Add noise objects to create different type of noise

docs/conf.py

@@ -92,6 +92,7 @@ def __getattr__(cls, name):
 
 numpydoc_show_class_members = False
 
+
 # Custom function to define some 'noisy' class members to skip
 def skip_member(app, what, name, obj, skip, options):
     exclusions = (

docs/make_materials_table.py

@@ -27,20 +27,17 @@ def format_freq(f):
 
 
 def print_section(title, data, headers, file):
-
     print(title, file=file)
     print("-" * len(title), file=file)
     print(file=file)
 
     for subtitle, materials in data.items():
-
         print(subtitle, file=file)
         print("^" * len(subtitle), file=file)
         print(file=file)
 
         table = []
         for keyword, p in materials.items():
-
             # fill the table
             row = [keyword, p["description"]]
             for c in p["coeffs"]:
@@ -57,7 +54,6 @@ def print_section(title, data, headers, file):
 
 
 if __name__ == "__main__":
-
     with open(datafile, "r") as f:
         data = json.load(f)
 
@@ -66,7 +62,6 @@ def print_section(title, data, headers, file):
     ]
 
     with open(docfile, "w") as f:
-
         print("Materials Database", file=f)
         print("==================", file=f)
         print(file=f)
@@ -77,7 +72,6 @@ def print_section(title, data, headers, file):
         }
 
         for key, sectitle in sections.items():
-
             print_section(
                 title=sectitle,
                 data=data[key],

examples/adaptive_filter_stft_domain.py

@@ -41,12 +41,7 @@
 num_blocks = 0
 X_concat = np.zeros((num_bands, n_samples // hop), dtype=np.complex64)
 while n_samples - n > hop:
-
-    stft_in.analysis(
-        x[
-            n : n + hop,
-        ]
-    )
+    stft_in.analysis(x[n : n + hop,])
     X_concat[:, num_blocks] = stft_in.X
 
     n += hop
@@ -73,7 +68,6 @@
 error_per_band = np.zeros((num_bands, num_blocks), dtype=np.complex64)
 time_idx = 0
 for n in range(num_blocks):
-
     # update filter with new samples
     adaptive_filters.update(X_concat[:, n], D_concat[:, n])
     error_per_band[:, n] = np.linalg.norm(adaptive_filters.W.conj() - W, axis=0)

examples/bss_example.py

@@ -75,7 +75,6 @@
 ]
 
 if __name__ == "__main__":
-
     choices = ["ilrma", "auxiva", "sparseauxiva", "fastmnmf", "fastmnmf2"]
 
     import argparse
@@ -153,7 +152,6 @@
     # Record each source separately
     separate_recordings = []
     for source, signal in zip(room.sources, signals):
-
         source.signal[:] = signal
 
         room.simulate()
@@ -293,7 +291,6 @@ def convergence_callback(Y):
             )
 
     if args.gui:
-
         # Make a simple GUI to listen to the separated samples
         from tkinter import Tk, Button, Label
         import sounddevice as sd

examples/bss_live.py

@@ -67,7 +67,6 @@
 
 
 if __name__ == "__main__":
-
     choices = ["ilrma", "auxiva", "sparseauxiva", "fastmnmf", "fastmnmf2"]
 
     import argparse

examples/cmu_arctic_corpus.py

@@ -18,7 +18,6 @@
 import os
 
 if __name__ == "__main__":
-
     parser = argparse.ArgumentParser(
         description="Example of using the CMUArcticCorpus wrapper"
     )

examples/directivities/plot_directivity_2D.py

@@ -19,7 +19,6 @@
 fig = plt.figure()
 ax = plt.subplot(111, projection="polar")
 for pattern in DirectivityPattern:
-
     dir_obj = CardioidFamily(orientation=orientation, pattern_enum=pattern)
     resp = dir_obj.get_response(azimuth=angles, magnitude=True, degrees=False)
     resp_db = dB(np.array(resp))

examples/doa_anechoic_room.py

@@ -11,7 +11,6 @@
 methods = ["MUSIC", "FRIDA", "WAVES", "TOPS", "CSSM", "SRP", "NormMUSIC"]
 
 if __name__ == "__main__":
-
     parser = argparse.ArgumentParser(
         description="Estimates the direction of arrival of a sound source."
     )

