/
plotting.py
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plotting.py
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import numpy as np
try:
import matplotlib as mpl
import matplotlib.pyplot as plt
from matplotlib import cm
from mpl_toolkits.axes_grid1 import make_axes_locatable
mpl.rc('font', size=16)
mpl.rc('figure', figsize=(8, 6))
except:
plt = None
cm = None
def plot_perturbation(model, model1, colorbar=True):
"""
Plot a two-dimensional velocity perturbation from two seismic `Model`
objects.
Parameters
----------
model : Model
The first velocity model.
model1 : Model
The second velocity model.
colorbar : bool
Option to plot the colorbar.
"""
domain_size = 1.e-3 * np.array(model.domain_size)
extent = [model.origin[0], model.origin[0] + domain_size[0],
model.origin[1] + domain_size[1], model.origin[1]]
dv = np.transpose(model.vp.data) - np.transpose(model1.vp.data)
plot = plt.imshow(dv, animated=True, cmap=cm.jet,
vmin=min(dv.reshape(-1)), vmax=max(dv.reshape(-1)),
extent=extent)
plt.xlabel('X position (km)')
plt.ylabel('Depth (km)')
# Create aligned colorbar on the right
if colorbar:
ax = plt.gca()
divider = make_axes_locatable(ax)
cax = divider.append_axes("right", size="5%", pad=0.05)
cbar = plt.colorbar(plot, cax=cax)
cbar.set_label('Velocity perturbation (km/s)')
plt.show()
def plot_velocity(model, source=None, receiver=None, colorbar=True, cmap="jet"):
"""
Plot a two-dimensional velocity field from a seismic `Model`
object. Optionally also includes point markers for sources and receivers.
Parameters
----------
model : Model
Object that holds the velocity model.
source : array_like or float
Coordinates of the source point.
receiver : array_like or float
Coordinates of the receiver points.
colorbar : bool
Option to plot the colorbar.
"""
domain_size = 1.e-3 * np.array(model.domain_size)
extent = [model.origin[0], model.origin[0] + domain_size[0],
model.origin[1] + domain_size[1], model.origin[1]]
slices = tuple(slice(model.nbl, -model.nbl) for _ in range(2))
if getattr(model, 'vp', None) is not None:
field = model.vp.data[slices]
else:
field = model.lam.data[slices]
plot = plt.imshow(np.transpose(field), animated=True, cmap=cmap,
vmin=np.min(field), vmax=np.max(field),
extent=extent)
plt.xlabel('X position (km)')
plt.ylabel('Depth (km)')
# Plot source points, if provided
if receiver is not None:
plt.scatter(1e-3*receiver[:, 0], 1e-3*receiver[:, 1],
s=25, c='green', marker='D')
# Plot receiver points, if provided
if source is not None:
plt.scatter(1e-3*source[:, 0], 1e-3*source[:, 1],
s=25, c='red', marker='o')
# Ensure axis limits
plt.xlim(model.origin[0], model.origin[0] + domain_size[0])
plt.ylim(model.origin[1] + domain_size[1], model.origin[1])
# Create aligned colorbar on the right
if colorbar:
ax = plt.gca()
divider = make_axes_locatable(ax)
cax = divider.append_axes("right", size="5%", pad=0.05)
cbar = plt.colorbar(plot, cax=cax)
cbar.set_label('Velocity (km/s)')
plt.show()
def plot_shotrecord(rec, model, t0, tn, colorbar=True):
"""
Plot a shot record (receiver values over time).
Parameters
----------
rec :
Receiver data with shape (time, points).
model : Model
object that holds the velocity model.
t0 : int
Start of time dimension to plot.
tn : int
End of time dimension to plot.
"""
scale = np.max(rec) / 10.
extent = [model.origin[0], model.origin[0] + 1e-3*model.domain_size[0],
1e-3*tn, t0]
plot = plt.imshow(rec, vmin=-scale, vmax=scale, cmap=cm.gray, extent=extent)
plt.xlabel('X position (km)')
plt.ylabel('Time (s)')
# Create aligned colorbar on the right
if colorbar:
ax = plt.gca()
divider = make_axes_locatable(ax)
cax = divider.append_axes("right", size="5%", pad=0.05)
plt.colorbar(plot, cax=cax)
plt.show()
def plot_image(data, vmin=None, vmax=None, colorbar=True, cmap="gray"):
"""
Plot image data, such as RTM images or FWI gradients.
Parameters
----------
data : ndarray
Image data to plot.
cmap : str
Choice of colormap. Defaults to gray scale for images as a
seismic convention.
"""
plot = plt.imshow(np.transpose(data),
vmin=vmin or 0.9 * np.min(data),
vmax=vmax or 1.1 * np.max(data),
cmap=cmap)
# Create aligned colorbar on the right
if colorbar:
ax = plt.gca()
divider = make_axes_locatable(ax)
cax = divider.append_axes("right", size="5%", pad=0.05)
plt.colorbar(plot, cax=cax)
plt.show()