Python io.save函数代码示例

 def save_traces_mseed(self, filename_tmpl='%(whichset)s_%(network)s_%(station)s_%(location)s_%(channel)s.mseed',
         overwrite_network=None, component_to_channel={}, location_map={}):
     
     station, network = self.get_station(), self.get_network()
     if overwrite_network is not None:
         network = overwrite_network
         
     fns = []
     for icomp, comp in enumerate(self.components):
         channel = component_to_channel.get(comp, comp)
         for (whichset, sgram) in zip(('references', 'synthetics'), 
                          (self.ref_seismograms[icomp], self.syn_seismograms[icomp])):
             if sgram and len(sgram[0]) > 1:
                 starttime = sgram[0][0]
                 endtime = sgram[0][-1]
                 deltat = (endtime-starttime)/(len(sgram[0])-1)
                 data = sgram[1]
                 location = location_map.get(whichset, whichset)
                 tr = trace.Trace(network[:2], station[:5], location[:2], channel[:3], 
                     tmin = starttime, tmax=endtime, deltat=deltat, ydata=data)
                     
                 fn = filename_tmpl % { 'whichset': whichset,
                                        'network': network,
                                        'station': station,
                                        'location': location,
                                        'channel': channel }
                                        
                 io.save([tr], fn)
                 fns.append(fn)
     return fns

    def call(self):
        template = 'trace_%(network)s.%(station)s.%(location)s.%(channel)s'
        try:

            if self.format == 'text':
                default_output_filename = template + '.dat'

            else:
                default_output_filename = template + '.' + self.format

            out_filename = self.output_filename('Template for output files',
                                                default_output_filename)
        except NoViewerSet:
            out_filename = self.out_filename

        traces = self.chopper_selected_traces(fallback=True)
        for trs in traces:
            for tr in trs:
                if self.format == 'mseed':
                    if len(tr.network) > 2:
                        tr.set_network(tr.network[:2])
                    if len(tr.station) > 5:
                        tr.set_station(tr.station[:5])
                    if len(tr.location) > 2:
                        tr.set_location(tr.location[:2])
                    if len(tr.channel) > 3:
                        tr.set_channel(tr.channel[:3])
                io.save(tr, out_filename, format=self.format)

    def call(self):
        p = self.get_pile()

        try:
            markers = self.get_selected_event_markers()
        except NoViewerSet:
            markers = load_markers(self.markers_filename)

        try:

            out_filename = self.output_filename('Template for output files',
                                                default_output_filename)
        except NoViewerSet:
            out_filename = self.out_filename

        for m in markers:
            event = m.get_event()
            eventname = event.name
            if not eventname:
                eventname = util.time_to_str(event.time, format='%Y-%m-%d_%H-%M-%S')

            traces = p.all(tmin=event.time + self.tbeg,
                           tmax=event.time + self.tend)

            io.save(traces, out_filename, additional=dict(
                eventname=eventname))

def write_container_to_dirs(container, base_dir, pad_traces=True):
    sources = container.sources
    targets = container.targets

    if not os.path.exists(base_dir):
        os.makedirs(base_dir)

    p = progressbar.ProgressBar(widgets=['writing: ',
                                         progressbar.Percentage(),
                                         progressbar.Bar()],
                                maxval=len(sources)).start()
    for i_s, s in enumerate(sources):
        _trs = [container[s][t] for t in targets]
        if pad_traces:
            _trs = do_pad_traces(_trs)
        e = s.pyrocko_event()
        e.set_name(str(i_s))
        out_dir = os.path.join(base_dir, dir_from_event(e))
        if not os.path.exists(out_dir):
            os.makedirs(out_dir)

        for tr in _trs:
            io.save(tr, filename_template=out_dir+'/tr_%(network)s.%(station)s.%(location)s.%(channel)s.mseed')

        e.dump(os.path.join(out_dir, 'event.pf'))

        p.update(i_s)
    p.finish()

