Example #1
0
 def test_sacpaz_from_dataless(self):
     # The following dictionary is extracted from a datalessSEED
     # file
     pazdict = {
         'sensitivity':
         2516580000.0,
         'digitizer_gain':
         1677720.0,
         'seismometer_gain':
         1500.0,
         'zeros': [0j, 0j],
         'gain':
         59198800.0,
         'poles': [(-0.037010000000000001 + 0.037010000000000001j),
                   (-0.037010000000000001 - 0.037010000000000001j),
                   (-131 + 467.30000000000001j),
                   (-131 - 467.30000000000001j), (-251.30000000000001 + 0j)]
     }
     tr = Trace()
     # This file was extracted from the datalessSEED file using rdseed
     pazfile = os.path.join(os.path.dirname(__file__), 'data',
                            'SAC_PZs_NZ_HHZ_10')
     attach_paz(tr, pazfile, todisp=False)
     sacconstant = pazdict['digitizer_gain'] * \
         pazdict['seismometer_gain'] * pazdict['gain']
     np.testing.assert_almost_equal(tr.stats.paz['gain'] / 1e17,
                                    sacconstant / 1e17,
                                    decimal=6)
     # pole-zero files according to the SAC convention are in displacement
     self.assertEqual(len(tr.stats.paz['zeros']), 3)
Example #2
0
    def test_sac_instrument_correction(self):
        # SAC recommends to taper the transfer function if a pure
        # deconvolution is done instead of simulating a different
        # instrument. This test checks the difference between the
        # result from removing the instrument response using SAC or
        # ObsPy. Visual inspection shows that the traces are pretty
        # much identical but differences remain (rms ~ 0.042). Haven't
        # found the cause for those, yet. One possible reason is the
        # floating point arithmetic of SAC vs. the double precision
        # arithmetic of Python. However differences still seem to be
        # too big for that.
        pzf = os.path.join(self.path, 'SAC_PZs_KARC_BHZ')
        sacf = os.path.join(self.path, 'KARC.LHZ.SAC.asc.gz')
        testsacf = os.path.join(self.path, 'KARC_corrected.sac.asc.gz')
        plow = 160.
        phigh = 4.
        fl1 = 1.0 / (plow + 0.0625 * plow)
        fl2 = 1.0 / plow
        fl3 = 1.0 / phigh
        fl4 = 1.0 / (phigh - 0.25 * phigh)
        # Uncomment the following to run the sac-commands
        # that created the testing file
        # if 1:
        #    import subprocess as sp
        #    p = sp.Popen('sac',shell=True,stdin=sp.PIPE)
        #    cd1 = p.stdin
        #    print("r %s"%sacf, file=cd1)
        #    print("rmean", file=cd1)
        #    print("rtrend", file=cd1)
        #    print("taper type cosine width 0.03", file=cd1)
        #    print("transfer from polezero subtype %s to none \
        #    freqlimits %f %f %f %f" % (pzf, fl1, fl2, fl3, fl4), file=cd1)
        #    print("w over ./data/KARC_corrected.sac", file=cd1)
        #    print("quit", file=cd1)
        #    cd1.close()
        #    p.wait()

        stats = {'network': 'KA', 'delta': 0.99999988079072466,
                 'station': 'KARC', 'location': 'S1',
                 'starttime': UTCDateTime(2001, 2, 13, 0, 0, 0, 993700),
                 'calib': 1.00868e+09, 'channel': 'BHZ'}
        with gzip.open(sacf) as f:
            tr = Trace(np.loadtxt(f), stats)

        attach_paz(tr, pzf, tovel=False)
        tr.data = simulate_seismometer(
            tr.data, tr.stats.sampling_rate, paz_remove=tr.stats.paz,
            remove_sensitivity=False, pre_filt=(fl1, fl2, fl3, fl4))

        with gzip.open(testsacf) as f:
            data = np.loadtxt(f)

