPTION['SNR_TIME'])
    plots.append(png)
    LOGGER.debug("Figure written to %s" % png)

    # -- write summary states to ASCII table and JSON
    json_ = {
        'user': getuser(),
        'host': getfqdn(),
        'date': str(datetime.datetime.now()),
        'configuration': inifile,
        'ifo': ifo,
        'gpsstart': start,
        'gpsend': end,
        'call': ' '.join(sys.argv),
        'rounds': [],
    }
    with open('summary-stats.txt', 'w') as f:
        # print header
        print('#N winner window SNR significance nveto use-percentage '
              'efficiency deadtime cumulative-efficiency cumulative-deadtime',
              file=f)
        for r in rounds:
            # extract relevant statistics
            results = [
                ('round', r.n),
                ('name', r.winner.name),
                ('window', r.winner.window),
                ('snr', r.winner.snr),
                ('significance', r.winner.significance),
                ('nveto', r.efficiency[0]),
                ('use-percentage',
                    r.use_percentage[0] / r.use_percentage[1] * 100.),
                ('efficiency', r.efficiency[0] / r.efficiency[1] * 100.),
                ('deadtime', r.deadtime[0] / r.deadtime[1] * 100.),
                ('cumulative-efficiency',
                    r.cum_efficiency[0] / r.cum_efficiency[1] * 100.),
                ('cumulative-deadtime',
                    r.cum_deadtime[0] / r.cum_deadtime[1] * 100.),
            ]
            # write to ASCII
            print(' '.join(map(str, list(zip(*results))[1])), file=f)
            # write to JSON
            results.append(('files', r.files))
            json_['rounds'].append(dict(results))
    LOGGER.debug("Summary table written to %s" % f.name)

    with open('summary-stats.json', 'w') as f:
        json.dump(json_, f, sort_keys=True)
    LOGGER.debug("Summary JSON written to %s" % f.name)

    # -- generate workflow for omega scans

    if args.omega_scans:
        omegatimes = list(map(str, sorted(numpy.unique(
            [t['time'] for r in rounds for t in r.scans]))))
        LOGGER.debug("Collected %d times to omega scan" % len(omegatimes))
        newtimes = [t for t in omegatimes if not
                    os.path.exists(os.path.join(omegadir, str(t)))]
        LOGGER.debug("%d scans already complete or in progress, %d remaining"
                     % (len(omegatimes) - len(newtimes), len(newtimes)))
        if len(newtimes) > 0:
            LOGGER.info('Creating workflow for omega scans')
            flags = batch.get_command_line_flags(
                ifo=ifo,
                ignore_state_flags=True)
            condorcmds = batch.get_condor_arguments(
                timeout=4,
                extra_commands=["request_disk='1G'"],
                gps=start)
            batch.generate_dag(
                newtimes,
                flags=flags,
                submit=True,
                outdir=omegadir,
                condor_commands=condorcmds)
            LOGGER.info('Launched {} omega scans to condor'.format(
                len(newtimes)))
        else:
            LOGGER.debug('Skipping omega scans')

    # -- write HTML and finish

    index = html.write_hveto_page(
        ifo, start, end, rounds, plots,
        winners=[r.winner.name for r in rounds], **htmlv)
    LOGGER.debug("HTML written to %s" % index)
    LOGGER.debug("Analysis completed in %d seconds" % (time.time() - JOBSTART))
    LOGGER.info("-- Hveto complete --")
Exemple #2
0
def main(args=None):
    """Run the software saturation command-line interface
    """
    parser = create_parser()
    args = parser.parse_args(args=args)

    # get IFO
    ifo = args.ifo.upper()
    site = ifo[0]
    frametype = args.frametype or '%s_R' % ifo

    # let's go
    LOGGER.info('{} Software saturations {}-{}'.format(
        args.ifo, int(args.gpsstart), int(args.gpsend)))

    # get segments
    span = Segment(args.gpsstart, args.gpsend)
    if args.state_flag:
        state = DataQualityFlag.query(args.state_flag, int(args.gpsstart),
                                      int(args.gpsend),
                                      url=const.DEFAULT_SEGMENT_SERVER)
        for i, seg in enumerate(state.active):
            state.active[i] = type(seg)(seg[0], seg[1]-args.pad_state_end)
        segs = state.active.coalesce()
        LOGGER.debug("Recovered %d seconds of time for %s"
                     % (abs(segs), args.state_flag))
    else:
        segs = SegmentList([Segment(args.gpsstart, args.gpsend)])

    # find frames
    cache = gwdatafind.find_urls(
        site, frametype, int(args.gpsstart), int(args.gpsend))

    # find channels
    if not os.getenv('LIGO_DATAFIND_SERVER'):
        raise RuntimeError("No LIGO_DATAFIND_SERVER variable set, don't know "
                           "how to discover channels")
    else:
        LOGGER.debug("Identifying channels in frame files")
        if len(cache) == 0:
            raise RuntimeError(
                "No frames recovered for %s in interval [%s, %s)" %
                (frametype, int(args.gpsstart),
                 int(args.gpsend)))
        allchannels = get_channel_names(cache[0])
        LOGGER.debug("   Found %d channels" % len(allchannels))
        sys.stdout.flush()
        channels = core.find_limit_channels(allchannels, skip=args.skip)
        LOGGER.info(
            "   Parsed %d channels with '_LIMIT' and '_LIMEN' or '_SWSTAT'"
            % sum(map(len, channels)))

    # -- read channels and check limits -------------

    saturations = DataQualityDict()
    bad = set()

    # TODO: use multiprocessing to separate channel list into discrete chunks
    #       should give a factor of X for X processes

    # check limens
    for suffix, clist in zip(['LIMEN', 'SWSTAT'], channels):
        nchans = len(clist)
        # group channels in sets for batch processing
        #     min of <number of channels>, user group size (sensible number),
        #     and 512 Mb of RAM for single-precision EPICS
        try:
            dur = max([float(abs(s)) for s in segs])
        except ValueError:
            ngroup = args.group_size
        else:
            ngroup = int(
                min(nchans, args.group_size, 2 * 1024**3 / 4. / 16. / dur))
        LOGGER.info('Processing %s channels in groups of %d' % (
            suffix, ngroup))
        sys.stdout.flush()
        sets = core.grouper(clist, ngroup)
        for i, cset in enumerate(sets):
            # remove empty entries use to pad the list to 8 elements
            cset = list(cset)
            while cset[-1] is None:
                cset.pop(-1)
            for seg in segs:
                cache2 = sieve_cache(cache, segment=seg)
                if not len(cache2):
                    continue
                saturated = core.is_saturated(
                    cset, cache2, seg[0], seg[1], indicator=suffix,
                    nproc=args.nproc)
                for new in saturated:
                    try:
                        saturations[new.name] += new
                    except KeyError:
                        saturations[new.name] = new
            for j, c in enumerate(cset):
                try:
                    sat = saturations[c]
                except KeyError:
                    LOGGER.debug('%40s:      SKIP      [%d/%d]'
                                 % (c, i*ngroup + j + 1, nchans))
                else:
                    if abs(sat.active):
                        LOGGER.debug('%40s: ---- FAIL ---- [%d/%d]'
                                     % (c, i*ngroup + j + 1, nchans))
                        for seg in sat.active:
                            LOGGER.debug(" " * 42 + str(seg))
                        bad.add(c)
                    else:
                        LOGGER.debug('%40s:      PASS      [%d/%d]'
                                     % (c, i*ngroup + j + 1, nchans))
                sys.stdout.flush()

