def post_process(self, engine, source, statics):
campaign = gnss.GNSSCampaign()
for ista in range(self.ntargets):
north = gnss.GNSSComponent(
shift=float(statics['displacement.n'][ista]))
east = gnss.GNSSComponent(
shift=float(statics['displacement.e'][ista]))
up = gnss.GNSSComponent(
shift=-float(statics['displacement.d'][ista]))
coords = self.coords5
station = gnss.GNSSStation(
lat=float(coords[ista, 0]),
lon=float(coords[ista, 1]),
east_shift=float(coords[ista, 2]),
north_shift=float(coords[ista, 3]),
elevation=float(coords[ista, 4]),
north=north,
east=east,
up=up)
campaign.add_station(station)
return meta.GNSSCampaignResult(result=statics, campaign=campaign)
def load_ascii_gnss_globk(filedir,
filename,
components=['east', 'north', 'up']):
"""
Load ascii file columns containing:
station name, Lon, Lat, ve, vn, vu, sigma_ve, sigma_vn, sigma_vu
location [decimal deg]
measurement unit [mm/yr]
Returns
-------
:class:`pyrocko.model.gnss.GNSSCampaign`
"""
from pyrocko.model import gnss
filepath = os.path.join(filedir, filename)
skiprows = 3
if os.path.exists(filepath):
names = num.loadtxt(filepath,
skiprows=skiprows,
usecols=[12],
dtype='str')
d = num.loadtxt(filepath,
skiprows=skiprows,
usecols=range(12),
dtype='float')
elif len(os.path.splitext(filepath)[1]) == 0:
logger.info('File %s is not an ascii text file!' % filepath)
return
else:
raise ImportError('Did not find data under: %s' % filepath)
component_to_idx_map = {'east': (2, 6), 'north': (3, 7), 'up': (9, 11)}
# velocity_idxs = [2, 3, 9]
# std_idxs = [6, 7, 11]
if names.size != d.shape[0]:
raise Exception('Number of stations and available data differs!')
data = gnss.GNSSCampaign(name=filename)
for i, name in enumerate(names):
#code = str(name.split('_')[0]) # may produce duplicate sites
code = str(name)
gnss_station = gnss.GNSSStation(code=code,
lon=float(d[i, 0]),
lat=float(d[i, 1]))
for j, comp in enumerate(components):
vel_idx, std_idx = component_to_idx_map[comp]
setattr(
gnss_station, comp,
gnss.GNSSComponent(shift=float(d[i, vel_idx] / km),
sigma=float(d[i, std_idx] / km)))
logger.debug('Loaded station %s' % gnss_station.code)
data.add_station(gnss_station)
return data
def plot_gnss(gnss_target, result, ifig, vertical=False):
campaign = gnss_target.campaign
item = PlotItem(
name='fig_%i' % ifig,
attributes={'targets': gnss_target.path},
title=u'Static GNSS Surface Displacements - Campaign %s' %
campaign.name,
description=u'''
Static surface displacement from GNSS campaign %s (black vectors) and
displacements derived from best model (red).
''' % campaign.name)
event = source.pyrocko_event()
locations = campaign.stations + [event]
lat, lon = od.geographic_midpoint_locations(locations)
if self.radius is None:
coords = num.array([loc.effective_latlon for loc in locations])
radius = od.distance_accurate50m_numpy(lat[num.newaxis],
lon[num.newaxis],
coords[:, 0].max(),
coords[:, 1]).max()
radius *= 1.1
if radius < 30. * km:
logger.warn('Radius of GNSS campaign %s too small, defaulting'
' to 30 km' % campaign.name)
radius = 30 * km
model_camp = gnss.GNSSCampaign(stations=copy.deepcopy(
campaign.stations),
name='grond model')
for ista, sta in enumerate(model_camp.stations):
sta.north.shift = result.statics_syn['displacement.n'][ista]
sta.north.sigma = 0.
sta.east.shift = result.statics_syn['displacement.e'][ista]
sta.east.sigma = 0.
if sta.up:
sta.up.shift = -result.statics_syn['displacement.d'][ista]
sta.up.sigma = 0.
m = automap.Map(width=self.size_cm[0],
height=self.size_cm[1],
lat=lat,
lon=lon,
radius=radius,
show_topo=self.show_topo,
show_grid=self.show_grid,
show_rivers=self.show_rivers,
color_wet=(216, 242, 254),
color_dry=(238, 236, 230))
all_stations = campaign.stations + model_camp.stations
offset_scale = num.zeros(len(all_stations))
for ista, sta in enumerate(all_stations):
for comp in sta.components.values():
offset_scale[ista] += comp.shift
offset_scale = num.sqrt(offset_scale**2).max()
m.add_gnss_campaign(campaign,
psxy_style={
'G': 'black',
'W': '0.8p,black',
},
offset_scale=offset_scale,
vertical=vertical)
m.add_gnss_campaign(model_camp,
psxy_style={
'G': 'red',
'W': '0.8p,red',
't': 30,
},
offset_scale=offset_scale,
vertical=vertical,
labels=False)
if isinstance(problem, CMTProblem) \
or isinstance(problem, VLVDProblem):
from pyrocko import moment_tensor
from pyrocko.plot import gmtpy
mt = event.moment_tensor.m_up_south_east()
ev_lat, ev_lon = event.effective_latlon
xx = num.trace(mt) / 3.
