main.py

@@ -1,33 +0,0 @@
-from tkinter import filedialog as fd
-import slider as sl
-from datetime import timedelta
-import place
-import sound_process
-
-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
-    print(beatmap.audio_filename)
-
-    timings, amplitudes, freqs = sound_process.process_song(beatmap.audio_filename, offset, bpm)
-
-    beatmap._hit_objects = place.greedy(bpm, offset, timings, amplitudes)
-    #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")
-    
-    #timings, intensities = alexandre_process(bpm, offset, beatmap.audio_filename)
-
-
-
-    print(bpm)
-    
-
-
-if __name__ == "__main__":
-    main()

place.py

@@ -1,43 +1,32 @@
 import numpy as np
-import slider as sl
-from datetime import timedelta
 
-QUARTER = 1
+"""
-HALF = 2
+whle 
-NOTE = 4
+"""
-
-def beatify(bpm:float, offset:int, time_ms:timedelta) -> float:
-    return bpm/60000 * (time_ms - offset)
-
-def debeatify(bpm:float, offset:int, beat:int) -> timedelta:
-    return timedelta(milliseconds=(beat*60000/bpm) + offset)
 
 def f(intensity): return np.pi/2 - np.arctan(2*intensity - 5)
 
-def greedy(bpm:int, offset:int, timings:list, amplitudes:list):
+def greedy():
     """
     input: takes Alexandre's note selection / intensity data
     output: list of object type / position
     """
     flow = 1
-    notes = [sl.HitObject(0, timedelta(milliseconds=0), 0) * len(timings)]
+    song_beat = 0
-    beats = np.array(beatify(timings))
+    notes = [0 * len(rhythms)]
-    for (delta, note_beat, intensity, i) in zip(timings, beats, amplitudes, range(len(timings))):
+    for (rhythm, i) in zip(rhythms, range(len(rhythms))):
+        song_beat += rhythm.time
         try:
-            duration = note_beat - beats[i + 1]
+            duration = rhythm.time - rhythms[i + 1].time
-            if duration in (QUARTER, HALF):
+            if duration in (1, 2):
-                notes[i] = sl.Circle(sl.Position(0, 0), delta, 0)
+                note_type = "cercle"
-            notes[i] = sl.Circle(sl.Position(0, 0), delta, 0)
-            """
             elif duration % 2 == 0:
                 rhythms.insert(0, f"slider {duration}")
             else:
                 rhythms.insert(0, f"reverse_slider {duration}")
-        """
         except IndexError:
-            notes[i] = sl.Circle(sl.Position(0, 0), delta, 0)
+            note_type = "cercle"
         # TODO mettre à jour flow
-        """
         if len(notes) > 2:
             angle = flow * f(rhythm.intensite)
             x1, y1 = notes[i-2].position
@@ -47,8 +36,6 @@ def greedy(bpm:int, offset:int, timings:list, amplitudes:list):
             y3 = y2 + (intensity * np.sin(angle + old_angle))
         else:
             pass
-        """
-    return notes
         
 
         

sound_process.py

@@ -11,7 +11,6 @@ import heapq
 import scipy
 import os
 import random
-from datetime import timedelta
 from pathlib import Path
 from time import sleep
 
@@ -381,15 +380,16 @@ def test_sample(timelist):
 #BPM = 140
 #Length = 32*60/BPM-0.01
 
-def convert_tuple(datares, freq) -> tuple[timedelta, int, float]:
+def convert_tuple(datares, freq):
     """
     Takes datares and converts it to a list of tuples (amplitude, time in ms)
     """
-    return [(timedelta(milliseconds=i), datares[i], freq[i]) for i in range(len(datares)) if datares[i] > 0]
+    return [(i, datares[i], freq[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):
+    #zaejzlk
     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)