From dcacf70a45d33bcc0a7d2ee8af1eacf2e7c86886 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Adrian=20St=C4=99pie=C5=84?=
 <4030444+adrian-stepien@users.noreply.github.com>
Date: Tue, 12 Feb 2019 16:18:23 +0000
Subject: [PATCH 1/2] [SIGNAL] Normalization using maximum absolute value

Fixed the `normalize` function to take into account the maximum of
absolute values, not only the positive ones.
---
 acoustics/_signal.pyx | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/acoustics/_signal.pyx b/acoustics/_signal.pyx
index 64faedec..ebe37704 100644
--- a/acoustics/_signal.pyx
+++ b/acoustics/_signal.pyx
@@ -1026,12 +1026,12 @@ class Signal(numpy.ndarray):
         By default a 6 decibel gap is used.
 
         """
-        factor = (self.max() * 10.0**(gap/20.0))
+        factor = (np.abs(self).max() * 10.0**(gap/20.0))
         if inplace:
-            self /= factor
+            self /= factor[..., None]
             return self
         else:
-            return self / factor
+            return self / factor[..., None]
 
 
     def to_wav(self, filename, depth=16):

From 33d4f8365ea25915b60f3941f586e7488836dd1d Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Adrian=20St=C4=99pie=C5=84?=
 <4030444+adrian-stepien@users.noreply.github.com>
Date: Tue, 12 Feb 2019 16:57:23 +0000
Subject: [PATCH 2/2] [SIGNAL] Loading backend switched to pysoundfile

Thanks to pysoundfile it's possible to laod WAV and FLAC files
with integer samples. (Floating point is there out of the box,
but requires a bit of API refactoring).

Things removed:
  - When saving, samples are no-longer normalized
  - Normalization is optional during loading - by default it's off
---
 acoustics/_signal.pyx | 27 +++++++++++++--------------
 requirements.txt      |  1 +
 setup.cfg             |  1 +
 tests/test__signal.py |  5 ++++-
 4 files changed, 19 insertions(+), 15 deletions(-)

diff --git a/acoustics/_signal.pyx b/acoustics/_signal.pyx
index ebe37704..43fae840 100644
--- a/acoustics/_signal.pyx
+++ b/acoustics/_signal.pyx
@@ -2,7 +2,7 @@ cimport cython
 cimport numpy
 import numpy as np
 import matplotlib.pyplot as plt
-from scipy.io import wavfile
+import soundfile as sf
 from scipy.signal import detrend, lfilter, bilinear, spectrogram, filtfilt, resample, fftconvolve
 import acoustics
 import itertools
@@ -1034,35 +1034,34 @@ class Signal(numpy.ndarray):
             return self / factor[..., None]
 
 
-    def to_wav(self, filename, depth=16):
+    def to_wav(self, filename, depth=16, format="WAV"):
         """Save signal as WAV file.
 
         :param filename: Name of file to save to.
         :param depth: If given, convert to integer with specified depth. Else, try to store using the original data type.
+        :param format: It can be either WAV or FLAC
 
-        By default, this function saves a normalized 16-bit version of the signal with at least 6 dB range till clipping occurs.
+        Note that the floating point samples are not yet supported.
 
         """
         data = self
-        dtype = data.dtype if not depth else 'int'+str(depth)
-        if depth:
-            data = (data * 2**(depth-1)-1).astype(dtype)
-        wavfile.write(filename, int(self.fs), data.T)
-        #wavfile.write(filename, int(self.fs), self._data/np.abs(self._data).max() *  0.5)
-        #wavfile.write(filename, int(self.fs), np.int16(self._data/(np.abs(self._data).max()) * 32767) )
+        subtype = "PCM_{}".format(depth)
+        to_save = data
+        sf.write(filename, to_save.T, int(self.fs), format=format, subtype=subtype)
 
     @classmethod
-    def from_wav(cls, filename):
+    def from_wav(cls, filename, normalize=False):
         """
         Create an instance of `Signal` from a WAV file.
 
         :param filename: Filename
+        :param normalize: Optionally normalize the input samples
 
         """
-        fs, data = wavfile.read(filename)
-        data = data.astype(np.float32, copy=False).T
-        data /= np.max(np.abs(data))
-        return cls(data, fs=fs)
+        data, fs = sf.read(filename)
+        if normalize:
+            data /= np.max(np.abs(data))
+        return cls(data.T, fs=fs)
 
 
 _PLOTTING_PARAMS = {
diff --git a/requirements.txt b/requirements.txt
index 992d16ef..1b926ac6 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -5,3 +5,4 @@ six
 cython
 pandas
 tabulate
+pysoundfile
\ No newline at end of file
diff --git a/setup.cfg b/setup.cfg
index 164bc238..38e9ffe7 100644
--- a/setup.cfg
+++ b/setup.cfg
@@ -25,6 +25,7 @@ install_requires =
     cython
     pandas >= 0.15
     tabulate
+    pysoundfile
 tests_require =
     pytest
 
diff --git a/tests/test__signal.py b/tests/test__signal.py
index 968a59e6..a240be9d 100644
--- a/tests/test__signal.py
+++ b/tests/test__signal.py
@@ -20,11 +20,14 @@ class test_wav():
     fs = 10025
     samples = int(fs*duration)
     channels = 3
+    values = np.random.randn(channels, samples)
 
-    signal = Signal(np.random.randn(channels, samples), fs)
+    signal = Signal(values, fs)
+    signal.normalize(inplace=True)
 
     with tempfile.TemporaryFile() as file:
         signal.to_wav(file)
+        file.seek(0)
         signal = Signal.from_wav(file)
         assert signal.samples == samples
         assert signal.fs == fs