r"""Compute the sound field generated by a sound source.
.. include:: math-definitions.rst
.. plot::
:context: reset
import sfs
import numpy as np
import matplotlib.pyplot as plt
plt.rcParams['figure.figsize'] = 8, 4.5 # inch
x0 = 1.5, 1, 0
f = 500 # Hz
omega = 2 * np.pi * f
normalization_point = 4 * np.pi
normalization_line = \
np.sqrt(8 * np.pi * omega / sfs.default.c) * np.exp(1j * np.pi / 4)
grid = sfs.util.xyz_grid([-2, 3], [-1, 2], 0, spacing=0.02)
# Grid for vector fields:
vgrid = sfs.util.xyz_grid([-2, 3], [-1, 2], 0, spacing=0.1)
"""
from itertools import product as _product
import numpy as _np
from scipy import special as _special
from .. import default as _default
from .. import util as _util
def point(omega, x0, grid, *, c=None):
r"""Sound pressure of a point source.
Parameters
----------
omega : float
Frequency of source.
x0 : (3,) array_like
Position of source.
grid : triple of array_like
The grid that is used for the sound field calculations.
See `sfs.util.xyz_grid()`.
c : float, optional
Speed of sound.
Returns
-------
numpy.ndarray
Sound pressure at positions given by *grid*.
Notes
-----
.. math::
G(\x-\x_0,\w) = \frac{1}{4\pi} \frac{\e{-\i\wc|\x-\x_0|}}{|\x-\x_0|}
Examples
--------
.. plot::
:context: close-figs
p = sfs.fd.source.point(omega, x0, grid)
sfs.plot2d.amplitude(p, grid)
plt.title("Point Source at {} m".format(x0))
Normalization ...
.. plot::
:context: close-figs
sfs.plot2d.amplitude(p * normalization_point, grid,
colorbar_kwargs=dict(label="p / Pa"))
plt.title("Point Source at {} m (normalized)".format(x0))
"""
k = _util.wavenumber(omega, c)
x0 = _util.asarray_1d(x0)
grid = _util.as_xyz_components(grid)
r = _np.linalg.norm(grid - x0)
# If r is 0, the sound pressure is complex infinity
numerator = _np.exp(-1j * k * r) / (4 * _np.pi)
with _np.errstate(invalid='ignore', divide='ignore'):
return numerator / r
def point_velocity(omega, x0, grid, *, c=None, rho0=None):
"""Particle velocity of a point source.
Parameters
----------
omega : float
Frequency of source.
x0 : (3,) array_like
Position of source.
grid : triple of array_like
The grid that is used for the sound field calculations.
See `sfs.util.xyz_grid()`.
c : float, optional
Speed of sound.
rho0 : float, optional
Static density of air.
Returns
-------
`XyzComponents`
Particle velocity at positions given by *grid*.
Examples
--------
The particle velocity can be plotted on top of the sound pressure:
.. plot::
:context: close-figs
v = sfs.fd.source.point_velocity(omega, x0, vgrid)
sfs.plot2d.amplitude(p * normalization_point, grid)
sfs.plot2d.vectors(v * normalization_point, vgrid)
plt.title("Sound Pressure and Particle Velocity")
"""
if c is None:
c = _default.c
if rho0 is None:
rho0 = _default.rho0
k = _util.wavenumber(omega, c)
x0 = _util.asarray_1d(x0)
grid = _util.as_xyz_components(grid)
offset = grid - x0
r = _np.linalg.norm(offset)
v = point(omega, x0, grid, c=c)
v *= (1+1j*k*r) / (rho0 * c * 1j*k*r)
return _util.XyzComponents([v * o / r for o in offset])
def point_averaged_intensity(omega, x0, grid, *, c=None, rho0=None):
"""Velocity of a point source.
Parameters
----------
omega : float
Frequency of source.
x0 : (3,) array_like
Position of source.
grid : triple of array_like
The grid that is used for the sound field calculations.
