from libs.scheduler import run_command
from libs.utils import get_logger, write_wav
from libs.opts import StrToFloatTupleAction, StrToBoolAction, str2tuple
from libs.sampler import UniformSampler
try:
import pyrirgen
pyrirgen_available = True
except ImportError:
pyrirgen_available = False
try:
import gpuRIR as pygpurir
gpu_rir_available = True
pygpurir.activateMixedPrecision(False)
pygpurir.activateLUT(True)
except ImportError:
gpu_rir_available = False
if shutil.which("rir-simulate"):
cpp_rir_available = True
else:
cpp_rir_available = False
plt.switch_backend("agg")
default_dpi = 200
default_fmt = "jpg"
logger = get_logger(__name__)
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
""" Example for simulating the recording of a moving source with a microphone array.
You need to have a 'source_signal.wav' audio file to use it as source signal and it will generate
the file 'filtered_signal.wav' with the stereo recording simulation.
"""
import numpy as np
import matplotlib.pyplot as plt
from scipy.io import wavfile
import gpuRIR
gpuRIR.activateMixedPrecision(False)
fs, source_signal = wavfile.read('source_signal.wav')
room_sz = [3, 4, 2.5] # Size of the room [m]
traj_pts = 64 # Number of trajectory points
pos_traj = np.tile(np.array([0.0, 3.0, 1.0]), (traj_pts, 1))
pos_traj[:,
0] = np.linspace(0.1, 2.9,
traj_pts) # Positions of the trajectory points [m]
nb_rcv = 2 # Number of receivers
pos_rcv = np.array([[1.4, 1, 1.5], [1.6, 1,
1.5]]) # Position of the receivers [m]
orV_rcv = np.array([[-1, 0, 0], [1, 0, 0]])
mic_pattern = "card" # Receiver polar pattern
T60 = 0.6 # Time for the RIR to reach 60dB of attenuation [s]
att_diff = 15.0 # Attenuation when start using the diffuse reverberation model [dB]
att_max = 60.0 # Attenuation at the end of the simulation [dB]
beta = gpuRIR.beta_SabineEstimation(room_sz, T60) # Reflection coefficients
