Merge a26e607 into 6d30e92

librosa/core/spectrum.py

@@ -13,6 +13,7 @@
 from .. import cache
 from .. import util
 from ..util.exceptions import ParameterError
+from ..filters import get_window
 
 __all__ = ['stft', 'istft', 'magphase',
            'ifgram',
@@ -72,12 +73,6 @@ def stft(y, n_fft=2048, hop_length=None, win_length=None, window=None,
         STFT matrix
 
 
-    Raises
-    ------
-    ParameterError
-        If `window` is supplied as a vector of length `n_fft`.
-
-
     See Also
     --------
     istft : Inverse STFT
@@ -138,24 +133,12 @@ def stft(y, n_fft=2048, hop_length=None, win_length=None, window=None,
 
     # Set the default hop, if it's not already specified
     if hop_length is None:
-        hop_length = int(win_length / 4)
+        hop_length = int(win_length // 4)
 
     if window is None:
-        # Default is an asymmetric Hann window
-        fft_window = scipy.signal.hann(win_length, sym=False)
-
-    elif six.callable(window):
-        # User supplied a window function
-        fft_window = window(win_length)
-
-    else:
-        # User supplied a window vector.
-        # Make sure it's an array:
-        fft_window = np.asarray(window)
+        window = 'hann'
 
-        # validate length compatibility
-        if fft_window.size != n_fft:
-            raise ParameterError('Size mismatch between n_fft and len(window)')
+    fft_window = get_window(window, win_length, fftbins=True)
 
     # Pad the window out to n_fft size
     fft_window = util.pad_center(fft_window, n_fft)
@@ -242,11 +225,6 @@ def istft(stft_matrix, hop_length=None, win_length=None, window=None,
     y : np.ndarray [shape=(n,)]
         time domain signal reconstructed from `stft_matrix`
 
-    Raises
-    ------
-    ParameterError
-        If `window` is supplied as a vector of length `n_fft`
-
     See Also
     --------
     stft : Short-time Fourier Transform
@@ -283,24 +261,13 @@ def istft(stft_matrix, hop_length=None, win_length=None, window=None,
 
     # Set the default hop, if it's not already specified
     if hop_length is None:
-        hop_length = int(win_length / 4)
+        hop_length = int(win_length // 4)
 
     if window is None:
         # Default is an asymmetric Hann window.
-        ifft_window = scipy.signal.hann(win_length, sym=False)
-
-    elif six.callable(window):
-        # User supplied a windowing function
-        ifft_window = window(win_length)
-
-    else:
-        # User supplied a window vector.
-        # Make it into an array
-        ifft_window = np.asarray(window)
+        window = 'hann'
 
-        # Verify that the shape matches
-        if ifft_window.size != n_fft:
-            raise ParameterError('Size mismatch between n_fft and window size')
+    ifft_window = get_window(window, win_length, fftbins=True)
 
     # Pad out to match n_fft
     ifft_window = util.pad_center(ifft_window, n_fft)
@@ -331,7 +298,8 @@ def istft(stft_matrix, hop_length=None, win_length=None, window=None,
 
 
 def ifgram(y, sr=22050, n_fft=2048, hop_length=None, win_length=None,
-           norm=False, center=True, ref_power=1e-6, clip=True, dtype=np.complex64):
+           norm=False, center=True, ref_power=1e-6, clip=True,
+           dtype=np.complex64):
     '''Compute the instantaneous frequency (as a proportion of the sampling rate)
     obtained as the time-derivative of the phase of the complex spectrum as
     described by [1]_.
@@ -419,7 +387,8 @@ def ifgram(y, sr=22050, n_fft=2048, hop_length=None, win_length=None,
         hop_length = int(win_length // 4)
 
     # Construct a padded hann window
-    window = util.pad_center(scipy.signal.hann(win_length, sym=False), n_fft)
+    window = util.pad_center(get_window('hann', win_length, fftbins=True),
+                             n_fft)
 
     # Window for discrete differentiation
     freq_angular = np.linspace(0, 2 * np.pi, n_fft, endpoint=False)

librosa/filters.py

@@ -14,21 +14,30 @@
     chroma
     constant_q
 
+Window functions
+----------------
+.. autosummary::
+    :toctree: generated/
+
+    window_bandwidth
+    get_window
+
+
 Miscellaneous
 -------------
 .. autosummary::
     :toctree: generated/
 
     constant_q_lengths
     cq_to_chroma
-    window_bandwidth
 """
 
 import warnings
 
 import numpy as np
 import scipy
 import scipy.signal
+import six
 
 from . import cache
 from . import util
@@ -46,7 +55,8 @@
            'constant_q',
            'constant_q_lengths',
            'cq_to_chroma',
-           'window_bandwidth']
+           'window_bandwidth',
+           'get_window']
 
 
 @cache(level=10)
@@ -744,3 +754,56 @@ def window_bandwidth(window, default=1.0):
         warnings.warn("Unknown window function '{:s}'.".format(key))
 
     return WINDOW_BANDWIDTHS.get(key, default)
+
+
+def get_window(window, Nx, fftbins=True):
+    '''Compute a window function
+
+    Parameters
+    ----------
+    window : string, tuple, callable, or list-like
+        The window specification:
+
+        - If string, it's the name of the window function (e.g., `'hann'`)
+        - If tuple, it's the name of the window function and any parameters
+          (e.g., `('kaiser', 4.0)`)
+        - If callable, it's a function that accepts one integer argument
+          (the window length)
+        - If list-like, it's a pre-computed window of the correct length `Nx`
+
+    Nx : int > 0
+        The length of the window
+
+    fftbins : bool, optional
+        If True (default), create a periodic window for use with FFT
+        If False, create a symmetric window for use with filter design
+
+    Returns
+    -------
+    get_window : np.ndarray
+        A window of length `Nx` and type `window`
+
+    See Also
+    --------
+    scipy.signal.get_window
+
+    Raises
+    ------
+    ParameterError
+        If `window` is supplied as a vector of length != `n_fft`,
+        or is otherwise mis-specified.
+    '''
+    if six.callable(window):
+        return window(Nx)
+
+    elif isinstance(window, (str, tuple)):
+        # TODO: if we add more window functions, put that index check here
+
+        return scipy.signal.get_window(window, Nx, fftbins=fftbins)
+    elif isinstance(window, (np.ndarray, list)):
+        if len(window) == Nx:
+            return np.asarray(window)
+        raise ParameterError('Window size mismatch: '
+                             '{:d} != {:d}'.format(len(window), Nx))
+    else:
+        raise ParameterError('Invalid window specification: {}'.format(window))

tests/test_filters.py

@@ -315,3 +315,17 @@ def __test(n_bins, bins_per_octave, n_chroma, fmin, base_c, window):
                                 tf = __test
                             yield (tf, n_bins, bins_per_octave,
                                    n_chroma, fmin, base_c, window)
+
+
+def test_get_window_tuple():
+
+    x1 = scipy.signal.get_window(('kaiser', 4.0), 32)
+    x2 = librosa.filters.get_window(('kaiser', 4.0), 32)
+
+    assert np.allclose(x1, x2)
+
+
+@raises(librosa.ParameterError)
+def test_get_window_fail():
+
+    librosa.filters.get_window(None, 32)