def test_midpoint(self):
center_lons = num.linspace(0., 180., 5)
center_lats = [0., 89.]
npoints = 10000
half_side_length = 1000000.
distance_error_max = 50000.
for lat in center_lats:
for lon in center_lons:
n = num.random.uniform(
-half_side_length, half_side_length, npoints)
e = num.random.uniform(
-half_side_length, half_side_length, npoints)
dlats, dlons = orthodrome.ne_to_latlon(lat, lon, n, e)
clat, clon = orthodrome.geographic_midpoint(dlats, dlons)
d = orthodrome.distance_accurate50m_numpy(
clat, clon, lat, lon)[0]
if plot:
import matplotlib.pyplot as plt
fig = plt.figure()
ax = fig.add_subplot(111)
ax.scatter(n, e)
c_n, c_e = orthodrome.latlon_to_ne_numpy(
lat, lon, clat, clon)
ax.plot(c_n, c_e, 'ro')
plt.show()
self.assertTrue(d < distance_error_max, 'Distance %s > %s' %
(d, distance_error_max) +
'(maximum error)\n tested lat/lon: %s/%s' %
(lat, lon))
def bounding_box(lat, lon, north, east, depth, scale=1.0):
lat, lon, north, east, depth = float_array_broadcast(
lat, lon, north, east, depth)
if num.all(lat[0] == lat) and num.all(lon[0] == lon):
return _scaled_bb(lat[0], lon[0], (num.min(north), num.max(north)),
(num.min(east), num.max(east)),
(num.min(depth), num.max(depth)), scale)
else:
elat, elon = od.ne_to_latlon(lat, lon, north, east)
enorth, eeast = od.latlon_to_ne_numpy(elat[0], elon[0], elat, elon)
enorth_min = num.min(enorth)
enorth_max = num.max(enorth)
eeast_min = num.min(eeast)
eeast_max = num.max(eeast)
mnorth = 0.5 * (enorth_min + enorth_max)
meast = 0.5 * (eeast_min + eeast_max)
lat0, lon0 = od.ne_to_latlon(elat[0], elon[0], mnorth, meast)
return _scaled_bb(lat0, lon0,
(enorth_min - mnorth, enorth_max - mnorth),
(eeast_min - meast, eeast_max - meast),
(num.min(depth), num.max(depth)), scale)
def process(sources, sandbox, nthreads=0):
result = {
'processor_profile': dict(),
'displacement.n': num.zeros(sandbox.frame.npixel),
'displacement.e': num.zeros(sandbox.frame.npixel),
'displacement.d': num.zeros(sandbox.frame.npixel),
}
src_nu = set(src.nu for src in sources)
for nu in src_nu:
nu_sources = [src for src in sources if src.nu == nu]
nsources = len(nu_sources)
src_arr = num.vstack([src.dislocSource() for src in nu_sources])
north_shifts, east_shifts = od.latlon_to_ne_numpy(
num.repeat(sandbox.frame.llLat, nsources),
num.repeat(sandbox.frame.llLon, nsources),
num.array([src.lat for src in nu_sources]),
num.array([src.lon for src in nu_sources]))
src_arr[:, 5] += east_shifts
src_arr[:, 6] += north_shifts
res = disloc_ext.disloc(src_arr, sandbox.frame.coordinatesMeter,
nu, nthreads)
result['displacement.e'] += res[:, 0]
result['displacement.n'] += res[:, 1]
result['displacement.d'] += -res[:, 2]
return result
def test_midpoint(self):
center_lons = num.linspace(0., 180., 5)
center_lats = [0., 89.]
npoints = 10000
half_side_length = 1000000.
distance_error_max = 50000.
for lat in center_lats:
for lon in center_lons:
n = num.random.uniform(-half_side_length, half_side_length,
npoints)
e = num.random.uniform(-half_side_length, half_side_length,
npoints)
dlats, dlons = orthodrome.ne_to_latlon(lat, lon, n, e)
clat, clon = orthodrome.geographic_midpoint(dlats, dlons)
d = orthodrome.distance_accurate50m_numpy(
clat, clon, lat, lon)[0]
if plot:
import matplotlib.pyplot as plt
fig = plt.figure()
ax = fig.add_subplot(111)
ax.scatter(n, e)
c_n, c_e = orthodrome.latlon_to_ne_numpy(
lat, lon, clat, clon)
ax.plot(c_n, c_e, 'ro')
plt.show()
self.assertTrue(
d < distance_error_max,
'Distance %s > %s' % (d, distance_error_max) +
'(maximum error)\n tested lat/lon: %s/%s' % (lat, lon))
def block_geometry(lons, lats, sources, reference):
"""
Construct block geometry determine stable and moving parts dependend
on the reference location.
Parameters
----------
lons : :class:`num.ndarray`
Longitudes [deg] of observation points
lats : :class:`num.ndarray`
Latitudes [deg] of observation points
sources : list
of RectangularFault objects
reference : :class:`heart.ReferenceLocation`
reference location that determines the stable block
Returns
-------
:class:`num.ndarray`
mask with zeros/ones for stable/moving observation points, respectively
"""
norths, easts = orthodrome.latlon_to_ne_numpy(reference.lat, reference.lon,
lats, lons)
return block_mask(easts, norths, sources, east_ref=0., north_ref=0.)
def _calculateMeterGrid(self):
if self.isMeter():
raise ValueError(
"Frame is defined in meter! " "Use gridE and gridN for meter grids"
)
if self._meter_grid is None:
self._log.debug("Transforming latlon grid to meters...")
gridN, gridE = latlon_to_ne_numpy(
self.llLat,
self.llLon,
self.llLat + self.gridN.data.ravel(),
self.llLon + self.gridE.data.ravel(),
)
valid_data = num.isnan(self._scene.displacement)
gridE = num.ma.masked_array(
gridE.reshape(self.gridE.shape), valid_data, fill_value=num.nan
)
gridN = num.ma.masked_array(
gridN.reshape(self.gridN.shape), valid_data, fill_value=num.nan
)
self._meter_grid = (gridE, gridN)
return self._meter_grid
class TestInterseismic(unittest.TestCase):
def __init__(self, *args, **kwargs):
unittest.TestCase.__init__(self, *args, **kwargs)
self.reference = None
self.amplitude = 0.02
self.azimuth = 115.
self.locking_depth = [6.3, 5.0]
def _get_store_superdir(self):
return os.path.abspath('data/')
def _get_gf_store(self, crust_ind):
store_superdir = self._get_store_superdir(self)
return os.path.join(store_superdir, 'psgrn_green_%i' % crust_ind)
def _get_synthetic_data(self):
lon = num.linspace(10.5, 13.5, 100.)
lat = num.linspace(44.0, 46.0, 100.)
Lon, Lat = num.meshgrid(lon, lat)
reference = ReferenceLocation(
lon=5., lat=45.)
self.lons = Lon.flatten()
self.lats = Lat.flatten()
self.reference = reference
def _get_sources(self, case=1):
if case == 1:
sources = [
pscmp.PsCmpRectangularSource(
lon=12., lat=45., strike=20., dip=90., length=125. * km),
pscmp.PsCmpRectangularSource(
lon=11.25, lat=44.35, strike=70., dip=90., length=80. * km)]
elif case == 2:
sources = [
pscmp.PsCmpRectangularSource(
lon=12.04, lat=45.000, strike= 329.35 -180, dip=90.,
length=117809.04),
pscmp.PsCmpRectangularSource(
lon=11.5, lat=45.75, strike=357.04-180, dip=90.,
length=80210.56)]
for source in sources:
north_shift, east_shift = orthodrome.latlon_to_ne_numpy(
self.reference.lat,
self.reference.lon,
source.effective_lat,
source.effective_lon,
)
source.update(
lat=self.reference.lat, lon=self.reference.lon,
north_shift=north_shift, east_shift=east_shift)
print source
return sources
def mean_latlondist(lats, lons):
if len(lats) == 0:
return 0., 0., 1000.
