testing

components/AudioVisualizer.py

@@ -12,6 +12,7 @@ class AudioVisualizer(QtWidgets.QWidget):
         self.x_resolution = x_resolution
         self.fft_analyser = FFTAnalyser(self.media_player, self.x_resolution)
         self.fft_analyser.calculatedVisual.connect(self.set_amplitudes)
+        self.fft_analyser.calculatedVisualRs.connect(self.set_rs)
         self.fft_analyser.start()
         self.amps = np.array([])
         self._plot_item = None
@@ -55,6 +56,9 @@ class AudioVisualizer(QtWidgets.QWidget):
     def get_amplitudes(self):
         return self.amps
 
+    def get_rs(self):
+        return self.rs
+
     def get_decibels(self):
         """Convert amplitude values to decibel scale
 
@@ -63,7 +67,7 @@ class AudioVisualizer(QtWidgets.QWidget):
         With a noise floor cutoff at around -96dB (for very small values)
         """
         # Avoid log(0) by adding a small epsilon
-        epsilon = 1e-30
+        epsilon = 1e-6
         amplitudes = np.maximum(self.amps, epsilon)
         # Convert to decibels (20*log10 is the standard formula for amplitude to dB)
         db_values = 20 * np.log10(amplitudes)
@@ -71,6 +75,9 @@ class AudioVisualizer(QtWidgets.QWidget):
         db_values = np.maximum(db_values, -96)
         return db_values
 
+    def set_rs(self, rs):
+        self.rs = np.array(rs)
+
     def set_amplitudes(self, amps):
         """
         This function is hooked into the calculatedVisual signal from FFTAnalyzer() object

utils/fft_analyser.py

@@ -13,6 +13,7 @@ class FFTAnalyser(QtCore.QThread):
     """Analyses a song using FFTs."""
 
     calculatedVisual = QtCore.pyqtSignal(np.ndarray)
+    calculatedVisualRs = QtCore.pyqtSignal(np.ndarray)
 
     def __init__(self, player, x_resolution):  # noqa: F821
         super().__init__()
@@ -122,11 +123,12 @@ class FFTAnalyser(QtCore.QThread):
                 self.points[n] = amp
 
             # Set a lower threshold to properly reach zero
-            if self.points[n] < 1e-4:
+            if self.points[n] < 1e-2:
                 self.points[n] = 0
 
+        print(self.points)
         # interpolate points
-        rs = gaussian_filter1d(self.points, sigma=1)
+        rs = gaussian_filter1d(self.points, sigma=2)
 
         # divide by the highest sample in the song to normalise the
         # amps in terms of decimals from 0 -> 1