diff --git a/cleaned_sp.py b/cleaned_sp.py
index fafcce5..ee33a94 100644
--- a/cleaned_sp.py
+++ b/cleaned_sp.py
@@ -27,10 +27,11 @@ def retrieve_dominant_freqs(song_name, offset, songlen, segsize):
     
     # remove high_pitched/low-pitched frequencies
     minfreq = 110
-    maxfreq = 440*8
+    maxfreq = 440*6
     
     # cutting the song to only keep the one we're interested in
     subprocess.run(["ffmpeg", "-ss", str(offset), "-t", str(songlen+offset), "-i", song_name, "crop.wav"], shell=False) 
+    subprocess.run(["clear"])
 
     # extracting data from cropped song
     sample_rate, raw_song_data = wavfile.read("crop.wav")
@@ -50,6 +51,9 @@ def retrieve_dominant_freqs(song_name, offset, songlen, segsize):
     else:
         song_data = raw_song_data
 
+    print("\nSampleRate : ", sample_rate)
+    print("SegSize : ", blit)
+
     # remove the copy of the song
     subprocess.run(["rm", "crop.wav"], shell=False)
     
@@ -77,6 +81,7 @@ def retrieve_dominant_freqs(song_name, offset, songlen, segsize):
         # calculate the fft, append it to fft_list
         pff = scp.fft.rfft(song_data[int(current_time*sample_rate):int(sample_rate*(current_time+segsize))])
         fft_list.append(pff)
+        #print("(k =", k, ") :", left_id, "to", right_id)
 
         # just to avoid what causes 0.1 + 0.1 == 0.2 to be False
         k += 1
@@ -96,9 +101,9 @@ def retrieve_dominant_freqs(song_name, offset, songlen, segsize):
     for i in range(len(fft_list)):
         current_max = -1
         current_fmax = 0
-        
+
         for j in range(len(fft_list[i])): 
-            if(pfreq[j] < maxfreq and pfreq[j] >= minfreq and np.abs(fft_list[i][j]) > current_max):
+            if(j < len(pfreq) and pfreq[j] < maxfreq and pfreq[j] >= minfreq and np.abs(fft_list[i][j]) > current_max):
                 current_max = np.abs(fft_list[i][j])
                 current_fmax = pfreq[j]
                 
@@ -111,17 +116,10 @@ def retrieve_dominant_freqs(song_name, offset, songlen, segsize):
 
 def void_freq_clean(song_name, offset, songlen, segsize, minfreq, maxfreq, ampthr, output_name):
     # removes unnecessary frequencies/amps from a song
-    #ampthr is in [0, 1]
-    
-    # remove high_pitched/low-pitched frequencies
-    minfreq = 110
-    maxfreq = 440*8
-    
-    # cutting the song to only keep the one we're interested in
-    subprocess.run(["ffmpeg", "-ss", str(offset), "-t", str(songlen+offset), "-i", song_name, "crop.wav"], shell=False) 
+    # ampthr is in [0, 1]
 
     # extracting data from cropped song
-    sample_rate, raw_song_data = wavfile.read("crop.wav")
+    sample_rate, raw_song_data = wavfile.read(song_name)
     blit = int(sample_rate*segsize) # Te
 
     song_data = [0 for i in range(len(raw_song_data))]
@@ -215,6 +213,7 @@ def retrieve_dominant_amps(song_name, offset, songlen, segsize, percent):
     
     # cutting the song to only keep the one we're interested in
     subprocess.run(["ffmpeg", "-ss", str(offset), "-t", str(songlen+offset), "-i", song_name, "crop.wav"], shell=False) 
+    subprocess.run(["clear"])
 
     # extracting data from cropped song
     sample_rate, raw_song_data = wavfile.read("crop.wav")
@@ -291,7 +290,7 @@ def convert_to_wav(song_name:str, output_file="audio.wav") -> str:
             return output_file
     return song_name
 
-def retrieve_all_from_song(filename, t0, t1, dt=0.001, threshold=0.1):
+def retrieve_all_from_song(filename, t0, t1, dta=0.001, dtf=0.01, threshold=0.1, show=True):
     # dt = sample interval
     # threshold is in percent
 
@@ -309,31 +308,39 @@ def retrieve_all_from_song(filename, t0, t1, dt=0.001, threshold=0.1):
     sample_rate, _ = wavfile.read("crop0.wav")
 
     print("Filtering song...")
-    void_freq_clean(new_fn, t0, t1-t0, dt, 200, 2500, 0.05, "crop1.wav")
+    #void_freq_clean(new_fn, t0, t1-t0, dt, 200, 2500, 0.05, "crop1.wav")
 
     print("Now retrieving the frequencies")
-    (maxlist, maxamps) = retrieve_dominant_freqs(new_fn, t0, t1-t0, dt)
+    (maxlist, maxamps) = retrieve_dominant_freqs(new_fn, t0, t1-t0, dtf)
     
     print("Now retrieving the amplitudes")
-    amps = retrieve_dominant_amps(new_fn, t0, t1-t0, dt, threshold)
+    amps = retrieve_dominant_amps(new_fn, t0, t1-t0, dta, threshold)
 
     print("Len of freqs : ", len(maxlist), "|", len(maxamps))
     print("Len of amps : ", len(maxlist), "|", len(amps))
 
-    timesF = [t0 + dt*k for k in range(len(maxlist))]
-    timesA = [t0 + dt*k for k in range(len(amps))]
+    maxa = amps[0]
+    for jj in amps:
+        if(jj > maxa):
+            maxa = jj
 
-    plt.plot(timesF, maxlist)
-    plt.show()
+    for i in range(len(amps)):
+        amps[i] = (amps[i] * 2000) / maxa
 
-    plt.plot(timesA, amps)
-    plt.show()
+    if(show):
+        timesF = [t0 + dtf*k for k in range(len(maxlist))]
+        timesA = [t0 + dta*k for k in range(len(amps))]
+
+        plt.plot(timesA, amps)
+        plt.plot(timesF, maxlist)
+        plt.show()
 
     # free()
     subprocess.run(["rm", "crop0.wav"], shell=False)
 
-retrieve_all_from_song("tetris_4.wav", 0, 5)
+retrieve_all_from_song("tetris_4.wav", 0, 5, dtf=0.375/2)
 print("yipee")
+print(1/(160/60));
 
 
 
diff --git a/crop1.wav b/crop1.wav
index 31148cb..530107d 100644
Binary files a/crop1.wav and b/crop1.wav differ