else:
ns, es = od.latlon_to_ne_numpy(lats[0], lons[0], lats, lons)
n, e = num.mean(ns), num.mean(es)
dists = num.sqrt((ns - n)**2 + (es - e)**2)
lat, lon = od.ne_to_latlon(lats[0], lons[0], n, e)
return float(lat), float(lon), float(num.max(dists))
def set_origin(self, lat, lon):
lat = float(lat)
lon = float(lon)
elat, elon = self.effective_latlon
n, e = orthodrome.latlon_to_ne_numpy(lat, lon, elat, elon)
self.lat = lat
self.lon = lon
self.north_shift = float(n)
self.east_shift = float(e)
self._latlon = elat, elon # unchanged
def set_origin(self, lat, lon):
lat = float(lat)
lon = float(lon)
elat, elon = self.effective_latlon
n, e = orthodrome.latlon_to_ne_numpy(lat, lon, elat, elon)
self.lat = lat
self.lon = lon
self.north_shift = float(n)
self.east_shift = float(e)
self._latlon = elat, elon # unchanged
def scaled_mesh(xin, yin):
x, y = num.meshgrid(xin, yin)
xs = num.zeros(x.shape)
ys = num.zeros(y.shape)
olats = num.zeros(y.shape[1])
olons = num.zeros(x.shape[1])
for i in xrange(len(x)):
xs[i], ys[i] = od.latlon_to_ne_numpy(olats, olons, y[i], x[i])
return xs, ys
def surface_points(self, system='latlon'):
x, y, z = self._get_coords()
xs = num.tile(x, y.size)
ys = num.repeat(y, x.size)
if system == 'latlon':
return od.ne_to_latlon(self.lat, self.lon, xs, ys)
elif system[0] == 'ne':
lat0, lon0 = system[1:]
if lat0 == self.lat and lon0 == self.lon:
return xs, ys
else:
elats, elons = od.ne_to_latlon(self.lat, self.lon, xs, ys)
return od.latlon_to_ne_numpy(lat0, lon0, elats, elons)
def get_shifts(stations, center_station, bazis, slownesses):
''' shape = (len(bazi), len(slow))'''
lats = num.array([s.lat for s in stations])
lons = num.array([s.lon for s in stations])
lat0 = num.array([center_station.lat] * len(stations))
lon0 = num.array([center_station.lon] * len(stations))
ns, es = ortho.latlon_to_ne_numpy(lat0, lon0, lats, lons)
station_vector = num.array((ns, es)).T
bazis = bazis * d2r
shifts = num.zeros((len(bazis)*len(slownesses), len(stations)))
ishift = 0
for ibazi, bazi in enumerate(bazis):
s_vector = num.array((num.cos(bazi), num.sin(bazi)))
for islowness, slowness in enumerate(slownesses):
shifts[ishift] = station_vector.dot(s_vector) * slowness
ishift += 1
return shifts
def get_shifts(stations, center_station, bazis, slownesses):
''' shape = (len(bazi), len(slow))'''
lats = num.array([s.lat for s in stations])
lons = num.array([s.lon for s in stations])
lat0 = num.array([center_station.lat] * len(stations))
lon0 = num.array([center_station.lon] * len(stations))
ns, es = ortho.latlon_to_ne_numpy(lat0, lon0, lats, lons)
station_vector = num.array((ns, es)).T
bazis = bazis * d2r
shifts = num.zeros((len(bazis) * len(slownesses), len(stations)))
ishift = 0
for ibazi, bazi in enumerate(bazis):
s_vector = num.array((num.cos(bazi), num.sin(bazi)))
for islowness, slowness in enumerate(slownesses):
shifts[ishift] = station_vector.dot(s_vector) * slowness
ishift += 1
return shifts
def locations_to_ned(self, locations, has_elevation=False):
npoints = len(locations)
lats = num.zeros(npoints)
lons = num.zeros(npoints)
depths = num.zeros(npoints)
for i_e, e in enumerate(locations):
lats[i_e] = float(e.lat)
lons[i_e] = float(e.lon)
if has_elevation:
depths[i_e] = float(e.depth) - float(e.elevation)
else:
depths[i_e] = float(e.depth)
depths *= self.z_scale
nz = num.zeros(npoints)
ns, es = ortho.latlon_to_ne_numpy(nz, nz, lats, lons)
return ns, es, depths
def locations_to_ned(locations, has_elevation=False, z_scale=1.):
npoints = len(locations)
lats = num.zeros(npoints)
lons = num.zeros(npoints)
depths = num.zeros(npoints)
for i_e, e in enumerate(locations):
lats[i_e] = float(e.lat)
lons[i_e] = float(e.lon)
if has_elevation:
depths[i_e] = float(e.depth) - float(e.elevation)
else:
depths[i_e] = float(e.depth)
depths *= z_scale
nz = num.zeros(npoints)
ns, es = ortho.latlon_to_ne_numpy(nz, nz, lats, lons)
return ns, es, depths
def points_coords(points, system=None):
a = num.zeros((len(points), 5))
for ir, r in enumerate(points):
a[ir, :] = r.vec
lats, lons, xs, ys, zs = a.T
if system is None:
return (lats, lons, xs, ys, zs)
elif system == 'latlon':
return od.ne_to_latlon(lats, lons, xs, ys)
elif system[0] == 'ne':
lat0, lon0 = system[1:3]
if num.all(lats == lat0) and num.all(lons == lon0):
return xs, ys
else:
elats, elons = od.ne_to_latlon(lats, lons, xs, ys)
return od.latlon_to_ne_numpy(lat0, lon0, elats, elons)
def pointCDMParameters(self):
if self._sandbox:
east_shift, north_shift = od.latlon_to_ne_numpy(
self._sandbox.frame.llLat, self._sandbox.frame.llLon, self.lat,
self.lon)
else:
east_shift = 0.
north_shift = 0.
params = {
'x0': self.easting + east_shift,
'y0': self.northing + north_shift,
'z0': self.depth,
'rotx': self.rotation_x,
'roty': self.rotation_y,
'rotz': self.rotation_z,
'dVx': self.dVx**3,
'dVy': self.dVy**3,
'dVz': self.dVz**3,
'nu': self.nu
}
return params
def pointCDMParameters(self):
if self._sandbox:
east_shift, north_shift = od.latlon_to_ne_numpy(
self._sandbox.frame.llLat, self._sandbox.frame.llLon, self.lat, self.lon
)
else:
east_shift = 0.0
north_shift = 0.0
params = {
"x0": self.easting + east_shift,
"y0": self.northing + north_shift,
"z0": self.depth,
"rotx": self.rotation_x,
"roty": self.rotation_y,
"rotz": self.rotation_z,
"dVx": self.dVx**3,
"dVy": self.dVy**3,
"dVz": self.dVz**3,
"nu": self.nu,
}
return params
def ECMParameters(self):
if self._sandbox:
east_shift, north_shift = od.latlon_to_ne_numpy(
self._sandbox.frame.llLat, self._sandbox.frame.llLon, self.lat, self.lon
)
else:
east_shift = 0.0
north_shift = 0.0
params = {
"x0": self.easting + east_shift,
"y0": self.northing + north_shift,
"z0": self.depth,
"rotx": self.rotation_x,
"roty": self.rotation_y,
"rotz": self.rotation_z,
"ax": self.length_x,
"ay": self.length_y,
"az": self.length_z,
"P": self.cavity_pressure * 1e9,
"mu": self.mu * 1e9,
"lamda": self.lamda * 1e9,
}
return params
def ECMParameters(self):
if self._sandbox:
east_shift, north_shift = od.latlon_to_ne_numpy(
self._sandbox.frame.llLat, self._sandbox.frame.llLon, self.lat,
self.lon)
else:
east_shift = 0.
north_shift = 0.
params = {
'x0': self.easting + east_shift,
'y0': self.northing + north_shift,
'z0': self.depth,
'rotx': self.rotation_x,
'roty': self.rotation_y,
'rotz': self.rotation_z,
'ax': self.length_x,
'ay': self.length_y,
'az': self.length_z,
'P': self.cavity_pressure * 1e9,
'mu': self.mu * 1e9,
'lamda': self.lamda * 1e9
}
return params
def make_time_line(self, markers, stations=None, cmap=cmap):
events = [m.get_event() for m in markers]
kinds = num.array([m.kind for m in markers])
if self.cli_mode:
self.fig = plt.figure()
else:
fframe = self.figure_frame()
self.fig = fframe.gcf()
ax = self.fig.add_subplot(311)
ax_cum = ax.twinx()
ax1 = self.fig.add_subplot(323)
ax2 = self.fig.add_subplot(325, sharex=ax1)
ax3 = self.fig.add_subplot(324, sharey=ax1)
num_events = len(events)
data = num.zeros((num_events, 6))
column_to_index = dict(zip(['magnitude', 'latitude', 'longitude', 'depth', 'time', 'kind'],
range(6)))
c2i = column_to_index
for i, e in enumerate(events):
if e.magnitude:
mag = e.magnitude
else:
mag = 0.
data[i, :] = mag, e.lat, e.lon, e.depth, e.time, kinds[i]
s_coords = num.array([])
s_labels = []
if stations is not None:
s_coords = num.array([(s.lon, s.lat, s.elevation-s.depth) for s in stations])
s_labels = ['.'.join(s.nsl()) for s in stations]
isorted = num.argsort(data[:, c2i['time']])
data = data[isorted]
def _D(key):
return data[:, c2i[key]]
tmin = _D('time').min()
tmax = _D('time').max()
lon_max = _D('longitude').max()
lon_min = _D('longitude').min()
lat_max = _D('latitude').max()
lat_min = _D('latitude').min()
depths_min = _D('depth').min()
depths_max = _D('depth').max()
mags_min = _D('magnitude').min()
mags_max = _D('magnitude').max()
moments = moment_tensor.magnitude_to_moment(_D('magnitude'))
dates = list(map(datetime.fromtimestamp, _D('time')))
fds = mdates.date2num(dates)
tday = 3600*24
tweek = tday*7
if tmax-tmin < 1*tday:
hfmt = mdates.DateFormatter('%Y-%m-%d %H:%M:%S')
elif tmax-tmin < tweek*52:
hfmt = mdates.DateFormatter('%Y-%m-%d')
else:
hfmt = mdates.DateFormatter('%Y/%m')
color_values = _D(self.color_by)
color_args = dict(c=color_values, vmin=color_values.min(),
vmax=color_values.max(), cmap=cmap)
ax.scatter(fds, _D('magnitude'), s=20, **color_args)
ax.xaxis.set_major_formatter(hfmt)
ax.spines['top'].set_color('none')
ax.spines['right'].set_color('none')
ax.set_ylim((mags_min, mags_max*1.10))
ax.set_xlim(map(datetime.fromtimestamp, (tmin, tmax)))
ax.xaxis.set_ticks_position('bottom')
ax.yaxis.set_ticks_position('left')
ax.set_ylabel('Magnitude')
init_pos = ax.get_position()
ax_cum.plot(fds, num.cumsum(moments), 'grey')
ax_cum.xaxis.set_major_formatter(hfmt)
ax_cum.spines['top'].set_color('none')
ax_cum.spines['right'].set_color('grey')
ax_cum.set_ylabel('Cumulative seismic moment')
lats_min = num.array([lat_min for x in range(num_events)])
lons_min = num.array([lon_min for x in range(num_events)])
if self.coord_system == 'cartesian':
lats, lons = orthodrome.latlon_to_ne_numpy(
lats_min, lons_min, _D('latitude'), _D('longitude'))
_x = num.empty((len(s_coords), 3))
for i, (slon, slat, sele) in enumerate(s_coords):