    # -- log results and exit -----------------------

    if len(bad):
        LOGGER.info("Saturations were found for all of the following:\n\n")
        for c in bad:
            print(c)
        print('\n\n')
    else:
        LOGGER.info("No software saturations were found in any channels")

    # write segments to file
    outfile = ('%s-SOFTWARE_SATURATIONS-%d-%d.h5'
               % (ifo, int(args.gpsstart),
                  int(args.gpsend) - int(args.gpsstart)))
    LOGGER.info("Writing saturation segments to %s" % outfile)
    saturations.write(outfile, path="segments", overwrite=True)

    if args.html:
        # get base path
        base = os.path.dirname(args.html)
        os.chdir(base)
        if args.plot:
            args.plot = os.path.curdir
        segfile = os.path.relpath(outfile, os.path.dirname(args.html))
        if os.path.basename(args.html) == 'index.html':
            links = [
                '%d-%d' % (int(args.gpsstart), int(args.gpsend)),
                ('Parameters', '#parameters'),
                ('Segments', [('Software saturations',
                               '#software-saturations')]),
                ('Results', '#results'),
            ]
            if args.state_flag:
                links[2][1].insert(0, ('State flag', '#state-flag'))
            (brand, class_) = htmlio.get_brand(ifo, 'Saturations',
                                               args.gpsstart)
            navbar = htmlio.navbar(links, class_=class_, brand=brand)
            page = htmlio.new_bootstrap_page(
                navbar=navbar, title='%s Saturations | %d-%d' % (
                    ifo, int(args.gpsstart), int(args.gpsend)))
        else:
            page = markup.page()
            page.div(class_='container')
        # -- header
        page.div(class_='pb-2 mt-3 mb-2 border-bottom')
        page.h1('%s Software Saturations: %d-%d'
                % (ifo, int(args.gpsstart), int(args.gpsend)))
        page.div.close()
        # -- paramters
        content = [
            ('State end padding', args.pad_state_end),
            ('Skip', ', '.join(map(repr, args.skip)))]
        page.h2('Parameters', class_='mt-4 mb-4', id_='parameters')
        page.div(class_='row')
        page.div(class_='col-md-9 col-sm-12')
        page.add(htmlio.parameter_table(
            content, start=args.gpsstart, end=args.gpsend,
            flag=args.state_flag))
        page.div.close()  # col-md-9 col-sm-12
        page.div(class_='col-md-3 col-sm-12')
        page.add(htmlio.download_btn(
            [('Segments (HDF)', segfile)],
            btnclass='btn btn-%s dropdown-toggle' % ifo.lower(),
        ))
        page.div.close()  # col-md-9 col-sm-12
        page.div.close()  # row
        page.h5('Command-line:')
        page.add(htmlio.get_command_line(about=False, prog=PROG))
        # -- segments
        page.h2('Segments', class_='mt-4', id_='segments')
        msg = ("This analysis searched {0} filter bank readback channels for "
               "time periods during which their OUTPUT value matched or "
               "exceeded the LIMIT value set in software. Signals that "
               "achieve saturation are shown below, and saturation segments "
               "are available by expanding a given panel.").format(
                   sum(map(len, channels)))
        page.add(htmlio.alert(msg, context=ifo.lower()))
        # record state segments
        if args.state_flag:
            page.h3('State flag', class_='mt-3', id_='state-flag')
            page.div(id_='accordion1')
            page.add(htmlio.write_flag_html(
                state, span, 'state', parent='accordion1', context='success',
                plotdir=args.plot, facecolor=(0.2, 0.8, 0.2),
                edgecolor='darkgreen', known={
                    'facecolor': 'red',
                    'edgecolor': 'darkred',
                    'height': 0.4},
            ))
            page.div.close()
        # record saturation segments
        if len(bad):
            page.h3('Software saturations', class_='mt-3',
                    id_='software-saturations')
            page.div(id_='accordion2')
            for i, (c, flag) in enumerate(saturations.items()):
                if abs(flag.active) > 0:
                    title = '%s [%d]' % (flag.name, len(flag.active))
                    page.add(htmlio.write_flag_html(
                        flag, span=span, id=i, parent='accordion2',
                        title=title, plotdir=args.plot))
            page.div.close()
        else:
            page.add(htmlio.alert('No software saturations were found in this '
                                  'analysis', context=ifo.lower(),
                                  dismiss=False))
        # -- results table
        page.h2('Results summary', class_='mt-4', id_='results')
        page.add(htmlio.alert('All channels for which the LIMIT setting was '
                              'active are shown below.', context=ifo.lower()))
        page.table(class_='table table-striped table-hover')
        # write table header
        page.thead()
        page.tr()
        for header in ['Channel', 'Result', 'Num. saturations']:
            page.th(header)
        page.thead.close()
        # write body
        page.tbody()
        for c, seglist in saturations.items():
            passed = abs(seglist.active) == 0
            if passed:
                page.tr()
            else:
                page.tr(class_='table-warning')
            page.td(c)
            page.td(passed and 'Pass' or 'Fail')
            page.td(len(seglist.active))
            page.tr.close()
        page.tbody.close()
        page.table.close()
        # close and write
        htmlio.close_page(page, args.html)
Exemple #3
0
def main(args=None):
    """Run the online Guardian node visualization tool
    """
    parser = create_parser()
    args = parser.parse_args(args=args)

    fec_map = args.fec_map
    simulink = args.simulink
    daqsvn = args.daqsvn or ('https://daqsvn.ligo-la.caltech.edu/websvn/'
                             'listing.php?repname=daq_maps')
    if args.ifo == 'H1':
        if not fec_map:
            fec_map = 'https://lhocds.ligo-wa.caltech.edu/exports/detchar/fec/'
        if not simulink:
            simulink = 'https://lhocds.ligo-wa.caltech.edu/daq/simulink/'
    if args.ifo == 'L1':
        if not fec_map:
            fec_map = 'https://llocds.ligo-la.caltech.edu/exports/detchar/fec/'
        if not simulink:
            simulink = 'https://llocds.ligo-la.caltech.edu/daq/simulink/'

    span = Segment(args.gpsstart, args.gpsend)

    # let's go
    LOGGER.info('{} Overflows {}-{}'.format(args.ifo, int(args.gpsstart),
                                            int(args.gpsend)))

    # get segments
    if args.state_flag:
        state = DataQualityFlag.query(args.state_flag,
                                      int(args.gpsstart),
                                      int(args.gpsend),
                                      url=const.DEFAULT_SEGMENT_SERVER)
        tmp = type(state.active)()
        for i, seg in enumerate(state.active):
            if abs(seg) < args.segment_end_pad:
                continue
            tmp.append(type(seg)(seg[0], seg[1] - args.segment_end_pad))
        state.active = tmp.coalesce()
        statea = state.active
    else:
        statea = SegmentList([span])

    if not args.output_file:
        duration = abs(span)
        args.output_file = ('%s-OVERFLOWS-%d-%d.h5' %
                            (args.ifo, int(args.gpsstart), duration))
        LOGGER.debug("Set default output file as %s" % args.output_file)

