Fixed snap error

main.py

@@ -13,7 +13,7 @@ def main():
     offset = timing.offset.total_seconds() * 1000
     print(beatmap.audio_filename)
 
-    data = sound_process.process_song(beatmap.audio_filename, int(bpm), offset0=offset)
+    data = sound_process.process_song(beatmap.audio_filename, int(bpm), offset0=offset, n_iter_2=48)
     # NOTE : remove n_iter_2 to map the whole music
     timings, amplitudes, freqs = [x[0] for x in data], [x[1] for x in data], [x[2] for x in data]
 

sound_process.py

@@ -195,44 +195,6 @@ def round_t(id, sample_rate, bpm, div, offset, k0):
         return t
     return (t - 1/(bpm*div), 0)
 
-def snap(data, sample_rate, bpm, divisor, show=False):
-    # adjust time amplitudes to match the given BPM 
-    new = [0 for x in range(int(1000*len(data)/sample_rate))] # 1pt per millisecond
-    print("old =", len(data))
-    print("len =", 1000*len(data)/sample_rate)
-    k = 0
-    t = 0
-    percent = 0
-    for i in range(len(data)):
-
-        while(t < i/sample_rate):
-            t = k/(bpm*divisor)
-            k += 60
-
-        '''
-        if(np.abs(i/sample_rate - k/(bpm*divisor)) > np.abs(i/sample_rate - (k-60)/(bpm*divisor))):
-            k -= 60
-            t = k/(bpm*divisor)'''
-
-        if(i%(len(data)//100) == 0):
-            print(percent, "%")
-            percent += 1
-
-        if(int(t*1000) < len(new)):
-            new[int(t*1000)] = max(data[i], new[int(t*1000)])
-        else:
-            new[len(new)-1] = max(data[i], new[len(new)-1])
-
-    if(show):
-        t = [j/1000 for j in range(len(new))]
-        plt.plot(t, new)
-        plt.xlabel("Time (e)")
-        plt.ylabel("Amplitude")
-        plt.grid()
-        plt.show()
-
-    return new
-
 def compress(Zxx):
     res = []
 
@@ -328,11 +290,17 @@ def void_freq(song_name, offset, songlen, increment, minfreq, maxfreq, upperthr,
     subprocess.run(["clear"])
     subprocess.run(["rm", "crop.wav"])
 
+    a = 0
+
     if(is_data_stereo(raw_global_data)):
         print("Converting to mono...")
         for x in range(len(raw_global_data)):
             global_data[x] = raw_global_data[x][0]/2 + raw_global_data[x][1]/2
 
+            if(x % (int(len(raw_global_data)/100)) == 0):
+                print(a, "/ 100")
+                a += 1
+    
     else:
         global_data = raw_global_data
 
@@ -438,6 +406,83 @@ def get_songlen(filename):
 
     return (len(global_data)/sample_rate)
 
+def snap(data, sample_rate, bpm, divisor, show=False):
+    # adjust time amplitudes to match the given BPM 
+    new = [0 for x in range(int(1000*len(data)/sample_rate))] # 1pt per millisecond
+    print("old =", len(data))
+    print("len =", 1000*len(data)/sample_rate)
+    k = 0
+    t = 0
+    percent = 0
+    for i in range(len(data)):
+
+        while(t < i/sample_rate):
+            t = k/(bpm*divisor)
+            k += 60
+
+        '''
+        if(np.abs(i/sample_rate - k/(bpm*divisor)) > np.abs(i/sample_rate - (k-60)/(bpm*divisor))):
+            k -= 60
+            t = k/(bpm*divisor)'''
+
+        if(i%(len(data)//100) == 0):
+            print(percent, "%")
+            percent += 1
+
+        if(int(t*1000) < len(new)):
+            new[int(t*1000)] = max(data[i], new[int(t*1000)])
+        else:
+            new[len(new)-1] = max(data[i], new[len(new)-1])
+
+    if(show):
+        t = [j/1000 for j in range(len(new))]
+        plt.plot(t, new)
+        plt.xlabel("Time (e)")
+        plt.ylabel("Amplitude")
+        plt.grid()
+        plt.show()
+
+    return new
+
+def snap2(data, sample_rate, bpm, first_offset=0, div=4, show=False):
+    """
+    data : list(int)
+    sample_rate : int
+    bpm = float
+    """
+
+    new = [0 for i in range(int(1000*len(data)/sample_rate))]
+
+    k = 0
+    current_t = first_offset
+
+    for i in range(len(data)):
+
+        if(i/sample_rate > current_t):
+            k += 1
+            current_t = first_offset + k*60/(bpm*div)
+
+        x = int(current_t*1000)
+        if(x < len(new)):
+            new[x] = max(new[x], data[i])
+
+    if(show):
+        t = [j/1000+first_offset for j in range(len(new))]
+        beats = [0 for j in range(len(new))]
+        k = 0
+        while((first_offset + k*60/(bpm*div)*1000 < len(new))):
+            beats[int(first_offset + k*60/(bpm*div)*1000)] = 16384
+            k += 1
+
+        plt.plot(t, beats)
+        plt.plot(t, new)
+        plt.xlabel("Time (s)")
+        plt.ylabel("Amplitude")
+        plt.grid()
+        plt.show()
+    
+    return new
+
 def convert_to_wav(song_name:str, output_file="audio.wav") -> str:
     """
     Converts the song to .wav, only if it's not already in wave format.
@@ -480,7 +525,8 @@ def process_song(filename, bpm, offset0=0, div_len_factor=1, n_iter_2=-1, thresh
     void_freq(filename, offset, min(song_len, offset+div_len*(n_iter+1)+0.01), 4*60/bpm, minfreq=0, maxfreq=220, upperthr=5000, ampthr=60, ampfreq = 1200, ampval = 5.0, leniency = 0.005, write=True, linear=False, output_file=filtered_name)
     #void_freq(filename, offset, offset+div_len*(n_iter+1)+0.01, 4*60/bpm, minfreq=0, maxfreq=330, upperthr=2500, ampthr=60, ampfreq = 1200, ampval = 1/2000, leniency = 0.0, write=True, linear=True, output_file=filtered_name)
     datares = filter_n_percent_serial(filtered_name, offset, n_iter, div_len, threshold) 
-    datares = snap(datares, 44100, bpm, 4, True)
+    #datares = snap(datares, 44100, bpm, 4, True)
+    datares = snap2(datares, 44100, bpm, first_offset=offset, div=4, show=True)
     frequencies = get_freq(filtered_name, offset, div_len, div_len*n_iter, datares, True)
     Path(f"{filename}_trimmed.wav").unlink()
     return convert_tuple(datares, frequencies)