Merge pull request #42 from fgnt/numpy2

Fixes for recent numpy and scipy versions

Author: boeddeker

.github/workflows/tests.yml

@@ -9,11 +9,14 @@ on:
 jobs:
   build:
 
-    runs-on: ubuntu-latest
+    runs-on: ${{ matrix.os || 'ubuntu-latest' }}
     strategy:
       matrix:
-        python-version: ['3.7', '3.8', '3.9', '3.10', '3.11']
-
+        python-version: ['3.9', '3.10', '3.11', '3.12']
+        os: ['ubuntu-latest']
+        include:
+          - python-version: '3.12'
+            os: 'macos-latest'
     steps:
     - uses: actions/checkout@v3
     - name: Set up Python ${{ matrix.python-version }}
@@ -26,6 +29,7 @@ jobs:
         trap 'echo -e "$ $BASH_COMMAND"' DEBUG
         sudo apt-get update
         sudo apt-get install libsndfile1 sox
+      if: matrix.os != 'macos-latest'
 
     - name: Install python dependencies
       run: |
@@ -36,6 +40,7 @@ jobs:
         python -m pip install wheel
         if [ -f requirements.txt ]; then pip install -r requirements.txt; fi
         pip install --editable .[all]
+        pip install https://github.com/ludlows/python-pesq/archive/master.zip
 
     - name: Lint with flake8
       run: |
@@ -50,3 +55,4 @@ jobs:
     - name: Codecov
       run: |
         codecov
+      if: matrix.os != 'macos-latest'

README.md

@@ -1,5 +1,6 @@
 # Blind Source Separation (BSS) algorithms
 
+[![pytest](https://github.com/fgnt/pb_bss/actions/workflows/tests.yml/badge.svg)](https://github.com/fgnt/pb_bss/actions)
 [![Build Status](https://dev.azure.com/fgnt/fgnt/_apis/build/status/fgnt.pb_bss?branchName=master)](https://dev.azure.com/fgnt/fgnt/_build/latest?definitionId=1&branchName=master)
 [![Azure DevOps tests](https://img.shields.io/azure-devops/tests/fgnt/fgnt/1)](https://dev.azure.com/fgnt/fgnt/_build/latest?definitionId=1&branchName=master)
 [![Azure DevOps coverage](https://img.shields.io/azure-devops/coverage/fgnt/fgnt/1)](https://dev.azure.com/fgnt/fgnt/_build/latest?definitionId=1&branchName=master)

azure-pipelines.yml

@@ -3,18 +3,9 @@ jobs:
 - job: test
   strategy:
     matrix:
-      Linux py37:
-        IMAGE_NAME: 'ubuntu-latest'
-        PYTHON_VERSION: '3.7'
-      OSX py37:
-        IMAGE_NAME: 'macos-latest'
-        PYTHON_VERSION: '3.7'
-      Linux py38:
-        IMAGE_NAME: 'ubuntu-latest'
-        PYTHON_VERSION: '3.8'
       Linux py39:
         IMAGE_NAME: 'ubuntu-latest'
-        PYTHON_VERSION: '3.9'
+        PYTHON_VERSION: '3.12'
   pool:
     vmImage: $(IMAGE_NAME)
   steps:

pb_bss/evaluation/module_pesq.py

@@ -14,18 +14,18 @@ def pesq(reference, estimation, sample_rate, mode=None):
         >>> np.random.seed(0)
         >>> a = np.random.normal(size=16_000)
         >>> b = a + np.random.normal(size=16_000)
-        >>> pesq(a, b, sample_rate=16000)
-        2.2297563552856445
+        >>> pesq(a, b, sample_rate=16000)  # doctest: +ELLIPSIS  # macOS doesn't yield the same as Ubuntu
+        2.22975...
         >>> pesq(a, b, sample_rate=8000)
         1.0334522724151611
-        >>> pesq(a, b, sample_rate=16000, mode='nb')
-        3.200247049331665
+        >>> pesq(a, b, sample_rate=16000, mode='nb')  # doctest: +ELLIPSIS  # macOS doesn't yield the same as Ubuntu
+        3.20024...
 