        # import matplotlib.pyplot as plt
        # plt.plot(tr.data)
        # plt.plot(data)
        # plt.show()
        rms = np.sqrt(np.sum((tr.data - data) ** 2) /
                      np.sum(tr.data ** 2))
        self.assertTrue(rms < 0.0421)
Example #3
0
 def test_attach_paz_diff_order(self):
     pazfile = os.path.join(os.path.dirname(__file__),
                            'data', 'NZCRLZ_HHZ10.pz')
     tr = Trace()
     attach_paz(tr, pazfile)
     np.testing.assert_array_almost_equal(tr.stats.paz['gain'],
                                          7.4592e-2, decimal=6)
     self.assertEqual(len(tr.stats.paz['zeros']), 5)
     self.assertEqual(len(tr.stats.paz['poles']), 4)
Example #4
0
 def test_attach_paz_diff_order(self):
     pazfile = os.path.join(os.path.dirname(__file__),
                            'data', 'NZCRLZ_HHZ10.pz')
     tr = Trace()
     attach_paz(tr, pazfile)
     np.testing.assert_array_almost_equal(tr.stats.paz['gain'],
                                          7.4592e-2, decimal=6)
     self.assertEqual(len(tr.stats.paz['zeros']), 5)
     self.assertEqual(len(tr.stats.paz['poles']), 4)
Example #5
0
def _read_paz(path):
    """
    Read a directory with paz files or a single file.

    Limitations:
    (1) directory must contain *only* paz files
    (2) paz file can optionally have ".pz" or ".paz" suffixes
    (3) paz file name (without prefix and suffix) *has* to have
        the trace_id (NET.STA.LOC.CHAN) of the corresponding trace
        in the last part of his name
        (e.g., 20110208_1600.NOW.IV.CRAC.00.EHZ.paz)
    """
    if path is None:
        return None

    logger.info('Reading PAZ...')
    paz = dict()
    if os.path.isdir(path):
        listing = os.listdir(path)
        # check if files have a common prefix: we will strip it later
        prefix = os.path.commonprefix(listing)
        for filename in listing:
            fullpath = os.path.join(path, filename)
            try:
                # This is a horrible hack!
                # Since attach_paz needs a trace,
                # we create a trace and then, later,
                # we just retrieve the paz object
                # from the trace ;)
                tr = Trace()
                attach_paz(tr, fullpath)
                bname = os.path.basename(filename)
                # strip .pz suffix, if there
                bname = re.sub('.pz$', '', bname)
                # strip .paz suffix, if there
                bname = re.sub('.paz$', '', bname)
                # and strip any common prefix
                bname = re.sub('^' + prefix, '', bname)
                # we assume that the last four fields of bname
                # (separated by '.') are the trace_id
                trace_id = '.'.join(bname.split('.')[-4:])
                paz[trace_id] = tr.stats.paz.copy()
            except IOError:
                continue
    elif os.path.isfile(path):
        # If a filename is provided, store it as
        # 'default' paz.
        filename = path
        tr = Trace()
        attach_paz(tr, filename)
        paz['default'] = tr.stats.paz.copy()
    logger.info('Reading PAZ: done')
    return paz
def removeInstrument(st,args):

    if(args.sim == 'PZs'):

       # prefilters
       f = args.flim.split()
       f0 = eval(f[0])
       f1 = eval(f[1])
       f2 = eval(f[2])
       f3 = eval(f[3])
       toPurge=  []   # station to purge if no Paz found

       for i in range(len(st)):
   
           # attach poles and zeros instrument
           if(args.dva=='1'):
              try:
                attach_paz(st[i], st[i].stats.PZs_file,todisp=False)
              except:
                print "No appropriate PZs file found for station " + st[i].stats.station,st[i].stats.channel,st[i].stats.network
                toPurge.append(st[i].stats.station)
           else:
              try:
                attach_paz(st[i], st[i].stats.PZs_file,tovel=True)
              except:
                print "No appropriate PZs file found for station " + st[i].stats.station,st[i].stats.channel,st[i].stats.network
                toPurge.append(st[i].stats.station)