n, e = orthodrome.latlon_to_ne(lat_min, lon_min, slat, slon)
_x[i, :] = (e, n, sele)
s_coords = _x
else:
lats = _D('latitude')
lons = _D('longitude')
s_coords = s_coords.T
ax1.scatter(lons, lats, s=20, **color_args)
ax1.set_aspect('equal')
ax1.grid(True, which='both')
ax1.set_ylabel('Northing [m]')
ax1.get_yaxis().tick_left()
if len(s_coords):
ax1.scatter(s_coords[0], s_coords[1], marker='v', s=40, color='black')
for c, sl in zip(s_coords.T, s_labels):
ax1.text(c[0], c[1], sl, color='black')
# bottom left plot
ax2.scatter(lons, _D('depth'), s=20, **color_args)
ax2.grid(True)
ax2.set_xlabel('Easting [m]')
ax2.set_ylabel('Depth [m]')
ax2.get_yaxis().tick_left()
ax2.get_xaxis().tick_bottom()
ax2.invert_yaxis()
ax2.text(1.1, 0, 'Origin at:\nlat=%1.3f, lon=%1.3f' %
(lat_min, lon_min), transform=ax2.transAxes)
# top right plot
ax3.scatter(_D('depth'), lats, s=20, **color_args)
ax3.set_xlim((depths_min, depths_max))
ax3.grid(True)
ax3.set_xlabel('Depth [m]')
ax3.get_xaxis().tick_bottom()
ax3.get_yaxis().tick_right()
self.fig.subplots_adjust(
bottom=0.05, right=0.95, left=0.075, top=0.95, wspace=0.02, hspace=0.02)
init_pos.y0 += 0.05
ax.set_position(init_pos)
ax_cum.set_position(init_pos)
if self.cli_mode:
plt.show()
else:
self.fig.canvas.draw()
def draw_static_fits(self, ds, history, optimiser, closeup=False):
from pyrocko.orthodrome import latlon_to_ne_numpy
problem = history.problem
sat_targets = problem.satellite_targets
for target in sat_targets:
target.set_dataset(ds)
source = history.get_best_source()
best_model = history.get_best_model()
results = problem.evaluate(best_model, targets=sat_targets)
def initAxes(ax, scene, title, last_axes=False):
ax.set_title(title)
ax.tick_params(length=2)
if scene.frame.isMeter():
ax.set_xlabel('Easting [km]')
scale_x = {'scale': 1. / km}
scale_y = {'scale': 1. / km}
if not self.relative_coordinates:
import utm
utm_E, utm_N, utm_zone, utm_zone_letter =\
utm.from_latlon(source.effective_lat,
source.effective_lon)
scale_x['offset'] = utm_E
scale_y['offset'] = utm_N
if last_axes:
ax.text(0.975,
0.025,
'UTM Zone %d%s' % (utm_zone, utm_zone_letter),
va='bottom',
ha='right',
fontsize=8,
alpha=.7,
transform=ax.transAxes)
ax.set_aspect('equal')
elif scene.frame.isDegree():
ax.set_xlabel('Lon [°]')
scale_x = {'scale': 1.}
scale_y = {'scale': 1.}
if not self.relative_coordinates:
scale_x['offset'] = source.effective_lon
scale_y['offset'] = source.effective_lat
ax.set_aspect(1. / num.cos(source.effective_lat * d2r))
scale_axes(ax.get_xaxis(), **scale_x)
scale_axes(ax.get_yaxis(), **scale_y)
def drawSource(ax, scene):
if scene.frame.isMeter():
fn, fe = source.outline(cs='xy').T
fn -= fn.mean()
fe -= fe.mean()
elif scene.frame.isDegree():
fn, fe = source.outline(cs='latlon').T
fn -= source.effective_lat
fe -= source.effective_lon
# source is centered
ax.scatter(0., 0., color='black', s=3, alpha=.5, marker='o')
ax.fill(fe,
fn,
edgecolor=(0., 0., 0.),
facecolor=(.5, .5, .5),
alpha=0.7)
ax.plot(fe[0:2], fn[0:2], 'k', linewidth=1.3)
def mapDisplacementGrid(displacements, scene):
arr = num.full_like(scene.displacement, fill_value=num.nan)
qt = scene.quadtree
for syn_v, l in zip(displacements, qt.leaves):
arr[l._slice_rows, l._slice_cols] = syn_v
arr[scene.displacement_mask] = num.nan
return arr
def drawLeaves(ax, scene, offset_e=0., offset_n=0.):
rects = scene.quadtree.getMPLRectangles()
for r in rects:
r.set_edgecolor((.4, .4, .4))
r.set_linewidth(.5)
r.set_facecolor('none')
r.set_x(r.get_x() - offset_e)
r.set_y(r.get_y() - offset_n)
map(ax.add_artist, rects)
ax.scatter(scene.quadtree.leaf_coordinates[:, 0] - offset_e,
scene.quadtree.leaf_coordinates[:, 1] - offset_n,
s=.25,
c='black',
alpha=.1)
def addArrow(ax, scene):
phi = num.nanmean(scene.phi)
los_dx = num.cos(phi + num.pi) * .0625
los_dy = num.sin(phi + num.pi) * .0625
az_dx = num.cos(phi - num.pi / 2) * .125
az_dy = num.sin(phi - num.pi / 2) * .125
anchor_x = .9 if los_dx < 0 else .1
anchor_y = .85 if los_dx < 0 else .975
az_arrow = patches.FancyArrow(x=anchor_x - az_dx,
y=anchor_y - az_dy,
dx=az_dx,
dy=az_dy,
head_width=.025,
alpha=.5,
fc='k',
head_starts_at_zero=False,
length_includes_head=True,
transform=ax.transAxes)
los_arrow = patches.FancyArrow(x=anchor_x - az_dx / 2,
y=anchor_y - az_dy / 2,
dx=los_dx,
dy=los_dy,
head_width=.02,
alpha=.5,
fc='k',
head_starts_at_zero=False,
length_includes_head=True,
transform=ax.transAxes)
ax.add_artist(az_arrow)
ax.add_artist(los_arrow)
urE, urN, llE, llN = (0., 0., 0., 0.)
for target in sat_targets:
if target.scene.frame.isMeter():
off_n, off_e = map(
float,
latlon_to_ne_numpy(target.scene.frame.llLat,
target.scene.frame.llLon,
source.effective_lat,
source.effective_lon))
if target.scene.frame.isDegree():
off_n = source.effective_lat - target.scene.frame.llLat
off_e = source.effective_lon - target.scene.frame.llLon
turE, turN, tllE, tllN = zip(
*[(l.gridE.max() - off_e, l.gridN.max() - off_n,
l.gridE.min() - off_e, l.gridN.min() - off_n)
for l in target.scene.quadtree.leaves])
turE, turN = map(max, (turE, turN))
tllE, tllN = map(min, (tllE, tllN))
urE, urN = map(max, ((turE, urE), (urN, turN)))
llE, llN = map(min, ((tllE, llE), (llN, tllN)))
def generate_plot(sat_target, result, ifig):
scene = sat_target.scene
fig = plt.figure()
fig.set_size_inches(*self.size_inch)
gs = gridspec.GridSpec(2,
3,
wspace=.15,
hspace=.2,
left=.1,
right=.975,
top=.95,
height_ratios=[12, 1])
item = PlotItem(name='fig_%i' % ifig,
attributes={'targets': [sat_target.path]},
title=u'Satellite Surface Displacements - %s' %
scene.meta.scene_title,
description=u'''
Surface displacements derived from satellite data.
(Left) the input data, (center) the modelled
data and (right) the model residual.
'''.format(meta=scene.meta))
stat_obs = result.statics_obs
stat_syn = result.statics_syn['displacement.los']
res = stat_obs - stat_syn
if scene.frame.isMeter():
offset_n, offset_e = map(
float,
latlon_to_ne_numpy(scene.frame.llLat, scene.frame.llLon,
source.effective_lat,
source.effective_lon))
elif scene.frame.isDegree():
offset_n = source.effective_lat - scene.frame.llLat
offset_e = source.effective_lon - scene.frame.llLon
im_extent = (scene.frame.E.min() - offset_e, scene.frame.E.max() -
offset_e, scene.frame.N.min() - offset_n,
scene.frame.N.max() - offset_n)
abs_displ = num.abs([
stat_obs.min(),
stat_obs.max(),
stat_syn.min(),
stat_syn.max(),
res.min(),
res.max()
]).max()
cmw = cm.ScalarMappable(cmap=self.colormap)
cmw.set_clim(vmin=-abs_displ, vmax=abs_displ)
cmw.set_array(stat_obs)
axes = [
fig.add_subplot(gs[0, 0]),
fig.add_subplot(gs[0, 1]),
fig.add_subplot(gs[0, 2])
]
ax = axes[0]
ax.imshow(mapDisplacementGrid(stat_obs, scene),
extent=im_extent,
cmap=self.colormap,
vmin=-abs_displ,
vmax=abs_displ,
origin='lower')
drawLeaves(ax, scene, offset_e, offset_n)
drawSource(ax, scene)
addArrow(ax, scene)
initAxes(ax, scene, 'Observed')
ax.text(.025,
.025,
'Scene ID: %s' % scene.meta.scene_id,
fontsize=8,
alpha=.7,
va='bottom',
transform=ax.transAxes)
if scene.frame.isDegree():
ax.set_ylabel('Lat [°]')
elif scene.frame.isMeter():
ax.set_ylabel('Northing [km]')
ax = axes[1]
ax.imshow(mapDisplacementGrid(stat_syn, scene),
extent=im_extent,
cmap=self.colormap,
vmin=-abs_displ,
vmax=abs_displ,
origin='lower')
drawLeaves(ax, scene, offset_e, offset_n)
drawSource(ax, scene)
addArrow(ax, scene)
initAxes(ax, scene, 'Model')
ax.get_yaxis().set_visible(False)
ax = axes[2]
ax.imshow(mapDisplacementGrid(res, scene),
extent=im_extent,
cmap=self.colormap,
vmin=-abs_displ,
vmax=abs_displ,
origin='lower')
drawLeaves(ax, scene, offset_e, offset_n)
drawSource(ax, scene)
addArrow(ax, scene)
initAxes(ax, scene, 'Residual', last_axes=True)
ax.get_yaxis().set_visible(False)
for ax in axes:
ax.set_xlim(llE, urE)
ax.set_ylim(llN, urN)
if closeup:
if scene.frame.isMeter():
fn, fe = source.outline(cs='xy').T
elif scene.frame.isDegree():
fn, fe = source.outline(cs='latlon').T
fn -= source.effective_lat
fe -= source.effective_lon
if fn.size > 1:
off_n = (fn[0] + fn[1]) / 2
off_e = (fe[0] + fe[1]) / 2
else:
off_n = fn[0]
off_e = fe[0]
fault_size = 2 * num.sqrt(
max(abs(fn - off_n))**2 + max(abs(fe - off_e))**2)
fault_size *= self.map_scale
if fault_size == 0.0:
extent = (scene.frame.N[-1] + scene.frame.E[-1]) / 2
fault_size = extent * .25
for ax in axes:
ax.set_xlim(-fault_size / 2 + off_e,
fault_size / 2 + off_e)
ax.set_ylim(-fault_size / 2 + off_n,
fault_size / 2 + off_n)
cax = fig.add_subplot(gs[1, :])
cbar = fig.colorbar(cmw,
cax=cax,
orientation='horizontal',
use_gridspec=True)
cbar.set_label('LOS Displacement [m]')
return (item, fig)
for ifig, (sat_target, result) in enumerate(zip(sat_targets, results)):
yield generate_plot(sat_target, result, ifig)
def generate_plot(sat_target, result, ifig):
scene = sat_target.scene
fig = plt.figure()
fig.set_size_inches(*self.size_inch)
gs = gridspec.GridSpec(2,
3,
wspace=.15,
hspace=.2,
left=.1,
right=.975,
top=.95,
height_ratios=[12, 1])
item = PlotItem(name='fig_%i' % ifig,
attributes={'targets': [sat_target.path]},
title=u'Satellite Surface Displacements - %s' %
scene.meta.scene_title,
description=u'''
Surface displacements derived from satellite data.
