"""Module for the radiosity simulation."""
import matplotlib as mpl
import numpy as np
import pyfar as pf
import sofar as sf
from sparrowpy.geometry import Polygon, SoundSource
[docs]
class PatchesKang(Polygon):
"""Class representing patches of a polygon."""
patches: list[Polygon]
other_wall_ids: list[int] # ids of the patches
form_factors: np.ndarray
E_matrix: np.ndarray
wall_id: int
scattering: np.ndarray
absorption: np.ndarray
n_bins: int
max_size: float
E_sampling_rate: int
E_n_samples: int
sound_attenuation_factor: np.ndarray
def __init__(
self, polygon, max_size, other_wall_ids, wall_id,
scattering=1, absorption=0.1, sound_attenuation_factor=0,
E_matrix=None):
"""Init Directional Patches.
Parameters
----------
polygon : Polygon
Wall that should be distributed into patches.
max_size : float
maximal patchsize in meters.
other_wall_ids : list[int]
Ids of the other walls.
wall_id : int
id of this Patch
scattering : np.ndarray, optional
Scattering coefficient of this wall for each freqeuncy
bin, by default 1
absorption : np.ndarray, optional
Absorption coefficient of this wall for each freqeuncy
bin, by default 0.1
sound_attenuation_factor : _type_, optional
Air attenuation factor for each frequncy bin, by default None
E_matrix : np.ndarray, optional
Energy exchange results, if already calcualted , by default None
"""
Polygon.__init__(self, polygon.pts, polygon.up_vector, polygon.normal)
min_point = np.min(polygon.pts, axis=0)
max_point = np.max(polygon.pts, axis=0)
size = max_point - min_point
patch_nums = np.array([int(n) for n in size/max_size])
real_size = size/patch_nums
self.scattering = np.atleast_1d(scattering)
self.absorption = np.atleast_1d(absorption)
self.sound_attenuation_factor = np.atleast_1d(sound_attenuation_factor)
assert self.scattering.size == self.absorption.size
assert self.scattering.size == self.sound_attenuation_factor.size
self.n_bins = self.absorption.size
if patch_nums[2] == 0:
x_idx = 0
y_idx = 1
if patch_nums[1] == 0:
x_idx = 0
y_idx = 2
if patch_nums[0] == 0:
x_idx = 1
y_idx = 2
x_min = np.min(polygon.pts.T[x_idx])
y_min = np.min(polygon.pts.T[y_idx])
patches = []
for i_x in range(patch_nums[x_idx]):
for i_y in range(patch_nums[y_idx]):
points = polygon.pts.copy()
points[0, x_idx] = x_min + i_x * real_size[x_idx]
points[0, y_idx] = y_min + i_y * real_size[y_idx]
points[1, x_idx] = x_min + (i_x+1) * real_size[x_idx]
points[1, y_idx] = y_min + i_y * real_size[y_idx]
points[3, x_idx] = x_min + i_x * real_size[x_idx]
points[3, y_idx] = y_min + (i_y+1) * real_size[y_idx]
points[2, x_idx] = x_min + (i_x+1) * real_size[x_idx]
points[2, y_idx] = y_min + (i_y+1) * real_size[y_idx]
patch = Polygon(points, polygon.up_vector, polygon.normal)
patches.append(patch)
self.patches = patches
self.other_wall_ids = np.atleast_1d(np.array(
other_wall_ids, dtype=int))
self.wall_id = wall_id
self.max_size = max_size
if E_matrix is not None:
self.E_matrix = np.array(E_matrix)
self.E_n_samples = self.E_matrix.shape[3]
[docs]
def to_dict(self) -> dict:
"""Convert this object to dictionary. Used for read write."""
return {
'pts': self.pts,
'up_vector': self.up_vector,
'normal': self.normal,
'max_size': self.max_size,
'other_wall_ids': self.other_wall_ids,
'wall_id': self.wall_id,
'scattering': self.scattering,
'absorption': self.absorption,
'sound_attenuation_factor': self.sound_attenuation_factor,
'E_matrix': self.E_matrix,
}
[docs]
@classmethod
def from_dict(cls, input_dict: dict):
"""Create an object from a dictionary. Used for read write."""
