updated docs and added full scipy.signal.get_window backwards compat …

…support

librosa/core/spectrum.py

@@ -53,11 +53,14 @@ def stft(y, n_fft=2048, hop_length=None, win_length=None, window='hann',
 
         If unspecified, defaults to ``win_length = n_fft``.
 
-    window : string, tuple, function, or np.ndarray [shape=(n_fft,)]
-        - a window specification (string or tuple); see `scipy.signal.get_window`
+    window : string, tuple, number, function, or np.ndarray [shape=(n_fft,)]
+        - a window specification (string, tuple, or number); 
+          see `scipy.signal.get_window`
         - a window function, such as `scipy.signal.hanning`
         - a vector or array of length `n_fft`
 
+        .. see also:: `filters.get_window`
+
     center      : boolean
         - If `True`, the signal `y` is padded so that frame
           `D[:, t]` is centered at `y[t * hop_length]`.
@@ -205,11 +208,14 @@ def istft(stft_matrix, hop_length=None, win_length=None, window='hann',
 
         If unspecified, defaults to `n_fft`.
 
-    window      : string, tuple, function, np.ndarray [shape=(n_fft,)]
-        - a window specification (string or tuple); see `scipy.signal.get_window`
+    window      : string, tuple, number, function, np.ndarray [shape=(n_fft,)]
+        - a window specification (string, tuple, or number);
+          see `scipy.signal.get_window`
         - a window function, such as `scipy.signal.hanning`
         - a user-specified window vector of length `n_fft`
 
+        .. see also:: `filters.get_window`
+
     center      : boolean
         - If `True`, `D` is assumed to have centered frames.
         - If `False`, `D` is assumed to have left-aligned frames.
@@ -324,12 +330,15 @@ def ifgram(y, sr=22050, n_fft=2048, hop_length=None, win_length=None,
         Window length. Defaults to `n_fft`.
         See `stft` for details.
 
-    window : string, tuple, function, or np.ndarray [shape=(n_fft,)]
-        - a window specification (string or tuple); see `scipy.signal.get_window`
+    window : string, tuple, number, function, or np.ndarray [shape=(n_fft,)]
+        - a window specification (string, tuple, number);
+          see `scipy.signal.get_window`
         - a window function, such as `scipy.signal.hanning`
         - a user-specified window vector of length `n_fft`
         See `stft` for details.
 
+        .. see also:: `filters.get_window`
+
     norm : bool
         Normalize the STFT.
 

librosa/feature/rhythm.py

@@ -48,8 +48,8 @@ def tempogram(y=None, sr=22050, onset_envelope=None, hop_length=512,
         If `True`, onset autocorrelation windows are centered.
         If `False`, windows are left-aligned.
 
-    window : string, function, tuple, or np.ndarray [shape=(win_length,)]
-        A window specification as in `core.stft`
+    window : string, function, number, tuple, or np.ndarray [shape=(win_length,)]
+        A window specification as in `core.stft`.
 
     norm : {np.inf, -np.inf, 0, float > 0, None}
         Normalization mode.  Set to `None` to disable normalization.

librosa/filters.py

@@ -765,12 +765,14 @@ def get_window(window, Nx, fftbins=True):
 
     Parameters
     ----------
-    window : string, tuple, callable, or list-like
+    window : string, tuple, number, 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 numeric, it is treated as the beta parameter of the `'kaiser'`
+          window.
         - 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`
@@ -780,7 +782,7 @@ def get_window(window, Nx, fftbins=True):
 
     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
+        If False, create a symmetric window for filter design applications.
 
     Returns
     -------
@@ -800,13 +802,16 @@ def get_window(window, Nx, fftbins=True):
     if six.callable(window):
         return window(Nx)
 
-    elif isinstance(window, (str, tuple)):
+    elif (isinstance(window, (six.string_types, tuple)) or
+          np.isscalar(window)):
         # TODO: if we add custom window functions in librosa, call them 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:

tests/test_filters.py

@@ -317,15 +317,20 @@ def __test(n_bins, bins_per_octave, n_chroma, fmin, base_c, window):
                                    n_chroma, fmin, base_c, window)
 
 
-def test_get_window_tuple():
+@raises(librosa.ParameterError)
+def test_get_window_fail():
 
-    x1 = scipy.signal.get_window(('kaiser', 4.0), 32)
-    x2 = librosa.filters.get_window(('kaiser', 4.0), 32)
+    librosa.filters.get_window(None, 32)
 
-    assert np.allclose(x1, x2)
 
+def test_get_window():
 
-@raises(librosa.ParameterError)
-def test_get_window_fail():
+    def __test(window):
 
-    librosa.filters.get_window(None, 32)
+        w1 = librosa.filters.get_window(window, 32)
+        w2 = scipy.signal.get_window(window, 32)
+
+        assert np.allclose(w1, w2)
+
+    for window in ['hann', u'hann', 4.0, ('kaiser', 4.0)]:
+        yield __test, window