(Left) the input data, (center) the modelled
data and (right) the model residual.
'''.format(meta=scene.meta))
stat_obs = result.statics_obs
stat_syn = result.statics_syn['displacement.los']
res = stat_obs - stat_syn
if scene.frame.isMeter():
offset_n, offset_e = map(
float,
latlon_to_ne_numpy(scene.frame.llLat, scene.frame.llLon,
source.effective_lat,
source.effective_lon))
elif scene.frame.isDegree():
offset_n = source.effective_lat - scene.frame.llLat
offset_e = source.effective_lon - scene.frame.llLon
im_extent = (scene.frame.E.min() - offset_e, scene.frame.E.max() -
offset_e, scene.frame.N.min() - offset_n,
scene.frame.N.max() - offset_n)
abs_displ = num.abs([
stat_obs.min(),
stat_obs.max(),
stat_syn.min(),
stat_syn.max(),
res.min(),
res.max()
]).max()
cmw = cm.ScalarMappable(cmap=self.colormap)
cmw.set_clim(vmin=-abs_displ, vmax=abs_displ)
cmw.set_array(stat_obs)
axes = [
fig.add_subplot(gs[0, 0]),
fig.add_subplot(gs[0, 1]),
fig.add_subplot(gs[0, 2])
]
ax = axes[0]
ax.imshow(mapDisplacementGrid(stat_obs, scene),
extent=im_extent,
cmap=self.colormap,
vmin=-abs_displ,
vmax=abs_displ,
origin='lower')
drawLeaves(ax, scene, offset_e, offset_n)
drawSource(ax, scene)
addArrow(ax, scene)
initAxes(ax, scene, 'Observed')
ax.text(.025,
.025,
'Scene ID: %s' % scene.meta.scene_id,
fontsize=8,
alpha=.7,
va='bottom',
transform=ax.transAxes)
if scene.frame.isDegree():
ax.set_ylabel('Lat [°]')
elif scene.frame.isMeter():
ax.set_ylabel('Northing [km]')
ax = axes[1]
ax.imshow(mapDisplacementGrid(stat_syn, scene),
extent=im_extent,
cmap=self.colormap,
vmin=-abs_displ,
vmax=abs_displ,
origin='lower')
drawLeaves(ax, scene, offset_e, offset_n)
drawSource(ax, scene)
addArrow(ax, scene)
initAxes(ax, scene, 'Model')
ax.get_yaxis().set_visible(False)
ax = axes[2]
ax.imshow(mapDisplacementGrid(res, scene),
extent=im_extent,
cmap=self.colormap,
vmin=-abs_displ,
vmax=abs_displ,
origin='lower')
drawLeaves(ax, scene, offset_e, offset_n)
drawSource(ax, scene)
addArrow(ax, scene)
initAxes(ax, scene, 'Residual', last_axes=True)
ax.get_yaxis().set_visible(False)
for ax in axes:
ax.set_xlim(llE, urE)
ax.set_ylim(llN, urN)
if closeup:
if scene.frame.isMeter():
fn, fe = source.outline(cs='xy').T
elif scene.frame.isDegree():
fn, fe = source.outline(cs='latlon').T
fn -= source.effective_lat
fe -= source.effective_lon
if fn.size > 1:
off_n = (fn[0] + fn[1]) / 2
off_e = (fe[0] + fe[1]) / 2
else:
off_n = fn[0]
off_e = fe[0]
fault_size = 2 * num.sqrt(
max(abs(fn - off_n))**2 + max(abs(fe - off_e))**2)
fault_size *= self.map_scale
if fault_size == 0.0:
extent = (scene.frame.N[-1] + scene.frame.E[-1]) / 2
fault_size = extent * .25
for ax in axes:
ax.set_xlim(-fault_size / 2 + off_e,
fault_size / 2 + off_e)
ax.set_ylim(-fault_size / 2 + off_n,
fault_size / 2 + off_n)
cax = fig.add_subplot(gs[1, :])
cbar = fig.colorbar(cmw,
cax=cax,
orientation='horizontal',
use_gridspec=True)
cbar.set_label('LOS Displacement [m]')
return (item, fig)
def getSandboxOffset(self):
if not self._sandbox or (self.lat == 0.0 and self.lon == 0.0):
return 0.0, 0.0
return od.latlon_to_ne_numpy(
self._sandbox.frame.llLat, self._sandbox.frame.llLon, self.lat, self.lon
)
def test_point_in_polygon(self):
if plot:
from pyrocko.plot import mpl_graph_color
import matplotlib.pyplot as plt
from matplotlib.patches import Polygon
axes = plt.gca()
nip = 100
for i in range(1):
np = 3
points = num.zeros((np, 2))
points[:, 0] = random_lat(size=3)
points[:, 1] = random_lon(size=3)
points_ip = num.zeros((nip*points.shape[0], 2))
for ip in range(points.shape[0]):
n, e = orthodrome.latlon_to_ne_numpy(
points[ip % np, 0], points[ip % np, 1],
points[(ip+1) % np, 0], points[(ip+1) % np, 1])
ns = num.arange(nip) * n / nip
es = num.arange(nip) * e / nip
lats, lons = orthodrome.ne_to_latlon(
points[ip % np, 0], points[ip % np, 1], ns, es)
points_ip[ip*nip:(ip+1)*nip, 0] = lats
points_ip[ip*nip:(ip+1)*nip, 1] = lons
if plot:
color = mpl_graph_color(i)
axes.add_patch(
Polygon(
num.fliplr(points_ip),
facecolor=light(color),
edgecolor=color,
alpha=0.5))
points_xyz = orthodrome.latlon_to_xyz(points_ip.T)
center_xyz = num.mean(points_xyz, axis=0)
assert num.all(
orthodrome.distances3d(
points_xyz, center_xyz[num.newaxis, :]) < 1.0)
lat, lon = orthodrome.xyz_to_latlon(center_xyz)
rot = orthodrome.rot_to_00(lat, lon)
points_rot_xyz = num.dot(rot, points_xyz.T).T
points_rot_pro = orthodrome.stereographic(points_rot_xyz) # noqa
poly_xyz = orthodrome.latlon_to_xyz(points_ip)
poly_rot_xyz = num.dot(rot, poly_xyz.T).T
groups = orthodrome.spoly_cut([poly_rot_xyz], axis=0)
num.zeros(points.shape[0], dtype=num.int)
if plot:
for group in groups:
for poly_rot_group_xyz in group:
axes.set_xlim(-180., 180.)
axes.set_ylim(-90., 90.)
plt.show()
def test_point_in_polygon(self):
if plot:
from pyrocko.plot import mpl_graph_color
import matplotlib.pyplot as plt
from matplotlib.patches import Polygon
axes = plt.gca()
nip = 100
for i in range(1):
np = 3
points = num.zeros((np, 2))
points[:, 0] = random_lat(size=3)
points[:, 1] = random_lon(size=3)
points_ip = num.zeros((nip*points.shape[0], 2))
for ip in range(points.shape[0]):
n, e = orthodrome.latlon_to_ne_numpy(
points[ip % np, 0], points[ip % np, 1],
points[(ip+1) % np, 0], points[(ip+1) % np, 1])
ns = num.arange(nip) * n / nip
es = num.arange(nip) * e / nip
lats, lons = orthodrome.ne_to_latlon(
points[ip % np, 0], points[ip % np, 1], ns, es)
points_ip[ip*nip:(ip+1)*nip, 0] = lats
points_ip[ip*nip:(ip+1)*nip, 1] = lons
if plot:
color = mpl_graph_color(i)
axes.add_patch(
Polygon(
num.fliplr(points_ip),
facecolor=light(color),
edgecolor=color,
alpha=0.5))
points_xyz = orthodrome.latlon_to_xyz(points_ip.T)
center_xyz = num.mean(points_xyz, axis=0)
assert num.all(
orthodrome.distances3d(
points_xyz, center_xyz[num.newaxis, :]) < 1.0)
lat, lon = orthodrome.xyz_to_latlon(center_xyz)
rot = orthodrome.rot_to_00(lat, lon)
points_rot_xyz = num.dot(rot, points_xyz.T).T
points_rot_pro = orthodrome.stereographic(points_rot_xyz) # noqa
poly_xyz = orthodrome.latlon_to_xyz(points_ip)
poly_rot_xyz = num.dot(rot, poly_xyz.T).T
groups = orthodrome.spoly_cut([poly_rot_xyz], axis=0)
num.zeros(points.shape[0], dtype=num.int)
if plot:
for group in groups:
for poly_rot_group_xyz in group:
axes.set_xlim(-180., 180.)
