# sfs.td.source¶

Compute the sound field generated by a sound source.

The Green’s function describes the spatial sound propagation over time.

import matplotlib.pyplot as plt
import numpy as np
from scipy.signal import unit_impulse
import sfs

xs = 1.5, 1, 0  # source position
rs = np.linalg.norm(xs)  # distance from origin
ts = rs / sfs.default.c  # time-of-arrival at origin

# Impulsive excitation
fs = 44100
signal = unit_impulse(512), fs

grid = sfs.util.xyz_grid([-2, 3], [-1, 2], 0, spacing=0.02)


Functions

 point(xs, signal, observation_time, grid[, c]) Source model for a point source: 3D Green’s function. point_image_sources(x0, signal, …[, coeffs, c]) Point source in a rectangular room using the mirror image source model.
sfs.td.source.point(xs, signal, observation_time, grid, c=None)[source]

Source model for a point source: 3D Green’s function.

Calculates the scalar sound pressure field for a given point in time, evoked by source excitation signal.

Parameters
• xs ((3,) array_like) – Position of source in cartesian coordinates.

• signal ((N,) array_like + float) – Excitation signal consisting of (mono) audio data and a sampling rate (in Hertz). A DelayedSignal object can also be used.

• observation_time (float) – Observed point in time.

• 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 – Scalar sound pressure field, evaluated at positions given by grid.

Notes

$g(x-x_s,t) = \frac{1}{4 \pi |x - x_s|} \dirac{t - \frac{|x - x_s|}{c}}$

Examples

p = sfs.td.source.point(xs, signal, ts, grid)
sfs.plot2d.level(p, grid) sfs.td.source.point_image_sources(x0, signal, observation_time, grid, L, max_order, coeffs=None, c=None)[source]

Point source in a rectangular room using the mirror image source model.

Parameters
• x0 ((3,) array_like) – Position of source in cartesian coordinates.

• signal ((N,) array_like + float) – Excitation signal consisting of (mono) audio data and a sampling rate (in Hertz). A DelayedSignal object can also be used.

• observation_time (float) – Observed point in time.

• 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 – Scalar sound pressure field, evaluated at positions given by grid.

Examples

room = 5, 3, 1.5  # room dimensions
order = 2  # image source order
coeffs = .8, .8, .6, .6, .7, .7  # wall reflection coefficients
grid = sfs.util.xyz_grid([0, room], [0, room], 0, spacing=0.01)
p = sfs.td.source.point_image_sources(
xs, signal, 1.5 * ts, grid, room, order, coeffs)
sfs.plot2d.level(p, grid) 