    # set up container
    overflows = DataQualityDict()

    # prepare data access
    if args.nds:
        from gwpy.io import nds2 as io_nds2
        host, port = args.nds.rsplit(':', 1)
        ndsconnection = io_nds2.connect(host, port=int(port))
        if ndsconnection.get_protocol() == 1:
            cachesegs = SegmentList(
                [Segment(int(args.gpsstart), int(args.gpsend))])
        else:
            cachesegs = io_nds2.get_availability(
                ['{0}:FEC-1_DAC_OVERFLOW_ACC_0_0'.format(args.ifo)],
                int(args.gpsstart),
                int(args.gpsend),
            )
    else:  # get frame cache
        cache = gwdatafind.find_urls(args.ifo[0], args.frametype,
                                     int(args.gpsstart), int(args.gpsend))
        cachesegs = statea & cache_segments(cache)

    flag_desc = "ADC/DAC Overflow indicated by {0}"

    # get channel and find overflows
    for dcuid in args.dcuid:
        LOGGER.info("Processing DCUID %d" % dcuid)
        channel = daq.ligo_accum_overflow_channel(dcuid, args.ifo)
        overflows[channel] = DataQualityFlag(channel, known=cachesegs)
        if args.deep:
            LOGGER.debug(" -- Getting list of overflow channels")
            try:
                channels = daq.ligo_model_overflow_channels(dcuid,
                                                            args.ifo,
                                                            args.frametype,
                                                            gpstime=span[0],
                                                            nds=args.nds)
            except IndexError:  # no frame found for GPS start, try GPS end
                channels = daq.ligo_model_overflow_channels(dcuid,
                                                            args.ifo,
                                                            args.frametype,
                                                            gpstime=span[-1])
            for chan in channels:  # set up flags early
                overflows[chan] = DataQualityFlag(
                    chan,
                    known=cachesegs,
                    description=flag_desc.format(chan),
                    isgood=False,
                )
            LOGGER.debug(" -- %d channels found" % len(channel))
        for seg in cachesegs:
            LOGGER.debug(" -- Processing {}-{}".format(*seg))
            if args.nds:
                read_kw = dict(connection=ndsconnection)
            else:
                read_kw = dict(source=cache, nproc=args.nproc)
            msg = "Reading ACCUM_OVERFLOW data:".rjust(30)
            data = get_data(channel,
                            seg[0],
                            seg[1],
                            pad=0.,
                            verbose=msg,
                            **read_kw)
            new = daq.find_overflow_segments(
                data,
                cumulative=True,
            )
            overflows[channel] += new
            LOGGER.info(" -- {} overflows found".format(len(new.active)))
            if not new.active:
                continue
            # go deep!
            for s, e in tqdm.tqdm(new.active.protract(2),
                                  unit='ovfl',
                                  desc='Going deep'.rjust(30)):
                data = get_data(channels, s, e, **read_kw)
                for ch in channels:
                    try:
                        overflows[ch] += daq.find_overflow_segments(
                            data[ch],
                            cumulative=True,
                        )
                    except KeyError:
                        warnings.warn("Skipping {}".format(ch), UserWarning)
                        continue
        LOGGER.debug(" -- Search complete")

    # write output
    LOGGER.info("Writing segments to %s" % args.output_file)
    table = table_from_segments(
        overflows,
        sngl_burst=args.output_file.endswith((".xml", ".xml.gz")),
    )
    if args.integer_segments:
        for key in overflows:
            overflows[key] = overflows[key].round()
    if args.output_file.endswith((".h5", "hdf", ".hdf5")):
        with h5py.File(args.output_file, "w") as h5f:
            table.write(h5f, path="triggers")
            overflows.write(h5f, path="segments")
    else:
        table.write(args.output_file, overwrite=True)
        overflows.write(args.output_file, overwrite=True, append=True)

    # write HTML
    if args.html:
        # get base path
        base = os.path.dirname(args.html)
        os.chdir(base)
        if args.plot:
            args.plot = os.path.curdir
        if args.output_file:
            args.output_file = os.path.relpath(args.output_file,
                                               os.path.dirname(args.html))
        if os.path.basename(args.html) == 'index.html':
            links = [
                '%d-%d' % (int(args.gpsstart), int(args.gpsend)),
                ('Parameters', '#parameters'),
                ('Segments', [('Overflows', '#overflows')]),
                ('Results', '#results'),
            ]
            if args.state_flag:
                links[2][1].insert(0, ('State flag', '#state-flag'))
            (brand, class_) = htmlio.get_brand(args.ifo, 'Overflows',
                                               args.gpsstart)
            navbar = htmlio.navbar(links, class_=class_, brand=brand)
            page = htmlio.new_bootstrap_page(
                title='%s Overflows | %d-%d' %
                (args.ifo, int(args.gpsstart), int(args.gpsend)),
                navbar=navbar)
        else:
            page = htmlio.markup.page()
            page.div(class_='container')

        # -- header
        page.div(class_='pb-2 mt-3 mb-2 border-bottom')
        page.h1('%s ADC/DAC Overflows: %d-%d' %
                (args.ifo, int(args.gpsstart), int(args.gpsend)))
        page.div.close()

        # -- paramters
        content = [('DCUIDs', ' '.join(map(str, args.dcuid)))]
        if daqsvn:
            content.append(('FEC configuration', (
                '<a href="{0}" target="_blank" title="{1} FEC configuration">'
                '{0}</a>').format(daqsvn, args.ifo)))
        if fec_map:
            content.append(
                ('FEC map', '<a href="{0}" target="_blank" title="{1} FEC '
                 'map">{0}</a>'.format(fec_map, args.ifo)))
        if simulink:
            content.append(
                ('Simulink models', '<a href="{0}" target="_blank" title="{1} '
                 'Simulink models">{0}</a>'.format(simulink, args.ifo)))
        page.h2('Parameters', class_='mt-4 mb-4', id_='parameters')
        page.div(class_='row')
        page.div(class_='col-md-9 col-sm-12')
        page.add(
            htmlio.parameter_table(content,
                                   start=args.gpsstart,
                                   end=args.gpsend,
                                   flag=args.state_flag))
        page.div.close()  # col-md-9 col-sm-12

        # link to summary file
        if args.output_file:
            ext = ('HDF' if args.output_file.endswith(
                (".h5", "hdf", ".hdf5")) else 'XML')
            page.div(class_='col-md-3 col-sm-12')
            page.add(
                htmlio.download_btn(
                    [('Segments ({})'.format(ext), args.output_file)],
                    btnclass='btn btn-%s dropdown-toggle' % args.ifo.lower(),
                ))
            page.div.close()  # col-md-3 col-sm-12
        page.div.close()  # row