axes.set_ylim(-90., 90.)
plt.show()
def draw_static_fits(self, ds, history, optimiser, closeup=False):
from pyrocko.orthodrome import latlon_to_ne_numpy
problem = history.problem
sat_targets = problem.satellite_targets
for target in sat_targets:
target.set_dataset(ds)
if self.fit == 'best':
source = history.get_best_source()
model = history.get_best_model()
elif self.fit == 'mean':
source = history.get_mean_source()
model = history.get_mean_model()
results = problem.evaluate(model, targets=sat_targets)
def init_axes(ax, scene, title, last_axes=False):
ax.set_title(title, fontsize=self.font_size)
ax.tick_params(length=2)
if scene.frame.isMeter():
import utm
ax.set_xlabel('Easting [km]', fontsize=self.font_size)
scale_x = dict(scale=1./km)
scale_y = dict(scale=1./km)
utm_E, utm_N, utm_zone, utm_zone_letter =\
utm.from_latlon(source.effective_lat,
source.effective_lon)
scale_x['offset'] = utm_E
scale_y['offset'] = utm_N
if last_axes:
ax.text(0.975, 0.025,
'UTM Zone %d%s' % (utm_zone, utm_zone_letter),
va='bottom', ha='right',
fontsize=8, alpha=.7,
transform=ax.transAxes)
ax.set_aspect('equal')
elif scene.frame.isDegree():
scale_x = dict(scale=1., suffix='°')
scale_y = dict(scale=1., suffix='°')
scale_x['offset'] = source.effective_lon
scale_y['offset'] = source.effective_lat
ax.set_aspect(1./num.cos(source.effective_lat*d2r))
if self.relative_coordinates:
scale_x['offset'] = 0.
scale_y['offset'] = 0.
nticks_x = 4 if abs(scene.frame.llLon) >= 100 else 5
ax.xaxis.set_major_locator(MaxNLocator(self.nticks_x or nticks_x))
ax.yaxis.set_major_locator(MaxNLocator(5))
ax.scale_x = scale_x
ax.scale_y = scale_y
scale_axes(ax.get_xaxis(), **scale_x)
scale_axes(ax.get_yaxis(), **scale_y)
def draw_source(ax, scene):
if scene.frame.isMeter():
fn, fe = source.outline(cs='xy').T
fn -= fn.mean()
fe -= fe.mean()
elif scene.frame.isDegree():
fn, fe = source.outline(cs='latlon').T
fn -= source.effective_lat
fe -= source.effective_lon
# source is centered
ax.scatter(0., 0., color='black', s=3, alpha=.5, marker='o')
ax.fill(fe, fn,
edgecolor=(0., 0., 0.),
facecolor=self.source_outline_color,
alpha=0.7)
ax.plot(fe[0:2], fn[0:2], 'k', linewidth=1.3)
def get_displacement_rgba(displacements, scene, mappable):
arr = num.full_like(scene.displacement, fill_value=num.nan)
qt = scene.quadtree
for syn_v, leaf in zip(displacements, qt.leaves):
arr[leaf._slice_rows, leaf._slice_cols] = syn_v
arr[scene.displacement_mask] = num.nan
if not self.common_color_scale \
and not self.displacement_unit == 'rad':
abs_displ = num.abs(displacements).max()
mappable.set_clim(-abs_displ, abs_displ)
if self.show_topo:
try:
elevation = scene.get_elevation()
return drape_displacements(arr, elevation, mappable)
except Exception as e:
logger.warning('could not plot hillshaded topo')
logger.exception(e)
return mappable.to_rgba(arr)
def draw_leaves(ax, scene, offset_e=0., offset_n=0.):
rects = scene.quadtree.getMPLRectangles()
for r in rects:
r.set_edgecolor((.4, .4, .4))
r.set_linewidth(.5)
r.set_facecolor('none')
r.set_x(r.get_x() - offset_e)
r.set_y(r.get_y() - offset_n)
map(ax.add_artist, rects)
if self.show_leaf_centres:
ax.scatter(scene.quadtree.leaf_coordinates[:, 0] - offset_e,
scene.quadtree.leaf_coordinates[:, 1] - offset_n,
s=.25, c='black', alpha=.1)
def add_arrow(ax, scene):
phi = num.nanmean(scene.phi)
los_dx = num.cos(phi + num.pi) * .0625
los_dy = num.sin(phi + num.pi) * .0625
az_dx = num.cos(phi - num.pi/2) * .125
az_dy = num.sin(phi - num.pi/2) * .125
anchor_x = .9 if los_dx < 0 else .1
anchor_y = .85 if los_dx < 0 else .975
az_arrow = patches.FancyArrow(
x=anchor_x-az_dx, y=anchor_y-az_dy,
dx=az_dx, dy=az_dy,
head_width=.025,
alpha=.5, fc='k',
head_starts_at_zero=False,
length_includes_head=True,
transform=ax.transAxes)
los_arrow = patches.FancyArrow(
x=anchor_x-az_dx/2, y=anchor_y-az_dy/2,
dx=los_dx, dy=los_dy,
head_width=.02,
alpha=.5, fc='k',
head_starts_at_zero=False,
length_includes_head=True,
transform=ax.transAxes)
ax.add_artist(az_arrow)
ax.add_artist(los_arrow)
urE, urN, llE, llN = (0., 0., 0., 0.)
for target in sat_targets:
if target.scene.frame.isMeter():
off_n, off_e = map(float, latlon_to_ne_numpy(
target.scene.frame.llLat, target.scene.frame.llLon,
source.effective_lat, source.effective_lon))
if target.scene.frame.isDegree():
off_n = source.effective_lat - target.scene.frame.llLat
off_e = source.effective_lon - target.scene.frame.llLon
turE, turN, tllE, tllN = zip(
*[(leaf.gridE.max()-off_e,
leaf.gridN.max()-off_n,
leaf.gridE.min()-off_e,
leaf.gridN.min()-off_n)
for leaf in target.scene.quadtree.leaves])
turE, turN = map(max, (turE, turN))
tllE, tllN = map(min, (tllE, tllN))
urE, urN = map(max, ((turE, urE), (urN, turN)))
llE, llN = map(min, ((tllE, llE), (llN, tllN)))
def generate_plot(sat_target, result, ifig):
scene = sat_target.scene
fig = plt.figure()
fig.set_size_inches(*self.size_inch)
gs = gridspec.GridSpec(
2, 3,
wspace=.15, hspace=.2,
left=.1, right=.975, top=.95,
height_ratios=[12, 1])
item = PlotItem(
name='fig_%i' % ifig,
attributes={'targets': [sat_target.path]},
title=u'Satellite Surface Displacements - %s'
% scene.meta.scene_title,
description=u'''
Surface displacements derived from satellite data.
(Left) the input data, (center) the modelled
data and (right) the model residual.
