from mpi4py import MPI
if __name__ == "__main__":
comm = MPI.COMM_WORLD
size = comm.Get_size()
rank = comm.Get_rank()
# Wrapper for handling parallelism over shots
pwrap = ParallelWrapShot(comm=MPI.COMM_WORLD)
if rank == 0:
ttt = time.time()
# Load or generate true wave speed
C, C0, m, d = marmousi(patch="mini_square")
# Set up shots
Nshots = size
sys.stdout.write("{0}: {1}\n".format(rank, Nshots / size))
shots = equispaced_acquisition(
m, RickerWavelet(10.0), sources=Nshots, source_depth=20.0, receivers="max", parallel_shot_wrap=pwrap
)
# Define and configure the wave solver
trange = (0.0, 3.0)
solver = ConstantDensityAcousticWave(m, spatial_accuracy_order=6, trange=trange, kernel_implementation="cpp")
size = comm.Get_size()
rank = comm.Get_rank()
print "size = %i and rank = %i"%(size, rank)
pwrap = ParallelWrapShot(comm=comm)
####### Here we set the wave speed
WaveSpeed.add_lower_bound(1000.0)
WaveSpeed.add_upper_bound(6500.0)
x_lbc = PML(600.0,100.0); x_rbc = PML(600.0,100.0); z_lbc = PML(600.0,100.0); z_rbc = PML(600.0,100.0)
C, C0, m, d = marmousi(patch='mini_square', x_lbc = x_lbc, x_rbc = x_rbc, z_lbc = z_lbc, z_rbc = z_rbc)
n_nodes_x = m.x.n
n_nodes_z = m.z.n
dx = m.x.delta
dz = m.z.delta
x_min = d.x.lbound
x_max = d.x.rbound
z_min = d.z.lbound
z_max = d.z.rbound
x_min_km = x_min/1000.0; x_max_km = x_max/1000.0; z_min_km = z_min/1000.0; z_max_km = z_max/1000.0
marmousi_baseline_true_2d = np.reshape(C , (n_nodes_z, n_nodes_x), 'F')
# Std import block
import time
import copy
import numpy as np
import matplotlib.pyplot as plt
from pysit import *
from pysit.gallery import marmousi
from pysit.gallery import marmousi2
if __name__ == '__main__':
# Load or generate true wave speed
C, C0, m, d = marmousi(patch='mini_square')
# C, C0, m, d = marmousi2(patch='mini_square')
# Set up shots
shots = equispaced_acquisition(m,
RickerWavelet(10.0),
sources=1,
source_depth=500.0,
source_kwargs={},
receivers='max',
receiver_kwargs={},
)
# Define and configure the wave solver
trange = (0.0, 3.0)
solver = ConstantDensityAcousticWave(m,
spatial_accuracy_order=6,
# Std import block
import time
import copy
import numpy as np
import matplotlib.pyplot as plt
from pysit import *
from pysit.gallery import marmousi
from pysit.gallery import marmousi2
if __name__ == '__main__':
# Load or generate true wave speed
C, C0, m, d = marmousi(patch='mini_square')
# C, C0, m, d = marmousi2(patch='mini_square')
# Set up shots
shots = equispaced_acquisition(
m,
RickerWavelet(10.0),
sources=1,
source_depth=500.0,
source_kwargs={},
receivers='max',
receiver_kwargs={},
)
# Define and configure the wave solver
trange = (0.0, 3.0)
solver = ConstantDensityAcousticWave(m,
pwrap = ParallelWrapShot()
if rank == 0:
ttt = time.time()
sys.stdout.write('Marmousi test \n')
# Set up domain, mesh and velocity model
m_param = {
'patch': 'mini_square',
# 'pixel_scale' : 'mini',
# 'initial_model_style' : 'smooth_low_pass',
# 'initial_config' : {'freq':1/3000.},
}
C, C0, m, d = marmousi(patch=m_param['patch'])
# pixel_scale=m_param['pixel_scale'],
# initial_model_style=m_param['initial_model_style'],
# initial_config=m_param['initial_config'])
if rank == 0:
sys.stdout.write('patch = %s \n' % m_param['patch'])
# sys.stdout.write('pixel_scale = %s \n' %m_param['pixel_scale'])
# sys.stdout.write('initial_model_style = %s \n' %m_param['initial_model_style'])
# sys.stdout.write('initial_config = %s \n' %m_param['initial_config'])
# Set up shots
zmin = d.z.lbound
zmax = d.z.rbound
zpos = 0.02 * 1.0
import os
import numpy as np
import matplotlib.pyplot as plt
from pysit import *
from pysit.gallery import marmousi
from pysit.gallery import marmousi2
if __name__ == '__main__':
os.environ["OMP_NUM_THREADS"] = "14"
# Load or generate true wave speed we can add the compact operator
# flag it will speed up the resolution
# uses a compact PML formulation
C, C0, m, d = marmousi(patch='mini_square', compact=True)