        # -- command-line
        page.h5('Command-line:')
        page.add(htmlio.get_command_line(about=False, prog=PROG))

        # -- segments
        page.h2('Segments', class_='mt-4', id_='segments')

        # give contextual information
        msg = ("This analysis searched for digital-to-analogue (DAC) or "
               "analogue-to-digital (ADC) conversion overflows in the {0} "
               "real-time controls system. ").format(
                   SITE_MAP.get(args.ifo, 'LIGO'))
        if args.deep:
            msg += (
                "A hierarchichal search was performed, with one cumulative "
                "overflow counter checked per front-end controller (FEC). "
                "For those models that indicated an overflow, the card- and "
                "slot-specific channels were then checked. ")
        msg += (
            "Consant overflow is shown as yellow, while transient overflow "
            "is shown as red. If a data-quality flag was loaded for this "
            "analysis, it will be displayed in green.")
        page.add(htmlio.alert(msg, context=args.ifo.lower()))
        # record state segments
        if args.state_flag:
            page.h3('State flag', class_='mt-3', id_='state-flag')
            page.div(id_='accordion1')
            page.add(
                htmlio.write_flag_html(state,
                                       span,
                                       'state',
                                       parent='accordion1',
                                       context='success',
                                       plotdir=args.plot,
                                       facecolor=(0.2, 0.8, 0.2),
                                       edgecolor='darkgreen',
                                       known={
                                           'facecolor': 'red',
                                           'edgecolor': 'darkred',
                                           'height': 0.4,
                                       }))
            page.div.close()
        # record overflow segments
        if sum(abs(s.active) for s in overflows.values()):
            page.h3('Overflows', class_='mt-3', id_='overflows')
            page.div(id_='accordion2')
            for i, (c, flag) in enumerate(list(overflows.items())):
                if abs(flag.active) == 0:
                    continue
                if abs(flag.active) == abs(cachesegs):
                    context = 'warning'
                else:
                    context = 'danger'
                try:
                    channel = cds.get_real_channel(flag.name)
                except Exception:
                    title = '%s [%d]' % (flag.name, len(flag.active))
                else:
                    title = '%s (%s) [%d]' % (flag.name, channel,
                                              len(flag.active))
                page.add(
                    htmlio.write_flag_html(flag,
                                           span,
                                           i,
                                           parent='accordion2',
                                           title=title,
                                           context=context,
                                           plotdir=args.plot))
            page.div.close()
        else:
            page.add(
                htmlio.alert('No overflows were found in this analysis',
                             context=args.ifo.lower(),
                             dismiss=False))

        # -- results table
        page.h2('Results summary', class_='mt-4', id_='results')
        page.table(class_='table table-striped table-hover')
        # write table header
        page.thead()
        page.tr()
        for header in ['Channel', 'Connected signal', 'Num. overflows']:
            page.th(header)
        page.thead.close()
        # write body
        page.tbody()
        for c, seglist in overflows.items():
            t = abs(seglist.active)
            if t == 0:
                page.tr()
            elif t == abs(cachesegs):
                page.tr(class_='table-warning')
            else:
                page.tr(class_='table-danger')
            page.td(c)
            try:
                page.td(cds.get_real_channel(str(c)))
            except Exception:
                page.td()
            page.td(len(seglist.active))
            page.tr.close()
        page.tbody.close()
        page.table.close()

        # -- close and write
        htmlio.close_page(page, args.html)
        LOGGER.info("HTML written to %s" % args.html)
Exemple #4
0
def main(args=None):
    """Run the online Guardian node visualization tool
    """
    parser = create_parser()
    args = parser.parse_args(args=args)

    # parse command line options
    ifo = args.ifo
    if not args.ifo:
        parser.error('--ifo must be given if not obvious from the host')
    start = getattr(args, 'gpsstart')
    end = getattr(args, 'gpsend')
    duration = int(ceil(end) - floor(start))
    categories = args.categories.split(',')
    for i, c in enumerate(categories):
        try:
            categories[i] = int(c)
        except (TypeError, ValueError):
            pass
    vetofile = getattr(args, 'veto-definer-file')
    vetofile = (urlparse(vetofile).netloc or os.path.abspath(vetofile))
    args.metric = args.metric or DEFAULT_METRICS

    # -- setup --------------------------------------

    tag = '%d-%d' % (start.seconds, end.seconds)
    outdir = os.path.abspath(os.path.join(args.output_directory, tag))
    mkdir(outdir)
    os.chdir(outdir)
    mkdir('etc', 'segments', 'condor')

    # -- segment handling ---------------------------

    os.chdir('segments')
    ALLSEGMENTS = DataQualityDict()

    # -- get analysis segments ----------------------

    aflags = args.analysis_segments
    asegments = DataQualityFlag('%s:VET-ANALYSIS_SEGMENTS:0' % ifo)
    for i, flag in enumerate(aflags):
        # use union of segments from a file
        if os.path.isfile(flag):
            asegments += DataQualityFlag.read(flag)
        # or intersection of segments from multiple flags
        else:
            new = DataQualityFlag.query(flag, start, end, url=args.segdb)
            if i:
                asegments.known &= new.known
                asegments.active &= new.active
            else:
                asegments.known = new.known
                asegments.active = new.active
    ALLSEGMENTS[asegments.name] = asegments

    if os.path.isfile(aflags[0]):
        asegments.filename = aflags

    # -- read veto definer and process --------------

    if urlparse(vetofile).netloc:
        tmp = urlopen(vetofile)
        vetofile = os.path.abspath(os.path.basename(vetofile))
        with open(vetofile, 'w') as f:
            f.write(tmp.read())
        LOGGER.info('Downloaded veto definer file')
    vdf = DataQualityDict.from_veto_definer_file(vetofile,
                                                 format='ligolw',
                                                 start=start,
                                                 end=end,
                                                 ifo=ifo)
    LOGGER.info('Read %d flags from veto definer' % len(vdf.keys()))

    # populate veto definer file from database
    vdf.populate(source=args.segdb, on_error=args.on_segdb_error)
    ALLSEGMENTS += vdf

    # organise flags into categories
    flags = dict((c, DataQualityDict()) for c in categories)
    for name, flag in vdf.items():
        try:
            flags[flag.category][name] = flag
        except KeyError:
            pass

    # find the states and segments for each category
    states, after, oldtitle = (dict(), None, '')
    for i, category in enumerate(categories):
        title = isinstance(category, int) and 'Cat %d' % category or category
        tag = re_cchar.sub('_', str(title).upper())
        states[category] = SummaryState(
            'After %s' % oldtitle,
            key=tag,
            known=after.known,
            active=after.active,
            definition=after.name,
        ) if i else SummaryState(
            args.analysis_name,
            key=args.analysis_name,
            definition=asegments.name,
        )
        try:
            segs = flags[category].union()
        except TypeError:  # no flags
            segs = DataQualityFlag()
        segs.name = '%s:VET-ANALYSIS_%s:0' % (ifo, tag)
        ALLSEGMENTS[segs.name] = segs
        after = (after - segs) if i else (asegments - segs)
        after.name = '%s:VET-ANALYSIS_AFTER_%s:0' % (ifo, tag)
        ALLSEGMENTS[after.name] = after
        oldtitle = title

    # write all segments to disk
    segfile = os.path.abspath('%s-VET_SEGMENTS-%d-%d.xml.gz' %
                              (ifo, start.seconds, duration))
    ALLSEGMENTS.write(segfile)

    os.chdir(os.pardir)

    if args.verbose:
        LOGGER.debug("All segments accessed and written to\n%s" % segfile)

    # -- job preparation ----------------------------

    os.chdir('etc')

    configs = []
    for category in categories:
        title = (isinstance(category, int) and 'Category %d' % category
                 or category)
        tab = 'tab-%s' % title
        config = ConfigParser()

        # add segment-database configuration
        add_config_section(config, 'segment-database', url=args.segdb)

        # add plot configurations
        pconfig = ConfigParser()
        pconfig.read(args.config_file)
        for section in pconfig.sections():
            if section.startswith('plot-'):
                config._sections[section] = pconfig._sections[section].copy()

        try:
            plots = pconfig.items('plots-%s' % category, raw=True)
        except NoSectionError:
            try:
                plots = pconfig.items('plots', raw=True)
            except NoSectionError:
                plots = []

        # add state
        if args.independent:
            state = states[categories[0]]
        else:
            state = states[category]
        sname = 'state-%s' % state.key
        add_config_section(config,
                           sname,
                           key=state.key,
                           name=state.name,
                           definition=state.definition,
                           filename=segfile)