return cls(
Polygon.from_dict(input_dict),
input_dict['max_size'],
input_dict['other_wall_ids'],
input_dict['wall_id'],
input_dict['scattering'],
input_dict['absorption'],
input_dict['sound_attenuation_factor'],
E_matrix=input_dict['E_matrix'])
[docs]
def plot(self, ax: mpl.axes.Axes = None, color=None):
"""Plot the patches."""
for patch in self.patches:
patch.plot_point(ax, color)
self.plot_view_up(ax, color)
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def init_energy_exchange(
self, max_order_k, ir_length_s, source, sampling_rate,
speed_of_sound):
"""Initialize the energy exchange Matrix with source energy.
It init the matrix self.E_matrix and add source energy after (6).
Parameters
----------
max_order_k : int
max order of energy exchange iterations.
ir_length_s : float
length of the impulse response in seconds.
source : SoundSource
sound source with ``sound_power`` and ``position``
sampling_rate : int, optional
Sampling rate of impulse response.
speed_of_sound : float, optional
speed of sound in m/s.
"""
self.E_sampling_rate = sampling_rate
self.E_n_samples = int(ir_length_s*sampling_rate)
self.E_matrix = np.zeros((
self.n_bins,
max_order_k+1, # order of energy exchange
len(self.patches), # receiver ids of patches
self.E_n_samples, # impulse response G_k(t)_receiverpatch
))
for i_receiver, receiver_patch in enumerate(self.patches):
source_pos = source.position.copy()
receiver_pos = receiver_patch.center.copy()
distance = np.linalg.norm(receiver_pos-source_pos)
delay_seconds = distance/speed_of_sound
delay_samples = int(delay_seconds*self.E_sampling_rate)
if np.abs(receiver_patch.normal[2]) > 0.99:
i = 2
indexes = [0, 1, 2]
elif np.abs(receiver_patch.normal[1]) > 0.99:
indexes = [2, 0, 1]
i = 1
elif np.abs(receiver_patch.normal[0]) > 0.99:
i = 0
indexes = [1, 2, 0]
else:
raise AssertionError()
offset = receiver_pos[i]
source_pos[i] = np.abs(source_pos[i] - offset)
receiver_pos[i] = np.abs(receiver_pos[i] - offset)
dl = receiver_pos[indexes[0]]
dm = receiver_pos[indexes[1]]
dn = receiver_pos[indexes[2]]
dd_l = receiver_patch.size[indexes[0]]
dd_m = receiver_patch.size[indexes[1]]
S_x = source_pos[indexes[0]]
S_y = source_pos[indexes[1]]
S_z = source_pos[indexes[2]]
energy = _init_energy_exchange(
dl, dm, dn, dd_l, dd_m, S_x, S_y, S_z,
source.sound_power, self.absorption, distance,
self.sound_attenuation_factor, self.n_bins)
self.E_matrix[:, 0, i_receiver, delay_samples] += energy
[docs]
def calculate_energy_exchange(
self, patches_list, current_order_k, speed_of_sound,
E_sampling_rate):
"""Calculate the energy exchange for a given order.
It implements formula 18 and save the result in self.E_matrix.
Parameters
----------
patches_list : list[Patches]
list of all patches
current_order_k : int
Order k
speed_of_sound : int, optional
speed of sound in m/s.
E_sampling_rate : int, optional
Sampling rate of histogram.
"""
k = current_order_k # real k 1 .. max_k
for i_receiver, receiver_patch in enumerate(self.patches):
receiver = receiver_patch.center
for wall_id in self.other_wall_ids:
wall = patches_list[wall_id]
for i_source, source_patch in enumerate(wall.patches):
source = source_patch.center
# distance between source and receiver patches
distance = np.linalg.norm(receiver-source)
delay_seconds = distance/speed_of_sound
# sample delay for the given distance
delay_samples = int(delay_seconds*E_sampling_rate)
for i_frequency in range(self.n_bins):
# access energy matrix of source patch, previous order
A_k_minus_1 = wall.E_matrix[
i_frequency, k-1, i_source, :]
# delay IR by delay_samples
A_k_minus1_delay = _add_delay(
A_k_minus_1, delay_samples)
# find form factor of source and receiver patches
form_factor = wall.get_form_factor(
patches_list, i_source, self.wall_id, i_receiver)
alpha = self.absorption[i_frequency]
# multiply delayed IR by form factor
energy = A_k_minus1_delay * form_factor \
* self.scattering[i_frequency] * \
(1-alpha) * np.exp(
-self.sound_attenuation_factor[
i_frequency] * distance)
# add energy to energy matrix of self
self.E_matrix[i_frequency, k, i_receiver, :] += energy
#
[docs]
def energy_at_receiver(
self, max_order, receiver,
speed_of_sound, sampling_rate):
"""Calculate the energy at the receiver.
