def read_rsf_XT(shots_rsf='shots_cmp_full.rsf',
logs_rsf='logs_full.rsf',
j_log_z=c.jlogz):
X = rsf_to_np(shots_rsf)
# single model exception
if X.ndim == 3:
X = np.expand_dims(X, axis=0)
X_f = np.flip(X, axis=2)
X = np.maximum(np.abs(X), np.abs(X_f)) * np.sign(X + X_f)
X = X[:, :, :(np.shape(X)[2] + 1) // 2, :]
T = rsf_to_np(logs_rsf)
# single model exception
if T.ndim == 2:
T = np.expand_dims(T, axis=0)
# decimate logs in vertical direction --2 times by default
T = resize(T, (*T.shape[0:2], np.shape(T)[2] // j_log_z))
T_size = np.shape(T)
print(T_size)
# ensure that the number of logs is equal to the number of CMPs
assert (X.shape[0:2] == T.shape[0:2])
return X, T
def show_model_generation():
stretch_X_train = c.stretch_X_train
vel = generate_model(stretch_X=stretch_X_train,
training_flag=False,
crop_flag=False,
distort_flag=False,
random_state_number=randint(10000))
vel = rsf_to_np("marmvel.hh")
plt_nb_T(aug_flip(vel), dx=4, dz=4, fname="../latex/Fig/marm_aug")
vel = generate_model(stretch_X=stretch_X_train,
distort_flag=False,
random_state_number=c.random_state_number,
show_flag=True)
plt_nb_T(vel, fname="../latex/Fig/cropMarm")
N = np.shape(vel)
vel_example = elastic_transform(np.atleast_3d(vel),
alpha_deform,
sigma_deform,
random_state_number=c.random_state_number,
plot_name="Normal")
N = np.shape(vel)
vel_example = generate_model(stretch_X=stretch_X_train,
training_flag=True,
random_state_number=c.random_state_number,
show_flag=True)
vel1 = generate_model(stretch_X=stretch_X_train,
training_flag=False,
random_state_number=randint(10000))
vel2 = generate_model(stretch_X=stretch_X_train,
training_flag=False,
random_state_number=randint(10000))
vel3 = generate_model(stretch_X=stretch_X_train,
training_flag=False,
random_state_number=randint(10000))
vel4 = generate_model(stretch_X=stretch_X_train,
training_flag=False,
random_state_number=randint(10000))
plt_nb_T(np.concatenate((vel_example, vel1, vel2, vel3, vel4), axis=1),
fname="../latex/Fig/random_model_example")
#run_all_tests(net_dict=singleCMP_net_dict, prefix="singleCMP", generate_rsf_data_flag=True)
run_all_tests(net_dict=multiCMP_net_dict, prefix="multiCMP", generate_rsf_data_flag=True)
print(f"Total execution time is {toc(tic_total)}")
#%% PLOT FWI RESULTS
# for folder in ["marm2",
# "seam_i_sediments",
# "seam100",
# "overthrust"]:
for folder in ["overthrust"]:
with cd(f"fwi_{folder}"):
cmd("scons -j 4")
fwi1 = rsf_to_np("fwi2.rsf")
fwi2 = rsf_to_np("fwi_shi.rsf")
velo = rsf_to_np("vel.rsf")
velsm = rsf_to_np("smvel.rsf")
R2o = r2_score(velo.flatten(), fwi2.flatten())
fwi2 = resize(fwi2, (fwi2.shape[0], 120))
fwi1 = resize(fwi1, (fwi2.shape[0], 120))
plt_nb_T(fwi2, title=f"DL+MSFWI, R2={R2o:.2f}, NRMS={nrms(velo,fwi2):.1f}%", fname=f"../../latex/Fig/msfwi_{folder}", dx=25, dz=25, figsize=(32,6), vmin=1.5, vmax=4.5)
plt_nb_T(velsm,
title=f"DL, R2={r2_score(velo.flatten(),velsm.flatten()):.2f}, NRMS={nrms(velo,velsm):.1f}%",
fname=f"../../latex/Fig/dl_{folder}",
dx=25, dz=25, figsize=(16,6), vmin=1.5, vmax=4.5)
plt_nb_T(velo,
title=f"True model",
fname=f"../../latex/Fig/true_{folder}",
dx=25, dz=25, figsize=(16,6), vmin=1.5, vmax=4.5)