        # add plugin
        add_config_section(config, 'plugins', **{'gwvet.tabs': ''})

        # define metrics
        if category == 1:
            metrics = ['Deadtime']
        else:
            metrics = args.metric

        # define summary tab
        if category == 1:
            tab = configure_veto_tab(config,
                                     title,
                                     title,
                                     state,
                                     flags[category].keys(),
                                     segfile,
                                     metrics,
                                     name='Summary',
                                     **{'veto-name': title})
        else:
            tab = configure_veto_tab(config,
                                     title,
                                     title,
                                     state,
                                     flags[category].keys(),
                                     segfile,
                                     metrics,
                                     name='Summary',
                                     **{
                                         'veto-name': title,
                                         'event-channel': args.event_channel,
                                         'event-generator':
                                         args.event_generator,
                                     })
        if len(categories) == 1:
            config.set(tab, 'index',
                       '%(gps-start-time)s-%(gps-end-time)s/index.html')
        for key, value in plots:
            if re.match('%\(flags\)s (?:plot-)?segments', value):  # noqa: W605
                config.set(tab, key, '%%(union)s,%s' % value)
                if '%s-labels' % key not in plots:
                    config.set(tab, '%s-labels' % key, 'Union,%(flags)s')
            else:
                config.set(tab, key, value)

        # now a tab for each flag
        for flag in flags[category]:
            if category == 1:
                tab = configure_veto_tab(config, flag, title, state, [flag],
                                         segfile, metrics)
            else:
                tab = configure_veto_tab(
                    config, flag, title, state, [flag], segfile, metrics, **{
                        'event-channel': args.event_channel,
                        'event-generator': args.event_generator
                    })
                if args.event_file:
                    config.set(tab, 'event-file', args.event_file)
            for key, value in plots:
                config.set(tab, key, value)

        if len(categories) > 1 and category != categories[-1]:
            with open('%s.ini' % re_cchar.sub('-', title.lower()), 'w') as f:
                config.write(f)
                configs.append(os.path.abspath(f.name))

    # configure summary job
    if len(categories) > 1:
        state = states[categories[0]]
        add_config_section(config,
                           'state-%s' % state.key,
                           key=state.key,
                           name=state.name,
                           definition=state.definition,
                           filename=segfile)
        try:
            plots = pconfig.items('plots', raw=True)
        except NoSectionError:
            plots = []
        flags = [f for c in categories for f in flags[c].keys()]
        tab = configure_veto_tab(
            config,
            'Impact of full veto definer file',
            None,
            state,
            flags,
            segfile,
            args.metric,
            shortname='Summary',
            index='%(gps-start-time)s-%(gps-end-time)s/index.html',
            **{
                'event-channel': args.event_channel,
                'event-generator': args.event_generator,
                'veto-name': 'All vetoes'
            })
        if args.event_file:
            config.set(tab, 'event-file', args.event_file)
        for key, value in plots:
            config.set(tab, key, value)
        with open('%s.ini' % re_cchar.sub('-', title.lower()), 'w') as f:
            config.write(f)
            configs.append(os.path.abspath(f.name))

    os.chdir(os.pardir)

    if args.verbose:
        LOGGER.debug("Generated configuration files for each category")

    # -- condor preparation -------------------------

    os.chdir(os.pardir)

    # get condor variables
    if getuser() == 'detchar':
        accgroup = 'ligo.prod.o1.detchar.dqproduct.gwpy'
    else:
        accgroup = 'ligo.dev.o1.detchar.dqproduct.gwpy'

    gwsumm_args = [
        '--gps-start-time',
        str(start.seconds),
        '--gps-end-time',
        str(end.seconds),
        '--ifo',
        ifo,
        '--file-tag',
        'gwpy-vet',
        '--condor-command',
        'accounting_group=%s' % accgroup,
        '--condor-command',
        'accounting_group_user=%s' % getuser(),
        '--on-segdb-error',
        args.on_segdb_error,
        '--output-dir',
        args.output_directory,
    ]
    for cf in args.global_config:
        gwsumm_args.extend(('--global-config', cf))
    for cf in configs:
        gwsumm_args.extend(('--config-file', cf))
    if args.verbose:
        gwsumm_args.append('--verbose')

    if args.verbose:
        LOGGER.debug('Generating summary DAG via:\n')
        LOGGER.debug(' '.join([batch.PROG] + gwsumm_args))

    # execute gwsumm in batch mode
    batch.main(args=gwsumm_args)
Exemple #5
0
def main(args=None):
    """Run the primary scattering command-line tool
    """
    parser = create_parser()
    args = parser.parse_args(args=args)

    # set up logger
    logger = cli.logger(
        name=PROG.split('python -m ').pop(),
        level='DEBUG' if args.verbose else 'INFO',
    )

    # useful variables
    fthresh = (
        int(args.frequency_threshold) if args.frequency_threshold.is_integer()
        else args.frequency_threshold)
    multiplier = args.multiplier_for_threshold
    tstr = str(fthresh).replace('.', '_')
    gpsstr = '%s-%s' % (int(args.gpsstart), int(args.gpsend - args.gpsstart))
    args.optic = args.optic or list(OPTIC_MOTION_CHANNELS.keys())

    # go to working directory
    indir = os.getcwd()
    if not os.path.isdir(args.output_dir):
        os.makedirs(args.output_dir)
    os.chdir(args.output_dir)

    # set up output files
    summfile = '{}-SCATTERING_SUMMARY-{}.csv'.format(
        args.ifo, gpsstr)
    segfile = '{}-SCATTERING_SEGMENTS_{}_HZ-{}.h5'.format(
        args.ifo, tstr, gpsstr)

    # log start of process
    logger.info('{} Scattering {}-{}'.format(
        args.ifo, int(args.gpsstart), int(args.gpsend)))

    # -- get state segments -----------

    span = Segment(args.gpsstart, args.gpsend)

    # get segments
    if args.state_flag is not None:
        state = DataQualityFlag.query(
            args.state_flag, int(args.gpsstart), int(args.gpsend),
            url=DEFAULT_SEGMENT_SERVER,
        ).coalesce()
        statea = []
        padding = args.segment_start_pad + args.segment_end_pad
        for i, seg in enumerate(state.active):
            if abs(seg) > padding:
                statea.append(Segment(
                    seg[0] + args.segment_start_pad,
                    seg[1] - args.segment_end_pad,
                ))
            else:
                logger.debug(
                    "Segment length {} shorter than padding length {}, "
                    "skipping segment {}-{}".format(abs(seg), padding, *seg),
                )
        statea = SegmentList(statea)
        logger.debug("Downloaded %d segments for %s"
                     % (len(statea), args.state_flag))
    else:
        statea = SegmentList([span])
    livetime = float(abs(statea))
    logger.debug("Processing %.2f s of livetime" % livetime)

