def test_process_adjoint():
array = np.array([1, 2, 3, 4, 5])
starttime = UTCDateTime(1990, 1, 1)
adjsrcs = get_sample_adjsrcs(array, starttime)
final_adjsrcs = pa.process_adjoint(adjsrcs,
interp_flag=False,
sum_over_comp_flag=False,
filter_flag=False,
add_missing_comp_flag=False,
rotate_flag=False)
assert len(final_adjsrcs) == 3
for adj1, adj2 in zip(adjsrcs, final_adjsrcs):
npt.assert_allclose(adj1.adjoint_source, adj2.adjoint_source[::-1])
assert adj1.id == adj2.id
adjsrcs = [adjsrcs[0], adjsrcs[1]]
final_adjsrcs = pa.process_adjoint(adjsrcs,
interp_flag=False,
sum_over_comp_flag=False,
filter_flag=False,
add_missing_comp_flag=True,
rotate_flag=False)
assert len(final_adjsrcs) == 3
assert adjsrcs[0].id == final_adjsrcs[0].id
npt.assert_allclose(adjsrcs[0].adjoint_source,
final_adjsrcs[0].adjoint_source[::-1])
assert final_adjsrcs[1].id == "II.AAK..BHR"
npt.assert_allclose(final_adjsrcs[1].adjoint_source,
adjsrcs[1].adjoint_source[::-1])
assert final_adjsrcs[2].id == "II.AAK..BHT"
npt.assert_allclose(final_adjsrcs[2].adjoint_source, np.zeros(len(array)))
def test_process_adjoint():
array = np.array([1, 2, 3, 4, 5])
starttime = UTCDateTime(1990, 1, 1)
adjsrcs = get_sample_adjsrcs(array, starttime)
final_adjsrcs = pa.process_adjoint(
adjsrcs, interp_flag=False, sum_over_comp_flag=False,
filter_flag=False, add_missing_comp_flag=False,
rotate_flag=False)
assert len(final_adjsrcs) == 3
for adj1, adj2 in zip(adjsrcs, final_adjsrcs):
npt.assert_allclose(adj1.adjoint_source, adj2.adjoint_source[::-1])
assert adj1.id == adj2.id
adjsrcs = [adjsrcs[0], adjsrcs[1]]
final_adjsrcs = pa.process_adjoint(
adjsrcs, interp_flag=False, sum_over_comp_flag=False,
filter_flag=False, add_missing_comp_flag=True,
rotate_flag=False)
assert len(final_adjsrcs) == 3
assert adjsrcs[0].id == final_adjsrcs[0].id
npt.assert_allclose(adjsrcs[0].adjoint_source,
final_adjsrcs[0].adjoint_source[::-1])
assert final_adjsrcs[1].id == "II.AAK..BHR"
npt.assert_allclose(final_adjsrcs[1].adjoint_source,
adjsrcs[1].adjoint_source[::-1])
assert final_adjsrcs[2].id == "II.AAK..BHT"
npt.assert_allclose(final_adjsrcs[2].adjoint_source,
np.zeros(len(array)))
def test_process_adjoint_2():
st, meta = prepare_real_adj_data()
inv = obspy.read_inventory()
event = obspy.read_events()[0]
adjs = pa.convert_stream_to_adjs(st, meta)
starttime = adjs[0].starttime - 20
delta = adjs[0].dt / 2.0
npts = 40 + 2 * len(adjs[0].adjoint_source)
new_adj = pa.process_adjoint(adjs,
interp_flag=True,
interp_starttime=starttime,
interp_delta=delta,
interp_npts=npts,
sum_over_comp_flag=True,
weight_flag=False,
filter_flag=True,
pre_filt=[0.02, 0.025, 0.059, 0.073],
taper_percentage=0.05,
taper_type="hann",
add_missing_comp_flag=True,
rotate_flag=True,
inventory=inv,
event=event)
assert len(new_adj) == 3
def test_process_adjoint_2():
st, meta = prepare_real_adj_data()
inv = obspy.read_inventory()
event = obspy.read_events()[0]
adjs = pa.convert_stream_to_adjs(st, meta)
starttime = adjs[0].starttime - 20
delta = adjs[0].dt / 2.0
npts = 40 + 2 * len(adjs[0].adjoint_source)
new_adj = pa.process_adjoint(
adjs, interp_flag=True, interp_starttime=starttime,
interp_delta=delta, interp_npts=npts, sum_over_comp_flag=True,
weight_flag=False, filter_flag=True,
pre_filt=[0.02, 0.025, 0.059, 0.073],
taper_percentage=0.05, taper_type="hann",
add_missing_comp_flag=True, rotate_flag=True,
inventory=inv, event=event
)
assert len(new_adj) == 3
def func_wrapper(obsd_station_group,
synt_station_group,
obsd_tag=None,
synt_tag=None,
event=None,
param=None,
_verbose=False,
figure_mode=False,
figure_dir=None):
"""
combo function, including:
1) observed data signal processing
2) synthetic data signal processing
3) window selection based on a pair of data
4) adjoint source constructor
"""
