# d_critical distance with defined angular position
azi = azi + np.pi # TODO: fix in srs library!!!
src_sph = np.array([azi, np.pi / 2 - incl, d_critical.mean()])
src_cart = masp.sph2cart(src_sph)
src = rec + src_cart
nSrc = src.shape[0]
# SH orders for receivers
rec_orders = np.array([1])
maxlim = rt60_0 # just stop if the echogram goes beyond that time ( or just set it to max(rt60) )
limits = np.ones(nBands) * maxlim # hardcoded!
abs_echograms = srs.compute_echograms_sh(room, src, rec, abs_wall, limits,
rec_orders)
irs = srs.render_rirs_sh(abs_echograms, band_centerfreqs, fs).squeeze().T
# Normalize as SN3D
irs *= np.sqrt(4 * np.pi)
irs *= np.asarray([1, 1. / np.sqrt(3), 1. / np.sqrt(3),
1. / np.sqrt(3)])[:, np.newaxis] ## ACN, SN3D
# %% SYNTHESIZE AUDIOS
af = audio_files[1]
# af = '/Volumes/Dinge/audio/410298__inspectorj__voice-request-26b-algeria-will-rise-again-serious.wav'
#
# # Open audio files and encode into ambisonics
audio_file_length_samples = int(audio_file_length * fs)
mono_s_t = librosa.core.load(af, sr=fs,
mono=True)[0][:audio_file_length_samples]
tic = time.time()
maxlim = 1.5 # just stop if the echogram goes beyond that time ( or just set it to max(rt60) )
limits = np.minimum(rt60, maxlim)
# Compute echograms
# abs_echograms, rec_echograms, echograms = srs.compute_echograms_sh(room, src, rec, abs_wall, limits, rec_orders)
abs_echograms = srs.compute_echograms_sh(room, src, rec, abs_wall, limits, rec_orders)
# %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
# RENDERING
# In this case all the information (e.g. SH directivities) are already
# encoded in the echograms, hence they are rendered directly to discrete RIRs
fs = 48000
sh_rirs = srs.render_rirs_sh(abs_echograms, band_centerfreqs, fs)
toc = time.time()
print('Elapsed time is ' + str(toc-tic) + 'seconds.')
# %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
# GENERATE SOUND SCENES
# Each source is convolved with the respective mic IR, and summed with
# the rest of the sources to create the microphone mixed signals
sourcepath = '../../data/milk_cow_blues_4src.wav'
src_sigs = librosa.core.load(sourcepath, sr=None, mono=False)[0].T[:,:nSrc]
sh_sigs = srs.apply_source_signals_sh(sh_rirs, src_sigs)
# Critical distance for the room
abs_wall = srs.find_abs_coeffs_from_rt(room, np.asarray([rt60]))[0]
_, d_critical, _ = srs.room_stats(room, abs_wall, verbose=False)
# Random source position, half critical distance
azi = np.random.rand() * 2 * np.pi
incl = np.random.rand() * np.pi
azi = azi + np.pi # TODO: fix in srs library!!!
src_sph = np.array([azi, np.pi/2-incl, d_critical.mean()/2])
src_cart = masp.sph2cart(src_sph)
src = rec + src_cart
nSrc = src.shape[0]
# Render echogram
abs_echograms = srs.compute_echograms_sh(room, src, rec, abs_wall, limits, rec_orders)
irs = srs.render_rirs_sh(abs_echograms, rt60_f, fs).squeeze().T
# Normalize as SN3D
irs *= np.sqrt(4 * np.pi)
# Write audio file
audio_file_name = str(i)+'.wav'
audio_file_path = os.path.join(IR_folder_path, audio_file_name)
sf.write(audio_file_path, irs.T, samplerate=fs)
# Write metadata file
metadata_file_name = str(i)+'.csv'
metadata_file_path = os.path.join(IR_folder_path, metadata_file_name)
with open(metadata_file_path, 'w', newline='') as file:
writer = csv.writer(file)
writer.writerow(["azi", (azi - np.pi)*360/(2*np.pi)])
writer.writerow(["ele", (np.pi/2 - incl)*360/(2*np.pi)])
