예제 #1
0
def test_adjoint_functions():

    observed = Trace(data=np.ones(25))
    synthetic = Trace(data=np.ones(25))
    synthetic.data[0:13] *= 2.0
    synthetic.stats.sac = {}
    synthetic.stats.sac['dist'] = 6000.
    observed.stats = synthetic.stats.copy()

    window_params = {}
    window_params['hw'] = 2.0
    window_params['sep_noise'] = 1.0
    window_params['win_overlap'] = False
    window_params['wtype'] = "hann"
    window_params['plot'] = False

    g_speed = 2000.

    adj, success = am.log_en_ratio_adj(observed, synthetic, g_speed,
                                       window_params)

    assert (success)
    assert (len(adj) == 25)
    assert (pytest.approx(adj[10]) == -0.16666666666666663)

    adj, success = am.windowed_waveform(observed, synthetic, g_speed,
                                        window_params)
    assert (success)
    assert (len(adj) == 25)
    assert (pytest.approx(adj[9]) == 1.)

    func = am.get_adj_func('energy_diff')
    adj, success = func(observed, synthetic, g_speed, window_params)
    assert (success)
    assert (len(adj) == 2)
    assert (type(adj) == list)
    assert (pytest.approx(adj[1].sum()) == 6.)
예제 #2
0
def measurement(source_config, mtype, step, ignore_net, ix_bandpass, bandpass,
                step_test, taper_perc, **options):
    """
    Get measurements on noise correlation data and synthetics.
    options: g_speed,window_params (only needed if
    mtype is ln_energy_ratio or enery_diff)
    """
    verbose = yaml.safe_load(
        open(os.path.join(source_config['project_path'],
                          'config.yml')))['verbose']
    step_n = 'iteration_{}'.format(int(step))
    step_dir = os.path.join(source_config['source_path'], step_n)

    if step_test:
        corr_dir = os.path.join(step_dir, 'obs_slt')
    else:
        corr_dir = os.path.join(source_config['source_path'],
                                'observed_correlations')

    files = [f for f in os.listdir(corr_dir)]
    files = [os.path.join(corr_dir, f) for f in files]
    synth_dir = os.path.join(step_dir, 'corr')

    columns = [
        'sta1', 'sta2', 'lat1', 'lon1', 'lat2', 'lon2', 'dist', 'az', 'baz',
        'syn', 'syn_a', 'obs', 'obs_a', 'l2_norm', 'snr', 'snr_a', 'nstack'
    ]
    measurements = pd.DataFrame(columns=columns)

    options['window_params']['causal_side'] = True  # relic for signal to noise
    _options_ac = copy.deepcopy(options)
    _options_ac['window_params']['causal_side'] = (
        not (options['window_params']['causal_side']))

    if files == []:
        msg = 'No input found!'
        raise ValueError(msg)

    for i, f in enumerate(files):

        # Read data
        try:
            tr_o = read(f)[0]
        except IOError:
            if verbose:
                print('\nCould not read data: ' + os.path.basename(f))
            continue

        # Read synthetics
        synth_filename = get_synthetics_filename(os.path.basename(f),
                                                 synth_dir,
                                                 ignore_network=ignore_net)

        if synth_filename is None:
            continue

        try:
            tr_s = read(synth_filename)[0]
        except IOError:
            if verbose:
                print('\nCould not read synthetics: ' + synth_filename)
            continue

        # Assigning stats to synthetics, cutting them to right length

        tr_s.stats.sac = tr_o.stats.sac.copy()
        tr_s.data = my_centered(tr_s.data, tr_o.stats.npts)
        # Get all the necessary information
        info = get_station_info(tr_o.stats)
        # Collect the adjoint source
        adjoint_source = Stream()
        adjoint_source += Trace()
        adjoint_source[0].stats.sampling_rate = tr_s.stats.sampling_rate
        adjoint_source[0].stats.sac = tr_s.stats.sac.copy()

        # Filter
        if bandpass is not None:
            tr_o.taper(taper_perc / 100.)
            tr_o.filter('bandpass',
                        freqmin=bandpass[0],
                        freqmax=bandpass[1],
                        corners=bandpass[2],
                        zerophase=True)
            tr_s.taper(taper_perc / 100.)
            tr_s.filter('bandpass',
                        freqmin=bandpass[0],
                        freqmax=bandpass[1],
                        corners=bandpass[2],
                        zerophase=True)