-        >>> pesq([a, a], [b, b], sample_rate=16000)
-        array([2.22975636, 2.22975636])
-        >>> pesq([[a, a], [b, a]], [[b, b], [b, b]], sample_rate=16000)
-        array([[2.22975636, 2.22975636],
-               [4.64388847, 2.22975636]])
+        >>> pesq([a, a], [b, b], sample_rate=16000)    # doctest: +ELLIPSIS  # macOS doesn't yield the same as Ubuntu
+        array([2.22975..., 2.22975...])
+        >>> pesq([[a, a], [b, a]], [[b, b], [b, b]], sample_rate=16000)    # doctest: +ELLIPSIS  # macOS doesn't yield the same as Ubuntu
+        array([[2.22975..., 2.22975...],
+               [4.64388847, 2.22975...]])
 
         >>> pesq(a, b, sample_rate=8000, mode='wb')
         Traceback (most recent call last):

pb_bss/evaluation/module_si_sdr.py

@@ -17,19 +17,19 @@ def si_sdr(reference, estimation):
 
     >>> np.random.seed(0)
     >>> reference = np.random.randn(100)
-    >>> si_sdr(reference, reference)
+    >>> print(si_sdr(reference, reference))
     inf
-    >>> si_sdr(reference, reference * 2)
+    >>> print(si_sdr(reference, reference * 2))
     inf
-    >>> si_sdr(reference, np.flip(reference))
+    >>> print(si_sdr(reference, np.flip(reference)))
     -25.127672346460717
-    >>> si_sdr(reference, reference + np.flip(reference))
+    >>> print(si_sdr(reference, reference + np.flip(reference)))
     0.481070445785553
-    >>> si_sdr(reference, reference + 0.5)
+    >>> print(si_sdr(reference, reference + 0.5))
     6.3704606032577304
-    >>> si_sdr(reference, reference * 2 + 1)
+    >>> print(si_sdr(reference, reference * 2 + 1))
     6.3704606032577304
-    >>> si_sdr([1., 0], [0., 0])  # never predict only zeros
+    >>> print(si_sdr([1., 0], [0., 0]))  # never predict only zeros
     nan
     >>> si_sdr([reference, reference], [reference * 2 + 1, reference * 1 + 0.5])
     array([6.3704606, 6.3704606])

pb_bss/evaluation/module_srmr.py

@@ -17,7 +17,7 @@ def srmr(signal, sample_rate: int = 16000, n_cochlear_filters: int = 23, low_fre
         >>> import paderbox as pb
         >>> a = pb.testing.testfile_fetcher.get_file_path('speech_bab_0dB.wav')
         >>> a = pb.io.load_audio(a)
-        >>> srmr(a, 16000)  # doctest: +ELLIPSIS
+        >>> print(srmr(a, 16000))  # doctest: +ELLIPSIS
         1.8561615800...
         >>> srmr([a, a], 16000)
         array([1.85616158, 1.85616158])
@@ -96,7 +96,7 @@ def SRMR(signal: np.ndarray, sample_rate: int = 16000, n: int = 23, low_freq: in
             temp = segment_axis(E[j][k], int(sample_rate/1000)*256, int(sample_rate/1000)*64)
 
             #Multiplication of a hamming window with each segment and summation of the result
-            hamm_window = sp.signal.hamming(int(sample_rate/1000)*256, sym=True)
+            hamm_window = sp.signal.windows.hamming(int(sample_rate/1000)*256, sym=True)
             for window in temp:
                 energy[j][k].append(np.sum(np.square(hamm_window*window)))
 

pb_bss/evaluation/sxr_module.py

@@ -40,7 +40,7 @@ def get_snr(X, N, *, axis=None, keepdims=False):
     Returns:
         SNR of time signals or STFT signals in dB.
 
