Python linear2DArray 예제들

예제 #1

파일: filter_sim_routines.py 프로젝트: LCAV/sketchrls

def shoebox_rir(room_dim, source, mic):

    # Some simulation parameters
    Fs = 8000
    t0 = 1.0 / (Fs * np.pi * 1e-2)  # starting time function of sinc decay in RIR response
    absorption = 0.90
    max_order_sim = 10

    # create a microphone array
    R = pra.linear2DArray(mic, 1, 0, 1)
    mics = pra.Beamformer(R, Fs)

    # create the room with sources and mics
    room1 = pra.Room.shoeBox2D(
        [0, 0], room_dim, Fs, t0=t0, max_order=max_order_sim, absorption=absorption, sigma2_awgn=0
    )

    # add source and interferer
    room1.addSource(source)
    room1.addMicrophoneArray(mics)

    room1.compute_RIR()
    h = room1.rir[0][0]

    return h

예제 #2

파일: filter_sim_routines.py 프로젝트: ml-lab/sketchrls

def shoebox_rir(room_dim, source, mic):

    # Some simulation parameters
    Fs = 8000
    t0 = 1./(Fs*np.pi*1e-2)  # starting time function of sinc decay in RIR response
    absorption = 0.90
    max_order_sim = 10

    # create a microphone array
    R = pra.linear2DArray(mic, 1, 0, 1) 
    mics = pra.Beamformer(R, Fs)

    # create the room with sources and mics
    room1 = pra.Room.shoeBox2D(
        [0,0],
        room_dim,
        Fs,
        t0 = t0,
        max_order=max_order_sim,
        absorption=absorption,
        sigma2_awgn=0)

    # add source and interferer
    room1.addSource(source)
    room1.addMicrophoneArray(mics)

    room1.compute_RIR()
    h = room1.rir[0][0]

    return h

예제 #3

파일: RakePerceptual.py 프로젝트: runngezhang/TimeDomainAcousticRakeReceiver

max_order_design = 1  # maximum image generation used in design
shape = 'Linear'  # array shape
Lg_t = 0.050  # Filter size in seconds
Lg = np.ceil(Lg_t * Fs)  # Filter size in samples
delay = 0.03

# define the FFT length
N = 1024

# create a microphone array
if shape is 'Circular':
    R = pra.circular2DArray(mic1, M, phi, d * M / (2 * np.pi))
elif shape is 'Poisson':
    R = pra.poisson2DArray(mic1, M, d)
else:
    R = pra.linear2DArray(mic1, M, phi, d)
mics = pra.Beamformer(R, Fs, N=N, Lg=Lg)

# The first signal (of interest) is singing
rate1, signal1 = wavfile.read('samples/singing_' + str(Fs) + '.wav')
signal1 = np.array(signal1, dtype=float)
signal1 = pra.normalize(signal1)
signal1 = pra.highpass(signal1, Fs)
delay1 = 0.

# the second signal (interferer) is some german speech
rate2, signal2 = wavfile.read('samples/german_speech_' + str(Fs) + '.wav')
signal2 = np.array(signal2, dtype=float)
signal2 = pra.normalize(signal2)
signal2 = pra.highpass(signal2, Fs)
delay2 = 1.

예제 #4

파일: RakeMaxUDR.py 프로젝트: LCAV/TimeDomainAcousticRakeReceiver

d = 0.04                # distance between microphones
phi = 0.                # angle from horizontal
max_order_design = 1    # maximum image generation used in design
shape = 'Linear'        # array shape
Lg_t = 0.05             # Filter size in seconds
Lg = np.ceil(Lg_t*Fs)   # Filter size in samples
delay = 0.02

# define the FFT length
N = 1024

# create a microphone array
if shape is 'Circular':
    R = pra.circular2DArray(mic1, M, phi, d*M/(2*np.pi)) 
else:
    R = pra.linear2DArray(mic1, M, phi, d) 
mics = pra.Beamformer(R, Fs, N=N, Lg=Lg)

# The first signal (of interest) is singing
rate1, signal1 = wavfile.read('samples/singing_'+str(Fs)+'.wav')
signal1 = np.array(signal1, dtype=float)
signal1 = pra.normalize(signal1)
signal1 = pra.highpass(signal1, Fs)
delay1 = 0.

# the second signal (interferer) is some german speech
rate2, signal2 = wavfile.read('samples/german_speech_'+str(Fs)+'.wav')
signal2 = np.array(signal2, dtype=float)
signal2 = pra.normalize(signal2)
signal2 = pra.highpass(signal2, Fs)
delay2 = 1.