        # Weight observed stack by nstack
        tr_o.data /= tr_o.stats.sac.user0

        # Take the measurement
        func = rm.get_measure_func(mtype)
        msr_o = func(tr_o, **options)
        msr_s = func(tr_s, **options)

        # Get the adjoint source
        adjt_func = am.get_adj_func(mtype)
        adjt, success = adjt_func(tr_o, tr_s, **options)
        if not success:
            continue

        # timeseries-like measurements:
        if mtype in ['square_envelope', 'full_waveform', 'windowed_waveform']:
            l2_so = 0.5 * np.sum(np.power((msr_s - msr_o), 2))
            snr = snratio(tr_o, **options)
            snr_a = snratio(tr_o, **_options_ac)
            info.extend([
                np.nan, np.nan, np.nan, np.nan, l2_so, snr, snr_a,
                tr_o.stats.sac.user0
            ])
            adjoint_source[0].data = adjt

        # single value measurements:
        else:
            if mtype == 'energy_diff':
                l2_so = 0.5 * (msr_s - msr_o)**2 / (msr_o)**2
                msr = msr_o[0]
                msr_a = msr_o[1]
                snr = snratio(tr_o, **options)
                snr_a = snratio(tr_o, **_options_ac)
                l2 = l2_so.sum()
                info.extend([
                    msr_s[0], msr_s[1], msr, msr_a, l2, snr, snr_a,
                    tr_o.stats.sac.user0
                ])

                adjoint_source += adjoint_source[0].copy()
                for ix_branch in range(2):
                    adjoint_source[ix_branch].data = adjt[ix_branch]
                    adjoint_source[ix_branch].data *= (
                        msr_s[ix_branch] -
                        msr_o[ix_branch]) / msr_o[ix_branch]**2

            elif mtype == 'ln_energy_ratio':
                l2_so = 0.5 * (msr_s - msr_o)**2
                msr = msr_o
                snr = snratio(tr_o, **options)
                snr_a = snratio(tr_o, **_options_ac)
                info.extend([
                    msr_s, np.nan, msr, np.nan, l2_so, snr, snr_a,
                    tr_o.stats.sac.user0
                ])
                adjt *= (msr_s - msr_o)
                adjoint_source[0].data = adjt

        measurements.loc[i] = info

        # save the adjoint source
        if len(adjoint_source) == 1:
            adjt_filename = os.path.basename(synth_filename).rstrip('sac') +\
                '{}.sac'.format(ix_bandpass)
            adjoint_source[0].write(os.path.join(step_dir, 'adjt',
                                                 adjt_filename),
                                    format='SAC')
        elif len(adjoint_source) == 2:
            for ix_branch, branch in enumerate(['c', 'a']):
                adjt_filename = os.path.basename(synth_filename).\
                    rstrip('sac') + '{}.{}.sac'.format(branch, ix_bandpass)
                adjoint_source[ix_branch].write(os.path.join(
                    step_dir, 'adjt', adjt_filename),
                                                format='SAC')
        else:
            raise ValueError("Some problem with adjoint sources.")

    return measurements
예제 #3
0
window_params['win_overlap']    =    False
window_params['wtype']          =    'hann'
window_params['causal_side']    =    False
window_params['plot']           =    False
# *********************************************
# *********************************************

# only for testing the test:
# def l2_simple(tr_1,tr_2):
# 	mf = np.sum(0.5 * (tr_1.data - tr_2.data) **2)
# 	adstf = (tr_1.data - tr_2.data)
# 	return mf,adstf

m_a_options = {'g_speed':g_speed,'window_params':window_params}
m_func = rm.get_measure_func(mtype)
a_func = af.get_adj_func(mtype)


# create observed data, synthetics and perturbation
c_obs = 2 * (np.random.rand(2401,) - 0.5)
c_ini = 2 * (np.random.rand(2401,) - 0.5)
d_c = 2 * (np.random.rand(2401,) - 0.5)
# form traces (measurement script works with obspy trace objects, not pure arrays)
c_obs = Trace(data=c_obs)
c_obs.stats.sampling_rate = 1.0
c_obs.stats.sac = sacdict

c_syn = Trace(data=c_ini)
c_syn.stats.sampling_rate = 1.0
c_syn.stats.sac = sacdict
예제 #4
0
def adjointsrcs(source_config,mtype,step,ignore_network,bandpass,
    taper_perc,**options):

