more

cleaned_sp.py

@@ -274,7 +274,8 @@ def keep_highest(song_name, offset, songlen, segsize, count, output_name, minfre
     
     # -------------------------------------------- Write -------------------------------------------- #
 
-    f = open("result_owen_2.txt", "w")
+    '''
+    f = open("result_megalovania.txt", "w")
     f.write("Song name : " + song_name + "\n")
     f.write("Start : " + str(offset) + "\n")
     f.write("End   : " + str(offset+songlen) + "\n\n")
@@ -285,6 +286,7 @@ def keep_highest(song_name, offset, songlen, segsize, count, output_name, minfre
         f.write("\n")
 
     f.close()
+    '''
 
     return (loct, locs)
 
@@ -301,48 +303,6 @@ 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, bpm, dta=0.001, dtf=0.01, threshold=0.06, show=True):
-    # dt = sample interval
-    # threshold is in percent
-
-    if(t1 <= t0):
-        print("ERROR : t1 <= t0\n")
-        exit(1)
-
-    # converts format to .wav
-    new_fn = convert_to_wav(filename)
-
-    print("Filtering song...")
-    #void_freq_clean(new_fn, t0, t1, dtf, 20, 20000, 0.05, "crop1.wav")
-    #def void_freq_clean(song_name, offset, songlen, segsize, minfreq, maxfreq, ampthr, output_name):
-
-    print("Now retrieving the frequencies")
-    (maxlist, maxamps) = retrieve_dominant_freqs(new_fn, t0, t1, dtf)
-    #def retrieve_dominant_freqs(song_name, offset, songlen, segsize):
-    
-    print("Now retrieving the amplitudes")
-    amps = retrieve_dominant_amps(new_fn, t0, t1, dta, threshold, (4/(bpm/60))/4)
-
-    print("Len of freqs : ", len(maxlist), "|", len(maxamps))
-    print("Len of amps : ", len(maxlist), "|", len(amps))
-
-    maxa = amps[0]
-    for jj in amps:
-        if(jj > maxa):
-            maxa = jj
-
-    for i in range(len(amps)):
-        amps[i] = (amps[i] * 2000) / maxa
-
-    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()
 '''
 # c-type
 SONG_LEN = 7
@@ -398,23 +358,23 @@ BPM = 157
 SEGSIZE = 1/(BPM/60)
 wavved_song = convert_to_wav("songs/owen(157.00024-1008).mp3")
 '''
-
+'''
 # Owen 2/2
 SONG_LEN = 7
 OFFSET = 25.466
 BPM = 157
 SEGSIZE = 1/(BPM/60)
 wavved_song = convert_to_wav("songs/owen(157.00024-1008).mp3")
-
+'''
 '''
 # death
-SONG_LEN = 8
+SONG_LEN = 10
 OFFSET = 21.750
 BPM = 180
 SEGSIZE = 1/(BPM/60)
 wavved_song = convert_to_wav("songs/Night of Knights.mp3")
 '''
-'''
+
 # Bad apple
 SONG_LEN = 20
 OFFSET = 0.152
@@ -422,7 +382,7 @@ BPM = 138
 SEGSIZE = 1/(BPM/60)
 #wavved_song = convert_to_wav("songs/Bad apple (138-152).mp3")
 wavved_song = convert_to_wav("songs/Bad apple (138-152)[filtered].wav")
-'''
+
 '''
 # Freedom dive
 SONG_LEN = 7
@@ -446,6 +406,21 @@ NOTE_DIST = (2**(1/4))
 OCTAVE_DIST = 0.05
 
 # keep_highest(song_name, offset, songlen, segsize, count, output_name, minfreq=110, maxfreq=5000, ampthr=250):
-(loct, locs) = keep_highest(wavved_song, OFFSET, SONG_LEN, SEGSIZE/4, 1, "Zblit.wav", minfreq=330, maxfreq=3000, ampthr=500)
+(loct, locs) = keep_highest(wavved_song, OFFSET, SONG_LEN, SEGSIZE/4, 1, "Zblit.wav", minfreq=220, maxfreq=3000, ampthr=800)
+
+import time
+import random
+loct2 = []
+
+for k in loct:
+    if(type(k) == float):
+        loct2.append(k)
+    else:
+        loct2.append(k[0])
+        loct2.append(k[1])
+
+for i in range(len(loct2)-1):
+    print("*"*(random.randint(10, 100)))
+    time.sleep(loct2[i+1]-loct2[i])
 
 print("yipee")

result_NoN.txt

@@ -0,0 +1,68 @@
+Song name : audio.wav
+Start : 21.75
+End   : 31.75
+
+Hit Objects : 
+21.80657596371882
+21.86517006802721
+21.954943310657598
+22.158684807256236
+22.288934240362813
+22.47361678004535
+22.554920634920634
+22.686349206349206
+22.807539682539684
+22.91013605442177
+23.045102040816328
+23.131043083900227
+23.180090702947847
+23.220328798185943
+[23.287528344671202, 23.367142857142856]
+[23.472698412698414, 23.55392290249433]
+23.821655328798187
+23.95299319727891
+24.15141723356009
+24.22986394557823
+24.498219954648526
+24.66047619047619
+[24.78424036281179, 24.884920634920636]
+25.170090702947846
+25.489603174603175
+25.57687074829932
+25.655873015873016
+25.812653061224488
+[25.908027210884356, 25.956757369614515]
+25.993038548752835
+[26.150385487528347, 26.199002267573697]
+26.305804988662132
+26.492925170068027
+26.652392290249434
+26.81343537414966
+27.013990929705216
+27.16793650793651
+27.28827664399093
+27.49448979591837
+27.838990929705215
+27.88766439909297
+27.953197278911563
+28.156689342403627
+28.287687074829932
+28.502426303854875
+28.686780045351476
+28.83141723356009
+29.16842403628118
+29.285532879818593
+[29.477437641723355, 29.53560090702948]
+29.660725623582767
+29.810306122448978
+29.866689342403628
+30.13770975056689
+[30.484603174603173, 30.555702947845806]
+30.623378684807257
+30.807585034013606
+30.956666666666667
+31.155680272108846
+31.289024943310658
+31.38056689342404
+31.4947052154195
+31.62167800453515

result_megalovania.txt

@@ -5,8 +5,7 @@ End   : 14.984
 Hit Objects : 
 [8.078591836734693, 8.132503401360545]
 8.204578231292517
-8.288115646258504
+[8.288115646258504, 8.34134693877551]
-8.34134693877551
 8.527968253968254
 [8.879102040816326, 8.922888888888888]
 [9.129260770975057, 9.181766439909296]
@@ -32,8 +31,7 @@ Hit Objects :
 12.076947845804987
 12.293716553287982
 12.344793650793651
-12.503886621315193
+[12.503886621315193, 12.549975056689341]
-12.549975056689341
 [12.88151700680272, 12.925519274376416]
 13.12928344671202
 13.183308390022676
@@ -43,7 +41,8 @@ Hit Objects :
 13.776233560090702
 13.816392290249432
 13.914839002267573
-[14.015201814058956, 14.068489795918367]
+14.015201814058956
+14.068489795918367
 14.142446712018142
 14.282956916099774
 14.527979591836734