def restitute_evalresp(tr_fn):
    traces = io.load(tr_fn)
    out_traces = []
    for tr in traces:
        try:
            try:
                evalresp = trace.Evalresp(respfile=evalresps['%s.%s'%(tr.station, tr.channel)],
                                          nslc_id=tr.nslc_id,
                                          target='dis')

            except KeyError:
                print 'skip ', '.'.join(tr.nslc_id[1:])
                continue

            if tr.station=='nkc' or tr.station=='zhc':
                t_taper = 30
                f_taper = (0.05, 0.08, 50., 75.),     # frequency domain taper in [hz]
            else:
                t_taper = 5.
                f_taper = (0.3, 0.6, 50., 75.),     # frequency domain taper in [hz]

            displacement =  tr.transfer(
                t_taper,                       # rise and fall of time domain taper in [s]
                *f_taper,     # frequency domain taper in [hz]
                transfer_function=evalresp, 
                invert=True)

        except trace.TraceTooShort:
            continue
        out_traces.append(displacement)
    tr_fn = tr_fn.replace(inputdir, outputdir)
    print tr_fn
    io.save(out_traces, tr_fn)

    del traces

    def make_noise_trace(
            self, tmin, tmax, nslc_id, target_nslc_id=None, merge_traces=None,
            outdir='noise_concat', template='tr_%n.%s.%l.%c.-%(tmin)s.mseed'):

        if target_nslc_id is None:
            target_nslc_id = nslc_id

        n, s, l, c = target_nslc_id
        noise_tr = self.noise[(n, s, l, c)]
        deltat = noise_tr.deltat
        self.resample_many(merge_traces, deltat)
        overlap = 0.2                           # 20 percent of sample length
        sample_length = 60.                     # seconds
        ns = int(sample_length/deltat)          # number of samples
        fader = trace.CosFader(xfrac=overlap)
        noisey = noise_tr.get_ydata()
        buffer_size = num.int(sample_length*60./deltat)
        i_dumped = 0.
        buffer_y = num.zeros(buffer_size)
        ioverflow = 0
        overflow = None
        taper = trace.costaper(
            0., overlap/2.*sample_length, sample_length*(1.0-overlap/2.),
            sample_length, ns, deltat)
        for i, istart in enumerate(num.arange(0, int(num.ceil((tmax-tmin)/deltat)), int(ns*(1.0 - overlap/2.0)))):
            istart = int(num.floor((istart+ioverflow) % buffer_size))
            istop = istart + ns
            nmissing = buffer_size - istop
            isample_start = int(num.floor(num.random.uniform(0, len(noisey)-ns)))
            isample_stop = isample_start + ns
            noise_sample = num.zeros(ns)
            noise_sample[:] = noisey[isample_start:isample_stop]
            noise_sample *= taper
            if nmissing<0:
                isample_stop = ns + nmissing
                istop = istart + ns + nmissing
                ioverflow = isample_stop
                overflow = noise_sample[ioverflow:]
                noise_sample = noise_sample[:ioverflow]
            buffer_y[istart: istop] += noise_sample
            # Problem mit ioverlap.
            if overflow is not None:
                tmin_tr = tmin+i_dumped*buffer_size*deltat
                tmax_tr = tmin_tr+(buffer_size-1)*deltat
                buff_tr = trace.Trace(network=n, station=s, location=l, channel=c,
                                      tmin=tmin_tr, tmax=tmax_tr,
                                      deltat=noise_tr.deltat, ydata=buffer_y)
                if merge_traces is not None:
                    for mtr in merge_traces:
                        if buff_tr.is_relevant(mtr.tmin, mtr.tmax):
                            mtr = mtr.taper(self.merge_fader, inplace=False)
                            buff_tr.add(mtr)
                            #print max(num.abs(mtr.ydata))
                            #trace.snuffle([mtr, buff_tr])
                io.save(buff_tr, pjoin(outdir, template))
                buffer_y = num.zeros(buffer_size)
                buffer_y[0:ns-ioverflow] = overflow
                i_dumped += 1.
                overflow = None