    """
    Get 'adjoint source' from noise correlation data and synthetics.
    options: g_speed,window_params (only needed if mtype is ln_energy_ratio or enery_diff)
    """


    files = [f for f in os.listdir(os.path.join(source_config['source_path'],
    'observed_correlations')) ]
    files = [os.path.join(source_config['source_path'],
    'observed_correlations',f) for f in files]


    step_n = 'step_{}'.format(int(step))
    synth_dir = os.path.join(source_config['source_path'],
    step_n,'corr')
    adj_dir = os.path.join(source_config['source_path'],
    step_n,'adjt')



    if files == []:
        msg = 'No input found!'
        raise ValueError(msg)

    #i = 0
    hws = options['window_params']['hw'][:]
    g_speed = options['g_speed'][:]


    with click.progressbar(files,label='Determining adjoint sources...') as bar:

        for f in bar:

            # read data
            try:
                tr_o = read(f)[0]
            except:
                print('\nCould not read data: '+os.path.basename(f))
                #i+=1
                continue

            # read synthetics
            try:
                synth_filename = get_synthetics_filename(os.path.basename(f),
                    synth_dir,ignore_network=ignore_network)
                if synth_filename is None:
                    continue
                #sname = glob(os.path.join(synth_dir,synth_filename))[0]
                print(synth_filename)
                tr_s = read(synth_filename)[0]

            except:
                print('\nCould not read synthetics: '+os.path.basename(f))
                #i+=1
                continue

            # Add essential metadata
            tr_s.stats.sac = get_essential_sacmeta(tr_o.stats.sac)

            # Check sampling rates.
            if round(tr_s.stats.sampling_rate,6) != round(tr_o.stats.
                sampling_rate,6):
                print("Sampling Rates (Hz):\n")
                print(tr_s.stats.sampling_rate)
                print(tr_o.stats.sampling_rate)
                msg = 'Sampling rates of data and synthetics must match.'
                raise ValueError(msg)

            
            func = af.get_adj_func(mtype)

            # ugly...sorry

            # Bandpasses
            for j in range(len(bandpass)):

                options['window_params']['hw'] = hws[j]
                options['g_speed'] = g_speed[j]

                tr_o_filt = tr_o.copy()
                tr_s_filt = tr_s.copy()
      
                # Waveforms must have same nr of samples.
                tr_s_filt.data = my_centered(tr_s_filt.data,tr_o.stats.npts)

                bp = bandpass[j]
                if bp != None:
                    tr_o_filt.taper(taper_perc)
                    tr_o_filt.filter('bandpass',freqmin=bp[0],freqmax=bp[1],
                        corners=bp[2],zerophase=True)
                    tr_s_filt.taper(taper_perc)
                    tr_s_filt.filter('bandpass',freqmin=bp[0],freqmax=bp[1],
                        corners=bp[2],zerophase=True)
                    



                #======================================================
                # Weight observed stack by nstack
                #======================================================

                tr_o_filt.data /= tr_o_filt.stats.sac.user0
                
                data, success = func(tr_o_filt,tr_s_filt,**options)
                if not success:
                    continue

                adj_src = Stream()

                if isinstance(data,list):

                    adj_src += Trace(data=data[0])
                    adj_src += Trace(data=data[1])
                    brnchs = ['c','a']
                    for k in range(2):
                        adjtrc = adj_src[k]
                        adjtrc.stats.sampling_rate = tr_s.stats.sampling_rate
                        adjtrc.stats.sac = tr_s.stats.sac.copy()
                        # Save the adjoint source
                        file_adj_src = os.path.join(adj_dir,
                            os.path.basename(synth_filename).
                            rstrip('sac')+'{}.{}.sac'.format(brnchs[k],j))
                        adjtrc.write(file_adj_src,format='SAC')


                else:
                    adj_src += Trace(data=data)
                    for adjtrc in adj_src:
                        adjtrc.stats.sampling_rate = tr_s.stats.sampling_rate
                        adjtrc.stats.sac = tr_s.stats.sac.copy()
                        # Save the adjoint source
                        file_adj_src = os.path.join(adj_dir,
                        os.path.basename(synth_filename).
                            rstrip('sac')+'{}.sac'.format(j))
                        adjtrc.write(file_adj_src,format='SAC')
    return()
예제 #5
0
파일: check_adjstf.py 프로젝트: jigel/noisi
window_params['win_overlap'] = False
window_params['wtype'] = 'hann'
window_params['causal_side'] = False
window_params['plot'] = False
# *********************************************
# *********************************************