See `sfs.util.xyz_grid()`.
c : float, optional
Speed of sound.
rho0 : float, optional
Static density of air.
Returns
-------
`XyzComponents`
Averaged intensity at positions given by *grid*.
"""
if c is None:
c = _default.c
if rho0 is None:
rho0 = _default.rho0
x0 = _util.asarray_1d(x0)
grid = _util.as_xyz_components(grid)
offset = grid - x0
r = _np.linalg.norm(offset)
i = 1 / (2 * rho0 * c)
return _util.XyzComponents([i * o / r**2 for o in offset])
def point_dipole(omega, x0, n0, grid, *, c=None):
r"""Point source with dipole characteristics.
Parameters
----------
omega : float
Frequency of source.
x0 : (3,) array_like
Position of source.
n0 : (3,) array_like
Normal vector (direction) of dipole.
grid : triple of array_like
The grid that is used for the sound field calculations.
See `sfs.util.xyz_grid()`.
c : float, optional
Speed of sound.
Returns
-------
numpy.ndarray
Sound pressure at positions given by *grid*.
Notes
-----
.. math::
G(\x-\x_0,\w) = \frac{1}{4\pi} \left(\i\wc + \frac{1}{|\x-\x_0|}\right)
\frac{\scalarprod{\x-\x_0}{\n_\text{s}}}{|\x-\x_0|^2}
\e{-\i\wc|\x-\x_0}
Examples
--------
.. plot::
:context: close-figs
n0 = 0, 1, 0
p = sfs.fd.source.point_dipole(omega, x0, n0, grid)
sfs.plot2d.amplitude(p, grid)
plt.title("Dipole Point Source at {} m".format(x0))
"""
k = _util.wavenumber(omega, c)
x0 = _util.asarray_1d(x0)
n0 = _util.asarray_1d(n0)
grid = _util.as_xyz_components(grid)
offset = grid - x0
r = _np.linalg.norm(offset)
return 1 / (4 * _np.pi) * (1j * k + 1 / r) * _np.inner(offset, n0) / \
_np.power(r, 2) * _np.exp(-1j * k * r)
def point_modal(omega, x0, grid, L, *, N=None, deltan=0, c=None):
"""Point source in a rectangular room using a modal room model.
Parameters
----------
omega : float
Frequency of source.
x0 : (3,) array_like
Position of source.
grid : triple of array_like
The grid that is used for the sound field calculations.
See `sfs.util.xyz_grid()`.
L : (3,) array_like
Dimensionons of the rectangular room.
N : (3,) array_like or int, optional
For all three spatial dimensions per dimension maximum order or
list of orders. A scalar applies to all three dimensions. If no
order is provided it is approximately determined.
deltan : float, optional
Absorption coefficient of the walls.
c : float, optional
Speed of sound.
Returns
-------
numpy.ndarray
Sound pressure at positions given by *grid*.
"""
k = _util.wavenumber(omega, c)
x0 = _util.asarray_1d(x0)
x, y, z = _util.as_xyz_components(grid)
if _np.isscalar(N):
N = N * _np.ones(3, dtype=int)
if N is None:
N = [None, None, None]
orders = [0, 0, 0]
for i in range(3):
if N[i] is None:
# compute max order
orders[i] = range(int(_np.ceil(L[i] / _np.pi * k) + 1))
elif _np.isscalar(N[i]):
# use given max order
orders[i] = range(N[i] + 1)
else:
# use given orders
orders[i] = N[i]
kmp0 = [((kx + 1j * deltan)**2, _np.cos(kx * x) * _np.cos(kx * x0[0]))
for kx in [m * _np.pi / L[0] for m in orders[0]]]
kmp1 = [((ky + 1j * deltan)**2, _np.cos(ky * y) * _np.cos(ky * x0[1]))
for ky in [n * _np.pi / L[1] for n in orders[1]]]
kmp2 = [((kz + 1j * deltan)**2, _np.cos(kz * z) * _np.cos(kz * x0[2]))
for kz in [l * _np.pi / L[2] for l in orders[2]]]
ksquared = k**2
p = 0
for (km0, p0), (km1, p1), (km2, p2) in _product(kmp0, kmp1, kmp2):
km = km0 + km1 + km2
p = p + 8 / (ksquared - km) * p0 * p1 * p2
return p
def point_modal_velocity(omega, x0, grid, L, *, N=None, deltan=0, c=None):
"""Velocity of point source in a rectangular room using a modal room model.
