def time2depth(self, dz):
if self.units == 'depth':
raise ValueError
vp_data = self.vp_data()
dt = self.depth / vp_data[0]
# This could be sped up if need be
data = np.asarray([time_to_depth(self.get_data(), vp_data,
dt, dz)
for i in range(data.shape[-1])])
def time2depth(self, data, point, dt, dz):
"""
Converts a data array from time to depth
Args:
data (array, 1d): A 1D numpy array.
point (float): distance along transect corresponding to
the trace location. Not actually used, as this model
assumes a constant velocity
dt (float): The sample interval of the input data.
dz (float): The sample interval of the depth converted
data.
"""
velocity = self.velocity
return time_to_depth(data, np.ones(data.size) * velocity, dt, dz)
def time2depth(self, data, point, dt, dz):
"""
Converts a data array from time to depth
Args:
data (array, 1d): A 1D numpy array.
point (float): distance along transect corresponding to
the trace location. Not actually used, as this model
assumes a constant velocity
dt (float): The sample interval of the input data.
dz (float): The sample interval of the depth converted
data.
"""
velocity = self.velocity
return time_to_depth(data, np.ones(data.size)*velocity, dt, dz)
def test_recip(self):
data = np.zeros((100, 100))
vmodel = np.zeros((100, 100))
data[0:50, :] += 100.0
data[50:, :] += 200.0
vmodel[0:50, :] += 1500.0
vmodel[50:, :] += 1800.0
dt = 0.001
dz = 1.
out1 = depth_to_time(data, vmodel, dz, dt)
v2 = depth_to_time(vmodel, vmodel, dz, dt)
out2 = time_to_depth(out1, v2, dt, dz)
"""plt.figure()
def test_timetodepth(self):
data = np.zeros((100, 100))
vmodel = np.zeros((100, 100))
data[0:50, :] += 100.0
data[50:, :] += 200.0
vmodel[0:50, :] += 1500.0
vmodel[50:, :] += 5000.0
dt = 0.001
dz = 1.0
output = time_to_depth(data, vmodel, dt, dz)
face_change = np.floor(((49 * dt) * 1500.0) / dz)
self.assertTrue((output[face_change + 1, 50] -
output[face_change, 50]) == 100)
def test_recip(self):
data = np.zeros( (100,100) )
vmodel = np.zeros( (100,100) )
data[0:50,:] += 100.0
data[50:,:] += 200.0
vmodel[0:50,:] += 1500.0
vmodel[50:,:] += 1800.0
dt = 0.001
dz = 1.
out1 = depth_to_time( data, vmodel, dz, dt )
v2 = depth_to_time( vmodel, vmodel, dz, dt )
out2 = time_to_depth( out1, v2, dt,dz )
"""plt.figure()
def test_timetodepth( self ):
data = np.zeros( (100,100) )
vmodel = np.zeros( (100,100) )
data[0:50,:] += 100.0
data[50:,:] += 200.0
vmodel[0:50,:] += 1500.0
vmodel[50:,:] += 5000.0
dt = 0.001
dz = 1.0
output = time_to_depth( data, vmodel,dt, dz )
face_change = np.floor( ( ( 49* dt ) * 1500.0 ) /
dz )
self.assertTrue( ( output[face_change+1,50] -
output[ face_change, 50 ] ) == 100 )
def time2depth(self, trace, point, dt, dz):
"""
Converts a seismic trace from time to depth.
Args:
trace (array, 1d): A 1D numpy array.
point (float): distance along transect corresponding to
the trace location.
"""
distance = [(p - point)**2.0 for p in self.coords]
idx = np.argmin(distance)
profile = self.data[idx]
seismic = np.array(trace)
# HACK TO MAKE FAKE VELOCITIES
velocity = np.ones(profile.data.size) * 2000.0
samp = profile.stats["sampling_rate"]
vel_t = np.arange(velocity.size) * 1.0 / samp
t = np.arange(seismic.size) * dt
velocity = np.interp(t, vel_t, velocity, velocity[0], velocity[-1])
z = np.arange(self.range[0], self.range[1], dz)
data = time_to_depth(seismic, velocity, t, z, mode="cubic")
return data
def time2depth(self, trace, point, dt, dz):
"""
Converts a seismic trace from time to depth.
Args:
trace (array, 1d): A 1D numpy array.
point (float): distance along transect corresponding to
the trace location.
"""
distance = [(p - point)**2.0 for p in self.coords]
idx = np.argmin(distance)
profile = self.data[idx]
seismic = np.array(trace)
# HACK TO MAKE FAKE VELOCITIES
velocity = np.ones(profile.data.size) * 2000.0
samp = profile.stats["sampling_rate"]
vel_t = np.arange(velocity.size) * 1.0 / samp
t = np.arange(seismic.size)*dt
velocity = np.interp(t, vel_t, velocity, velocity[0], velocity[-1])
z = np.arange(self.range[0], self.range[1], dz)
data = time_to_depth(seismic, velocity, t, z, mode="cubic")
return data