this is supposed to be from just one wall
Parameters
----------
max_order : _type_
_description_
sound_source : _type_
_description_
receiver : _type_
_description_
speed_of_sound : float, optional
_description_
sampling_rate : int, optional
_description_
Returns
-------
_type_
_description_
"""
energy_response = np.zeros((self.n_bins, self.E_n_samples))
for i_source, source_patch in enumerate(self.patches):
source_pos = source_patch.center
receiver_pos = receiver.position
difference = np.abs(receiver_pos-source_pos)
R = np.linalg.norm(source_pos-receiver_pos)
delay = int(R/speed_of_sound * sampling_rate)
cos_xi = np.abs(np.sum(source_patch.normal*difference)) / \
np.linalg.norm(source_pos-receiver_pos)
for k in range(max_order+1):
for i_frequency in range(self.n_bins):
energy = self.E_matrix[i_frequency, k, i_source, :]
delayed_energy = _add_delay(energy, delay)
# Equation 20
factor = cos_xi * (np.exp(
-self.sound_attenuation_factor[i_frequency]*R)) / (
np.pi * R**2)
receiver_energy = delayed_energy * factor
if factor <0:
print(factor)
energy_response[i_frequency, ...] += receiver_energy
return energy_response
[docs]
class PatchesDirectionalKang(PatchesKang):
"""Class representing patches with directional scattering behaviour."""
directivity_data: np.ndarray
directivity_sources: pf.Coordinates
directivity_receivers: pf.Coordinates
def __init__(
self, polygon, max_size, other_wall_ids, wall_id,
data, sources, receivers, absorption=None,
sound_attenuation_factor=None, already_converted=False,
E_matrix=None):
"""Init Directional Patches.
Parameters
----------
polygon : Polygon
Wall that should be distributed into patches.
max_size : float
maximal patchsize in meters.
other_wall_ids : list[int]
Ids of the other walls.
wall_id : int
id of this Patch
data : pf.FrequencyData
Directional Data
sources : pf.Coordinates
source positions of the directivity data
receivers : pf.Coordinates
receiver positions of the directivity data
absorption : np.ndarray, optional
Absorption coefficient of this wall for each freqeuncy
bin, by default None
sound_attenuation_factor : _type_, optional
Air attenuation factor for each frequncy bin, by default None
already_converted : bool, optional
is ``sources`` and ``receivers`` already converted, by default
False.
E_matrix : np.ndarray, optional
Energy exchange results, if already calcualted , by default None
"""
self.directivity_data = data
if absorption is None:
absorption = np.zeros_like(data.frequencies)+0.1
if sound_attenuation_factor is None:
sound_attenuation_factor = np.zeros_like(data.frequencies)
PatchesKang.__init__(
self, polygon, max_size, other_wall_ids, wall_id,
scattering=np.ones_like(data.frequencies),
absorption=absorption,
sound_attenuation_factor=sound_attenuation_factor,
E_matrix=E_matrix,
)
self.directivity_data.freq = np.abs(self.directivity_data.freq)
self.directivity_sources = sources
self.directivity_receivers = receivers
if not already_converted:
self.directivity_data.freq *= np.pi
o1 = pf.Orientations.from_view_up(
polygon.normal, polygon.up_vector)
o2 = pf.Orientations.from_view_up([0, 0, 1], [1, 0, 0])
o_diff = o1.inv()*o2
euler = o_diff.as_euler('xyz', True).flatten()
self.directivity_receivers.rotate('xyz', euler)
self.directivity_receivers.radius = 1
self.directivity_sources.rotate('xyz', euler)
self.directivity_sources.radius = 1
[docs]
@classmethod
def from_sofa(cls, polygon, max_size, other_wall_ids, wall_id,
wall_directivity_path, absorption=None,
sound_attenuation_factor=None):
"""Create object with directional data from sofa."""
