def mogi_deformation(shape,
source_geom,
resolution=60.,
scale=1.,
display=True):
"""Simulate 2D deformation caused by the overpress of a Mogi source underneath
Parameters: shape: 2-tuple of int in (length, width) or 2D np.ndarray in size of (length, width) in np.bool_
source_geom : 4-tuple of float, Mogi source geometry: East, North, Depth, Volomn change in SI unit.
"""
if isinstance(shape, np.ndarray):
mask = np.multiply(np.array(shape != 0), ~np.isnan(shape))
shape = mask.shape
else:
mask = np.ones(shape, np.bool_)
length, width = shape
yy, xx = np.mgrid[0:length:length * 1j, 0:width:width * 1j]
yy *= resolution
xx *= resolution
xloc = np.vstack((xx.reshape(1, -1), yy.reshape(1, -1)))
dis_map = mogi(source_geom, xloc)[0]
dis_e = dis_map[0, :].reshape(length, width)
dis_n = dis_map[1, :].reshape(length, width)
dis_u = dis_map[2, :].reshape(length, width)
dis_los = ut.enu2los(dis_e, dis_n, dis_u)
dis_los[mask == 0.] = np.nan
dis_los *= scale
if display:
fig, ax = plt.subplots(1, 4, figsize=[10, 3], sharey=True)
dmin = np.nanmin(dis_los)
dmax = np.nanmax(dis_los)
for i, fig_title in enumerate(['east', 'north', 'vertical']):
ax[i].imshow(dis_map[i, :].reshape(length, width),
vmin=dmin,
vmax=dmax)
ax[i].set_title(fig_title)
im = ax[3].imshow(dis_los, vmin=dmin, vmax=dmax)
ax[3].set_title('los - SenD')
fig.subplots_adjust(right=0.90)
cax = fig.add_axes([0.92, 0.25, 0.01, 0.5])
cbar = fig.colorbar(im, cax=cax)
cbar.set_label('Displacement [m]')
plt.show()
return dis_los
def cgps_process(gpsname, geometry):
"""process single gps site"""
gps_obj = CGPS(site=gpsname)
gps_obj.open()
if not geometry:
vel_los = ut.enu2los(gps_obj.vel_e, gps_obj.vel_n, gps_obj.vel_u)
los_vel = vel_los
else:
gps_obj.read_gps_los_velocity(geometry)
los_vel = gps_obj.vel_los
site_inve = np.array([[
gps_obj.site, gps_obj.site_lat, gps_obj.site_lon, los_vel,
gps_obj.vel_n, gps_obj.vel_e
]])
return site_inve
def mogi_deformation(shape, source_geom, resolution=60., scale=1., display=True):
"""Simulate 2D deformation caused by the overpress of a Mogi source underneath
Parameters: shape: 2-tuple of int in (length, width) or 2D np.ndarray in size of (length, width) in np.bool_
source_geom : 4-tuple of float, Mogi source geometry: East, North, Depth, Volomn change in SI unit.
"""
if isinstance(shape, np.ndarray):
mask = np.multiply(np.array(shape != 0), ~np.isnan(shape))
shape = mask.shape
else:
mask = np.ones(shape, np.bool_)
length, width = shape
yy, xx = np.mgrid[0:length:length*1j, 0:width:width*1j]
yy *= resolution
xx *= resolution
xloc = np.vstack((xx.reshape(1, -1), yy.reshape(1, -1)))
dis_map = mogi(source_geom, xloc)[0]
dis_e = dis_map[0, :].reshape(length, width)
dis_n = dis_map[1, :].reshape(length, width)
dis_u = dis_map[2, :].reshape(length, width)
dis_los = ut.enu2los(dis_e, dis_n, dis_u)
dis_los[mask == 0.] = np.nan
dis_los *= scale
if display:
fig, ax = plt.subplots(1, 4, figsize=[10, 3], sharey=True)
dmin = np.nanmin(dis_los)
dmax = np.nanmax(dis_los)
for i, fig_title in enumerate(['east','north','vertical']):
ax[i].imshow(dis_map[i, :].reshape(length, width), vmin=dmin, vmax=dmax)
ax[i].set_title(fig_title)
im = ax[3].imshow(dis_los, vmin=dmin, vmax=dmax)
ax[3].set_title('los - SenD')
fig.subplots_adjust(right=0.90)
cax = fig.add_axes([0.92, 0.25, 0.01, 0.5])