                
       # remove stations if len(toPurge>0)
       if len(toPurge) > 0:
           st = purgeListStation(st,toPurge,'r')
           print "Check if station/channel/network/location of the PZs files and the same string within loaded binary files "
           print "do correspond. It may occour for instance that the headers strings of the waveform files (e.g. sac, fseed) "
           print "do not agrees with the same strings of the PZs name files. For instance the name of the network. "
           print "If these strings do not correspond, modify the name of the PZs files or the header values of the waveforms"
           print "You may also choose to remove this station using the option --purge (see help for details)"

       # now do remove
       for i in range(len(st)):

           # remove instrument to displacement
#          st[i].data=detrend(st[i].data)
           st[i].data = simulate_seismometer(st[i].data,st[i].stats.sampling_rate,paz_remove=st[i].stats.paz, \
                        taper=True, taper_fraction=0.050, pre_filt=(f0,f1,f2,f3)) #,water_level=60.0) 

           # from meters to centimeters
           st[i].data = st[i].data * 100
       
    
    return st
Example #7
0
 def test_sacpaz_from_resp(self):
     # The following two files were both extracted from a dataless
     # seed file using rdseed
     respfile = os.path.join(os.path.dirname(__file__),
                             'data', 'RESP.NZ.CRLZ.10.HHZ')
     sacpzfile = os.path.join(os.path.dirname(__file__),
                              'data', 'SAC_PZs_NZ_CRLZ_HHZ')
     # This is a rather lengthy test, in which the
     # poles, zeros and the gain of each instrument response file
     # are converted into the corresponding velocity frequency response
     # function which have to be sufficiently close. Possibly due to
     # different truncations in the RESP-formatted and SAC-formatted
     # response files the frequency response functions are not identical.
     tr1 = Trace()
     tr2 = Trace()
     attach_resp(tr1, respfile, torad=True, todisp=False)
     attach_paz(tr2, sacpzfile, torad=False, tovel=True)
     p1 = tr1.stats.paz.poles
     z1 = tr1.stats.paz.zeros
     g1 = tr1.stats.paz.gain
     t_samp = 0.01
     n = 32768
     fy = 1 / (t_samp * 2.0)
     # start at zero to get zero for offset/ DC of fft
     f = np.arange(0, fy + fy / n, fy / n)  # arange should includes fy
     w = f * 2 * np.pi
     s = 1j * w
     a1 = np.poly(p1)
     b1 = g1 * np.poly(z1)
     h1 = np.polyval(b1, s) / np.polyval(a1, s)
     h1 = np.conj(h1)
     h1[-1] = h1[-1].real + 0.0j
     p2 = tr2.stats.paz.poles
     z2 = tr2.stats.paz.zeros
     g2 = tr2.stats.paz.gain
     a2 = np.poly(p2)
     b2 = g2 * np.poly(z2)
     h2 = np.polyval(b2, s) / np.polyval(a2, s)
     h2 = np.conj(h2)
     h2[-1] = h2[-1].real + 0.0j
     amp1 = abs(h1)
     amp2 = abs(h2)
     phase1 = np.unwrap(np.arctan2(-h1.imag, h1.real))
     phase2 = np.unwrap(np.arctan2(-h2.imag, h2.real))
     np.testing.assert_almost_equal(phase1, phase2, decimal=4)
     rms = np.sqrt(np.sum((amp1 - amp2) ** 2) /
                   np.sum(amp2 ** 2))
     self.assertTrue(rms < 2.02e-06)
     self.assertTrue(tr1.stats.paz.t_shift, 0.4022344)
Example #8
0