''')
stat_obs = result.statics_obs['displacement.los']
stat_syn = result.statics_syn['displacement.los']
res = stat_obs - stat_syn
if scene.frame.isMeter():
offset_n, offset_e = map(float, latlon_to_ne_numpy(
scene.frame.llLat, scene.frame.llLon,
source.effective_lat, source.effective_lon))
elif scene.frame.isDegree():
offset_n = source.effective_lat - scene.frame.llLat
offset_e = source.effective_lon - scene.frame.llLon
im_extent = (
scene.frame.E.min() - offset_e,
scene.frame.E.max() - offset_e,
scene.frame.N.min() - offset_n,
scene.frame.N.max() - offset_n)
if self.displacement_unit == 'rad':
wavelength = scene.meta.wavelength
if wavelength is None:
raise AttributeError(
'The satellite\'s wavelength is not set')
stat_obs = displ2rad(stat_obs, wavelength)
stat_syn = displ2rad(stat_syn, wavelength)
res = displ2rad(res, wavelength)
self.colormap = 'hsv'
data_range = (0., num.pi)
else:
abs_displ = num.abs([stat_obs.min(), stat_obs.max(),
stat_syn.min(), stat_syn.max(),
res.min(), res.max()]).max()
data_range = (-abs_displ, abs_displ)
cmw = cm.ScalarMappable(cmap=self.colormap)
cmw.set_clim(*data_range)
cmw.set_array(stat_obs)
axes = [fig.add_subplot(gs[0, 0]),
fig.add_subplot(gs[0, 1]),
fig.add_subplot(gs[0, 2])]
ax = axes[0]
ax.imshow(
get_displacement_rgba(stat_obs, scene, cmw),
extent=im_extent, origin='lower')
draw_leaves(ax, scene, offset_e, offset_n)
draw_source(ax, scene)
add_arrow(ax, scene)
init_axes(ax, scene, 'Observed')
ax.text(.025, .025, 'Scene ID: %s' % scene.meta.scene_id,
fontsize=8, alpha=.7,
va='bottom', transform=ax.transAxes)
if scene.frame.isMeter():
ax.set_ylabel('Northing [km]', fontsize=self.font_size)
ax = axes[1]
ax.imshow(
get_displacement_rgba(stat_syn, scene, cmw),
extent=im_extent, origin='lower')
draw_leaves(ax, scene, offset_e, offset_n)
draw_source(ax, scene)
add_arrow(ax, scene)
init_axes(ax, scene, 'Model')
ax.get_yaxis().set_visible(False)
ax = axes[2]
ax.imshow(
get_displacement_rgba(res, scene, cmw),
extent=im_extent, origin='lower')
draw_leaves(ax, scene, offset_e, offset_n)
draw_source(ax, scene)
add_arrow(ax, scene)
init_axes(ax, scene, 'Residual', last_axes=True)
ax.get_yaxis().set_visible(False)
for ax in axes:
ax.set_xlim(*im_extent[:2])
ax.set_ylim(*im_extent[2:])
if closeup:
if scene.frame.isMeter():
fn, fe = source.outline(cs='xy').T
elif scene.frame.isDegree():
fn, fe = source.outline(cs='latlon').T
fn -= source.effective_lat
fe -= source.effective_lon
if fn.size > 1:
off_n = (fn[0] + fn[1]) / 2
off_e = (fe[0] + fe[1]) / 2
else:
off_n = fn[0]
off_e = fe[0]
fault_size = 2*num.sqrt(max(abs(fn-off_n))**2
+ max(abs(fe-off_e))**2)
fault_size *= self.map_scale
if fault_size == 0.0:
extent = (scene.frame.N[-1] + scene.frame.E[-1]) / 2
fault_size = extent * .25
for ax in axes:
ax.set_xlim(-fault_size/2 + off_e, fault_size/2 + off_e)
ax.set_ylim(-fault_size/2 + off_n, fault_size/2 + off_n)
if self.map_limits is not None:
xmin, xmax, ymin, ymax = self.map_limits
assert xmin < xmax, 'bad map_limits xmin > xmax'
assert ymin < ymax, 'bad map_limits ymin > ymax'
for ax in axes:
ax.set_xlim(
xmin/ax.scale_x['scale'] - ax.scale_x['offset'],
xmax/ax.scale_x['scale'] - ax.scale_x['offset'],)
ax.set_ylim(
ymin/ax.scale_y['scale'] - ax.scale_y['offset'],
ymax/ax.scale_y['scale'] - ax.scale_y['offset'])
if self.displacement_unit == 'm':
def cfmt(x, p):
return '%.2f' % x
elif self.displacement_unit == 'cm':
def cfmt(x, p):
return '%.1f' % (x * 1e2)
elif self.displacement_unit == 'mm':
def cfmt(x, p):
return '%.0f' % (x * 1e3)
elif self.displacement_unit == 'rad':
def cfmt(x, p):
return '%.2f' % x
else:
raise AttributeError(
'unknown displacement unit %s' % self.displacement_unit)
cbar_args = dict(
orientation='horizontal',
format=FuncFormatter(cfmt),
use_gridspec=True)
cbar_label = 'LOS Displacement [%s]' % self.displacement_unit
if self.common_color_scale:
cax = fig.add_subplot(gs[1, 1])
cax.set_aspect(.05)
cbar = fig.colorbar(cmw, cax=cax, **cbar_args)
cbar.set_label(cbar_label)
else:
for idata, data in enumerate((stat_syn, stat_obs, res)):
cax = fig.add_subplot(gs[1, idata])
cax.set_aspect(.05)
if not self.displacement_unit == 'rad':
abs_displ = num.abs(data).max()
cmw.set_clim(-abs_displ, abs_displ)
cbar = fig.colorbar(cmw, cax=cax, **cbar_args)
cbar.set_label(cbar_label)
return (item, fig)
for ifig, (sat_target, result) in enumerate(zip(sat_targets, results)):
yield generate_plot(sat_target, result, ifig)
def process(self,
event,
timing,
bazi=None,
slow=None,
restitute=False,
*args,
**kwargs):
'''
:param timing: CakeTiming. Uses the definition without the offset.
:param fn_dump_center: filename to where center stations shall be dumped
:param fn_beam: filename of beam trace
:param model: earthmodel to use(optional)
:param earthmodel to use(optional)
:param network: network code(optional)
:param station: station code(optional)
'''
logger.debug('start beam forming')
stations = self.stations
network_code = kwargs.get('responses', None)
network_code = kwargs.get('network', '')
station_code = kwargs.get('station', 'STK')
c_station_id = (network_code, station_code)
t_shifts = []
lat_c, lon_c, z_c = self.c_lat_lon_z
self.station_c = Station(lat=float(lat_c),
lon=float(lon_c),
elevation=float(z_c),
depth=0.,
name='Array Center',
network=c_station_id[0],
station=c_station_id[1][:5])
fn_dump_center = kwargs.get('fn_dump_center', 'array_center.pf')
fn_beam = kwargs.get('fn_beam', 'beam.mseed')
if event:
mod = cake.load_model(crust2_profile=(event.lat, event.lon))
dist = ortho.distance_accurate50m(event, self.station_c)
ray = timing.t(mod, (event.depth, dist), get_ray=True)
if ray is None:
logger.error(
'None of defined phases available at beam station:\n %s' %
self.station_c)
return
else:
b = ortho.azimuth(self.station_c, event)
if b >= 0.:
self.bazi = b
elif b < 0.:
self.bazi = 360. + b
self.slow = ray.p / (cake.r2d * cake.d2m)
else:
self.bazi = bazi
self.slow = slow
logger.info(
'stacking %s with slowness %1.4f s/km at back azimut %1.1f '
'degrees' %
('.'.join(c_station_id), self.slow * cake.km, self.bazi))
lat0 = num.array([lat_c] * len(stations))
lon0 = num.array([lon_c] * len(stations))
lats = num.array([s.lat for s in stations])
lons = num.array([s.lon for s in stations])
ns, es = ortho.latlon_to_ne_numpy(lat0, lon0, lats, lons)
theta = num.float(self.bazi * num.pi / 180.)
R = num.array([[num.cos(theta), -num.sin(theta)],
[num.sin(theta), num.cos(theta)]])
distances = R.dot(num.vstack((es, ns)))[1]
channels = set()
self.stacked = {}
num_stacked = {}
self.t_shifts = {}
self.shifted_traces = []
taperer = trace.CosFader(xfrac=0.05)
if self.diff_dt_treat == 'downsample':
self.traces.sort(key=lambda x: x.deltat)
elif self.diff_dt_treat == 'oversample':
dts = [t.deltat for t in self.traces]
for tr in self.traces:
tr.resample(min(dts))
for tr in self.traces:
if tr.nslc_id[:2] == c_station_id:
continue
tr = tr.copy(data=True)
tr.ydata = tr.ydata.astype(
num.float64) - tr.ydata.mean(dtype=num.float64)
tr.taper(taperer)
try:
stack_trace = self.stacked[tr.channel]
num_stacked[tr.channel] += 1
except KeyError:
stack_trace = tr.copy(data=True)
stack_trace.set_ydata(num.zeros(len(stack_trace.get_ydata())))
stack_trace.set_codes(network=c_station_id[0],
station=c_station_id[1],
location='',
channel=tr.channel)
self.stacked[tr.channel] = stack_trace
channels.add(tr.channel)
num_stacked[tr.channel] = 1
nslc_id = tr.nslc_id
try:
stats = list(
filter(
lambda x: util.match_nslc('%s.%s.%s.*' % x.nsl(),
nslc_id), stations))
stat = stats[0]
except IndexError:
break
i = stations.index(stat)
d = distances[i]
t_shift = d * self.slow
t_shifts.append(t_shift)
tr.shift(t_shift)
self.t_shifts[tr.nslc_id[:2]] = t_shift
if self.normalize_std:
tr.ydata = tr.ydata / tr.ydata.std()
if num.abs(tr.deltat - stack_trace.deltat) > 0.000001:
if self.diff_dt_treat == 'downsample':
stack_trace.downsample_to(tr.deltat)
elif self.diff_dt_treat == 'upsample':
raise Exception(
'something went wrong with the upsampling, previously')
stack_trace.add(tr)
self.shifted_traces.append(tr)
if self.post_normalize:
for ch, tr in self.stacked.items():
tr.set_ydata(tr.get_ydata() / num_stacked[ch])
self.save_station(fn_dump_center)
self.checked_nslc([stack_trace])
self.save(stack_trace, fn_beam)
return self.shifted_traces, stack_trace, t_shifts
def call(self):
self.cleanup()
c_station_id = ('_', 'STK')
if self.unit == 's/deg':
slow_factor = 1. / onedeg
elif self.unit == 's/km':
slow_factor = 1. / 1000.
slow = self.slow * slow_factor
if self.stacked_traces is not None:
self.add_traces(self.stacked_traces)
viewer = self.get_viewer()
if self.station_c:
viewer.stations.pop(c_station_id)
stations = self.get_stations()
if len(stations) == 0:
self.fail('No station meta information found')
traces = list(self.chopper_selected_traces(fallback=True))
traces = [tr for trs in traces for tr in trs]
visible_nslcs = [tr.nslc_id for tr in traces]
stations = [
x for x in stations
if util.match_nslcs("%s.%s.%s.*" % x.nsl(), visible_nslcs)
]
if not self.lat_c or not self.lon_c or not self.z_c:
self.lat_c, self.lon_c, self.z_c = self.center_lat_lon(stations)
self.set_parameter('lat_c', self.lat_c)
self.set_parameter('lon_c', self.lon_c)
self.station_c = Station(lat=float(self.lat_c),
lon=float(self.lon_c),
elevation=float(self.z_c),
depth=0.,
name='Array Center',
network=c_station_id[0],
station=c_station_id[1])
viewer.add_stations([self.station_c])
lat0 = num.array([self.lat_c] * len(stations))
lon0 = num.array([self.lon_c] * len(stations))
lats = num.array([s.lat for s in stations])
lons = num.array([s.lon for s in stations])
ns, es = ortho.latlon_to_ne_numpy(lat0, lon0, lats, lons)
theta = num.float(self.bazi * num.pi / 180.)