Parameters
----------
omega : float
Frequency of source.
x0 : (3,) array_like
Position of source.
grid : triple of array_like
The grid that is used for the sound field calculations.
See `sfs.util.xyz_grid()`.
L : (3,) array_like
Dimensionons of the rectangular room.
N : (3,) array_like or int, optional
Combination of modal orders in the three-spatial dimensions to
calculate the sound field for or maximum order for all
dimensions. If not given, the maximum modal order is
approximately determined and the sound field is computed up to
this maximum order.
deltan : float, optional
Absorption coefficient of the walls.
c : float, optional
Speed of sound.
Returns
-------
`XyzComponents`
Particle velocity at positions given by *grid*.
"""
k = _util.wavenumber(omega, c)
x0 = _util.asarray_1d(x0)
x, y, z = _util.as_xyz_components(grid)
if N is None:
# determine maximum modal order per dimension
Nx = int(_np.ceil(L[0] / _np.pi * k))
Ny = int(_np.ceil(L[1] / _np.pi * k))
Nz = int(_np.ceil(L[2] / _np.pi * k))
mm = range(Nx)
nn = range(Ny)
ll = range(Nz)
elif _np.isscalar(N):
# compute up to a given order
mm = range(N)
nn = range(N)
ll = range(N)
else:
# compute field for one order combination only
mm = [N[0]]
nn = [N[1]]
ll = [N[2]]
kmp0 = [((kx + 1j * deltan)**2, _np.sin(kx * x) * _np.cos(kx * x0[0]))
for kx in [m * _np.pi / L[0] for m in mm]]
kmp1 = [((ky + 1j * deltan)**2, _np.sin(ky * y) * _np.cos(ky * x0[1]))
for ky in [n * _np.pi / L[1] for n in nn]]
kmp2 = [((kz + 1j * deltan)**2, _np.sin(kz * z) * _np.cos(kz * x0[2]))
for kz in [l * _np.pi / L[2] for l in ll]]
ksquared = k**2
vx = 0+0j
vy = 0+0j
vz = 0+0j
for (km0, p0), (km1, p1), (km2, p2) in _product(kmp0, kmp1, kmp2):
km = km0 + km1 + km2
vx = vx - 8*1j / (ksquared - km) * p0
vy = vy - 8*1j / (ksquared - km) * p1
vz = vz - 8*1j / (ksquared - km) * p2
return _util.XyzComponents([vx, vy, vz])
def point_image_sources(omega, x0, grid, L, *, max_order, coeffs=None, c=None):
"""Point source in a rectangular room using the mirror image source model.
Parameters
----------
omega : float
Frequency of source.
x0 : (3,) array_like
Position of source.
grid : triple of array_like
The grid that is used for the sound field calculations.
See `sfs.util.xyz_grid()`.
L : (3,) array_like
Dimensions of the rectangular room.
max_order : int
Maximum number of reflections for each image source.
coeffs : (6,) array_like, optional
Reflection coeffecients of the walls.
If not given, the reflection coefficients are set to one.
c : float, optional
Speed of sound.
Returns
-------
numpy.ndarray
Sound pressure at positions given by *grid*.
"""
if coeffs is None:
coeffs = _np.ones(6)
xs, order = _util.image_sources_for_box(x0, L, max_order)
source_strengths = _np.prod(coeffs**order, axis=1)
p = 0
for position, strength in zip(xs, source_strengths):
if strength != 0:
# point can be complex infinity
with _np.errstate(invalid='ignore'):
p += strength * point(omega, position, grid, c=c)
return p
def line(omega, x0, grid, *, c=None):
r"""Line source parallel to the z-axis.