sofa = sf.read_sofa(wall_directivity_path, True, False)
data, sources, receivers = pf.io.convert_sofa(sofa)
sources.weights = sofa.SourceWeights
receivers.weights = sofa.ReceiverWeights
assert sources.weights is not None, "No source weights in sofa file"
assert receivers.weights is not None, \
"No receiver weights in sofa file"
return cls(
polygon, max_size, other_wall_ids, wall_id,
data, sources, receivers, absorption=absorption,
sound_attenuation_factor=sound_attenuation_factor)
[docs]
def to_dict(self) -> dict:
"""Convert this object to dictionary. Used for read write."""
return {
**PatchesKang.to_dict(self),
'directivity_data': self.directivity_data.freq,
'directivity_data_frequencies': self.directivity_data.frequencies,
'directivity_sources': self.directivity_sources.cartesian,
'directivity_receivers': self.directivity_receivers.cartesian,
'directivity_sources_weights': self.directivity_sources.weights,
'directivity_receivers_weights': \
self.directivity_receivers.weights,
}
[docs]
@classmethod
def from_dict(cls, input_dict: dict):
"""Create an object from a dictionary. Used for read write."""
data = pf.FrequencyData(
input_dict['directivity_data'],
input_dict['directivity_data_frequencies'])
sources = pf.Coordinates(
np.array(input_dict['directivity_sources']).T[0],
np.array(input_dict['directivity_sources']).T[1],
np.array(input_dict['directivity_sources']).T[2],
weights=input_dict['directivity_sources_weights'])
receivers = pf.Coordinates(
np.array(input_dict['directivity_receivers']).T[0],
np.array(input_dict['directivity_receivers']).T[1],
np.array(input_dict['directivity_receivers']).T[2],
weights=input_dict['directivity_receivers_weights'])
return cls(
Polygon.from_dict(input_dict),
max_size=input_dict['max_size'],
other_wall_ids=input_dict['other_wall_ids'],
wall_id=input_dict['wall_id'],
data=data,
sources=sources,
receivers=receivers,
absorption=input_dict['absorption'],
sound_attenuation_factor=input_dict['sound_attenuation_factor'],
E_matrix=input_dict['E_matrix'],
already_converted=True,
)
[docs]
def init_energy_exchange(
self, max_order_k, ir_length_s, source,
sampling_rate, speed_of_sound):
"""Initialize the energy exchange Matrix with source energy.
Parameters
----------
max_order_k : int
max order of energy exchange iterations.
ir_length_s : float
length of the impulse response in seconds.
source : SoundSource
Sound source with ``sound_power`` and ``position``
sampling_rate : int
Sample rate of histogram, by default 1000 -> 1ms
speed_of_sound : float,
speed of sound in m/s.
"""
PatchesKang.init_energy_exchange(
self, max_order_k, ir_length_s, source, sampling_rate,
speed_of_sound=speed_of_sound)
test = self.E_matrix.copy()
self.E_matrix = self.E_matrix[..., np.newaxis]
self.E_matrix = np.tile(
self.E_matrix, self.directivity_receivers.csize)
assert np.sum(test-self.E_matrix[..., 0]) == 0
patches_center = np.array([patch.center for patch in self.patches])
difference = source.position - patches_center
difference = pf.Coordinates(
difference.T[0], difference.T[1], difference.T[2])
source_idx = self.directivity_sources.find_nearest(difference)[0][0]
# get directional scattering coefficient for
# all incident angles x receiver
for i_frequency in range(self.directivity_data.n_bins):
scattering = self.directivity_data.freq[source_idx, :, i_frequency]
if len(self.patches) == 1:
self.E_matrix[i_frequency, 0, 0, :, :] *= np.abs(
scattering)
else:
for i_patch in range(len(self.patches)):
self.E_matrix[i_frequency, 0, i_patch, :, :] *= np.abs(
scattering[i_patch, :])
[docs]
def calculate_energy_exchange(
self, patches_list, current_order_k, speed_of_sound,
E_sampling_rate):
"""Calculate the energy exchange for a given order.
