mikkeli/uj-mastering-master
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

objectification, but with minor problems

Browse Source
This commit is contained in:
Mikkeli Matlock
2024-10-11 14:23:56 +09:00
parent 25d334251e
commit 79005de818
2 changed files with 21 additions and 12 deletions
Download Patch File Download Diff File Expand all files Collapse all files
master_core.py
+21 -12
View File
@@ -46,16 +46,16 @@ class AudioFile:
hop (int, optional): Length of window hop in seconds. Defaults to 2.
"""
# check if the window and hop are the same as before
if (self.window != window) or (self.hop != hop):
if (not hasattr(self, 'window')) or ((self.window != window) or (self.hop != hop)):
self.window, self.hop = window, hop
# only calculate if not already calculated
if self.rms_array is None:
if not hasattr(self, 'rms_array'):
# window and hop are in seconds
window_samples = window * self.sr
hop_samples = hop * self.sr
# Calculate RMS over the rolling windows
self.rms_array = librosa.feature.rms(y=y, frame_length=window_samples, hop_length=hop_samples)
self.rms_array = librosa.feature.rms(y=self.y, frame_length=window_samples, hop_length=hop_samples)
def plot_energy_levels_over_time(self, display='window'):
"""_summary_
@@ -65,14 +65,21 @@ class AudioFile:
'window' - display in a pyplot window
'gui' - for directing to the GUI (TBD)
"""
# Convert frame indices to time
times = librosa.frames_to_time(np.arange(self.rms_array.shape[1]), sr=sr, hop_length=hop_samples)
if self.rms_array is None:
if not hasattr(self, 'rms_array'):
self.get_energy_levels_over_time()
# Convert frame indices to time
times = librosa.frames_to_time(np.arange(self.rms_array.shape[1]), sr=self.sr, hop_length=self.hop*self.sr)
# Normalize RMS for color mapping
self.norm = mcolors.Normalize(vmin=0, vmax=1.0)
# check maximum amplitude to determine mastering headspace
if self.max_amplitude > 0.95:
norm = mcolors.Normalize(vmin=0, vmax=0.6)
maxpower = 0.6
else:
norm = mcolors.Normalize(vmin=0, vmax=0.3)
maxpower = 0.3
# colour map
cmap = cm.autumn
@@ -80,9 +87,9 @@ class AudioFile:
# Plot
if display == 'window':
fig, ax = plt.subplots(figsize=(10, 4))
ax.set_ylim(0., 0.4)
ax.set_ylim(0., maxpower)
for i in range(len(times)-1):
ax.fill_between(times[i:i+2], 0, rms[0][i], color=cmap(norm(rms[0][i])), edgecolor='none')
ax.fill_between(times[i:i+2], 0, self.rms_array[0][i], color=cmap(norm(self.rms_array[0][i])), edgecolor='none')
# Adding a colorbar to indicate the scale of RMS values
sm = cm.ScalarMappable(cmap=cmap, norm=norm)
@@ -92,7 +99,7 @@ class AudioFile:
ax.set_ylabel('Power')
ax.set_xlabel('Time')
ax.set_title(f'{os.path.basename(file_path)}')
ax.set_title(f'{os.path.basename(self.file_path)}')
plt.show(block=False)
plt.pause(0.001)
@@ -193,6 +200,8 @@ for file in file_path:
print(f"Average Amplitude: {avg_amplitude:.2f} dBFS")
print(f"Average Power: {avg_power:.2f} dBFS")
print(f"Average Power (STFT): {avg_power_stft:.2f} dBFS")
plot_macro_time_power_graph(file)
currentsong = AudioFile(file)
currentsong.plot_energy_levels_over_time()
# plot_macro_time_power_graph(file)
plt.show()