Prepare friendly song_process function

new-process.py

@@ -11,6 +11,7 @@ import heapq
 import scipy
 import os
 import random
+from pathlib import Path
 from time import sleep
 
 print("Starting...\n")
@@ -184,7 +185,7 @@ 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):
+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))
@@ -225,7 +226,7 @@ def snap(data, sample_rate, bpm, divisor, show):
 def compress(Zxx):
     res = []
 
-def get_freq(song_name, offset, step, songlen, data):
+def get_freq(song_name, offset, step, songlen, data, display=False):
     fft_list = []
     times = []
     current_time = offset
@@ -260,7 +261,7 @@ def get_freq(song_name, offset, step, songlen, data):
         elif s != 0:
             frequencies[s] = 0
 
-    if(True):
+    if(display):
         plt.plot([t/1000 for t in range(len(data))], frequencies)
         plt.grid()
         plt.xlabel("Time (s)")
@@ -271,7 +272,7 @@ def get_freq(song_name, offset, step, songlen, data):
     return frequencies
 
 
-def void_freq(song_name, offset, songlen, increment, minfreq, maxfreq, upperthr, ampthr, ampfreq, ampval, leniency, write):
+def void_freq(song_name, offset, songlen, increment, minfreq, maxfreq, upperthr, ampthr, ampfreq, ampval, leniency, write, output_file="trimmed.wav"):
     fft_list = []
     times = []
     current_time = offset
@@ -341,7 +342,7 @@ def void_freq(song_name, offset, songlen, increment, minfreq, maxfreq, upperthr,
             res[i] = np.int16(32767*res[i]/mx)
 
         res = np.array(res)
-        wavfile.write("trimmed.wav", 44100, res)
+        wavfile.write(output_file, 44100, res)
 
     #plt.plot(np.abs(pfreq[:len(fft_list[0])]), np.abs(fft_list[0]))
     #plt.grid()
@@ -379,39 +380,32 @@ def test_sample(timelist):
 #BPM = 140
 #Length = 32*60/BPM-0.01
 
-Offset = 0
-BPM = 160
-Length = 30*60/BPM-0.01
-DivLen = 60/BPM-0.01
-N_iter = 48
-
-print("Total length :", np.round(DivLen*N_iter, 3), "s")
-
-subprocess.run(["sleep", "1"]) 
-
-if(True):
-    #void_freq("tetris_4.wav", Offset, Offset+Length, 4*60/BPM, minfreq=0, maxfreq=330, upperthr=5000, ampthr=60, ampfreq = 1200, ampval = 7.27, leniency = 0.005, write=True)
-    void_freq("tetris_4.wav", Offset, Offset+DivLen*(N_iter+1)+0.01, 4*60/BPM, minfreq=0, maxfreq=330, upperthr=5000, ampthr=60, ampfreq = 1200, ampval = 7.27, leniency = 0.005, write=True)
-
-if(False):  
-    #data2 = filter_n_percent("worlds_end_3.wav", 74.582, 15, 0.2, reduce=False, show=True)
-    data2 = filter_n_percent("trimmed.wav", 0, Length, 0.5, reduce=False, show=False)
-    #data2 = filter_n_percent("tetris_3.wav", 7, Length, 0.01, reduce=False, show=False)
-    data2 = snap(data2, 44100, BPM, 4, show=True)
-
-    #timing_pts = get_tpts(data2, 1000, 1000)
-    #test_sample(timing_pts)
-
-    write_to_file_thr(1000, data2, Offset, 0.02, "timing_points.csv")
-
-if(True):
-    datares = filter_n_percent_serial("trimmed.wav", Offset, N_iter, DivLen, 0.5)
-    datares = snap(datares, 44100, BPM, 4, show=True)
-    freqs = get_freq("trimmed.wav", Offset, DivLen, DivLen*N_iter, datares)
+def convert_tuple(datares):
+    """
+    Takes datares and converts it to a list of tuples (amplitude, time in ms)
+    """
+    return [(i, datares[i]) for i in range(len(datares)) if datares[i] > 0]
 
 
+def process_song(filename, offset, bpm, div_len_factor=60, n_iter=48, threshold=0.5, divisor=4):
+    div_len = div_len_factor/bpm-0.01
+    filtered_name = f"{filename}_trimmed.wav"
+    void_freq(filename, offset, offset+div_len*(n_iter+1)+0.01, 4*60/bpm, minfreq=0, maxfreq=330, upperthr=5000, ampthr=60, ampfreq = 1200, ampval = 7.27, leniency = 0.005, write=True, output_file=filtered_name)
+    datares = filter_n_percent_serial(filtered_name, offset, n_iter, div_len, threshold) 
+    datares = snap(datares, 44100, bpm, 4)
+    frequencies = get_freq(filtered_name, offset, div_len, div_len*n_iter, datares)
+    Path(f"{filename}_trimmed.wav").unlink()
+    return convert_tuple(datares), frequencies
+
+
+def main():
+    data, freq = process_song("tetris_4.wav", 0, 160)
+    print(data)
     print("Program finished with return 0")
 
+if __name__ == "__main__":
+    main()
+