It implements formula 18 and save the result in self.E_matrix.
Parameters
----------
patches_list : list[Patches]
list of all patches
current_order_k : int
Order k
speed_of_sound : int, optional
speed of sound in m/s.
E_sampling_rate : int, optional
Sampling rate of histogram, e.g. 1000 Hz -> 1ms.
"""
k = current_order_k # real k 1 .. max_k
for i_receiver, receiver_patch in enumerate(self.patches):
receiver = receiver_patch.center
for wall_id in self.other_wall_ids:
wall = patches_list[wall_id]
for i_source, source_patch in enumerate(wall.patches):
source = source_patch.center
# distance between source and receiver patches
distance = np.linalg.norm(receiver-source)
delay_seconds = distance/speed_of_sound
# sample delay for the given distance
delay_samples = int(delay_seconds*E_sampling_rate)
# find form factor of source and receiver patches
form_factor = wall.get_form_factor(
patches_list, i_source, self.wall_id, i_receiver)
for i_frequency in range(self.directivity_data.n_bins):
# access energy matrix of source patch, previous order
A_k_minus_1 = wall.E_matrix[
i_frequency, k-1, i_source, :, :]
# delay IR by delay_samples
A_k_minus1_delay = _add_delay(
A_k_minus_1, delay_samples, 0)
# multiply delayed IR by form factor
alpha = self.absorption[i_frequency]
energy = A_k_minus1_delay * form_factor * (
1-alpha) * np.exp(
-self.sound_attenuation_factor[i_frequency] \
* distance)
# find directional scattering coefficient
difference = source_patch.center - \
receiver_patch.center
difference = pf.Coordinates(
difference.T[0], difference.T[1], difference.T[2])
source_idx = self.directivity_sources.find_nearest(
difference)[0][0]
# get directional scattering coefficient for
# all incident angles x receiver
scattering = self.directivity_data.freq[
source_idx, :, i_frequency]
energy *= scattering
# add energy to energy matrix of self
self.E_matrix[
i_frequency, k, i_receiver, :, :] += energy
[docs]
def energy_at_receiver(
self, max_order, receiver,
speed_of_sound, sampling_rate):
"""Calculate the energy at the receiver.
this is supposed to be from just one wall
Parameters
----------
max_order : int
max order of energy exchange iterations.
sound_source : SoundSource
sound source with ``sound_power`` and ``position``
receiver : Receiver
receiver object with position.
speed_of_sound : float, optional
Speed of sound in m/s.
sampling_rate : int, optional
_description_, by default 1000
Returns
-------
_type_
_description_
"""
energy_response = np.zeros((self.n_bins, self.E_n_samples))
for i_source, source_patch in enumerate(self.patches):
source_pos = source_patch.center
receiver_pos = receiver.position
cos_xi = np.abs(np.sum(
source_patch.normal*np.abs(receiver_pos-source_pos))) / \
np.linalg.norm(source_pos-receiver_pos)
difference = receiver_pos-source_pos
difference = pf.Coordinates(
difference[0], difference[1], difference[2])
difference.radius = 1
R = np.linalg.norm(receiver_pos-source_pos)
delay = int(R/speed_of_sound * sampling_rate)
i_patch = self.directivity_receivers.find_nearest(
difference)[0][0]
for k in range(max_order+1):
for i_frequency in range(self.n_bins):
energy = self.E_matrix[
i_frequency, k, i_source, :, i_patch]
delayed_energy = _add_delay(energy, delay, axis=-1)
# Equation 20
factor = cos_xi * (np.exp(
-self.sound_attenuation_factor[i_frequency]*R)) / (
np.pi * R**2)
if factor <0:
print(factor)
receiver_energy = delayed_energy * factor
energy_response[i_frequency, ...] += receiver_energy
return energy_response