Parameters
----------
omega : float
Frequency of source.
x0 : (3,) array_like
Position of source. Note: third component of x0 is ignored.
grid : triple of array_like
The grid that is used for the sound field calculations.
See `sfs.util.xyz_grid()`.
c : float, optional
Speed of sound.
Returns
-------
numpy.ndarray
Sound pressure at positions given by *grid*.
Notes
-----
.. math::
G(\x-\x_0,\w) = -\frac{\i}{4} \Hankel{2}{0}{\wc|\x-\x_0|}
Examples
--------
.. plot::
:context: close-figs
p = sfs.fd.source.line(omega, x0, grid)
sfs.plot2d.amplitude(p, grid)
plt.title("Line Source at {} m".format(x0[:2]))
Normalization ...
.. plot::
:context: close-figs
sfs.plot2d.amplitude(p * normalization_line, grid,
colorbar_kwargs=dict(label="p / Pa"))
plt.title("Line Source at {} m (normalized)".format(x0[:2]))
"""
k = _util.wavenumber(omega, c)
x0 = _util.asarray_1d(x0)[:2] # ignore z-component
grid = _util.as_xyz_components(grid)
r = _np.linalg.norm(grid[:2] - x0)
p = -1j/4 * _hankel2_0(k * r)
return _duplicate_zdirection(p, grid)
def line_velocity(omega, x0, grid, *, c=None, rho0=None):
"""Velocity of line source parallel to the z-axis.
Parameters
----------
omega : float
Frequency of source.
x0 : (3,) array_like
Position of source. Note: third component of x0 is ignored.
grid : triple of array_like
The grid that is used for the sound field calculations.
See `sfs.util.xyz_grid()`.
c : float, optional
Speed of sound.
Returns
-------
`XyzComponents`
Particle velocity at positions given by *grid*.
Examples
--------
The particle velocity can be plotted on top of the sound pressure:
.. plot::
:context: close-figs
v = sfs.fd.source.line_velocity(omega, x0, vgrid)
sfs.plot2d.amplitude(p * normalization_line, grid)
sfs.plot2d.vectors(v * normalization_line, vgrid)
plt.title("Sound Pressure and Particle Velocity")
"""
if c is None:
c = _default.c
if rho0 is None:
rho0 = _default.rho0
k = _util.wavenumber(omega, c)
x0 = _util.asarray_1d(x0)[:2] # ignore z-component
grid = _util.as_xyz_components(grid)
offset = grid[:2] - x0
r = _np.linalg.norm(offset)
v = -1/(4 * c * rho0) * _special.hankel2(1, k * r)
v = [v * o / r for o in offset]
assert v[0].shape == v[1].shape
if len(grid) > 2:
v.append(_np.zeros_like(v[0]))
return _util.XyzComponents([_duplicate_zdirection(vi, grid) for vi in v])
def line_dipole(omega, x0, n0, grid, *, c=None):
r"""Line source with dipole characteristics parallel to the z-axis.
Parameters
----------
omega : float
Frequency of source.
x0 : (3,) array_like
Position of source. Note: third component of x0 is ignored.
x0 : (3,) array_like
Normal vector of the source.
grid : triple of array_like
The grid that is used for the sound field calculations.
See `sfs.util.xyz_grid()`.
c : float, optional
Speed of sound.
Notes
-----
.. math::
G(\x-\x_0,\w) = \frac{\i k}{4} \Hankel{2}{1}{\wc|\x-\x_0|} \cos{\phi}
"""
k = _util.wavenumber(omega, c)
x0 = _util.asarray_1d(x0)[:2] # ignore z-components
n0 = _util.asarray_1d(n0)[:2]
grid = _util.as_xyz_components(grid)
dx = grid[:2] - x0
r = _np.linalg.norm(dx)
p = 1j*k/4 * _special.hankel2(1, k * r) * _np.inner(dx, n0) / r
return _duplicate_zdirection(p, grid)
def line_bandlimited(omega, x0, grid, *, max_order=None, c=None):
r"""Spatially bandlimited (modal) line source parallel to the z-axis.