 def test_sacpaz_from_resp(self):
     # The following two files were both extracted from a dataless
     # seed file using rdseed
     respfile = os.path.join(os.path.dirname(__file__),
                             'data', 'RESP.NZ.CRLZ.10.HHZ')
     sacpzfile = os.path.join(os.path.dirname(__file__),
                              'data', 'SAC_PZs_NZ_CRLZ_HHZ')
     # This is a rather lengthy test, in which the
     # poles, zeros and the gain of each instrument response file
     # are converted into the corresponding velocity frequency response
     # function which have to be sufficiently close. Possibly due to
     # different truncations in the RESP-formatted and SAC-formatted
     # response files the frequency response functions are not identical.
     tr1 = Trace()
     tr2 = Trace()
     attach_resp(tr1, respfile, torad=True, todisp=False)
     attach_paz(tr2, sacpzfile, torad=False, tovel=True)
     p1 = tr1.stats.paz.poles
     z1 = tr1.stats.paz.zeros
     g1 = tr1.stats.paz.gain
     t_samp = 0.01
     n = 32768
     fy = 1 / (t_samp * 2.0)
     # start at zero to get zero for offset/ DC of fft
     f = np.arange(0, fy + fy / n, fy / n)  # arange should includes fy
     w = f * 2 * np.pi
     s = 1j * w
     a1 = np.poly(p1)
     b1 = g1 * np.poly(z1)
     h1 = np.polyval(b1, s) / np.polyval(a1, s)
     h1 = np.conj(h1)
     h1[-1] = h1[-1].real + 0.0j
     p2 = tr2.stats.paz.poles
     z2 = tr2.stats.paz.zeros
     g2 = tr2.stats.paz.gain
     a2 = np.poly(p2)
     b2 = g2 * np.poly(z2)
     h2 = np.polyval(b2, s) / np.polyval(a2, s)
     h2 = np.conj(h2)
     h2[-1] = h2[-1].real + 0.0j
     amp1 = abs(h1)
     amp2 = abs(h2)
     phase1 = np.unwrap(np.arctan2(-h1.imag, h1.real))
     phase2 = np.unwrap(np.arctan2(-h2.imag, h2.real))
     np.testing.assert_almost_equal(phase1, phase2, decimal=4)
     rms = np.sqrt(np.sum((amp1 - amp2) ** 2) /
                   np.sum(amp2 ** 2))
     self.assertTrue(rms < 2.02e-06)
     self.assertTrue(tr1.stats.paz.t_shift, 0.4022344)
Example #9
0
 def test_attach_paz(self):
     fvelhz = io.StringIO("""ZEROS 3
     -5.032 0.0
     POLES 6
     -0.02365 0.02365
     -0.02365 -0.02365
     -39.3011 0.
     -7.74904 0.
     -53.5979 21.7494
     -53.5979 -21.7494
     CONSTANT 2.16e18""")
     tr = Trace()
     attach_paz(tr, fvelhz, torad=True, todisp=True)
     np.testing.assert_array_almost_equal(tr.stats.paz['zeros'][0],
                                          - 31.616988, decimal=6)
     self.assertEqual(len(tr.stats.paz['zeros']), 4)
Example #10
0
 def test_attach_paz(self):
     fvelhz = io.StringIO("""ZEROS 3
     -5.032 0.0
     POLES 6
     -0.02365 0.02365
     -0.02365 -0.02365
     -39.3011 0.
     -7.74904 0.
     -53.5979 21.7494
     -53.5979 -21.7494
     CONSTANT 2.16e18""")
     tr = Trace()
     attach_paz(tr, fvelhz, torad=True, todisp=True)
     np.testing.assert_array_almost_equal(tr.stats.paz['zeros'][0],
                                          - 31.616988, decimal=6)
     self.assertEqual(len(tr.stats.paz['zeros']), 4)
def decon(stf, PZ=None, lowf=0.005, highf=0.008):
    nqf = stf[0].stats.sampling_rate / 2
    pre_filt = [lowf, highf, nqf - 2, nqf]

    if stf[0].stats.station == 'HNR':
        stf.remove_response(pre_filt=pre_filt, output='disp')