def _init_energy_exchange(
dl, dm, dn, dd_l, dd_m, S_x, S_y, S_z,
sound_power, absorption, distance, attenuation, n_bins):
half_l = dd_l/2
half_m = dd_m/2
sin_phi_delta = (dl + half_l - S_x)/ (np.sqrt(np.square(
dl+half_l-S_x) + np.square(dm-S_y) + np.square(dn-S_z)))
test1 = (dl - half_l) <= S_x
test2 = S_x <= (dl + half_l)
k_phi = -1 if test1 and test2 else 1
sin_phi = k_phi * (dl - half_l - S_x) / (np.sqrt(np.square(
dl-half_l-S_x) + np.square(dm-S_y) + np.square(dn-S_z)))
if (sin_phi_delta-sin_phi) < 1e-11:
sin_phi *= -1
plus = np.arctan(np.abs((dm+half_m-S_y)/np.abs(S_z)))
minus = np.arctan(np.abs((dm-half_m-S_y)/np.abs(S_z)))
test1 = (dm - half_m) <= S_y
test2 = S_y <= (dm + half_m)
k_beta = -1 if test1 and test2 else 1
beta = np.abs(plus-(k_beta*minus))
# don't forget to add constants
# constants are
energies = np.zeros(n_bins)
for i_frequency in range(n_bins):
alpha = absorption[i_frequency]
constant = sound_power * (1-alpha) * (
np.exp(-attenuation[i_frequency]*distance))
energy = constant * (
np.abs(sin_phi_delta-sin_phi) ) * beta / (4*np.pi)
energies[i_frequency] = energy
return energies
def _add_delay(ir, delay_samples, axis=-1):
"""Add delay to impulse response.
Parameters
----------
ir : np.ndarray
impulse response which should be shifted.
delay_samples : int
delay samples.
axis : int, optional
axis which should be rolled, by default -1
Returns
-------
ir : np.ndarray
shifted impulse response.
"""
## add delay
if delay_samples > ir.shape[axis]:
raise ValueError(
'length of ir is longer then ir delay is '
f'{delay_samples} > {ir.shape[-1]}')
ir_delayed = np.roll(ir, delay_samples, axis=axis)
return ir_delayed
def _calc_incident_direction(position, normal, up_vector, target_position):
"""Calculate the incident direction of a sound wave.
Parameters
----------
position : np.ndarray
Position of the wall.
normal : np.ndarray
Normal vector of the wall.
up_vector : np.ndarray
Up vector of the wall.
target_position : np.ndarray
Position of the source or other wall.
Returns
-------
pf.Coordinates
Incident direction of the sound wave.
"""
direction = np.array(target_position) - np.array(position)
x_dash = np.cross(normal, up_vector)
y_dash = np.array(up_vector)
z_dash = -np.array(normal)
w_x_local = np.dot(direction, x_dash)
w_y_local = np.dot(direction, y_dash)
w_z_local = np.dot(direction, z_dash)
azimuth = np.arctan2(-w_x_local, -w_z_local)
w_y_local_normalized = w_y_local / np.linalg.norm(
[w_x_local, w_y_local, w_z_local])
elevation = np.arcsin(w_y_local_normalized)
return pf.Coordinates.from_spherical_colatitude(
azimuth, elevation, 1)
[docs]
class RadiosityKang():
"""Radiosity object simulation."""
speed_of_sound: float
max_order_k: int
sampling_rate: int
patch_size: float
ir_length_s: float
patch_list: list[PatchesKang]
def __init__(
self, walls, patch_size, max_order_k, ir_length_s,
speed_of_sound=346.18, sampling_rate=1000, absorption=0.1,
source=None):
"""Create Radiosity Object for simulation.
Parameters
----------
walls : list[Polygon]
list of patches
patch_size : float
maximal patchsize in meters.
max_order_k : int
max order of energy exchange iterations.
ir_length_s : float
length of ir in seconds.
speed_of_sound : float, optional
Speed of sound in m/s, by default 346.18 m/s
sampling_rate : int, optional
sampling rate of the Energy histogram, by default 1000 -> 1ms
absorption: np.ndarray
Absorption coefficient of this wall for each frequency bin
source : SoundSource, optional
Source object, by default None, can be added later.