R = num.array([[num.cos(theta), -num.sin(theta)],
[num.sin(theta), num.cos(theta)]])
distances = R.dot(num.vstack((es, ns)))[1]
channels = set()
self.stacked = {}
num_stacked = {}
self.t_shifts = {}
shifted_traces = []
taperer = trace.CosFader(xfrac=0.05)
if self.diff_dt_treat == 'downsample':
traces.sort(key=lambda x: x.deltat)
elif self.diff_dt_treat == 'oversample':
dts = [t.deltat for t in traces]
for tr in traces:
tr.resample(min(dts))
for tr in traces:
if tr.nslc_id[:2] == c_station_id:
continue
tr = tr.copy(data=True)
tr.ydata = tr.ydata.astype(num.float64)
tr.ydata -= tr.ydata.mean(dtype=num.float64)
tr.taper(taperer)
try:
stack_trace = self.stacked[tr.channel]
num_stacked[tr.channel] += 1
except KeyError:
stack_trace = tr.copy(data=True)
stack_trace.set_ydata(num.zeros(len(stack_trace.get_ydata())))
stack_trace.set_codes(network=c_station_id[0],
station=c_station_id[1],
location='',
channel=tr.channel)
self.stacked[tr.channel] = stack_trace
channels.add(tr.channel)
num_stacked[tr.channel] = 1
nslc_id = tr.nslc_id
try:
stats = [
x for x in stations
if util.match_nslc('%s.%s.%s.*' % x.nsl(), nslc_id)
]
stat = stats[0]
except IndexError:
break
i = stations.index(stat)
d = distances[i]
t_shift = d * slow
tr.shift(t_shift)
stat = viewer.get_station(tr.nslc_id[:2])
self.t_shifts[stat] = t_shift
if self.normalize_std:
tr.ydata = tr.ydata / tr.ydata.std()
if num.abs(tr.deltat - stack_trace.deltat) > 0.000001:
if self.diff_dt_treat == 'downsample':
stack_trace.downsample_to(tr.deltat)
elif self.diff_dt_treat == 'upsample':
print(
'something went wrong with the upsampling, previously')
stack_trace.add(tr)
if self.add_shifted:
tr.set_station('%s_s' % tr.station)
shifted_traces.append(tr)
if self.post_normalize:
for ch, tr in self.stacked.items():
tr.set_ydata(tr.get_ydata() / num_stacked[ch])
self.cleanup()
for ch, tr in self.stacked.items():
if num_stacked[ch] > 1:
self.add_trace(tr)
if self.add_shifted:
self.add_traces(shifted_traces)
def process(self, event, timing, bazi=None, slow=None, restitute=False, *args, **kwargs):
'''
:param timing: CakeTiming. Uses the definition without the offset.
:param fn_dump_center: filename to where center stations shall be dumped
:param fn_beam: filename of beam trace
:param model: earthmodel to use (optional)
:param earthmodel to use (optional)
:param network: network code (optional)
:param station: station code (optional)
'''
logger.debug('start beam forming')
stations = self.stations
network_code = kwargs.get('responses', None)
network_code = kwargs.get('network', '')
station_code = kwargs.get('station', 'STK')
c_station_id = (network_code, station_code)
lat_c, lon_c, z_c = self.c_lat_lon_z
self.station_c = Station(lat=float(lat_c),
lon=float(lon_c),
elevation=float(z_c),
depth=0.,
name='Array Center',
network=c_station_id[0],
station=c_station_id[1][:5])
fn_dump_center = kwargs.get('fn_dump_center', 'array_center.pf')
fn_beam = kwargs.get('fn_beam', 'beam.mseed')
if event:
mod = cake.load_model(crust2_profile=(event.lat, event.lon))
dist = ortho.distance_accurate50m(event, self.station_c)
ray = timing.t(mod, (event.depth, dist), get_ray=True)
if ray is None:
logger.error('None of defined phases available at beam station:\n %s' % self.station_c)
return
else:
b = ortho.azimuth(self.station_c, event)
if b>=0.:
self.bazi = b
elif b<0.:
self.bazi = 360.+b
self.slow = ray.p/(cake.r2d*cake.d2m)
else:
self.bazi = bazi
self.slow = slow
logger.info('stacking %s with slowness %1.4f s/km at back azimut %1.1f '
'degrees' %('.'.join(c_station_id), self.slow*cake.km, self.bazi))
lat0 = num.array([lat_c]*len(stations))
lon0 = num.array([lon_c]*len(stations))
lats = num.array([s.lat for s in stations])
lons = num.array([s.lon for s in stations])
ns, es = ortho.latlon_to_ne_numpy(lat0, lon0, lats, lons)
theta = num.float(self.bazi*num.pi/180.)
R = num.array([[num.cos(theta), -num.sin(theta)],
[num.sin(theta), num.cos(theta)]])
distances = R.dot(num.vstack((es, ns)))[1]
channels = set()
self.stacked = {}
num_stacked = {}
self.t_shifts = {}
self.shifted_traces = []
taperer = trace.CosFader(xfrac=0.05)
if self.diff_dt_treat=='downsample':
self.traces.sort(key=lambda x: x.deltat)
elif self.diff_dt_treat=='oversample':
dts = [t.deltat for t in self.traces]
for tr in self.traces:
tr.resample(min(dts))
for tr in self.traces:
if tr.nslc_id[:2] == c_station_id:
continue
tr = tr.copy(data=True)
tr.ydata = tr.ydata.astype(num.float64) - tr.ydata.mean(dtype=num.float64)
tr.taper(taperer)
try:
stack_trace = self.stacked[tr.channel]
num_stacked[tr.channel] += 1
except KeyError:
stack_trace = tr.copy(data=True)
stack_trace.set_ydata(num.zeros(
len(stack_trace.get_ydata())))
stack_trace.set_codes(network=c_station_id[0],
station=c_station_id[1],
location='',
channel=tr.channel)
self.stacked[tr.channel] = stack_trace
channels.add(tr.channel)
num_stacked[tr.channel] = 1
nslc_id = tr.nslc_id
try:
stats = filter(lambda x: util.match_nslc(
'%s.%s.%s.*' % x.nsl(), nslc_id), stations)
stat = stats[0]
except IndexError:
break
i = stations.index(stat)
d = distances[i]
t_shift = d*self.slow
tr.shift(t_shift)
#stat = viewer.get_station(tr.nslc_id[:2])
self.t_shifts[tr.nslc_id[:2]] = t_shift
if self.normalize_std:
tr.ydata = tr.ydata/tr.ydata.std()
if num.abs(tr.deltat-stack_trace.deltat)>0.000001:
if self.diff_dt_treat=='downsample':
stack_trace.downsample_to(tr.deltat)
elif self.diff_dt_treat=='upsample':
raise Exception('something went wrong with the upsampling, previously')
stack_trace.add(tr)
tr.set_station('%s_s' % tr.station)
self.shifted_traces.append(tr)
if self.post_normalize:
for ch, tr in self.stacked.items():
tr.set_ydata(tr.get_ydata()/num_stacked[ch])
#for ch, tr in self.stacked.items():
# if num_stacked[ch]>1:
# self.add_trace(tr)
self.save_station(fn_dump_center)
self.checked_nslc([stack_trace])
self.save(stack_trace, fn_beam)
def generate_plot(sat_target, result, ifig):
scene = sat_target.scene
fig = plt.figure()
fig.set_size_inches(*self.size_inch)
gs = gridspec.GridSpec(
2, 3,
wspace=.15, hspace=.2,
left=.1, right=.975, top=.95,
height_ratios=[12, 1])
item = PlotItem(
name='fig_%i' % ifig,
attributes={'targets': [sat_target.path]},
title=u'Satellite Surface Displacements - %s'
% scene.meta.scene_title,
description=u'''
Surface displacements derived from satellite data.
(Left) the input data, (center) the modelled
data and (right) the model residual.