examples/google_speech_commands_corpus.py

@@ -13,7 +13,6 @@
 import pyroomacoustics as pra
 
 if __name__ == "__main__":
-
     parser = argparse.ArgumentParser(
         description="Example of using the GoogleSpeechCommands wrapper"
     )

examples/hmm_training.py

@@ -12,7 +12,6 @@
 from pyroomacoustics import HMM, CircularGaussianEmission, GaussianEmission
 
 if __name__ == "__main__":
-
     K = 4  # number of states
     O = 6  # dimension of the emission vector
     model = "left-right"  # transition matrix model

examples/noise_reduction_spectral_subtraction.py

@@ -80,7 +80,6 @@
 processed_audio = np.zeros(signal.shape)
 n = 0
 while noisy_signal.shape[0] - n >= hop:
-
     # SCNR in frequency domain
     stft.analysis(noisy_signal[n : (n + hop)])
     gain_filt = scnr.compute_gain_filter(stft.X)

examples/noise_reduction_subspace.py

@@ -63,10 +63,7 @@
 start_time = time.time()
 hop = frame_len // 2
 while noisy_signal.shape[0] - n >= hop:
-
-    processed_audio[
-        n : n + hop,
-    ] = scnr.apply(noisy_signal[n : n + hop])
+    processed_audio[n : n + hop,] = scnr.apply(noisy_signal[n : n + hop])
 
     # update step
     n += hop

examples/noise_reduction_wiener_filtering.py

@@ -69,7 +69,6 @@
 processed_audio = np.zeros(noisy_signal.shape)
 n = 0
 while noisy_signal.shape[0] - n >= hop:
-
     # to frequency domain, 50% overlap
     stft.analysis(noisy_signal[n : (n + hop)])
 

examples/randomized_image_method.py

@@ -79,7 +79,6 @@
 
 print("Sweeping echo measure for ISM is :")
 for n in range(M):
-
     if n == 0:
         S = stft.analysis(
             room.rir[n][0], fft_size, fft_hop, win=analysis_window, zp_back=fft_zp
@@ -133,7 +132,6 @@
 
 print("Sweeping echo measure for randomized ISM is:")
 for n in range(M):
-
     if n == 0:
         S = stft.analysis(
             room.rir[n][0], fft_size, fft_hop, win=analysis_window, zp_back=fft_zp

examples/raytracing.py

@@ -32,7 +32,6 @@
 
 
 def get_rir(size, reverb):
-
     # We construct a non-shoebox room
     pol = size_opts[size]["mult"] * np.array([[0, 0], [0, 4], [3, 2], [3, 0]]).T
     mat = pra.Material(reverb_opts[reverb]["e_abs"])
@@ -66,7 +65,6 @@ def get_rir(size, reverb):
 
 
 if __name__ == "__main__":
-
     parser = argparse.ArgumentParser(
         description=(
             "Demonstrates the use of ray tracing for rooms of "

examples/room_from_rt60.py

@@ -14,7 +14,6 @@
 methods = ["ism", "hybrid"]
 
 if __name__ == "__main__":
-
     parser = argparse.ArgumentParser(
         description="Simulates and adds reverberation to a dry sound sample. Saves it into `./examples/samples`."
     )

examples/room_from_stl.py

@@ -27,7 +27,6 @@
 default_stl_path = Path(__file__).parent / "data/INRIA_MUSIS.stl"
 
 if __name__ == "__main__":
-
     parser = argparse.ArgumentParser(description="Basic room from STL file example")
     parser.add_argument(
         "--file", type=str, default=default_stl_path, help="Path to STL file"

examples/room_shoebox_3d_rt.py

@@ -79,11 +79,9 @@ def chrono(f, *args, **kwargs):
 
 
 if __name__ == "__main__":
-
     rirs = {}
 
     for name, config in params.items():
-
         print("Simulate: ", name)
 
         shoebox = make_room(config)

examples/stft_block_processing.py

@@ -51,7 +51,6 @@
 # process the signals while full blocks are available
 n = 0
 while audio.shape[0] - n > hop:
-
     # go to frequency domain
     stft.analysis(audio[n : n + hop])
 

pyroomacoustics/__init__.py

@@ -128,6 +128,16 @@
 from .directivities import *
 from .metrics import *
 from .multirate import *
+from .noise import (
+    Noise,
+    WhiteNoise,
+    DiffuseNoise,
+    mix_signal_noise,
+    compute_power,
+    compute_rmse,
+    compute_snr,
+    scale_signal,
+)
 from .parameters import *
 from .recognition import *
 from .room import *

