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This documentation is not for the latest stable Salvus version.

This tutorial is presented as Python code running inside a Jupyter Notebook, the recommended way to use Salvus. To run it yourself you can copy/type each individual cell or directly download the full notebook, including all required files.

# Model Interpolation

This notebook shows how to interpolate a given model defined on a regular grid to a Salvus mesh using the Marmousi model as an example.

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# initialize notebook
%matplotlib inline
import matplotlib.pyplot as plt
import numpy as np
import obspy
from salvus.mesh.structured_grid_2D import StructuredGrid2D

plt.rcParams["figure.figsize"] = (10, 8)

The Marmousi model is provided in a segy file, which we open with obspy and map to numpy arrays.

def get_marmousi():
nx, ny = 2301, 751
dx, dy = 4.0, 4.0

rho = np.empty((ny, nx))
for _i, tr in enumerate(st):
rho[_i, :] = tr.data

vp = np.empty((ny, nx))
for _i, tr in enumerate(st):
vp[_i, :] = tr.data

x = np.arange(nx) * dx
y = np.arange(ny) * dy

return x, y, vp, rho

Plot the model to verify we got it in correctly:

x, y, vp, rho = get_marmousi()
fig, axes = plt.subplots(2, 1)
axes[0].imshow(vp)
axes[1].imshow(rho)
plt.show()

Build a rectilinear mesh for a subregion of the model. While this might be simplistic, note that the model interpolation afterwards would be the same for any unstructured mesh.

fmax = 10.0  # maximum frequency in Hz
elements_per_wavelength = 2.0  # resolution criterion

# region in the marmousi model to mesh
mesh_min_x = x.max() * 0.2
mesh_max_x = x.max() * 0.7
mesh_min_y = y.min()
mesh_max_y = y.max()

hmax = vp.min() / fmax / elements_per_wavelength
nelem_x = int((mesh_max_x - mesh_min_x) / hmax) + 1
nelem_y = int((mesh_max_y - mesh_min_y) / hmax) + 1

sg = StructuredGrid2D.rectangle(
nelem_x=nelem_x,
nelem_y=nelem_y,
min_x=mesh_min_x,
max_x=mesh_max_x,
min_y=mesh_min_y,
max_y=mesh_max_y,
)
m = sg.get_unstructured_mesh()
m.change_tensor_order(4)

Interpolate the model to the mesh's element nodes using a scipy function and attach it to the mesh for plotting:

from scipy.interpolate import RectBivariateSpline

f_vp = RectBivariateSpline(x, y, vp.T[:, ::-1])
f_rho = RectBivariateSpline(x, y, rho.T[:, ::-1])

nodes = m.get_element_nodes()

nodes_x = nodes[:, :, 0]
nodes_y = nodes[:, :, 1]

vp_nodes = f_vp(nodes_x, nodes_y, grid=False)
rho_nodes = f_rho(nodes_x, nodes_y, grid=False)

m.attach_field("VP", vp_nodes)
m.attach_field("RHO", rho_nodes)
m.attach_field("fluid", np.ones(m.nelem))
m
/miniconda/envs/salvus/lib/python3.7/_collections_abc.py:702: MatplotlibDeprecationWarning: The global colormaps dictionary is no longer considered public API.
return len(self._mapping)
/miniconda/envs/salvus/lib/python3.7/_collections_abc.py:720: MatplotlibDeprecationWarning: The global colormaps dictionary is no longer considered public API.
yield from self._mapping

When run interactively in a Jupyter Notebook, this output cell contains a widget. Click the button below to load a preview of it. Please note that most interactive functionality does not work without a running Python kernel.
<salvus.mesh.unstructured_mesh.UnstructuredMesh at 0x7f1ba2039e50>
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