cbar = fig.colorbar(im, cax=cax)
cbar.set_label('Displacement [m]')
plt.show()
return dis_los
def ngps_process(gpsname, geometry, gps_dir):
"""process ngps sites"""
gps_obj = GPS(site=gpsname, data_dir=gps_dir)
print('process {} site'.format(gpsname))
gps_obj.open()
if not geometry:
dis_los = ut.enu2los(gps_obj.dis_e, gps_obj.dis_n, gps_obj.dis_u)
dates = gps_obj.dates
los_vel = dis_velocity(dates, dis_los)
else:
dates, dis_los = gps_obj.read_gps_los_displacement(geometry)
gps_obj.get_gps_los_velocity(geometry)
los_vel = gps_obj.velocity
e_vel = dis_velocity(dates, gps_obj.dis_e)
n_vel = dis_velocity(dates, gps_obj.dis_n)
site_inve = np.array([[
gps_obj.site, gps_obj.site_lat, gps_obj.site_lon, los_vel, n_vel, e_vel
]])
return site_inve
def main(iargs=None):
inps = cmd_line_parse(iargs)
print('-' * 50)
print(os.path.abspath(__file__))
## Setup
# LOS incidence / azimuth angles
los_inc_angle = np.array([30, 30], dtype=np.float32)
los_az_angle = np.array([102, -102], dtype=np.float32)
# specify horz / vert [truth]
length, width = 5, 5
simH = np.ones((length, width), dtype=np.float32) * 0.5
simV = np.ones((length, width), dtype=np.float32) * 1.0
# azimuth angle in horizontal direction in degrees
# measured from the north with anti-clockwise as positive
# [0 for north, -90 for east]
horz_az_angle = 30
## Testing
# horz / vert --> east / north / up
dE = simH * np.sin(np.deg2rad(horz_az_angle)) * -1
dN = simH * np.cos(np.deg2rad(horz_az_angle))
dU = simV
# east / north / up --> asc / desc LOS
dlos0 = ut.enu2los(dE,
dN,
dU,
inc_angle=los_inc_angle[0],
az_angle=los_az_angle[0])
dlos1 = ut.enu2los(dE,
dN,
dU,
inc_angle=los_inc_angle[1],
az_angle=los_az_angle[1])
# asc / desc LOS --> horz / vert [estimation]
dlos = np.vstack((dlos0.reshape(1, length,
width), dlos1.reshape(1, length, width)))
estH, estV = asc_desc2horz_vert(dlos, los_inc_angle, los_az_angle,
horz_az_angle)
# check difference between the trush and estimation
print(
f'mean difference for horz / vert: {np.nanmean(estH - simH)} / {np.nanmean(estH - simH)}'
)
assert np.allclose(simH, estH)
assert np.allclose(simV, estV)
# Plotting
if inps.plot:
print('plot test result of {}'.format(os.path.basename(__file__)))
fig, axs = plt.subplots(nrows=3,
ncols=4,
figsize=[8, 6],
sharex=True,
sharey=True)
kwargs = dict(vmin=-1.5,
vmax=1.5,
cmap='RdBu',
interpolation='nearest')
# horz / vert [truth]
ax = axs[0, 0]
im = ax.imshow(simH, **kwargs)
ax.set_title('Horz [sim]')
ax = axs[1, 0]
im = ax.imshow(simV, **kwargs)
ax.set_title('Vert [sim]')
ax = axs[2, 0]
ax.axis('off')
# east / north / up
ax = axs[0, 1]
im = ax.imshow(dE, **kwargs)
ax.set_title('East [sim]')
ax = axs[1, 1]
im = ax.imshow(dN, **kwargs)
ax.set_title('North [sim]')
ax = axs[2, 1]
im = ax.imshow(dU, **kwargs)
ax.set_title('Up [sim]')
# asc / desc
ax = axs[0, 2]
im = ax.imshow(dlos0, **kwargs)
ax.set_title('Asc [obs]')
ax = axs[1, 2]
im = ax.imshow(dlos1, **kwargs)
ax.set_title('Desc [obs]')
ax = axs[2, 2]
ax.axis('off')
# horz / vert [estimation]
ax = axs[0, 3]
im = ax.imshow(estH, **kwargs)
ax.set_title('Horz [est]')
ax = axs[1, 3]
im = ax.imshow(estV, **kwargs)
ax.set_title('Vert [est]')
ax = axs[2, 3]
ax.axis('off')
# axis format
fig.tight_layout()
# colorbar
cax = fig.add_axes([0.6, 0.2, 0.3, 0.02])
fig.colorbar(im, cax=cax, orientation='horizontal')
plt.show()