mc = num.matrix([[xx, 0., 0.], [0., xx, 0.], [0., 0., xx]])
mc = mt - mc
mc = mc / event.moment_tensor.scalar_moment() * \
moment_tensor.magnitude_to_moment(5.0)
m6 = tuple(moment_tensor.to6(mc))
symbol_size = 20.
m.gmt.psmeca(S='%s%g' % ('d', symbol_size / gmtpy.cm),
in_rows=[(ev_lon, ev_lat, 10) + m6 + (1, 0, 0)],
M=True,
*m.jxyr)
elif isinstance(problem, RectangularProblem):
m.gmt.psxy(in_rows=source.outline(cs='lonlat'),
L='+p2p,black',
W='1p,black',
G='black',
t=60,
*m.jxyr)
elif isinstance(problem, VolumePointProblem):
ev_lat, ev_lon = event.effective_latlon
dV = abs(source.volume_change)
sphere_radius = num.cbrt(dV / (4. / 3. * num.pi))
volcanic_circle = [ev_lon, ev_lat, '%fe' % sphere_radius]
m.gmt.psxy(S='E-',
in_rows=[volcanic_circle],
W='1p,black',
G='orange3',
*m.jxyr)
return (item, m)
from pyrocko.model import gnss, location
from pyrocko.plot.automap import Map
km = 1e3
DIST_MAX = 80. * km
RIDGECREST_EQ = location.Location(lat=35.766, lon=-117.605)
GNSS_URL = 'http://geodesy.unr.edu/news_items/20190707/ci38457511_forweb.txt'
fname = 'ci38457511_forweb.txt'
# Download the data
with open(fname, 'wb') as f:
print('Downloading data from UNR...')
r = requests.get(GNSS_URL)
f.write(r.content)
campaign = gnss.GNSSCampaign(name='Ridgecrest coseismic (UNR)')
print('Loading Ridgecrest GNSS data from %s (max_dist = %.1f km)' %
(fname, DIST_MAX / km))
# load station names and data
with open(fname, 'r') as f:
for header in range(2):
next(f)
names = [line.split(' ')[0] for line in f]
gnss_data = num.loadtxt(fname, skiprows=2, usecols=(1, 2, 3, 4, 5, 6, 7, 8))
for ista, sta_data in enumerate(gnss_data):
name = names[ista]
lon, lat, de, dn, du, sde, sdn, sdu = map(float, sta_data)
station = gnss.GNSSStation(code=name, lat=lat, lon=lon, elevation=0.)
# K. W. Hudnut, Z. Shen, M. Murray, S. McClusky, R. King, T. Herring,
# B. Hager, Y. Feng, P. Fang, A. Donnellan, Y. Bock;
# Co-seismic displacements of the 1994 Northridge, California, earthquake.
# Bulletin of the Seismological Society of America ; 86 (1B): S19–S36. doi:
# https://pasadena.wr.usgs.gov/office/hudnut/hudnut/nr_bssa.html
mm = 1e3
fn_stations = 'GPS_Stations-Northridge-1994_Hudnut.csv'
fn_displacements = 'GPS_Data-Northridge-1994_Hudnut.csv'
get_example_data(fn_stations)
get_example_data(fn_displacements)
campaign = gnss.GNSSCampaign(name='Northridge 1994')
# Load the stations
with open(fn_stations, 'r') as f:
for line in f:
if line.startswith('#'):
continue
row = line.split(',')
sta = gnss.GNSSStation(
code=row[0].strip(),
lat=float(row[1]),
lon=float(row[2]),
elevation=float(row[3]))
campaign.add_station(sta)
# Load the displacements
def export(self,
point,
results_path,
stage_number,
fix_output=False,
force=False,
update=False):
from pyrocko.guts import dump
from kite.scene import Scene, UserIOWarning
from beat.plotting import map_displacement_grid
gc = self.config
results = self.assemble_results(point)
def get_filename(attr, ending='csv'):
return os.path.join(
results_path, '{}_{}_{}.{}'.format(
os.path.splitext(dataset.name)[0], attr, stage_number,
ending))
# export for gnss
for typ, config in gc.types.items():
if 'GNSS' == typ:
from pyrocko.model import gnss
logger.info('Exporting GNSS data ...')