# Make sure everything thats required is there.
_station_name = obsd_station_group._station_name
if not hasattr(obsd_station_group, "StationXML"):
raise ValueError("obsd station group '%s' missing 'StationXML'" %
_station_name)
if not hasattr(synt_station_group, "StationXML"):
raise ValueError("synt station group '%s' missing 'StationXML'" %
_station_name)
if not hasattr(obsd_station_group, obsd_tag):
raise ValueError("obsd station group '%s' missing '%s'" %
(_station_name, obsd_tag))
if not hasattr(synt_station_group, synt_tag):
raise ValueError("synt station group '%s' missing '%s'" %
(_station_name, synt_tag))
param = copy.deepcopy(param)
obsd_staxml = obsd_station_group.StationXML
synt_staxml = synt_station_group.StationXML
observed = getattr(obsd_station_group, obsd_tag)
synthetic = getattr(synt_station_group, synt_tag)
# keep a reference for construct adjoint source, which
# should be same length and dt as raw synt
_raw_synt_tr = synthetic[0].copy()
obsd_param = param["proc_obsd_param"]
new_obsd = process_stream(observed, inventory=obsd_staxml, **obsd_param)
synt_param = param["proc_synt_param"]
new_synt = process_stream(synthetic, inventory=synt_staxml, **synt_param)
window_config = load_window_config(param["window_param"])
windows = window_on_stream(new_obsd,
new_synt,
window_config,
station=synt_staxml,
event=event,
figure_mode=figure_mode,
figure_dir=figure_dir,
_verbose=_verbose)
if len(windows) == 0:
# No windows selected
return
windows = smart_transform_window(windows)
adj_config, adj_src_type = load_adjoint_config(param["adjsrc_param"])
adjsrcs = calculate_adjsrc_on_stream(new_obsd,
new_synt,
windows,
adj_config,
adj_src_type,
figure_mode=figure_mode,
figure_dir=figure_dir,
adjoint_src_flag=True)
chan_weight_dict = calculate_chan_weight(adjsrcs, windows)
interp_starttime = _raw_synt_tr.stats.starttime
interp_delta = _raw_synt_tr.stats.delta
interp_npts = _raw_synt_tr.stats.npts
pre_filt = obsd_param["pre_filt"]
new_adjsrcs = process_adjoint(adjsrcs,
interp_starttime,
interp_delta,
interp_npts,
rotate_flag=True,
inventory=synt_staxml,
event=event,
sum_over_comp_flag=True,
weight_flag=True,
weight_dict=chan_weight_dict,
filter_flag=True,
pre_filt=pre_filt)
origin = event.preferred_origin() or event.origins[0]
time_offset = interp_starttime - origin.time
results = reshape_adj(new_adjsrcs, time_offset, synt_staxml)
return results
def adjoint_wrapper(obsd_station_group,
synt_station_group,
config=None,
obsd_tag=None,
synt_tag=None,
windows=None,
event=None,
adj_src_type="multitaper_misfit",
postproc_param=None,
figure_mode=False,
figure_dir=False,
adjoint_src_flag=True):
"""
Function wrapper for pyasdf.
:param obsd_station_group: observed station group, which contains
seismogram(stream) and station information(inventory)
:param synt_station_group: synthetic station group. Same as
obsd_station_group
:param config: config object for adjoint source
:type config: pyadjoint.Config
:param obsd_tag: observed seismogram tag, used for extracting the
seismogram in observed asdf file
:type obsd_tag: str
:param synt_tag: synthetic seismogram tag, used for extracting the
seismogram in synthetic asdf file
:type synt_tag: str
:param windows: windows for this station group. Two dimension list.
The first dimension is different channels, the second dimension
is windows for this channel, like [[chan1_win1, chan1_win2],
[chan2_win1,], ...]
:type windows: list
:param event: event information
:type event: obspy.Inventory
:param adj_src_type: adjoint source type, currently support:
1) "cc_traveltime_misfit"
2) "multitaper_misfit"
3) "waveform_misfit"
:type adj_src_type: st
:param adjoint_src_flag: calcualte adjoint source, put this to true.
If false, only make measurements but no adjoint sources.