Parameters
----------
omega : float
Frequency of source.
x0 : (3,) array_like
Position of source. Note: third component of x0 is ignored.
grid : triple of array_like
The grid that is used for the sound field calculations.
See `sfs.util.xyz_grid()`.
max_order : int, optional
Number of elements for series expansion of the source.
No bandlimitation if not given.
c : float, optional
Speed of sound.
Returns
-------
numpy.ndarray
Sound pressure at positions given by *grid*.
Notes
-----
.. math::
G(\x-\x_0,\w) = -\frac{\i}{4} \sum_{\nu = - N}^{N}
e^{j \nu (\alpha - \alpha_0)}
\begin{cases}
J_\nu(\frac{\omega}{c} r) H_\nu^\text{(2)}(\frac{\omega}{c} r_0)
& \text{for } r \leq r_0 \\
J_\nu(\frac{\omega}{c} r_0) H_\nu^\text{(2)}(\frac{\omega}{c} r)
& \text{for } r > r_0 \\
\end{cases}
Examples
--------
.. plot::
:context: close-figs
p = sfs.fd.source.line_bandlimited(omega, x0, grid, max_order=10)
sfs.plot2d.amplitude(p * normalization_line, grid)
plt.title("Bandlimited Line Source at {} m".format(x0[:2]))
"""
k = _util.wavenumber(omega, c)
x0 = _util.asarray_1d(x0)[:2] # ignore z-components
r0 = _np.linalg.norm(x0)
phi0 = _np.arctan2(x0[1], x0[0])
grid = _util.as_xyz_components(grid)
r = _np.linalg.norm(grid[:2])
phi = _np.arctan2(grid[1], grid[0])
if max_order is None:
max_order = int(_np.ceil(k * _np.max(r)))
p = _np.zeros((grid[1].shape[0], grid[0].shape[1]), dtype=complex)
idxr = (r <= r0)
for m in range(-max_order, max_order + 1):
p[idxr] -= 1j/4 * _special.hankel2(m, k * r0) * \
_special.jn(m, k * r[idxr]) * _np.exp(1j * m * (phi[idxr] - phi0))
p[~idxr] -= 1j/4 * _special.hankel2(m, k * r[~idxr]) * \
_special.jn(m, k * r0) * _np.exp(1j * m * (phi[~idxr] - phi0))
return _duplicate_zdirection(p, grid)
def line_dirichlet_edge(omega, x0, grid, *, alpha=_np.pi*3/2, Nc=None, c=None):
"""Line source scattered at an edge with Dirichlet boundary conditions.
:cite:`Moser2012`, eq.(10.18/19)
Parameters
----------
omega : float
Angular frequency.
x0 : (3,) array_like
Position of line source.
grid : triple of array_like
The grid that is used for the sound field calculations.
See `sfs.util.xyz_grid()`.
alpha : float, optional
Outer angle of edge.
Nc : int, optional
Number of elements for series expansion of driving function.
Estimated if not given.
c : float, optional
Speed of sound
Returns
-------
numpy.ndarray
Complex pressure at grid positions.
