Added alternative TimbreTrack.

comsar/tracks/timbre.py

@@ -113,3 +113,85 @@ class TimbreTrack:
         self.pace[idx] = pace
         print(f'{pace:.4} s.')
         return res
+
+
+class TimbreTrackAlt:
+    """Compute timbre track of an audio file. Do not use correlogram.
+    """
+    def __init__(self,
+                 stft_params: Optional[container.StftParams] = None,
+                 corr_dim_params: Optional[container.CorrDimParams] = None,
+                 ) -> None:
+        """
+        Args:
+        """
+        self.params = TimbreTrackParams(stft_params or STFT_DEFAULT,
+                                        corr_dim_params or CORR_DIM_DEFAULT,
+                                        corr_gram_params or CORR_GRAM_DEFAULT)
+
+        self.cutter = Segmentation(self.params.stft.n_perseg,
+                                   self.params.stft.n_overlap,
+                                   self.params.stft.extend,
+                                   self.params.stft.pad)
+
+        self.stft = StftSegments(self.params.stft.fps, self.params.stft.window,
+                                 self.params.stft.n_fft)
+
+        self.feature_names = ('Spectral Centroid', 'Spectral Spread',
+                              'Spectral Flux', 'Roughness', 'Sharpness',
+                              'SPL', 'Correlation Dimension')
+
+        self.funcs = [features.spectral_centroid,
+                      features.spectral_spread,
+                      features.spectral_flux,
+                      features.roughness_helmholtz,
+                      features.sharpness,
+                      features.spl,
+                      features.cdim]
+
+        self.pace = np.zeros(self.n_features)
+        self.verbose = False
+
+    @property
+    def n_features(self) -> int:
+        """Number of features on track"""
+        return len(self.feature_names)
+
+    def extract(self, path) -> pd.DataFrame:
+        """Perform extraction.
+        """
+        snd = AudioFile(path)
+        if snd.fps != self.params.stft.fps:
+            snd.close()
+            raise ValueError('Sample rate of {snd!str} differs from init.')
+
+        segs = self.cutter.transform(snd.data.squeeze())
+        sxx = self.stft.transform(segs)
+
+        args = [(sxx.frqs, sxx.power),
+                (sxx.frqs, sxx.power),
+                (sxx.abs,),
+                (sxx.d_frq, sxx.abs, 15000),
+                (sxx.frqs, sxx.abs),
+                (segs.data,),
+                (segs.data,)]
+
+        kwargs = [{}, {}, {}, {}, {}, {}, self.params.corr_dim.to_dict()]
+
+        out = np.zeros((segs.n_segs, self.n_features))
+        for i, (fun, arg, kwarg) in enumerate(zip(self.funcs, args, kwargs)):
+            out[:, i] = self._worker(i, fun, arg, kwarg)
+        snd.close()
+
+        meta = TrackMeta(comsar.__version__, time_stamp(), snd.file_name)
+        out = pd.DataFrame(data=out, columns=self.feature_names)
+        return TrackResult(meta, self.params, out)
+
+    def _worker(self, idx, func, args, kwargs) -> np.ndarray:
+        print(self.feature_names[idx], end=' ... ')
+        pace = timer()
+        res = func(*args, **kwargs)
+        pace = timer() - pace
+        self.pace[idx] = pace
+        print(f'{pace:.4} s.')
+        return res