"""
self.speed_of_sound = speed_of_sound
self.max_order_k = max_order_k
self.sampling_rate = sampling_rate
self.patch_size = patch_size
self.ir_length_s = ir_length_s
# A. Patch division
patch_list = []
n_patches = len(walls)
for i, wall in enumerate(walls):
index_list = [j for j in range(n_patches) if j != i]
patches = wall if isinstance(wall, PatchesKang) else PatchesKang(
wall, self.patch_size, index_list, i,absorption=absorption)
patch_list.append(patches)
self.patch_list = patch_list
if source is not None:
self.source = source
[docs]
def to_dict(self) -> dict:
"""Convert this object to dictionary. Used for read write."""
is_source = hasattr(self, 'source')
source = self.source if is_source else None
return {
'patch_size': self.patch_size,
'max_order_k': self.max_order_k,
'ir_length_s': self.ir_length_s,
'speed_of_sound': self.speed_of_sound,
'sampling_rate': self.sampling_rate,
'patches': [patch.to_dict() for patch in self.patch_list],
'source_position': source.position if is_source else None,
'source_view': source.view if is_source else None,
'source_up': source.up if is_source else None,
}
[docs]
@classmethod
def from_dict(cls, input_dict: dict):
"""Create an object from a dictionary. Used for read write."""
patch_list = [
PatchesKang.from_dict(patch) for patch in input_dict['patches']]
source = None
if input_dict is not None:
source = SoundSource(
input_dict['source_position'],
input_dict['source_view'], input_dict['source_up'])
obj = cls(
patch_list, input_dict['patch_size'], input_dict['max_order_k'],
input_dict['ir_length_s'],
input_dict['speed_of_sound'], input_dict['sampling_rate'],
source=source)
return obj
[docs]
def run(self, source):
"""Execute the radiosity algorithm."""
self.source = source
# B. First-order patch sources
for patches in self.patch_list:
patches.init_energy_exchange(
self.max_order_k, self.ir_length_s, source,
sampling_rate=self.sampling_rate,
speed_of_sound=self.speed_of_sound)
# C. Form factors
if len(self.patch_list) > 1:
for patches in self.patch_list:
patches.calculate_form_factor(self.patch_list)
# D. Energy exchange between patches
if len(self.patch_list) > 1:
for k in range(1, self.max_order_k+1):
for patches in self.patch_list:
patches.calculate_energy_exchange(
self.patch_list, k, speed_of_sound=self.speed_of_sound,
E_sampling_rate=self.sampling_rate)
[docs]
def energy_at_receiver(
self, receiver, max_order_k=None, ignore_direct=False):
"""Return the energetic impulse response at the receiver."""
ir = 0
if max_order_k is None:
max_order_k = self.max_order_k
M_value = self.patch_list[0].sound_attenuation_factor
for patches in self.patch_list:
ir += patches.energy_at_receiver(
max_order_k, receiver,
speed_of_sound=self.speed_of_sound,
sampling_rate=self.sampling_rate)
if not ignore_direct:
r = np.sqrt(np.sum((receiver.position-self.source.position)**2))
direct_sound = (1/(4 * np.pi * np.square(r))) * np.exp(-M_value*r)
delay_dir = int(r/self.speed_of_sound*self.sampling_rate)
ir[:, delay_dir] += direct_sound
return ir
[docs]
def write(self, filename, compress=True):
"""Write the object to a far file."""
pf.io.write(filename, compress=compress, **self.to_dict())
[docs]
@classmethod
def from_read(cls, filename):
"""Read the object to a far file."""
data = pf.io.read(filename)
return cls.from_dict(data)
[docs]
class DirectionalRadiosityKang():
"""Radiosity object for directional scattering coefficients."""
def __init__(
self, polygon_list, patch_size, max_order_k, ir_length_s,
sofa_path, speed_of_sound=346.18, sampling_rate=1000, source=None):
"""Create a Radiosity object for directional scattering coefficients.
Parameters
----------
polygon_list : list[PatchesDirectional]
list of patches
patch_size : float
maximal patchsize in meters.
max_order_k : int
max order of energy exchange iterations.
ir_length_s : float
length of ir in seconds.
sofa_path : Path, string, list of Path, list of string
path of directional scattering coefficients or list of path
for each Patch.
speed_of_sound : float, optional
Speed of sound in m/s, by default 346.18 m/s
sampling_rate : int, optional
sampling rate of the Energy histogram, by default 1000 -> 1ms
source : SoundSource, optional
Source object, by default None, can be added later.