:type adjoint_src_flag: bool
:param figure_mode: plot figures for adjoint source or not
:type figure_mode: bool
:param figure_dir: output figure directory
:type figure_dir: str
:return: adjoint sources for pyasdf write out(reshaped)
"""
# Make sure everything thats required is there.
if not hasattr(obsd_station_group, obsd_tag):
print("Missing tag '%s' from obsd_station_group %s. Skipped." %
(obsd_tag, obsd_station_group._station_name))
return
if not hasattr(synt_station_group, synt_tag):
print("Missing tag '%s' from synt_station_group %s. Skipped." %
(synt_tag, synt_station_group._station_name))
return
if not hasattr(obsd_station_group, "StationXML"):
print("Missing tag 'STATIONXML' from obsd_station_group %s. Skipped" %
(obsd_tag, obsd_station_group._station_name))
try:
window_sta = windows[obsd_station_group._station_name]
except:
return
# check total number of windows. If total number of
# window is 0, return None
nwin_total = 0
for value in window_sta.itervalues():
nwin_total += len(value)
if nwin_total == 0:
return
observed = getattr(obsd_station_group, obsd_tag)
synthetic = getattr(synt_station_group, synt_tag)
obsd_staxml = getattr(obsd_station_group, "StationXML")
adjsrcs = calculate_adjsrc_on_stream(observed,
synthetic,
window_sta,
config,
adj_src_type,
figure_mode=figure_mode,
figure_dir=figure_dir,
adjoint_src_flag=adjoint_src_flag)
if postproc_param["weight_flag"]:
chan_weight_dict = calculate_chan_weight(adjsrcs, window_sta)
else:
chan_weight_dict = None
origin = event.preferred_origin() or event.origins[0]
focal = event.preferred_focal_mechanism()
hdr = focal.moment_tensor.source_time_function.duration / 2.0
# according to SPECFEM starttime convention
time_offset = -1.5 * hdr
starttime = origin.time + time_offset
new_adjsrcs = process_adjoint(adjsrcs,
interp_starttime=starttime,
inventory=obsd_staxml,
event=event,
weight_dict=chan_weight_dict,
**postproc_param)
_final = reshape_adj(new_adjsrcs, time_offset, obsd_staxml)
if _final is None:
return
else:
return _final
def func_wrapper(obsd_station_group, synt_station_group, obsd_tag=None,
synt_tag=None, event=None, param=None, _verbose=False,
figure_mode=False, figure_dir=None):
"""
combo function, including:
1) observed data signal processing
2) synthetic data signal processing
3) window selection based on a pair of data
4) adjoint source constructor
"""
# Make sure everything thats required is there.
_station_name = obsd_station_group._station_name
if not hasattr(obsd_station_group, "StationXML"):
raise ValueError("obsd station group '%s' missing 'StationXML'"
% _station_name)
if not hasattr(synt_station_group, "StationXML"):
raise ValueError("synt station group '%s' missing 'StationXML'"
% _station_name)
if not hasattr(obsd_station_group, obsd_tag):
raise ValueError("obsd station group '%s' missing '%s'"
% (_station_name, obsd_tag))
if not hasattr(synt_station_group, synt_tag):
raise ValueError("synt station group '%s' missing '%s'"
% (_station_name, synt_tag))
param = copy.deepcopy(param)
obsd_staxml = obsd_station_group.StationXML
synt_staxml = synt_station_group.StationXML
observed = getattr(obsd_station_group, obsd_tag)
synthetic = getattr(synt_station_group, synt_tag)
# keep a reference for construct adjoint source, which
# should be same length and dt as raw synt
_raw_synt_tr = synthetic[0].copy()
obsd_param = param["proc_obsd_param"]
new_obsd = process_stream(observed, inventory=obsd_staxml, **obsd_param)
synt_param = param["proc_synt_param"]
new_synt = process_stream(synthetic, inventory=synt_staxml, **synt_param)
window_config = load_window_config(param["window_param"])
windows = window_on_stream(new_obsd, new_synt, window_config,
station=synt_staxml, event=event,
figure_mode=figure_mode, figure_dir=figure_dir,
_verbose=_verbose)
if len(windows) == 0:
# No windows selected
return
windows = smart_transform_window(windows)
adj_config, adj_src_type = load_adjoint_config(param["adjsrc_param"])
adjsrcs = calculate_adjsrc_on_stream(
new_obsd, new_synt, windows, adj_config, adj_src_type,
figure_mode=figure_mode, figure_dir=figure_dir,
adjoint_src_flag=True)
chan_weight_dict = calculate_chan_weight(adjsrcs, windows)
interp_starttime = _raw_synt_tr.stats.starttime
interp_delta = _raw_synt_tr.stats.delta
interp_npts = _raw_synt_tr.stats.npts
pre_filt = obsd_param["pre_filt"]
new_adjsrcs = process_adjoint(
adjsrcs, interp_starttime, interp_delta, interp_npts,
rotate_flag=True, inventory=synt_staxml, event=event,
sum_over_comp_flag=True, weight_flag=True,
weight_dict=chan_weight_dict, filter_flag=True,
pre_filt=pre_filt)
origin = event.preferred_origin() or event.origins[0]
time_offset = interp_starttime - origin.time
results = reshape_adj(new_adjsrcs, time_offset, synt_staxml)
return results