    # -- load h(t) --------------------

    args.main_channel = args.main_channel.format(IFO=args.ifo)
    logger.debug("Loading Omicron triggers for %s" % args.main_channel)

    if args.gpsstart >= 1230336018:  # Jan 1 2019
        ext = "h5"
        names = ["time", "frequency", "snr"]
        read_kw = {
            "columns": names,
            "selection": [
                "{0} < frequency < {1}".format(
                    args.fmin, multiplier * fthresh),
                ("time", in_segmentlist, statea),
            ],
            "format": "hdf5",
            "path": "triggers",
        }
    else:
        ext = "xml.gz"
        names = ['peak', 'peak_frequency', 'snr']
        read_kw = {
            "columns": names,
            "selection": [
                "{0} < peak_frequency < {1}".format(
                    args.fmin, multiplier * fthresh),
                ('peak', in_segmentlist, statea),
            ],
            "format": 'ligolw',
            "tablename": "sngl_burst",
        }

    fullcache = []
    for seg in statea:
        cache = gwtrigfind.find_trigger_files(
            args.main_channel, 'omicron', seg[0], seg[1], ext=ext,
        )
        if len(cache) == 0:
            warnings.warn(
                "No Omicron triggers found for %s in segment [%d .. %d)"
                % (args.main_channel, seg[0], seg[1]),
            )
            continue
        fullcache.extend(cache)

    # read triggers
    if fullcache:
        trigs = EventTable.read(fullcache, nproc=args.nproc, **read_kw)
    else:  # no files (no livetime?)
        trigs = EventTable(names=names)

    highsnrtrigs = trigs[trigs['snr'] >= 8]
    logger.debug("%d read" % len(trigs))

    # -- prepare HTML -----------------

    links = [
        '%d-%d' % (int(args.gpsstart), int(args.gpsend)),
        ('Parameters', '#parameters'),
        ('Segments', (
            ('State flag', '#state-flag'),
            ('Optical sensors', '#osems'),
            ('Transmons', '#transmons'),
        )),
    ]
    if args.omega_scans:
        links.append(('Scans', '#omega-scans'))
    (brand, class_) = htmlio.get_brand(args.ifo, 'Scattering', args.gpsstart)
    navbar = htmlio.navbar(links, class_=class_, brand=brand)
    page = htmlio.new_bootstrap_page(
        title='%s Scattering | %d-%d' % (
            args.ifo, int(args.gpsstart), int(args.gpsend)),
        navbar=navbar)
    page.div(class_='pb-2 mt-3 mb-2 border-bottom')
    page.h1('%s Scattering: %d-%d'
            % (args.ifo, int(args.gpsstart), int(args.gpsend)))
    page.div.close()  # pb-2 mt-3 mb-2 border-bottom
    page.h2('Parameters', class_='mt-4 mb-4', id_='parameters')
    page.div(class_='row')
    page.div(class_='col-md-9 col-sm-12')
    page.add(htmlio.parameter_table(
        start=int(args.gpsstart), end=int(args.gpsend), flag=args.state_flag))
    page.div.close()  # col-md-9 col-sm-12

    # link to summary files
    page.div(class_='col-md-3 col-sm-12')
    page.add(htmlio.download_btn(
        [('Segments (HDF)', segfile),
         ('Triggers (CSV)', summfile)],
        btnclass='btn btn-%s dropdown-toggle' % args.ifo.lower(),
    ))
    page.div.close()  # col-md-3 col-sm-12
    page.div.close()  # row

    # command-line
    page.h5('Command-line:')
    page.add(htmlio.get_command_line(about=False, prog=PROG))

    # section header
    page.h2('Segments', class_='mt-4', id_='segments')

    if statea:  # contextual information
        paper = markup.oneliner.a(
            'Accadia et al. (2010)', target='_blank', class_='alert-link',
            href='http://iopscience.iop.org/article/10.1088/0264-9381/27'
                 '/19/194011')
        msg = (
            "Segments marked \"optical sensors\" below show evidence of beam "
            "scattering between {0} and {1} Hz based on the velocity of optic "
            "motion, with fringe frequencies projected using equation (3) of "
            "{2}. Segments marked \"transmons\" are based on whitened, "
            "band-limited RMS trends of transmon sensors. In both cases, "
            "yellow panels denote weak evidence for scattering, while red "
            "panels denote strong evidence."
         ).format(args.fmin, multiplier * fthresh, str(paper))
        page.add(htmlio.alert(msg, context=args.ifo.lower()))
    else:  # null segments
        page.add(htmlio.alert('No active analysis segments were found',
                              context='warning', dismiss=False))

    # record state segments
    if args.state_flag is not None:
        page.h3('State flag', class_='mt-3', id_='state-flag')
        page.div(id_='accordion1')
        page.add(htmlio.write_flag_html(
            state, span, 'state', parent='accordion1', context='success',
            plotdir='', facecolor=(0.2, 0.8, 0.2), edgecolor='darkgreen',
            known={'facecolor': 'red', 'edgecolor': 'darkred', 'height': 0.4}))
        page.div.close()

    # -- find scattering evidence -----

    # read data for OSEMs and transmons
    osems = ['%s:%s' % (args.ifo, c) for optic in args.optic for
             c in OPTIC_MOTION_CHANNELS[optic]]
    transmons = ['%s:%s' % (args.ifo, c) for c in TRANSMON_CHANNELS]
    allchannels = osems + transmons

    logger.info("Reading all timeseries data")
    alldata = []
    n = len(statea)
    for i, seg in enumerate(statea):
        msg = "{0}/{1} {2}:".rjust(30).format(
            str(i + 1).rjust(len(str(n))),
            n,
            str(seg),
        ) if args.verbose else False
        alldata.append(
            get_data(allchannels, seg[0], seg[1],
                     frametype=args.frametype.format(IFO=args.ifo),
                     verbose=msg, nproc=args.nproc).resample(128))
    try:  # ensure that only available channels are analyzed
        osems = list(
            set(alldata[0].keys()) & set(alldata[-1].keys()) & set(osems))
        transmons = list(
            set(alldata[0].keys()) & set(alldata[-1].keys()) & set(transmons))
    except IndexError:
        osems = []
        transmons = []

    # initialize scattering segments
    scatter_segments = DataQualityDict()
    actives = SegmentList()

    # scattering based on OSEM velocity
    if statea:
        page.h3('Optical sensors (OSEMs)', class_='mt-3', id_='osems')
        page.div(id_='osems-group')
    logger.info('Searching for scatter based on OSEM velocity')

    for i, channel in enumerate(sorted(osems)):
        logger.info("-- Processing %s --" % channel)
        chanstr = re.sub('[:-]', '_', channel).replace('_', '-', 1)
        optic = channel.split('-')[1].split('_')[0]
        flag = '%s:DCH-%s_SCATTERING_GE_%s_HZ:1' % (args.ifo, optic, tstr)
        scatter_segments[channel] = DataQualityFlag(
            flag,
            isgood=False,
            description="Evidence for scattering above {0} Hz from {1} in "
                        "{2}".format(fthresh, optic, channel),
        )
        # set up plot(s)
        plot = Plot(figsize=[12, 12])
        axes = {}
        axes['position'] = plot.add_subplot(
            411, xscale='auto-gps', xlabel='')
        axes['fringef'] = plot.add_subplot(
            412, sharex=axes['position'], xlabel='')
        axes['triggers'] = plot.add_subplot(
            413, sharex=axes['position'], xlabel='')
        axes['segments'] = plot.add_subplot(
            414, projection='segments', sharex=axes['position'])
        plot.subplots_adjust(bottom=.07, top=.95)
        fringecolors = [None] * len(FREQUENCY_MULTIPLIERS)
        histdata = dict((x, numpy.ndarray((0,))) for
                        x in FREQUENCY_MULTIPLIERS)
        linecolor = None
        # loop over state segments and find scattering fringes
        for j, seg in enumerate(statea):
            logger.debug("Processing segment [%d .. %d)" % seg)
            ts = alldata[j][channel]
            # get raw data and plot
            line = axes['position'].plot(ts, color=linecolor)[0]
            linecolor = line.get_color()
            # get fringe frequency and plot
            fringef = get_fringe_frequency(ts, multiplier=1)
            for k, m in list(enumerate(FREQUENCY_MULTIPLIERS))[::-1]:
                fm = fringef * m
                line = axes['fringef'].plot(
                    fm, color=fringecolors[k],
                    label=(j == 0 and r'$f\times%d$' % m or None))[0]
                fringecolors[k] = line.get_color()
                histdata[m] = numpy.resize(
                    histdata[m], (histdata[m].size + fm.size,))
                histdata[m][-fm.size:] = fm.value
            # get segments and plot
            scatter = get_segments(
                fringef * multiplier,
                fthresh,
                name=flag,
                pad=args.segment_padding
            )
            axes['segments'].plot(
                scatter, facecolor='red', edgecolor='darkred',
                known={'alpha': 0.6, 'facecolor': 'lightgray',
                       'edgecolor': 'gray', 'height': 0.4},
                height=0.8, y=0, label=' ',
            )
            scatter_segments[channel] += scatter
            logger.debug(
                "    Found %d scattering segments" % (len(scatter.active)))
        logger.debug("Completed channel %s, found %d segments in total"
                     % (channel, len(scatter_segments[channel].active)))