 def testLongCode(self):
     c = '1234567'
     tr = trace.Trace(c, c, c, c, ydata=num.zeros(10))
     e = None
     try:
         io.save(tr, 'test.mseed')
     except mseed.CodeTooLong as e:
         assert isinstance(e, mseed.CodeTooLong)

 def testLongCode(self):
     c = '1234567'
     tr = trace.Trace(c,c,c,c, ydata=num.zeros(10))
     e = None
     try:
         io.save(tr, 'test.mseed')
     except mseed.CodeTooLong, e:
         pass

def command_extract(args):
    def setup(parser):
        parser.add_option(
            '--format', dest='format', default='mseed',
            choices=['mseed', 'sac', 'text', 'yaff'],
            help='export to format "mseed", "sac", "text", or "yaff". '
                 'Default is "mseed".')

        fndfl = 'extracted/%(irecord)s_%(args)s.%(extension)s'
        parser.add_option(
            '--output', dest='output_fn', default=fndfl, metavar='TEMPLATE',
            help='output path template [default: "%s"]' % fndfl)

    parser, options, args = cl_parse('extract', args, setup=setup)
    try:
        sdef = args.pop()
    except Exception:
        parser.error('cannot get <selection> argument')

    try:
        gdef = gf.meta.parse_grid_spec(sdef)
    except gf.meta.GridSpecError as e:
        die(e)

    store_dir = get_store_dir(args)

    extensions = {
        'mseed': 'mseed',
        'sac': 'sac',
        'text': 'txt',
        'yaff': 'yaff'}

    try:
        store = gf.Store(store_dir)
        for args in store.config.iter_extraction(gdef):
            gtr = store.get(args)
            if gtr:
                tr = trace.Trace(
                    '', '', '', util.zfmt(store.config.ncomponents) % args[-1],
                    ydata=gtr.data,
                    deltat=gtr.deltat,
                    tmin=gtr.deltat * gtr.itmin)

                additional = dict(
                    args='_'.join('%g' % x for x in args),
                    irecord=store.str_irecord(args),
                    extension=extensions[options.format])

                io.save(
                    tr,
                    options.output_fn,
                    format=options.format,
                    additional=additional)

    except (gf.meta.GridSpecError, gf.StoreError, gf.meta.OutOfBounds) as e:
        die(e)

    def save(self):
        if not self.current_stuff:
            self.fail('Nothing to save.')
        
        data_fn = self.output_filename(caption='Save Data', dir='data-%(network)s-%(station)s-%(location)s-%(channel)s-%(tmin)s.mseed')
        stations_fn = self.output_filename(caption='Save Stations File', dir='stations.txt')        

        all_traces, stations = self.current_stuff
        io.save(all_traces, data_fn)
        model.dump_stations(stations, stations_fn)

    def dump_waveforms(self, engine, sources, path,
                       tmin=None, tmax=None, overwrite=False):
        path_waveforms = op.join(path, 'waveforms')
        gf.store.remake_dir(path_waveforms, force=overwrite)

        path_traces = op.join(
            path_waveforms,
            '%(wmin_year)s',
            '%(wmin_month)s',
            '%(wmin_day)s',
            'waveform_%(network)s_%(station)s_' +
            '%(location)s_%(channel)s_%(tmin)s_%(tmax)s.mseed')

        tmin_all, tmax_all = self.get_time_range(sources)
        tmin = tmin if tmin is not None else tmin_all
        tmax = tmax if tmax is not None else tmax_all
        tts = util.time_to_str

        tinc = self.tinc or self.get_useful_time_increment(engine, sources)
        tmin = math.floor(tmin / tinc) * tinc
        tmax = math.ceil(tmax / tinc) * tinc

        nwin = int(round((tmax - tmin) / tinc))

        pbar = util.progressbar('Generating waveforms', nwin)
        for iwin in range(nwin):
            pbar.update(iwin)
            tmin_win = max(tmin, tmin + iwin*tinc)
            tmax_win = min(tmax, tmin + (iwin+1)*tinc)

            if tmax_win <= tmin_win:
                continue

            trs = self.get_waveforms(engine, sources, tmin_win, tmax_win)