''')
stat_obs = result.statics_obs['displacement.los']
stat_syn = result.statics_syn['displacement.los']
res = stat_obs - stat_syn
if scene.frame.isMeter():
offset_n, offset_e = map(float, latlon_to_ne_numpy(
scene.frame.llLat, scene.frame.llLon,
source.effective_lat, source.effective_lon))
elif scene.frame.isDegree():
offset_n = source.effective_lat - scene.frame.llLat
offset_e = source.effective_lon - scene.frame.llLon
im_extent = (
scene.frame.E.min() - offset_e,
scene.frame.E.max() - offset_e,
scene.frame.N.min() - offset_n,
scene.frame.N.max() - offset_n)
if self.displacement_unit == 'rad':
wavelength = scene.meta.wavelength
if wavelength is None:
raise AttributeError(
'The satellite\'s wavelength is not set')
stat_obs = displ2rad(stat_obs, wavelength)
stat_syn = displ2rad(stat_syn, wavelength)
res = displ2rad(res, wavelength)
self.colormap = 'hsv'
data_range = (0., num.pi)
else:
abs_displ = num.abs([stat_obs.min(), stat_obs.max(),
stat_syn.min(), stat_syn.max(),
res.min(), res.max()]).max()
data_range = (-abs_displ, abs_displ)
cmw = cm.ScalarMappable(cmap=self.colormap)
cmw.set_clim(*data_range)
cmw.set_array(stat_obs)
axes = [fig.add_subplot(gs[0, 0]),
fig.add_subplot(gs[0, 1]),
fig.add_subplot(gs[0, 2])]
ax = axes[0]
ax.imshow(
get_displacement_rgba(stat_obs, scene, cmw),
extent=im_extent, origin='lower')
draw_leaves(ax, scene, offset_e, offset_n)
draw_source(ax, scene)
add_arrow(ax, scene)
init_axes(ax, scene, 'Observed')
ax.text(.025, .025, 'Scene ID: %s' % scene.meta.scene_id,
fontsize=8, alpha=.7,
va='bottom', transform=ax.transAxes)
if scene.frame.isMeter():
ax.set_ylabel('Northing [km]', fontsize=self.font_size)
ax = axes[1]
ax.imshow(
get_displacement_rgba(stat_syn, scene, cmw),
extent=im_extent, origin='lower')
draw_leaves(ax, scene, offset_e, offset_n)
draw_source(ax, scene)
add_arrow(ax, scene)
init_axes(ax, scene, 'Model')
ax.get_yaxis().set_visible(False)
ax = axes[2]
ax.imshow(
get_displacement_rgba(res, scene, cmw),
extent=im_extent, origin='lower')
draw_leaves(ax, scene, offset_e, offset_n)
draw_source(ax, scene)
add_arrow(ax, scene)
init_axes(ax, scene, 'Residual', last_axes=True)
ax.get_yaxis().set_visible(False)
for ax in axes:
ax.set_xlim(*im_extent[:2])
ax.set_ylim(*im_extent[2:])
if closeup:
if scene.frame.isMeter():
fn, fe = source.outline(cs='xy').T
elif scene.frame.isDegree():
fn, fe = source.outline(cs='latlon').T
fn -= source.effective_lat
fe -= source.effective_lon
if fn.size > 1:
off_n = (fn[0] + fn[1]) / 2
off_e = (fe[0] + fe[1]) / 2
else:
off_n = fn[0]
off_e = fe[0]
fault_size = 2*num.sqrt(max(abs(fn-off_n))**2
+ max(abs(fe-off_e))**2)
fault_size *= self.map_scale
if fault_size == 0.0:
extent = (scene.frame.N[-1] + scene.frame.E[-1]) / 2
fault_size = extent * .25
for ax in axes:
ax.set_xlim(-fault_size/2 + off_e, fault_size/2 + off_e)
ax.set_ylim(-fault_size/2 + off_n, fault_size/2 + off_n)
if self.map_limits is not None:
xmin, xmax, ymin, ymax = self.map_limits
assert xmin < xmax, 'bad map_limits xmin > xmax'
assert ymin < ymax, 'bad map_limits ymin > ymax'
for ax in axes:
ax.set_xlim(
xmin/ax.scale_x['scale'] - ax.scale_x['offset'],
xmax/ax.scale_x['scale'] - ax.scale_x['offset'],)
ax.set_ylim(
ymin/ax.scale_y['scale'] - ax.scale_y['offset'],
ymax/ax.scale_y['scale'] - ax.scale_y['offset'])
if self.displacement_unit == 'm':
def cfmt(x, p):
return '%.2f' % x
elif self.displacement_unit == 'cm':
def cfmt(x, p):
return '%.1f' % (x * 1e2)
elif self.displacement_unit == 'mm':
def cfmt(x, p):
return '%.0f' % (x * 1e3)
elif self.displacement_unit == 'rad':
def cfmt(x, p):
return '%.2f' % x
else:
raise AttributeError(
'unknown displacement unit %s' % self.displacement_unit)
cbar_args = dict(
orientation='horizontal',
format=FuncFormatter(cfmt),
use_gridspec=True)
cbar_label = 'LOS Displacement [%s]' % self.displacement_unit
if self.common_color_scale:
cax = fig.add_subplot(gs[1, 1])
cax.set_aspect(.05)
cbar = fig.colorbar(cmw, cax=cax, **cbar_args)
cbar.set_label(cbar_label)
else:
for idata, data in enumerate((stat_syn, stat_obs, res)):
cax = fig.add_subplot(gs[1, idata])
cax.set_aspect(.05)
if not self.displacement_unit == 'rad':
abs_displ = num.abs(data).max()
cmw.set_clim(-abs_displ, abs_displ)
cbar = fig.colorbar(cmw, cax=cax, **cbar_args)
cbar.set_label(cbar_label)
return (item, fig)
def call(self):
self.cleanup()
if self.stacked_traces is not None:
self.add_traces(self.stacked_traces)
viewer = self.get_viewer()
if self.station_c:
viewer.stations.pop(('', 'STK'))
stations = self.get_stations()
if not self.lat_c or not self.lon_c or not self.z_c:
self.lat_c, self.lon_c, self.z_c = self.center_lat_lon(stations)
self.set_parameter('lat_c', self.lat_c)
self.set_parameter('lon_c', self.lon_c)
self.station_c = Station(lat=float(self.lat_c),
lon=float(self.lon_c),
elevation=float(self.z_c),
depth=0.,
name='Array Center',
network='',
station='STK')
viewer.add_stations([self.station_c])
lat0 = num.array([self.lat_c]*len(stations))
lon0 = num.array([self.lon_c]*len(stations))
lats = num.array([s.lat for s in stations])
lons = num.array([s.lon for s in stations])
ns, es = ortho.latlon_to_ne_numpy(lat0, lon0, lats, lons)
theta = num.float(self.bazi*num.pi/180.)
R = num.array([[num.cos(theta), -num.sin(theta)],
[num.sin(theta), num.cos(theta)]])
distances = R.dot(num.vstack((es, ns)))[1]
channels = set()
self.stacked = {}
num_stacked = {}
self.t_shifts = {}
shifted_traces = []
traces = list(self.chopper_selected_traces(fallback=True))
traces = [tr for trs in traces for tr in trs ]
taperer = trace.CosFader(xfrac=0.05)
if self.diff_dt_treat=='downsample':
traces.sort(key=lambda x: x.deltat)
elif self.diff_dt_treat=='oversample':
dts = [t.deltat for t in traces]
for tr in traces:
tr.resample(min(dts))
for tr in traces:
if tr.nslc_id[:3] == ('_', 'STK', ''):
continue
tr = tr.copy(data=True)
tr.ydata = tr.ydata.astype(num.float64)
tr.ydata -= tr.ydata.mean(dtype=num.float64)
tr.taper(taperer)
try:
stack_trace = self.stacked[tr.channel]
num_stacked[tr.channel] += 1
except KeyError:
stack_trace = tr.copy(data=True)
stack_trace.set_ydata(num.zeros(
len(stack_trace.get_ydata())))
stack_trace.set_codes(network='_',
station='STK',
location='',
channel=tr.channel)
self.stacked[tr.channel] = stack_trace
channels.add(tr.channel)
num_stacked[tr.channel] = 1
nslc_id = tr.nslc_id
try:
stats = filter(lambda x: util.match_nslc(
'%s.%s.%s.*' % x.nsl(), nslc_id), stations)
stat = stats[0]
except IndexError:
break
i = stations.index(stat)
d = distances[i]
t_shift = d*self.slow/1000.
tr.shift(t_shift)
stat = viewer.get_station(tr.nslc_id[:2])
self.t_shifts[stat] = t_shift
if self.normalize_std:
tr.ydata = tr.ydata/tr.ydata.std()
if num.abs(tr.deltat-stack_trace.deltat)>0.000001:
if self.diff_dt_treat=='downsample':
stack_trace.downsample_to(tr.deltat)
elif self.diff_dt_treat=='upsample':
print 'something went wrong with the upsampling, previously'
stack_trace.add(tr)
if self.add_shifted:
tr.set_station('%s_s' % tr.station)
shifted_traces.append(tr)
if self.post_normalize:
for ch, tr in self.stacked.items():
tr.set_ydata(tr.get_ydata()/num_stacked[ch])
self.stacked_traces = self.stacked.values()
self.cleanup()
self.add_traces(self.stacked_traces)
if self.add_shifted:
self.add_traces(shifted_traces)
import numpy as num
from pyrocko import topo, plot, orthodrome as od
lon_min, lon_max, lat_min, lat_max = 14.34, 14.50, 40.77, 40.87
dem_name = 'SRTMGL3'
# extract gridded topography (possibly downloading first)
tile = topo.get(dem_name, (lon_min, lon_max, lat_min, lat_max))
# geographic to local cartesian coordinates
lons = tile.x()
lats = tile.y()
lons2 = num.tile(lons, lats.size)
lats2 = num.repeat(lats, lons.size)
norths, easts = od.latlon_to_ne_numpy(lats[0], lons[0], lats2, lons2)
norths = norths.reshape((lats.size, lons.size))
easts = easts.reshape((lats.size, lons.size))
# plot it
plt = plot.mpl_init(fontsize=10.)
fig = plt.figure(figsize=plot.mpl_papersize('a5', 'landscape'))
axes = fig.add_subplot(1, 1, 1, aspect=1.0)
cbar = axes.pcolormesh(easts, norths, tile.data,
cmap='gray', shading='gouraud')
fig.colorbar(cbar, label='Altitude [m]')
axes.set_title(dem_name)
axes.set_xlim(easts.min(), easts.max())
axes.set_ylim(norths.min(), norths.max())
axes.set_xlabel('Easting [m]')
axes.set_ylabel('Northing [m]')
fig.savefig('topo_example.png')
def get_scenario(engine, source, store_id, extent=30, ngrid=40, stations=None):
'''
Setup scenario with source model, STF and a rectangular grid of targets.
'''
# physical grid size in [m]
grid_extent = extent * km
lat, lon = source.lat, source.lon
# number of grid points
nnorth = neast = ngrid
try:
stf_spec = BruneResponse(duration=source.duration)
except AttributeError:
stf_spec = BruneResponse(duration=0.5)
store = engine.get_store(store_id)
if stations is None:
# receiver grid
r = grid_extent / 2.0
norths = num.linspace(-r, r, nnorth)
easts = num.linspace(-r, r, neast)
norths2, easts2 = coords_2d(norths, easts)
targets = []
for i in range(norths2.size):
for component in 'ZNE':
target = gf.Target(quantity='displacement',
codes=('', '%04i' % i, '', component),
lat=lat,
lon=lon,
north_shift=float(norths2[i]),
east_shift=float(easts2[i]),
store_id=store_id,
interpolation='nearest_neighbor')
# in case we have not calculated GFs for zero distance
if source.distance_to(target) >= store.config.distance_min:
targets.append(target)
else:
targets = []
norths = []
easts = []
# here maybe use common ne frame?
for i, st in enumerate(stations):
north, east = orthodrome.latlon_to_ne_numpy(
lat,
lon,
st.lat,
st.lon,
)
norths.append(north[0])
easts.append(east[0])
norths2, easts2 = coords_2d(north, east)
for cha in st.channels:
target = gf.Target(quantity='displacement',
codes=(str(st.network), i, str(st.location),
str(cha.name)),
lat=lat,
lon=lon,
north_shift=float(norths2),
east_shift=float(easts2),
store_id=store_id,
interpolation='nearest_neighbor')
# in case we have not calculated GFs for zero distance
if source.distance_to(target) >= store.config.distance_min:
targets.append(target)
norths = num.asarray(norths)
easts = num.asarray(easts)
return targets, norths, easts, stf_spec