        # calculate efficiency and deadtime of veto
        deadtime = abs(scatter_segments[channel].active)
        try:
            deadtimepc = deadtime / livetime * 100
        except ZeroDivisionError:
            deadtimepc = 0.
        logger.info("Deadtime: %.2f%% (%.2f/%ds)"
                    % (deadtimepc, deadtime, livetime))
        efficiency = in_segmentlist(highsnrtrigs[names[0]],
                                    scatter_segments[channel].active).sum()
        try:
            efficiencypc = efficiency / len(highsnrtrigs) * 100
        except ZeroDivisionError:
            efficiencypc = 0.
        logger.info("Efficiency (SNR>=8): %.2f%% (%d/%d)"
                    % (efficiencypc, efficiency, len(highsnrtrigs)))
        if deadtimepc == 0.:
            effdt = 0
        else:
            effdt = efficiencypc/deadtimepc
        logger.info("Efficiency/Deadtime: %.2f" % effdt)

        if abs(scatter_segments[channel].active):
            actives.extend(scatter_segments[channel].active)

        # finalize plot
        logger.debug("Plotting")
        name = texify(channel)
        axes['position'].set_title("Scattering evidence in %s" % name)
        axes['position'].set_xlabel('')
        axes['position'].set_ylabel(r'Position [$\mu$m]')
        axes['position'].text(
            0.01, 0.95, 'Optic position',
            transform=axes['position'].transAxes, va='top', ha='left',
            bbox={'edgecolor': 'none', 'facecolor': 'white', 'alpha': .5})
        axes['fringef'].plot(
            span, [fthresh, fthresh], 'k--')
        axes['fringef'].set_xlabel('')
        axes['fringef'].set_ylabel(r'Frequency [Hz]')
        axes['fringef'].yaxis.tick_right()
        axes['fringef'].yaxis.set_label_position("right")
        axes['fringef'].set_ylim(0, multiplier * fthresh)
        axes['fringef'].text(
            0.01, 0.95, 'Calculated fringe frequency',
            transform=axes['fringef'].transAxes, va='top', ha='left',
            bbox={'edgecolor': 'none', 'facecolor': 'white', 'alpha': .5})
        handles, labels = axes['fringef'].get_legend_handles_labels()
        axes['fringef'].legend(handles[::-1], labels[::-1], loc='upper right',
                               borderaxespad=0, bbox_to_anchor=(-0.01, 1.),
                               handlelength=1)

        axes['triggers'].scatter(
            trigs[names[0]],
            trigs[names[1]],
            c=trigs[names[2]],
            edgecolor='none',
        )
        name = texify(args.main_channel)
        axes['triggers'].text(
            0.01, 0.95,
            '%s event triggers (Omicron)' % name,
            transform=axes['triggers'].transAxes, va='top', ha='left',
            bbox={'edgecolor': 'none', 'facecolor': 'white', 'alpha': .5})
        axes['triggers'].set_ylabel('Frequency [Hz]')
        axes['triggers'].set_ylim(args.fmin, multiplier * fthresh)
        axes['triggers'].colorbar(cmap='YlGnBu', clim=(3, 100), norm='log',
                                  label='Signal-to-noise ratio')
        axes['segments'].set_ylim(-.55, .55)
        axes['segments'].text(
            0.01, 0.95,
            r'Time segments with $f\times%d > %.2f$ Hz' % (
                multiplier, fthresh),
            transform=axes['segments'].transAxes, va='top', ha='left',
            bbox={'edgecolor': 'none', 'facecolor': 'white', 'alpha': .5})
        for ax in axes.values():
            ax.set_epoch(int(args.gpsstart))
            ax.set_xlim(*span)
        png = '%s_SCATTERING_%s_HZ-%s.png' % (chanstr, tstr, gpsstr)
        try:
            plot.save(png)
        except OverflowError as e:
            warnings.warn(str(e))
            plot.axes[1].set_ylim(0, multiplier * fthresh)
            plot.refresh()
            plot.save(png)
        plot.close()
        logger.debug("%s written." % png)

        # make histogram
        histogram = Plot(figsize=[12, 6])
        ax = histogram.gca()
        hrange = (0, multiplier * fthresh)
        for m, color in list(zip(histdata, fringecolors))[::-1]:
            if histdata[m].size:
                ax.hist(
                    histdata[m], facecolor=color, alpha=.6, range=hrange,
                    bins=50, histtype='stepfilled', label=r'$f\times%d$' % m,
                    cumulative=-1, weights=ts.dx.value, bottom=1e-100,
                    log=True)
            else:
                ax.plot(histdata[m], color=color, label=r'$f\times%d$' % m)
                ax.set_yscale('log')
        ax.set_ylim(.01, float(livetime))
        ax.set_ylabel('Time with fringe above frequency [s]')
        ax.set_xlim(*hrange)
        ax.set_xlabel('Frequency [Hz]')
        ax.set_title(axes['position'].get_title())
        handles, labels = ax.get_legend_handles_labels()
        ax.legend(handles[::-1], labels[::-1], loc='upper right')
        hpng = '%s_SCATTERING_HISTOGRAM-%s.png' % (chanstr, gpsstr)
        histogram.save(hpng)
        histogram.close()
        logger.debug("%s written." % hpng)