            try:
                io.save(
                    trs, path_traces,
                    additional=dict(
                        wmin_year=tts(tmin_win, format='%Y'),
                        wmin_month=tts(tmin_win, format='%m'),
                        wmin_day=tts(tmin_win, format='%d'),
                        wmin=tts(tmin_win, format='%Y-%m-%d_%H-%M-%S'),
                        wmax_year=tts(tmax_win, format='%Y'),
                        wmax_month=tts(tmax_win, format='%m'),
                        wmax_day=tts(tmax_win, format='%d'),
                        wmax=tts(tmax_win, format='%Y-%m-%d_%H-%M-%S')),
                    overwrite=overwrite)
            except FileSaveError as e:
                logger.debug('Waveform exists %s' % e)

        pbar.finish()

        return [path_waveforms]

    def call(self):
        self.cleanup()

        if self.tinc is not None:
            template = \
                'trace_%n.%s.%l.%c_%(tmin_us)s'
        else:
            template = 'trace_%n.%s.%l.%c'

        if self.format == 'text':
            default_output_filename = template + '.dat'

        else:
            default_output_filename = template + '.' + self.format

        out_filename = self.output_filename('Template for output files',
                                            default_output_filename)

        viewer = self.get_viewer()
        for trs in self.chopper_selected_traces(fallback=True, tinc=self.tinc):
            trs2save = []
            for tr in trs:
                if self.format == 'mseed':
                    if len(tr.network) > 2:
                        tr.set_network(tr.network[:2])
                    if len(tr.station) > 5:
                        tr.set_station(tr.station[:5])
                    if len(tr.location) > 2:
                        tr.set_location(tr.location[:2])
                    if len(tr.channel) > 3:
                        tr.set_channel(tr.channel[:3])

                if viewer.lowpass:
                    if viewer.lowpass < 0.5/tr.deltat:
                        tr.lowpass(4, viewer.lowpass, demean=False)
                if viewer.highpass:
                    if viewer.highpass < 0.5/tr.deltat:
                        tr.highpass(4, viewer.highpass, demean=False)

                trs2save.append(tr)

            try:
                io.save(
                    trs2save, out_filename,
                    format=self.format,
                    overwrite=True)

            except io.io_common.FileSaveError as e:
                self.fail(str(e))

        if self.save_stations:
            stations = viewer.stations.values()
            fn = self.output_filename('Save Stations', 'stations.pf')
            model.dump_stations(list(stations), fn)

    def save(self):
        if not self.current_stuff:
            self.fail("Nothing to save.")

        data_fn = self.output_filename(
            caption="Save Data", dir="data-%(network)s-%(station)s-%(location)s-%(channel)s-%(tmin)s.mseed"
        )
        stations_fn = self.output_filename(caption="Save Stations File", dir="stations.txt")

        all_traces, stations = self.current_stuff
        io.save(all_traces, data_fn)
        model.dump_stations(stations, stations_fn)

 def testDownsampling(self):
     
     n = 1024
     dt1 = 1./125.
     dt2 = 1./10.
     dtinter = 1./util.lcm(1./dt1,1./dt2)
     upsratio = dt1/dtinter
     xdata = num.arange(n,dtype=num.float)
     ydata = num.exp(-((xdata-n/2)/10.)**2)
     t = trace.Trace(ydata=ydata, tmin=sometime, deltat=dt1, location='1')
     t2 = t.copy()
     t2.set_codes(location='2')
     t2.downsample_to(dt2, allow_upsample_max = 10)
     io.save([t,t2], 'test.mseed')

 def testWriteText(self):
     networks = [rn(2) for i in range(5)]
     deltat = 0.1
     tr = trace.Trace(
         rc(networks), rn(4), rn(2), rn(3),
         tmin=time.time()+deltat,
         deltat=deltat,
         ydata=num.arange(100, dtype=num.int32),
         mtime=time.time())
     io.save(
         tr,
         pjoin(
             self.tmpdir,
             '%(network)s_%(station)s_%(location)s_%(channel)s'),
         format='text')