-    >>> get_snr([1, 2, 3], [1, 2, 3])
+    >>> print(get_snr([1, 2, 3], [1, 2, 3]))
     0.0
     """
     power_X = get_variance_for_zero_mean_signal(X, axis=axis, keepdims=keepdims)

pb_bss/evaluation/wrapper.py

@@ -290,9 +290,9 @@ def __init__(
             ... )
 
             # Obtain all metrics (recommended)
-            >>> with np.printoptions(precision=4):
+            >>> with np.printoptions(precision=4):  # doctest: +ELLIPSIS  # macOS doesn't yield the same as Ubuntu
             ...     pprint(metrics.as_dict())
-            {'pesq': array([1.2235, 1.225 ]),
+            {'pesq': array([1.22..., 1.225 ]),
              'stoi': array([0.0503, 0.0638]),
              'mir_eval_sdr': array([7.2565, 7.3303]),
              'mir_eval_sir': array([25.6896, 46.638 ]),
@@ -301,12 +301,12 @@ def __init__(
              'srmr': array([203.3988, 203.3988])}
 
             # Obtain particular metric (e.g. pesq)
-            >>> metrics.pesq
-            array([1.22345543, 1.2250005 ])
+            >>> metrics.pesq  # doctest: +ELLIPSIS  # macOS doesn't yield the same as Ubuntu
+            array([1.22..., 1.225000...])
 
             # Obtain multiple metrics (e.g. pesq and stoi)
             >>> pprint({m: metrics[m] for m in ['pesq', 'stoi']})
-            {'pesq': array([1.22345543, 1.2250005 ]),
+            {'pesq': array([1.22..., 1.225000...]),
              'stoi': array([0.05026565, 0.06377457])}
         """
         self.speech_prediction = speech_prediction

pb_bss/extraction/beamformer.py

@@ -247,7 +247,7 @@ def get_mvdr_vector(atf_vector, noise_psd_matrix):
         noise_psd_matrix + np.conj(noise_psd_matrix.swapaxes(-1, -2))
     )
     try:
-        numerator = solve(noise_psd_matrix, atf_vector)
+        numerator = np.squeeze(solve(noise_psd_matrix, atf_vector[..., None]), axis=-1)
     except np.linalg.LinAlgError:
         bins = noise_psd_matrix.shape[0]
         numerator = np.empty_like(atf_vector)

pb_bss/testing/dummy_data.py

@@ -57,8 +57,7 @@ def read_audio(example):
 def low_reverberation_data():
     """
     >>> import numpy as np
-    >>> np.set_string_function(lambda a: f'array(shape={a.shape}, dtype={a.dtype})')
-    >>> from IPython.lib.pretty import pprint
+    >>> from paderbox.utils.pretty import pprint
     >>> pprint(low_reverberation_data())  # doctest: +ELLIPSIS
     {'audio_path': ...,
      'gender': ['m', 'm'],
@@ -86,7 +85,6 @@ def low_reverberation_data():
       'speech_reverberation_early': array(shape=(2, 6, 38520), dtype=float64),
       'speech_reverberation_tail': array(shape=(2, 6, 38520), dtype=float64),
       'speech_source': array(shape=(2, 38520), dtype=float64)}}
-    >>> np.set_string_function(None)  # needed for pytest. np.set_string_function is not properly reseted.
     """
     return _get_data()['low_reverberation']
 
@@ -95,8 +93,7 @@ def reverberation_data():
     """
 
     >>> import numpy as np
-    >>> np.set_string_function(lambda a: f'array(shape={a.shape}, dtype={a.dtype})')
-    >>> from IPython.lib.pretty import pprint
+    >>> from paderbox.utils.pretty import pprint
     >>> pprint(reverberation_data())  # doctest: +ELLIPSIS
     {'audio_path': ...,
      'gender': ['m', 'm'],
@@ -116,7 +113,6 @@ def reverberation_data():
      'example_id': 'reverberation',
      'dataset': 'test',
      'audio_data': ...
-    >>> np.set_string_function(None)  # needed for pytest. np.set_string_function is not properly reseted.
 
     """
     return _get_data()['reverberation']