# C, C0, m, d = marmousi2(patch='mini_square', compact = True)
# C, C0, m, d = marmousi(patch='mini_square')
# C, C0, m, d = marmousi2(patch='mini_square')
# Set up shots
shots = equispaced_acquisition(
m,
RickerWavelet(10.0),
sources=20,
source_depth=500.0,
source_kwargs={},
receivers='max',
receiver_kwargs={},
)
from pysit.gallery import marmousi
import scipy.io as io
import os
import matplotlib.pyplot as plt
import time
import numpy as np
if __name__ == '__main__':
# 生成默认的二维marmousi模型
# 物理尺寸：横坐标-0~9200；纵坐标-0~3000；单位-m
# 网格参数：横向网格数-460；纵向网格数-150；
# 网格划分间隔-20；单位-m；横向网格点数-461；纵向网格点数-151
# C-二维Marmousi模型各网格波速；C0-反演初始模型各网格波速；
# m-网格对象，保存二维Marmousi模型的网格剖分信息；
# d-物理模型对象，保存二维Marmousi模型的物理信息
# initial_model_style-初始模型生成规则，可填参数constant、smooth_width、smooth_low_pass、gradient
C, C0, m, d = marmousi(patch='mini_square',
initial_model_style='smooth_low_pass')
# 绘制模型
plt.figure()
plt.subplot(2, 1, 1)
vis.plot(C0, m)
b1 = plt.colorbar()
b1.set_label('Velocity (m/s)')
plt.title('Initial Model')
plt.xlabel('Length (m)')
plt.ylabel('Depth (m)')
plt.subplot(2, 1, 2)
vis.plot(C, m)
b2 = plt.colorbar()
b2.set_label('Velocity (m/s)')
plt.title('True Model')
plt.xlabel('Length (m)')
import os
import numpy as np
import matplotlib.pyplot as plt
from pysit import *
from pysit.gallery import marmousi
from pysit.gallery import marmousi2
if __name__ == '__main__':
os.environ["OMP_NUM_THREADS"] = "14"
# Load or generate true wave speed we can add the compact operator
# flag it will speed up the resolution
# uses a compact PML formulation
C, C0, m, d = marmousi(patch='mini_square', compact = True)
# C, C0, m, d = marmousi2(patch='mini_square', compact = True)
# C, C0, m, d = marmousi(patch='mini_square')
# C, C0, m, d = marmousi2(patch='mini_square')
# Set up shots
shots = equispaced_acquisition(m,
RickerWavelet(10.0),
sources=20,
source_depth=500.0,
source_kwargs={},
receivers='max',
receiver_kwargs={},
)
# Define and configure the wave solver
from pysit.util.compute_tools import *
from pysit.gallery import marmousi
from pysit.gallery import marmousi2
from pysit.util.parallel import *
if __name__ == '__main__':
# Set up parallel computing environment
comm = MPI.COMM_WORLD
size = comm.Get_size()
rank = comm.Get_rank()
pwrap = ParallelWrapShot()
# Set up domain, mesh and velocity model
C, C0, m, d = marmousi(pixel_scale='mini')
if rank == 0:
plt.figure()
vis.plot(C, m)
plt.show()
comm.Barrier()
m_shape = m._shapes[(False, True)]
pmlx = PML(0.5, 1000)
pmlz = PML(0.5, 1000)
x_config = (d.x.lbound / 1000.0, d.x.rbound / 1000.0, pmlx, pmlx)
z_config = (d.z.lbound / 1000.0, d.z.rbound / 1000.0, pmlz, pmlz)
aux_info_copy = copy.deepcopy(aux_info)
solver.model_parameters = joint_model.m_1
gradient_m_1 = objective.compute_gradient(shots_1, joint_model.m_1, aux_info=aux_info_copy)
objective_value_m_1 = aux_info_copy['objective_value'][1]
joint_data_obj = objective_value_m_0 + objective_value_m_1
joint_data_gradient = JointPerturbation(gradient_m_0, gradient_m_1)
return joint_data_obj, joint_data_gradient
if __name__ == '__main__':
pixel_scale = [50.0, 50.0]
C, C0, m, d = marmousi(patch='mini_square', pixel_scale=pixel_scale)
shots = equispaced_acquisition(m,
RickerWavelet(4.0),
sources=3,
source_depth=200.0,
source_kwargs={},
receivers='max',
receiver_kwargs={},
)
trange = (0.0, 3.0)
solver = ConstantDensityAcousticWave(m,
spatial_accuracy_order=6,
trange=trange,
# Std import block
import time
import copy
import numpy as np
import matplotlib.pyplot as plt
from pysit import *
from pysit.gallery import marmousi
from pysit.gallery import marmousi2
if __name__ == '__main__':
# Load or generate true wave speed
C, C0, m, d = marmousi(patch='mini_square', pixel_scale='medium')
# C, C0, m, d = marmousi2(patch='mini_square')
# Set up shots
shots = equispaced_acquisition(m,
RickerWavelet(10.0),
sources=1,
source_depth=500.0,
source_kwargs={},
receivers='max',
receiver_kwargs={},
)
# Define and configure the wave solver
trange = (0.0, 3.0)
solver = ConstantDensityAcousticWave(m,
spatial_accuracy_order=2,
