/
plot_symmetrize.py
executable file
·100 lines (86 loc) · 3.19 KB
/
plot_symmetrize.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
r"""
Symmetrize
==========
This example shows how to use the :py:class:`pylops.Symmetrize`
operator which takes an input signal and returns a symmetric signal
by pre-pending the input signal in reversed order. Such an operation can be
inverted as we will see in this example.
Moreover the :py:class:`pylops.Symmetrize` can be used as *preconditioning*
to any inverse problem where we are after inverting for a signal that we
want to ensure is symmetric. Refer to :ref:`sphx_glr_gallery_plot_wavest.py`
for an example of such a type.
"""
import numpy as np
import matplotlib.pyplot as plt
import pylops
plt.close('all')
###############################################################################
# Let's start with a 1D example. Define an input signal composed of
# ``nt`` samples
nt = 10
x = np.arange(nt)
###############################################################################
# We can now create our flip operator and apply it to the input
# signal. We can also apply the adjoint to the flipped signal and we can
# see how for this operator the adjoint is effectively equivalent to
# the inverse.
Sop = pylops.Symmetrize(nt)
y = Sop*x
xadj = Sop.H*y
xinv = Sop / y
plt.figure(figsize=(7, 3))
plt.plot(x, 'k', lw=3, label=r'$x$')
plt.plot(y, 'r', lw=3, label=r'$y=Fx$')
plt.plot(xadj, '--g', lw=3, label=r'$x_{adj} = F^H y$')
plt.plot(xinv, '--m', lw=3, label=r'$x_{inv} = F^{-1} y$')
plt.title('Symmetrize in 1st direction', fontsize=14, fontweight='bold')
plt.legend()
###############################################################################
# Let's now repeat the same exercise on a two dimensional signal. We will
# first flip the model along the first axis and then along the second axis
nt, nx = 10, 6
x = np.outer(np.arange(nt), np.ones(nx))
Sop = pylops.Symmetrize(nt*nx, dims=(nt, nx), dir=0)
y = Sop*x.flatten()
xadj = Sop.H*y.flatten()
xinv = Sop / y
y = y.reshape(2*nt-1, nx)
xadj = xadj.reshape(nt, nx)
xinv = xinv.reshape(nt, nx)
fig, axs = plt.subplots(1, 3, figsize=(7, 3))
fig.suptitle('Symmetrize in 2nd direction for 2d data',
fontsize=14, fontweight='bold', y=0.95)
axs[0].imshow(x, cmap='rainbow', vmin=0, vmax=9)
axs[0].set_title(r'$x$')
axs[0].axis('tight')
axs[1].imshow(y, cmap='rainbow', vmin=0, vmax=9)
axs[1].set_title(r'$y=Fx$')
axs[1].axis('tight')
axs[2].imshow(xinv, cmap='rainbow', vmin=0, vmax=9)
axs[2].set_title(r'$x_{adj}=F^{-1}y$')
axs[2].axis('tight')
plt.tight_layout()
plt.subplots_adjust(top=0.8)
x = np.outer(np.ones(nt), np.arange(nx))
Sop = pylops.Symmetrize(nt*nx, dims=(nt, nx), dir=1)
y = Sop*x.flatten()
xadj = Sop.H*y.flatten()
xinv = Sop / y
y = y.reshape(nt, 2*nx-1)
xadj = xadj.reshape(nt, nx)
xinv = xinv.reshape(nt, nx)
# sphinx_gallery_thumbnail_number = 3
fig, axs = plt.subplots(1, 3, figsize=(7, 3))
fig.suptitle('Symmetrize in 2nd direction for 2d data',
fontsize=14, fontweight='bold', y=0.95)
axs[0].imshow(x, cmap='rainbow', vmin=0, vmax=9)
axs[0].set_title(r'$x$')
axs[0].axis('tight')
axs[1].imshow(y, cmap='rainbow', vmin=0, vmax=9)
axs[1].set_title(r'$y=Fx$')
axs[1].axis('tight')
axs[2].imshow(xinv, cmap='rainbow', vmin=0, vmax=9)
axs[2].set_title(r'$x_{adj}=F^{-1}y$')
axs[2].axis('tight')
plt.tight_layout()
plt.subplots_adjust(top=0.8)