pyroomacoustics/acoustics.py

@@ -82,7 +82,6 @@ def bandpass_filterbank(bands, fs=1.0, order=8, output="sos"):
     nyquist = fs / 2.0
 
     for band in bands:
-
         # remove bands above nyquist frequency
         if band[0] >= nyquist:
             raise ValueError("Bands should be below Nyquist frequency")
@@ -161,7 +160,6 @@ class OctaveBandsFactory(object):
     """
 
     def __init__(self, base_frequency=125.0, fs=16000, n_fft=512):
-
         self.base_freq = base_frequency
         self.fs = fs
         self.n_fft = n_fft

pyroomacoustics/adaptive/adaptive_filter.py

@@ -11,7 +11,6 @@ class AdaptiveFilter:
     """
 
     def __init__(self, length):
-
         # filter length
         self.length = length
 
@@ -54,5 +53,4 @@ def update(self, x_n, d_n):
         self.d = d_n
 
     def name(self):
-
         return self.__class__.__name__

pyroomacoustics/adaptive/data_structures.py

@@ -16,7 +16,6 @@ class Buffer:
     """
 
     def __init__(self, length=20, dtype=np.float64):
-
         self.buf = np.zeros(length, dtype=dtype)
         self.len = length
         self.head = self.len
@@ -71,7 +70,6 @@ def __getitem__(self, r):
         return ptr[r]
 
     def __repr__(self):
-
         if self.head == self.len:
             return "[]"
         else:
@@ -103,12 +101,10 @@ class Powers:
     """
 
     def __init__(self, a, length=20, dtype=np.float64):
-
         self.a = dtype(a)
         self.pwr = self.a ** np.arange(length)
 
     def __getitem__(self, r):
-
         # find maximum power requested
         if isinstance(r, int):
             high = r + 1
@@ -148,7 +144,6 @@ class CoinFlipper:
     """
 
     def __init__(self, p, length=10000):
-
         self.p = p
         self.length = length
         self.buffer = np.random.random(length) < p

pyroomacoustics/adaptive/lms.py

@@ -26,7 +26,6 @@ class NLMS(AdaptiveFilter):
     """
 
     def __init__(self, length, mu=0.5):
-
         self.mu = mu
         AdaptiveFilter.__init__(self, length)
 
@@ -65,7 +64,6 @@ class BlockLMS(NLMS):
     """
 
     def __init__(self, length, mu=0.01, L=1, nlms=False):
-
         self.nlms = nlms
 
         # sketching parameters
@@ -103,7 +101,6 @@ def update(self, x_n, d_n):
 
         # Block update
         if self.n % self.L == 0:
-
             # block-update parameters
             X = la.hankel(self.x[: self.L], r=self.x[self.L - 1 :])
 

pyroomacoustics/adaptive/rls.py

@@ -12,6 +12,7 @@
 from .adaptive_filter import AdaptiveFilter
 from .util import hankel_stride_trick
 
+
 # First the classic RLS (for real numbered signals)
 class RLS(AdaptiveFilter):
     """
@@ -32,7 +33,6 @@ class RLS(AdaptiveFilter):
     """
 
     def __init__(self, length, lmbd=0.999, delta=10, dtype=np.float32):
-
         self.lmbd = lmbd
         self.lmbd_inv = 1 / lmbd
         self.delta = delta
@@ -129,7 +129,6 @@ class BlockRLS(RLS):
     """
 
     def __init__(self, length, lmbd=0.999, delta=10, dtype=np.float32, L=None):
-
         # block size
         if L is None:
             self.block = length
@@ -178,7 +177,6 @@ def update(self, x_n, d_n):
 
         # Block update
         if self.n % self.block == 0:
-
             x_vec = self.x.top(self.block + self.length - 1)
             d_vec = self.d.top(self.block)
 

pyroomacoustics/adaptive/subband_lms.py

@@ -44,7 +44,6 @@ class SubbandLMS:
     """
 
     def __init__(self, num_taps, num_bands, mu=0.5, nlms=True):
-
         self.num_taps = num_taps
         self.num_bands = num_bands
         self.mu = mu
@@ -53,7 +52,6 @@ def __init__(self, num_taps, num_bands, mu=0.5, nlms=True):
         self.reset()
 
     def reset(self):
-
         # filter bank
         self.W = np.zeros((self.num_taps, self.num_bands), dtype=np.complex64)