# only for testing the test:
# def l2_simple(tr_1,tr_2):
# 	mf = np.sum(0.5 * (tr_1.data - tr_2.data) **2)
# 	adstf = (tr_1.data - tr_2.data)
# 	return mf,adstf

m_a_options = {'g_speed': g_speed, 'window_params': window_params}
m_func = rm.get_measure_func(mtype)
a_func = af.get_adj_func(mtype)

# create observed data, synthetics and perturbation
c_obs = 2 * (np.random.rand(2401, ) - 0.5)
c_ini = 2 * (np.random.rand(2401, ) - 0.5)
d_c = 2 * (np.random.rand(2401, ) - 0.5)
# form traces (measurement script works with obspy trace objects, not pure arrays)
c_obs = Trace(data=c_obs)
c_obs.stats.sampling_rate = 1.0
c_obs.stats.sac = sacdict

c_syn = Trace(data=c_ini)
c_syn.stats.sampling_rate = 1.0
c_syn.stats.sac = sacdict

#tr_taper_filter = Trace(data=np.ones(c_obs.stats.npts))
예제 #6
0
def adjointsrcs(source_config,mtype,step,ignore_network,**options):
    
    """
    Get 'adjoint source' from noise correlation data and synthetics. 
    options: g_speed,window_params (only needed if mtype is ln_energy_ratio or enery_diff)
    """
    
    
    files = [f for f in os.listdir(os.path.join(source_config['source_path'],
    'observed_correlations')) ]
    files = [os.path.join(source_config['source_path'],
    'observed_correlations',f) for f in files]
    
   
    step_n = 'step_{}'.format(int(step))
    synth_dir = os.path.join(source_config['source_path'],
    step_n,'corr')
    adj_dir = os.path.join(source_config['source_path'],
    step_n,'adjt')
    
    
   
    if files == []:
        msg = 'No input found!'
        raise ValueError(msg)
    
    #i = 0
    with click.progressbar(files,label='Determining adjoint sources...') as bar:
        
        for f in bar:
            
            try: 
                tr_o = read(f)[0]
            except:
                print('\nCould not read data: '+os.path.basename(f))
                #i+=1
                continue
            try:
                synth_filename = get_synthetics_filename(os.path.basename(f),synth_dir,
                    ignore_network=ignore_network)
                if synth_filename is None:
                    continue
                #sname = glob(os.path.join(synth_dir,synth_filename))[0]
                print(synth_filename)
                tr_s = read(synth_filename)[0]
                
            except:
                print('\nCould not read synthetics: '+os.path.basename(f))
                #i+=1
                continue

            # Add essential metadata
            tr_s.stats.sac = get_essential_sacmeta(tr_o.stats.sac)

            # Check sampling rates. 
            if round(tr_s.stats.sampling_rate,6) != round(tr_o.stats.sampling_rate,6):
                print("Sampling Rates (Hz)")
                print(tr_s.stats.sampling_rate)
                print(tr_o.stats.sampling_rate)
                msg = 'Sampling rates of data and synthetics must match.'
                raise ValueError(msg)

            # Waveforms must have same nr of samples.
            tr_s.data = my_centered(tr_s.data,tr_o.stats.npts)    
           
           
            # Get the adjoint source
            func = af.get_adj_func(mtype)
            data, success = func(tr_o,tr_s,**options)
            if not success:
                continue
            
            adj_src = Stream()

            if isinstance(data,list):
                
                adj_src += Trace(data=data[0])
                adj_src += Trace(data=data[1])
                
                # TODO: super ugly
                brnch = 'c'
                for adjtrc in adj_src:
                    adjtrc.stats.sampling_rate = tr_s.stats.sampling_rate
                    adjtrc.stats.sac = tr_s.stats.sac.copy()
            # Save the adjoint source
                    file_adj_src = os.path.join(adj_dir,
                        os.path.basename(synth_filename).
                        rstrip('sac')+'{}.sac'.format(brnch))
                    print(file_adj_src)
                    adjtrc.write(file_adj_src,format='SAC')
                    brnch = 'a'
            
            else:
                adj_src += Trace(data=data)
                for adjtrc in adj_src:
                    adjtrc.stats.sampling_rate = tr_s.stats.sampling_rate
                    adjtrc.stats.sac = tr_s.stats.sac.copy()
            # Save the adjoint source
                    file_adj_src = os.path.join(adj_dir,
                        os.path.basename(synth_filename))
                    adjtrc.write(file_adj_src,format='SAC')
예제 #7
0
def adjointsrcs(source_config, mtype, step, ignore_network, bandpass,
                taper_perc, **options):
    """
    Get 'adjoint source' from noise correlation data and synthetics.
    options: g_speed,window_params (only needed if mtype is ln_energy_ratio or enery_diff)
    """