        # write HTML
        if deadtime != 0 and effdt > 2:
            context = 'danger'
        elif ((deadtime != 0 and effdt < 2) or
              (histdata[multiplier].size and
               histdata[multiplier].max() >=
                  fthresh/2.)):
            context = 'warning'
        else:
            continue
        page.div(class_='card border-%s mb-1 shadow-sm' % context)
        page.div(class_='card-header text-white bg-%s' % context)
        page.a(channel, class_='collapsed card-link cis-link',
               href='#osem%s' % i, **{'data-toggle': 'collapse'})
        page.div.close()  # card-header
        page.div(id_='osem%s' % i, class_='collapse',
                 **{'data-parent': '#osems-group'})
        page.div(class_='card-body')
        page.div(class_='row')
        img = htmlio.FancyPlot(
            png, caption=SCATTER_CAPTION.format(CHANNEL=channel))
        page.div(class_='col-md-10 offset-md-1')
        page.add(htmlio.fancybox_img(img))
        page.div.close()  # col-md-10 offset-md-1
        himg = htmlio.FancyPlot(
            hpng, caption=HIST_CAPTION.format(CHANNEL=channel))
        page.div(class_='col-md-10 offset-md-1')
        page.add(htmlio.fancybox_img(himg))
        page.div.close()  # col-md-10 offset-md-1
        page.div.close()  # row
        segs = StringIO()
        if deadtime:
            page.p("%d segments were found predicting a scattering fringe "
                   "above %.2f Hz." % (
                       len(scatter_segments[channel].active),
                       fthresh))
            page.table(class_='table table-sm table-hover')
            page.tbody()
            page.tr()
            page.th('Deadtime')
            page.td('%.2f/%d seconds' % (deadtime, livetime))
            page.td('%.2f%%' % deadtimepc)
            page.tr.close()
            page.tr()
            page.th('Efficiency<br><small>(SNR&ge;8 and '
                    '%.2f Hz</sub>&ltf<sub>peak</sub>&lt;%.2f Hz)</small>'
                    % (args.fmin, multiplier * fthresh))
            page.td('%d/%d events' % (efficiency, len(highsnrtrigs)))
            page.td('%.2f%%' % efficiencypc)
            page.tr.close()
            page.tr()
            page.th('Efficiency/Deadtime')
            page.td()
            page.td('%.2f' % effdt)
            page.tr.close()
            page.tbody.close()
            page.table.close()
            scatter_segments[channel].active.write(segs, format='segwizard',
                                                   coltype=float)
            page.pre(segs.getvalue())
        else:
            page.p("No segments were found with scattering above %.2f Hz."
                   % fthresh)
        page.div.close()  # card-body
        page.div.close()  # collapse
        page.div.close()  # card

    if statea:  # close accordion
        page.div.close()  # osems-group

    # scattering based on transmon BLRMS
    if statea:
        page.h3('Transmons', class_='mt-3', id_='transmons')
        page.div(id_='transmons-group')
    logger.info('Searching for scatter based on band-limited RMS of transmons')

    for i, channel in enumerate(sorted(transmons)):
        logger.info("-- Processing %s --" % channel)
        optic = channel.split('-')[1][:6]
        flag = '%s:DCH-%s_SCATTERING_BLRMS:1' % (args.ifo, optic)
        scatter_segments[channel] = DataQualityFlag(
            flag,
            isgood=False,
            description="Evidence for scattering from whitened, band-limited "
                        "RMS trends of {0}".format(channel),
        )

        # loop over state segments and compute BLRMS
        for j, seg in enumerate(statea):
            logger.debug("Processing segment [%d .. %d)" % seg)
            wblrms = get_blrms(
                alldata[j][channel],
                flow=args.bandpass_flow,
                fhigh=args.bandpass_fhigh,
            )
            scatter = get_segments(
                wblrms,
                numpy.mean(wblrms) + args.sigma * numpy.std(wblrms),
                name=flag,
            )
            scatter_segments[channel] += scatter
            logger.debug(
                "    Found %d scattering segments" % (len(scatter.active)))
        logger.debug("Completed channel %s, found %d segments in total"
                     % (channel, len(scatter_segments[channel].active)))

        # calculate efficiency and deadtime of veto
        deadtime = abs(scatter_segments[channel].active)
        try:
            deadtimepc = deadtime / livetime * 100
        except ZeroDivisionError:
            deadtimepc = 0.
        logger.info("Deadtime: %.2f%% (%.2f/%ds)"
                    % (deadtimepc, deadtime, livetime))
        highsnrtrigs = trigs[trigs['snr'] <= 200]
        efficiency = in_segmentlist(highsnrtrigs[names[0]],
                                    scatter_segments[channel].active).sum()
        try:
            efficiencypc = efficiency / len(highsnrtrigs) * 100
        except ZeroDivisionError:
            efficiencypc = 0.
        logger.info("Efficiency (SNR>=8): %.2f%% (%d/%d)"
                    % (efficiencypc, efficiency, len(highsnrtrigs)))
        if deadtimepc == 0.:
            effdt = 0
        else:
            effdt = efficiencypc/deadtimepc
        logger.info("Efficiency/Deadtime: %.2f" % effdt)

        if abs(scatter_segments[channel].active):
            actives.extend(scatter_segments[channel].active)

        # write HTML
        if deadtime != 0 and effdt > 2:
            context = 'danger'
        elif deadtime != 0 and effdt < 2:
            context = 'warning'
        else:
            continue
        page.add(htmlio.write_flag_html(
            scatter_segments[channel], span, i, parent='transmons-group',
            title=channel, context=context, plotdir=''))

    if statea:  # close accordion
        page.div.close()  # transmons-group

    actives = actives.coalesce()  # merge contiguous segments
    if statea and not actives:
        page.add(htmlio.alert(
            'No evidence of scattering found in the channels analyzed',
            context=args.ifo.lower(), dismiss=False))

    # identify triggers during active segments
    logger.debug('Writing a summary CSV record')
    ind = [i for i, trigtime in enumerate(highsnrtrigs[names[0]])
           if trigtime in actives]
    gps = highsnrtrigs[names[0]][ind]
    freq = highsnrtrigs[names[1]][ind]
    snr = highsnrtrigs[names[2]][ind]
    segs = [y for x in gps for y in actives if x in y]
    table = EventTable(
        [gps, freq, snr, [seg[0] for seg in segs], [seg[1] for seg in segs]],
        names=('trigger_time', 'trigger_frequency', 'trigger_snr',
               'segment_start', 'segment_end'))
    logger.info('The following {} triggers fell within active scattering '
                'segments:\n\n'.format(len(table)))
    print(table)
    print('\n\n')
    table.write(summfile, overwrite=True)

    # -- launch omega scans -----------

    nscans = min(args.omega_scans, len(table))
    if nscans > 0:
        # launch scans
        scandir = 'scans'
        ind = random.sample(range(0, len(table)), nscans)
        omegatimes = [str(t) for t in table['trigger_time'][ind]]
        logger.debug('Collected {} event times to omega scan: {}'.format(
            nscans, ', '.join(omegatimes)))
        logger.info('Creating workflow for omega scans')
        flags = batch.get_command_line_flags(
            ifo=args.ifo, ignore_state_flags=True)
        condorcmds = batch.get_condor_arguments(timeout=4, gps=args.gpsstart)
        batch.generate_dag(omegatimes, flags=flags, submit=True,
                           outdir=scandir, condor_commands=condorcmds)
        logger.info('Launched {} omega scans to condor'.format(nscans))
        # render HTML
        page.h2('Omega scans', class_='mt-4', id_='omega-scans')
        msg = (
            'The following event times correspond to significant Omicron '
            'triggers that occur during the scattering segments found above. '
            'To compare these against fringe frequency projections, please '
            'use the "simple scattering" module:',
            markup.oneliner.pre(
                '$ python -m gwdetchar.scattering.simple --help',
            ),
        )
        page.add(htmlio.alert(msg, context=args.ifo.lower()))
        page.add(htmlio.scaffold_omega_scans(
            omegatimes, args.main_channel, scandir=scandir))
    elif args.omega_scans:
        logger.info('No events found during active scattering segments')

    # -- finalize ---------------------

    # write segments
    scatter_segments.write(segfile, path="segments", overwrite=True)
    logger.debug("%s written" % segfile)

    # write HTML
    htmlio.close_page(page, 'index.html')
    logger.info("-- index.html written, all done --")

    # return to original directory
    os.chdir(indir)