"""
k = _util.wavenumber(omega, c)
x0 = _util.asarray_1d(x0)
phi_s = _np.arctan2(x0[1], x0[0])
if phi_s < 0:
phi_s = phi_s + 2 * _np.pi
r_s = _np.linalg.norm(x0)
grid = _util.XyzComponents(grid)
r = _np.linalg.norm(grid[:2])
phi = _np.arctan2(grid[1], grid[0])
phi = _np.where(phi < 0, phi + 2 * _np.pi, phi)
if Nc is None:
Nc = _np.ceil(2 * k * _np.max(r) * alpha / _np.pi)
epsilon = _np.ones(Nc) # weights for series expansion
epsilon[0] = 2
p = _np.zeros((grid[1].shape[0], grid[0].shape[1]), dtype=complex)
idxr = (r <= r_s)
idxa = (phi <= alpha)
for m in _np.arange(Nc):
nu = m * _np.pi / alpha
f = 1/epsilon[m] * _np.sin(nu*phi_s) * _np.sin(nu*phi)
p[idxr & idxa] = p[idxr & idxa] + f[idxr & idxa] * \
_special.jn(nu, k*r[idxr & idxa]) * _special.hankel2(nu, k*r_s)
p[~idxr & idxa] = p[~idxr & idxa] + f[~idxr & idxa] * \
_special.jn(nu, k*r_s) * _special.hankel2(nu, k*r[~idxr & idxa])
p = p * -1j * _np.pi / alpha
pl = line(omega, x0, grid, c=c)
p[~idxa] = pl[~idxa]
return p
def plane(omega, x0, n0, grid, *, c=None):
r"""Plane wave.
Parameters
----------
omega : float
Frequency of plane wave.
x0 : (3,) array_like
Position of plane wave.
n0 : (3,) array_like
Normal vector (direction) of plane wave.
grid : triple of array_like
The grid that is used for the sound field calculations.
See `sfs.util.xyz_grid()`.
c : float, optional
Speed of sound.
Returns
-------
numpy.ndarray
Sound pressure at positions given by *grid*.
Notes
-----
.. math::
G(\x,\w) = \e{-\i\wc\n\x}
Examples
--------
.. plot::
:context: close-figs
direction = 45 # degree
n0 = sfs.util.direction_vector(np.radians(direction))
p = sfs.fd.source.plane(omega, x0, n0, grid)
sfs.plot2d.amplitude(p, grid, colorbar_kwargs=dict(label="p / Pa"))
plt.title("Plane wave with direction {} degree".format(direction))
"""
k = _util.wavenumber(omega, c)
x0 = _util.asarray_1d(x0)
n0 = _util.normalize_vector(n0)
grid = _util.as_xyz_components(grid)
return _np.exp(-1j * k * _np.inner(grid - x0, n0))
def plane_velocity(omega, x0, n0, grid, *, c=None, rho0=None):
r"""Velocity of a plane wave.
Parameters
----------
omega : float
Frequency of plane wave.
x0 : (3,) array_like
Position of plane wave.
n0 : (3,) array_like
Normal vector (direction) of plane wave.
grid : triple of array_like
The grid that is used for the sound field calculations.
See `sfs.util.xyz_grid()`.
c : float, optional
Speed of sound.
rho0 : float, optional
Static density of air.
Returns
-------
`XyzComponents`
Particle velocity at positions given by *grid*.
Notes
-----
.. math::
V(\x,\w) = \frac{1}{\rho c} \e{-\i\wc\n\x} \n
Examples
--------
The particle velocity can be plotted on top of the sound pressure:
.. plot::
:context: close-figs
v = sfs.fd.source.plane_velocity(omega, x0, n0, vgrid)
sfs.plot2d.amplitude(p, grid)
sfs.plot2d.vectors(v, vgrid)
plt.title("Sound Pressure and Particle Velocity")
"""
if c is None:
c = _default.c
if rho0 is None:
rho0 = _default.rho0
v = plane(omega, x0, n0, grid, c=c) / (rho0 * c)
return _util.XyzComponents([v * n for n in n0])
def plane_averaged_intensity(omega, x0, n0, grid, *, c=None, rho0=None):
r"""Averaged intensity of a plane wave.
Parameters
----------
omega : float
Frequency of plane wave.
x0 : (3,) array_like
Position of plane wave.
n0 : (3,) array_like
Normal vector (direction) of plane wave.
grid : triple of array_like
The grid that is used for the sound field calculations.
See `sfs.util.xyz_grid()`.
c : float, optional
Speed of sound.
rho0 : float, optional
Static density of air.
