def test_no_adjoint_src_calculation_is_honored(adj_src):
"""
If no adjoint source is requested, it should not be returned/calculated.
"""
config = pyadjoint.Config(min_period=30.0,
max_period=75.0,
lnpt=15,
transfunc_waterlevel=1.0E-10,
water_threshold=0.02,
ipower_costaper=10,
min_cycle_in_window=3,
taper_percentage=0.3,
taper_type='hann',
mt_nw=4,
phase_step=1.5,
use_cc_error=False,
use_mt_error=False)
obs, syn = pyadjoint.utils.get_example_data()
obs = obs.select(component="Z")[0]
syn = syn.select(component="Z")[0]
window = [[2076., 2418.0]]
a_src = pyadjoint.calculate_adjoint_source(adj_src_type=adj_src,
observed=obs,
synthetic=syn,
config=config,
window=window,
adjoint_src=False,
plot=False)
# start, end = pyadjoint.utils.EXAMPLE_DATA_PDIFF
# a_src = pyadjoint.calculate_adjoint_source(
# adj_src, obs, syn, 20, 100, start, end, adjoint_src=False)
assert a_src.adjoint_source is None
def load_adjoint_config(config):
"""
Load config into pyadjoint.Config
:param param:
:return:
"""
check_config_keywords(config)
return pyadjoint.Config(**config)
def load_adjoint_config_yaml(filename):
"""
load yaml and setup pyadjoint.Config object
"""
with open(filename) as fh:
data = yaml.load(fh)
if data["min_period"] > data["max_period"]:
raise ValueError("min_period is larger than max_period in config "
"file: %s" % filename)
return pyadjoint.Config(**data)
def test_normal_adjoint_source_calculation(adj_src):
"""
Make sure everything at least runs. Executed for every adjoint source type.
"""
config = pyadjoint.Config(min_period=30.0,
max_period=75.0,
lnpt=15,
transfunc_waterlevel=1.0E-10,
water_threshold=0.02,
ipower_costaper=10,
min_cycle_in_window=3,
taper_percentage=0.3,
taper_type='hann',
mt_nw=4,
phase_step=1.5,
use_cc_error=False,
use_mt_error=False)
obs, syn = pyadjoint.utils.get_example_data()
obs = obs.select(component="Z")[0]
syn = syn.select(component="Z")[0]
# start, end = pyadjoint.utils.EXAMPLE_DATA_PDIFF
window = [[2076., 2418.0]]
a_src = pyadjoint.calculate_adjoint_source(adj_src_type=adj_src,
observed=obs,
synthetic=syn,
config=config,
window=window,
adjoint_src=True,
plot=False)
# a_src = pyadjoint.calculate_adjoint_source(
# adj_src, obs, syn, 20, 100, start, end)
assert a_src.adjoint_source.any()
assert a_src.misfit >= 0.0
assert isinstance(a_src.adjoint_source, np.ndarray)
def load_adjoint_config(param):
adj_src_type = param["adj_src_type"]
param.pop("adj_src_type", None)
config = pyadjoint.Config(**param)
return config, adj_src_type
def write_adjoint_traces(misfit_type, misfit_parameters, filter_parameters,
paths, obs_tag, syn_tag):
"""
Makes misfit measurements using observed and synthetic data;
writes out misfit values and corresponding "adjoint sources"
:param misfit_type: type of data misfit function,
e.g. waveform_difference, multitaper_misfit
:param misfit_parameters: dictionary passed directly to pyadjoint.Config
:param paths.obs: ASDF observed data filename
:param paths.syn: ASDF synthetic data filename
:param paths.windows: JSON windows filename
:param paths.adjoint_sources: adjoint_sources will be written to an ASDF
file with this name
:param paths.misfit: misfit values will be written a JSON file with this name
:param obs_tag: observed data are read using this ASDF tag
:param syn_tag: synthetic data are read using this ASDF tag
"""
from mpi4py import MPI
comm = MPI.COMM_WORLD
rank = comm.rank
cwd = dirname(__file__)
# read data
fullpath = join(cwd, paths.obs)
obs = pyasdf.ASDFDataSet(fullpath, compression=None, mode="a")
event = obs.events[0]
# read synthetics
fullpath = join(cwd, paths.syn)
syn = pyasdf.ASDFDataSet(fullpath, compression=None, mode="a")
# read windows
fullpath = join(cwd, paths.windows)
windows = read_json_mpi(paths.windows, comm)
# generate pyadjoint.Config objects
config = pyadjoint.Config(**misfit_parameters)
# wrapper is required for ASDF processing
def wrapped_function(obs, syn):
# TODO: modify pytomo3d to make the following
# function call more readable?
return pytomo3d.adjoint.calculate_and_process_adjsrc_on_stream(
obs[obs_tag],
syn[syn_tag],
windows[obs._station_name],
obs.StationXML,
config,
event,
misfit_type,
filter_parameters,
figure_mode=False,
figure_dir=None)
adjoint_sources = obs.process_two_files_without_parallel_output(
syn, wrapped_function)
if rank == 0:
# save as ASDF waveforms
ds = pyasdf.ASDFDataSet(paths.adjoint_sources, mpi=False, mode="a")
tag = 'processed_adjoint'
add_adjoint_source_waveforms(ds, adjoint_sources, tag)
del ds
# write misfit
pass