    else:
        for i in range(3):
            attach_paz(stf[i], PZ[0])

        paz = dict(stf[0].stats.paz)
        stf.simulate(paz_remove=paz, pre_filt=pre_filt)

    stf.taper(0.05, type='hann')

    return stf
Example #12
0
 def test_sacpaz_from_dataless(self):
     # The following dictionary is extracted from a datalessSEED
     # file
     pazdict = {'sensitivity': 2516580000.0,
                'digitizer_gain': 1677720.0, 'seismometer_gain': 1500.0,
                'zeros': [0j, 0j], 'gain': 59198800.0,
                'poles': [(-0.037010000000000001 + 0.037010000000000001j),
                          (-0.037010000000000001 - 0.037010000000000001j),
                          (-131 + 467.30000000000001j),
                          (-131 - 467.30000000000001j),
                          (-251.30000000000001 + 0j)]}
     tr = Trace()
     # This file was extracted from the datalessSEED file using rdseed
     pazfile = os.path.join(os.path.dirname(__file__),
                            'data', 'SAC_PZs_NZ_HHZ_10')
     attach_paz(tr, pazfile, todisp=False)
     sacconstant = pazdict['digitizer_gain'] * \
         pazdict['seismometer_gain'] * pazdict['gain']
     np.testing.assert_almost_equal(tr.stats.paz['gain'] / 1e17,
                                    sacconstant / 1e17, decimal=6)
     # pole-zero files according to the SAC convention are in displacement
     self.assertEqual(len(tr.stats.paz['zeros']), 3)
Example #13
0
def _add_paz_and_coords(trace, dataless, paz_dict=None):
    trace.stats.paz = None
    trace.stats.coords = None
    traceid = trace.get_id()
    time = trace.stats.starttime
    # We first look into the dataless dictionary, if available
    if isinstance(dataless, dict):
        for sp in dataless.values():
            # Check first if our traceid is in the dataless file
            if traceid not in str(sp):
                continue
            try:
                paz = AttribDict(sp.get_paz(traceid, time))
                coords = AttribDict(sp.get_coordinates(traceid, time))
            except SEEDParserException as err:
                logger.error('%s time: %s' % (err, str(time)))
                pass
    elif isinstance(dataless, Inventory):
        try:
            with warnings.catch_warnings(record=True) as warns:
                # get_sacpz() can issue warnings on more than one PAZ found,
                # so let's catch those warnings and log them properly
                sacpz = dataless.get_response(traceid, time).get_sacpz()
                for w in warns:
                    message = str(w.message)
                    logger.warning('%s: %s' % (traceid, message))
            attach_paz(trace, io.StringIO(sacpz))
            paz = trace.stats.paz
            coords = AttribDict(dataless.get_coordinates(traceid, time))
        except Exception as err:
            logger.error('%s traceid: %s time: %s' % (err, traceid, str(time)))
            pass
    try:
        trace.stats.paz = paz
        # elevation is in meters in the dataless
        coords.elevation /= 1000.
        trace.stats.coords = coords
    except Exception:
        pass
    # If we couldn't find any PAZ in the dataless dictionary,
    # we try to attach paz from the paz dictionary passed
    # as argument
    if trace.stats.paz is None and paz_dict is not None:
        # Look for traceid or for a generic paz
        net, sta, loc, chan = trace.id.split('.')
        ids = [
            trace.id, '.'.join(('__', '__', '__', '__')), '.'.join(
                (net, '__', '__', '__')), '.'.join((net, sta, '__', '__')),
            '.'.join((net, sta, loc, '__')), 'default'