Returns
-------
`XyzComponents`
Averaged intensity at positions given by *grid*.
Notes
-----
.. math::
I(\x,\w) = \frac{1}{2\rho c} \n
"""
if c is None:
c = _default.c
if rho0 is None:
rho0 = _default.rho0
i = 1 / (2 * rho0 * c)
return _util.XyzComponents([i * n for n in n0])
def pulsating_sphere(omega, center, radius, amplitude, grid, *, inside=False,
c=None):
"""Sound pressure of a pulsating sphere.
Parameters
---------
omega : float
Frequency of pulsating sphere
center : (3,) array_like
Center of sphere.
radius : float
Radius of sphere.
amplitude : float
Amplitude of displacement.
grid : triple of array_like
The grid that is used for the sound field calculations.
See `sfs.util.xyz_grid()`.
inside : bool, optional
As default, `numpy.nan` is returned for inside the sphere.
If ``inside=True``, the sound field inside the sphere is extrapolated.
c : float, optional
Speed of sound.
Returns
-------
numpy.ndarray
Sound pressure at positions given by *grid*.
If ``inside=False``, `numpy.nan` is returned for inside the sphere.
Examples
--------
.. plot::
:context: close-figs
radius = 0.25
amplitude = 1 / (radius * omega * sfs.default.rho0 * sfs.default.c)
p = sfs.fd.source.pulsating_sphere(omega, x0, radius, amplitude, grid)
sfs.plot2d.amplitude(p, grid)
plt.title("Sound Pressure of a Pulsating Sphere")
"""
if c is None:
c = _default.c
k = _util.wavenumber(omega, c)
center = _util.asarray_1d(center)
grid = _util.as_xyz_components(grid)
distance = _np.linalg.norm(grid - center)
theta = _np.arctan(1, k * distance)
impedance = _default.rho0 * c * _np.cos(theta) * _np.exp(1j * theta)
radial_velocity = 1j * omega * amplitude * radius / distance \
* _np.exp(-1j * k * (distance - radius))
if not inside:
radial_velocity[distance <= radius] = _np.nan
return impedance * radial_velocity
def pulsating_sphere_velocity(omega, center, radius, amplitude, grid, *,
c=None):
"""Particle velocity of a pulsating sphere.
Parameters
---------
omega : float
Frequency of pulsating sphere
center : (3,) array_like
Center of sphere.
radius : float
Radius of sphere.
amplitude : float
Amplitude of displacement.
grid : triple of array_like
The grid that is used for the sound field calculations.
See `sfs.util.xyz_grid()`.
c : float, optional
Speed of sound.
Returns
-------
`XyzComponents`
Particle velocity at positions given by *grid*.
`numpy.nan` is returned for inside the sphere.
Examples
--------
.. plot::
:context: close-figs
v = sfs.fd.source.pulsating_sphere_velocity(omega, x0, radius, amplitude, vgrid)
sfs.plot2d.amplitude(p, grid)
sfs.plot2d.vectors(v, vgrid)
plt.title("Sound Pressure and Particle Velocity of a Pulsating Sphere")
"""
if c is None:
c = _default.c
k = _util.wavenumber(omega, c)
grid = _util.as_xyz_components(grid)
center = _util.asarray_1d(center)
offset = grid - center
distance = _np.linalg.norm(offset)
radial_velocity = 1j * omega * amplitude * radius / distance \
* _np.exp(-1j * k * (distance - radius))
radial_velocity[distance <= radius] = _np.nan
return _util.XyzComponents(
[radial_velocity * o / distance for o in offset])
def _duplicate_zdirection(p, grid):
"""If necessary, duplicate field in z-direction."""
gridshape = _np.broadcast(*grid).shape
if len(gridshape) > 2:
return _np.tile(p, [1, 1, gridshape[2]])
else:
return p
def _hankel2_0(x):
"""Wrapper for Hankel function of the second type using fast versions
of the Bessel functions of first/second kind in scipy"""
return _special.j0(x) - 1j * _special.y0(x)
