Fix dumb type errors

main.py

@@ -3,22 +3,22 @@ import slider as sl
 from datetime import timedelta
 import place
 import sound_process
-
+import numpy as np
-def alexandre_process(bpm, offset, filename):
-    pass
 
 def main():
     filename = fd.askopenfilename()
     beatmap = sl.Beatmap.from_path(filename)
     timing = beatmap.timing_points[0]
     bpm = timing.bpm
-    offset = timing.offset.total_seconds() * 10e3
+    offset = timing.offset.total_seconds() * 1000
     print(beatmap.audio_filename)
 
-    timings, amplitudes, freqs = sound_process.process_song(beatmap.audio_filename, int(bpm), offset0=offset, n_iter_2=48)
+    data = sound_process.process_song(beatmap.audio_filename, int(bpm), offset0=offset)
     # 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]
 
     beatmap._hit_objects = place.greedy(bpm, offset, timings, amplitudes)
+    beatmap.display_name = "TIPE's Extra"
     #beatmap._hit_objects = [sl.Slider(sl.Position(0, 0), timedelta(milliseconds=3), timedelta(milliseconds=130), 0, sl.curve.Linear([sl.Position(0, 0), sl.Position(100, 100)], 100), 100, 2, 1, 1, 1, timing.ms_per_beat, [], [],)]
     beatmap.write_path("rewrite.osu")
     

sound_process.py

@@ -13,6 +13,7 @@ import os
 import random
 from pathlib import Path
 from time import sleep
+from datetime import timedelta
 
 print("Starting...\n")
 
@@ -283,8 +284,20 @@ def get_freq(song_name, offset, step, songlen, data, display=False):
 
     return frequencies
 
+def is_data_stereo(raw_global_data:list) -> bool:
+    """
+    raw_global_data : list
+    """
+    try:
+        assert(raw_global_data[0][0])
+    except IndexError:
+        return False
+    except AssertionError:
+        return True
+    return True
 
-def void_freq(song_name, offset, songlen, increment, minfreq, maxfreq, upperthr, ampthr, ampfreq, ampval, leniency, write, linear, is_stereo, output_file="trimmed.wav"):
+
+def void_freq(song_name, offset, songlen, increment, minfreq, maxfreq, upperthr, ampthr, ampfreq, ampval, leniency, write, linear, output_file="trimmed.wav"):
     """
     song_name : string
     offset : int 
@@ -315,7 +328,7 @@ def void_freq(song_name, offset, songlen, increment, minfreq, maxfreq, upperthr,
     subprocess.run(["clear"])
     subprocess.run(["rm", "crop.wav"])
 
-    if(is_stereo):
+    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
@@ -412,9 +425,9 @@ def test_sample(timelist):
 
 def convert_tuple(datares, freq):
     """
-    Takes datares and converts it to a list of tuples (amplitude, time in ms)
+    Takes datares and converts it to a list of tuples (amplitude, datetimes)
     """
-    return [(i, datares[i], freq[i]) for i in range(len(datares)) if datares[i] > 0]
+    return [(timedelta(milliseconds=i), datares[i], freq[i]) for i in range(len(datares)) if datares[i] > 0]
 
 def get_songlen(filename):
     """
@@ -425,6 +438,20 @@ def get_songlen(filename):
 
     return (len(global_data)/sample_rate)
 
+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.
+    Currently relies on file extension.
+    Returns: the song_name that should be used afterwards.
+    """
+    extension = Path(song_name).suffix
+    match extension:
+        case ".mp3" | ".ogg":
+            print("Converting to .wav...")
+            subprocess.run(["ffmpeg", "-y", "-i", song_name, output_file]) 
+            return output_file
+    return song_name
+
 def process_song(filename, bpm, offset0=0, div_len_factor=1, n_iter_2=-1, threshold=0.5, divisor=4):
     """
     filename : string (name of the song)
@@ -436,6 +463,8 @@ def process_song(filename, bpm, offset0=0, div_len_factor=1, n_iter_2=-1, thresh
     divisor : int [+] (beat divisor used to snap the notes, default is 4)
     """
 
+    filename = convert_to_wav(filename)
+
     offset = offset0/1000
 
     div_len = div_len_factor*60/bpm-0.01
@@ -448,7 +477,7 @@ def process_song(filename, bpm, offset0=0, div_len_factor=1, n_iter_2=-1, thresh
 
     filtered_name = f"{filename}_trimmed.wav"
 
-    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, is_stereo=True, output_file=filtered_name)
+    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)
@@ -456,7 +485,6 @@ def process_song(filename, bpm, offset0=0, div_len_factor=1, n_iter_2=-1, thresh
     Path(f"{filename}_trimmed.wav").unlink()
     return convert_tuple(datares, frequencies)
 
-
 def main():
     data = process_song("tetris_4.wav", 160, n_iter_2 = 64)
     #print(data)