    files = [
        f for f in os.listdir(
            os.path.join(source_config['source_path'],
                         'observed_correlations'))
    ]
    files = [
        os.path.join(source_config['source_path'], 'observed_correlations', f)
        for f in files
    ]

    step_n = 'step_{}'.format(int(step))
    synth_dir = os.path.join(source_config['source_path'], step_n, 'corr')
    adj_dir = os.path.join(source_config['source_path'], step_n, 'adjt')

    if files == []:
        msg = 'No input found!'
        raise ValueError(msg)

    #i = 0
    hws = options['window_params']['hw'][:]
    g_speed = options['g_speed'][:]

    with click.progressbar(files,
                           label='Determining adjoint sources...') as bar:

        for f in bar:

            # read data
            try:
                tr_o = read(f)[0]
            except:
                print('\nCould not read data: ' + os.path.basename(f))
                #i+=1
                continue

            # read synthetics
            try:
                synth_filename = get_synthetics_filename(
                    os.path.basename(f),
                    synth_dir,
                    ignore_network=ignore_network)
                if synth_filename is None:
                    continue
                #sname = glob(os.path.join(synth_dir,synth_filename))[0]
                print(synth_filename)
                tr_s = read(synth_filename)[0]

            except:
                print('\nCould not read synthetics: ' + os.path.basename(f))
                #i+=1
                continue

            # Add essential metadata
            tr_s.stats.sac = get_essential_sacmeta(tr_o.stats.sac)

            # Check sampling rates.
            if round(tr_s.stats.sampling_rate, 6) != round(
                    tr_o.stats.sampling_rate, 6):
                print("Sampling Rates (Hz):\n")
                print(tr_s.stats.sampling_rate)
                print(tr_o.stats.sampling_rate)
                msg = 'Sampling rates of data and synthetics must match.'
                raise ValueError(msg)

            func = af.get_adj_func(mtype)

            # ugly...sorry

            # Bandpasses
            for j in range(len(bandpass)):

                options['window_params']['hw'] = hws[j]
                options['g_speed'] = g_speed[j]

                tr_o_filt = tr_o.copy()
                tr_s_filt = tr_s.copy()

                # Waveforms must have same nr of samples.
                tr_s_filt.data = my_centered(tr_s_filt.data, tr_o.stats.npts)

                bp = bandpass[j]
                if bp != None:
                    tr_o_filt.taper(taper_perc)
                    tr_o_filt.filter('bandpass',
                                     freqmin=bp[0],
                                     freqmax=bp[1],
                                     corners=bp[2],
                                     zerophase=True)
                    tr_s_filt.taper(taper_perc)
                    tr_s_filt.filter('bandpass',
                                     freqmin=bp[0],
                                     freqmax=bp[1],
                                     corners=bp[2],
                                     zerophase=True)

                #======================================================
                # Weight observed stack by nstack
                #======================================================

                tr_o_filt.data /= tr_o_filt.stats.sac.user0

                data, success = func(tr_o_filt, tr_s_filt, **options)
                if not success:
                    continue

                adj_src = Stream()

                if isinstance(data, list):

                    adj_src += Trace(data=data[0])
                    adj_src += Trace(data=data[1])
                    brnchs = ['c', 'a']
                    for k in range(2):
                        adjtrc = adj_src[k]
                        adjtrc.stats.sampling_rate = tr_s.stats.sampling_rate
                        adjtrc.stats.sac = tr_s.stats.sac.copy()
                        # Save the adjoint source
                        file_adj_src = os.path.join(
                            adj_dir,
                            os.path.basename(synth_filename).rstrip('sac') +
                            '{}.{}.sac'.format(brnchs[k], j))
                        adjtrc.write(file_adj_src, format='SAC')

                else:
                    adj_src += Trace(data=data)
                    for adjtrc in adj_src:
                        adjtrc.stats.sampling_rate = tr_s.stats.sampling_rate
                        adjtrc.stats.sac = tr_s.stats.sac.copy()
                        # Save the adjoint source
                        file_adj_src = os.path.join(
                            adj_dir,
                            os.path.basename(synth_filename).rstrip('sac') +
                            '{}.sac'.format(j))
                        adjtrc.write(file_adj_src, format='SAC')
    return ()