campaigns = config.load_data(campaign=True)
for campaign in campaigns:
model_camp = gnss.GNSSCampaign(
stations=copy.deepcopy(campaign.stations),
name='%s_model' % campaign.name)
dataset_to_result = {}
for dataset, result in zip(self.datasets, results):
if dataset.typ == 'GNSS':
dataset_to_result[dataset] = result
for dataset, result in dataset_to_result.items():
for ista, sta in enumerate(model_camp.stations):
comp = getattr(sta, dataset.component)
comp.shift = result.processed_syn[ista]
comp.sigma = 0.
outname = os.path.join(
results_path, 'gnss_synths_%i.yaml' % stage_number)
dump(model_camp, filename=outname)
elif 'SAR' == typ:
logger.info('Exporting SAR data ...')
for dataset, result in zip(self.datasets, results):
if dataset.typ == 'SAR':
try:
scene_path = os.path.join(config.datadir,
dataset.name)
logger.info(
'Loading full resolution kite scene: %s' %
scene_path)
scene = Scene.load(scene_path)
except UserIOWarning:
logger.warning('Full resolution data could not be'
' loaded! Skipping ...')
continue
for attr in [
'processed_obs', 'processed_syn',
'processed_res'
]:
filename = get_filename(attr, ending='csv')
displacements = getattr(result, attr)
dataset.export_to_csv(filename, displacements)
logger.info('Stored CSV file to: %s' % filename)
filename = get_filename(attr, ending='yml')
vals = map_displacement_grid(displacements, scene)
scene.displacement = vals
scene.save(filename)
logger.info('Stored kite scene to: %s' % filename)
def plot_gnss(gnss_target, result, ifig, vertical=False):
campaign = gnss_target.campaign
item = PlotItem(
name='fig_%i' % ifig,
attributes={'targets': gnss_target.path},
title=u'Static GNSS Surface Displacements - Campaign %s' %
campaign.name,
description=u'Static surface displacement from GNSS campaign '
u'%s (black vectors) and displacements derived '
u'from best rupture model (red).' % campaign.name)
lat, lon = campaign.get_center_latlon()
if self.radius is None:
radius = campaign.get_radius()
if radius == 0.:
logger.warn('Radius of GNSS campaign %s too small, defaulting'
' to 30 km' % campaign.name)
radius = 30 * km
model_camp = gnss.GNSSCampaign(stations=copy.deepcopy(
campaign.stations),
name='grond model')
for ista, sta in enumerate(model_camp.stations):
sta.north.shift = result.statics_syn['displacement.n'][ista]
sta.north.sigma = 0.
sta.east.shift = result.statics_syn['displacement.e'][ista]
sta.east.sigma = 0.
sta.up.shift = -result.statics_syn['displacement.d'][ista]
sta.up.sigma = 0.
m = automap.Map(width=self.size_cm[0],
height=self.size_cm[1],
lat=lat,
lon=lon,
radius=radius,
show_topo=self.show_topo,
show_grid=self.show_grid,
show_rivers=self.show_rivers,
color_wet=(216, 242, 254),
color_dry=(238, 236, 230))
if vertical:
m.add_gnss_campaign(campaign,
psxy_style={
'G': 'black',
'W': '0.8p,black',
},
vertical=True)
m.add_gnss_campaign(model_camp,
psxy_style={
'G': 'red',
'W': '0.8p,red',
't': 30,
},
vertical=True,
labels=False)
else:
m.add_gnss_campaign(campaign,
psxy_style={
'G': 'black',
'W': '0.8p,black',
})
m.add_gnss_campaign(model_camp,
psxy_style={
'G': 'red',
'W': '0.8p,red',
't': 30,
},
labels=False)
if isinstance(problem, CMTProblem):
from pyrocko import moment_tensor
from pyrocko.plot import gmtpy
event = source.pyrocko_event()
mt = event.moment_tensor.m_up_south_east()
xx = num.trace(mt) / 3.
mc = num.matrix([[xx, 0., 0.], [0., xx, 0.], [0., 0., xx]])
mc = mt - mc
mc = mc / event.moment_tensor.scalar_moment() * \
moment_tensor.magnitude_to_moment(5.0)
m6 = tuple(moment_tensor.to6(mc))
symbol_size = 20.
m.gmt.psmeca(S='%s%g' % ('d', symbol_size / gmtpy.cm),
in_rows=[
(source.lon, source.lat, 10) + m6 + (1, 0, 0)
],
M=True,
*m.jxyr)
elif isinstance(problem, RectangularProblem):
m.gmt.psxy(in_rows=source.outline(cs='lonlat'),
L='+p2p,black',
W='1p,black',
G='black',
t=60,
*m.jxyr)
return (item, m)