        ]
        for id in ids:
            try:
                paz = paz_dict[id]
                trace.stats.paz = paz
            except KeyError:
                pass
    # If we're still out of luck,
    # we try to build the sensitivity from the
    # user2 and user3 header fields (ISNet format)
    if trace.stats.paz is None and trace.stats.format == 'ISNet':
        try:
            # instrument constants
            u2 = trace.stats.sac.user2
            u3 = trace.stats.sac.user3
            paz = AttribDict()
            paz.sensitivity = u3 / u2
            paz.poles = []
            paz.zeros = []
            paz.gain = 1
            trace.stats.paz = paz
        except AttributeError:
            pass
    # Still no paz? Antilles or IPOC format!
    if (trace.stats.paz is None and
        (trace.stats.format == 'Antilles' or trace.stats.format == 'IPOC')):
        paz = AttribDict()
        paz.sensitivity = 1
        paz.poles = []
        paz.zeros = []
        paz.gain = 1
        trace.stats.paz = paz
    # If we still don't have trace coordinates,
    # we try to get them from SAC header
    if trace.stats.coords is None:
        try:
            stla = trace.stats.sac.stla
            stlo = trace.stats.sac.stlo
            try:
                stel = trace.stats.sac.stel
                # elevation is in meters in SAC header:
                stel /= 1000.
            except AttributeError:
                stel = 0.
            coords = AttribDict()
            coords.elevation = stel
            coords.latitude = stla
            coords.longitude = stlo
            trace.stats.coords = coords
        except AttributeError:
            pass
    # Still no coords? Raise an exception
    if trace.stats.coords is None:
        raise Exception('%s: could not find coords for trace: skipping trace' %
                        traceid)
Example #14
0
    def test_sac_instrument_correction(self):
        # SAC recommends to taper the transfer function if a pure
        # deconvolution is done instead of simulating a different
        # instrument. This test checks the difference between the
        # result from removing the instrument response using SAC or
        # ObsPy. Visual inspection shows that the traces are pretty
        # much identical but differences remain (rms ~ 0.042). Haven't
        # found the cause for those, yet. One possible reason is the
        # floating point arithmetic of SAC vs. the double precision
        # arithmetic of Python. However differences still seem to be
        # too big for that.
        pzf = os.path.join(self.path, 'SAC_PZs_KARC_BHZ')
        sacf = os.path.join(self.path, 'KARC.LHZ.SAC.asc.gz')
        testsacf = os.path.join(self.path, 'KARC_corrected.sac.asc.gz')
        plow = 160.
        phigh = 4.
        fl1 = 1.0 / (plow + 0.0625 * plow)
        fl2 = 1.0 / plow
        fl3 = 1.0 / phigh
        fl4 = 1.0 / (phigh - 0.25 * phigh)
        # Uncomment the following to run the sac-commands
        # that created the testing file
        # if 1:
        #    import subprocess as sp
        #    p = sp.Popen('sac',shell=True,stdin=sp.PIPE)
        #    cd1 = p.stdin
        #    print("r %s"%sacf, file=cd1)
        #    print("rmean", file=cd1)
        #    print("rtrend", file=cd1)
        #    print("taper type cosine width 0.03", file=cd1)
        #    print("transfer from polezero subtype %s to none \
        #    freqlimits %f %f %f %f" % (pzf, fl1, fl2, fl3, fl4), file=cd1)
        #    print("w over ./data/KARC_corrected.sac", file=cd1)
        #    print("quit", file=cd1)
        #    cd1.close()
        #    p.wait()