"""
self.speed_of_sound = speed_of_sound
self.max_order_k = max_order_k
self.sampling_rate = sampling_rate
self.patch_size = patch_size
self.ir_length_s = ir_length_s
# A. Patch division
patch_list = []
n_points = len(polygon_list)
for i in range(n_points):
index_list = [j for j in range(n_points) if j != i]
path = sofa_path[i] if isinstance(sofa_path, list) else sofa_path
patches = polygon_list[i] if isinstance(
polygon_list[i], PatchesDirectionalKang) else \
PatchesDirectionalKang.from_sofa(
polygon_list[i], self.patch_size, index_list, i, path)
patch_list.append(patches)
self.patch_list = patch_list
n_bins = self.patch_list[0].n_bins
for patches in self.patch_list:
assert patches.n_bins == n_bins, \
'Number of bins is not the same for all patches. ' + \
f'{patches.n_bins} != {n_bins}'
if source is not None:
self.source = source
[docs]
def write(self, filename, compress=True):
"""Write the object to a far file."""
pf.io.write(filename, compress=compress, **self.to_dict())
[docs]
@classmethod
def from_read(cls, filename):
"""Read the object to a far file."""
data = pf.io.read(filename)
return cls.from_dict(data)
[docs]
def to_dict(self) -> dict:
"""Convert this object to dictionary. Used for read write."""
is_source = hasattr(self, 'source')
source = self.source if is_source else None
return {
'patch_size': self.patch_size,
'max_order_k': self.max_order_k,
'ir_length_s': self.ir_length_s,
'speed_of_sound': self.speed_of_sound,
'sampling_rate': self.sampling_rate,
'patches': [patch.to_dict() for patch in self.patch_list],
'source_position': source.position if is_source else None,
'source_view': source.view if is_source else None,
'source_up': source.up if is_source else None,
}
[docs]
@classmethod
def from_dict(cls, input_dict: dict):
"""Create an object from a dictionary. Used for read write."""
patch_list = [
PatchesDirectionalKang.from_dict(patch) for patch in input_dict[
'patches']]
source = None
if input_dict['source_position'] is not None:
source = SoundSource(
input_dict['source_position'],
input_dict['source_view'], input_dict['source_up'])
obj = cls(
patch_list, input_dict['patch_size'], input_dict['max_order_k'],
input_dict['ir_length_s'],
sofa_path=None,
speed_of_sound=input_dict['speed_of_sound'],
sampling_rate=input_dict['sampling_rate'],
source=source,
)
return obj
[docs]
def run(self, source):
"""Execute the radiosity algorithm."""
self.source = source
# B. First-order patch sources
for patches in self.patch_list:
patches.init_energy_exchange(
self.max_order_k, self.ir_length_s, source,
sampling_rate=self.sampling_rate,
speed_of_sound=self.speed_of_sound)
# C. Form factors
if len(self.patch_list) > 1:
for patches in self.patch_list:
patches.calculate_form_factor(self.patch_list)
# D. Energy exchange between patches
if len(self.patch_list) > 1:
for k in range(1, self.max_order_k+1):
for patches in self.patch_list:
patches.calculate_energy_exchange(
self.patch_list, k, speed_of_sound=self.speed_of_sound,
E_sampling_rate=self.sampling_rate)
[docs]
def energy_at_receiver(self, receiver, order_k=None):
"""Return the energetic impulse response at the receiver."""
ir = 0
if order_k is None:
order_k = self.max_order_k
M = self.patch_list[0].sound_attenuation_factor
for patches in self.patch_list:
ir += patches.energy_at_receiver(
order_k, receiver,
speed_of_sound=self.speed_of_sound,
sampling_rate=self.sampling_rate)
r = np.sqrt(np.sum((receiver.position-self.source.position)**2))
direct_sound = (1/(4 * np.pi * np.square(r))) * np.exp(-M*r)
delay_dir = int(r/self.speed_of_sound*self.sampling_rate)
ir[:, delay_dir] += direct_sound
return ir