        stats = {
            'network': 'KA',
            'delta': 0.99999988079072466,
            'station': 'KARC',
            'location': 'S1',
            'starttime': UTCDateTime(2001, 2, 13, 0, 0, 0, 993700),
            'calib': 1.00868e+09,
            'channel': 'BHZ'
        }
        with gzip.open(sacf) as f:
            tr = Trace(np.loadtxt(f), stats)

        attach_paz(tr, pzf, tovel=False)
        tr.data = simulate_seismometer(tr.data,
                                       tr.stats.sampling_rate,
                                       paz_remove=tr.stats.paz,
                                       remove_sensitivity=False,
                                       pre_filt=(fl1, fl2, fl3, fl4))

        with gzip.open(testsacf) as f:
            data = np.loadtxt(f)

        # import matplotlib.pyplot as plt
        # plt.plot(tr.data)
        # plt.plot(data)
        # plt.show()
        rms = np.sqrt(np.sum((tr.data - data)**2) / np.sum(tr.data**2))
        self.assertTrue(rms < 0.0421)
Example #15
0
def _add_paz_and_coords(trace, metadata, paz_dict, config):
    traceid = trace.get_id()
    # If we already know that traceid is skipped, raise a silent exception
    if traceid in _add_paz_and_coords.skipped:
        raise Exception()
    trace.stats.paz = None
    trace.stats.coords = None
    time = trace.stats.starttime
    # We first check whether metadata is a dataless dictionary
    if isinstance(metadata, dict):
        for sp in metadata.values():
            # Check first if our traceid is in the dataless file
            if traceid not in str(sp):
                continue
            try:
                paz = AttribDict(sp.get_paz(traceid, time))
                coords = AttribDict(sp.get_coordinates(traceid, time))
            except SEEDParserException as err:
                logger.error('%s time: %s' % (err, str(time)))
                pass
    elif isinstance(metadata, Inventory):
        try:
            with warnings.catch_warnings(record=True) as warns:
                # get_sacpz() can issue warnings on more than one PAZ found,
                # so let's catch those warnings and log them properly
                sacpz = metadata.get_response(traceid, time).get_sacpz()
                for w in warns:
                    message = str(w.message)
                    logger.warning('%s: %s' % (traceid, message))
            attach_paz(trace, io.StringIO(sacpz))
            paz = trace.stats.paz
            coords = AttribDict(metadata.get_coordinates(traceid, time))
        except Exception as err:
            logger.error('%s traceid: %s time: %s' % (err, traceid, str(time)))
            pass
    try:
        trace.stats.paz = paz
        # elevation is in meters
        coords.elevation /= 1000.
        trace.stats.coords = coords
    except Exception:
        pass
    # If we couldn't find any PAZ in the dataless dictionary
    # or in the Inventory, we try to attach paz from a paz dictionary
    if trace.stats.paz is None and paz_dict is not None:
        # Look for traceid or for a generic paz
        net, sta, loc, chan = trace.id.split('.')
        ids = [
            trace.id,
            '.'.join(('__', '__', '__', '__')),
            '.'.join((net, '__', '__', '__')),
            '.'.join((net, sta, '__', '__')),
            '.'.join((net, sta, loc, '__')),
            'default'
        ]
        for id in ids:
            try:
                paz = paz_dict[id]
                trace.stats.paz = paz
            except KeyError:
                pass
    # If a "sensitivity" config option is provided, override the paz computed
    # from metadata or paz_dict
    if config.sensitivity is not None:
        # instrument constants
        paz = AttribDict()
        paz.sensitivity = _compute_sensitivity(trace, config)
        paz.poles = []
        paz.zeros = []
        paz.gain = 1
        trace.stats.paz = paz
    # If we still don't have trace coordinates,
    # we try to get them from SAC header
    if trace.stats.coords is None:
        try:
            stla = trace.stats.sac.stla
            stlo = trace.stats.sac.stlo
            try:
                stel = trace.stats.sac.stel
                # elevation is in meters in SAC header:
                stel /= 1000.
            except AttributeError:
                stel = 0.
            coords = AttribDict()
            coords.elevation = stel
            coords.latitude = stla
            coords.longitude = stlo
            trace.stats.coords = coords
        except AttributeError:
            pass
    # Still no coords? Raise an exception
    if trace.stats.coords is None:
        _add_paz_and_coords.skipped.append(traceid)
        raise Exception(
            '%s: could not find coords for trace: skipping trace' % traceid)
    if trace.stats.coords.latitude == trace.stats.coords.longitude == 0:
        logger.warning(
            '{}: trace has latitude and longitude equal to zero!'.format(
                traceid))