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new-process.py

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+from math import *
+import numpy as np
+from scipy.io import wavfile
+from scipy import signal
+import matplotlib.pyplot as plt
+import subprocess
+import wave as wv
+import struct
+import librosa
+
+print("Starting...\n")
+
+def fct(song_name, offset, increment, songlen, maxfreq, display):
+    to_cut = 20000//maxfreq
+    global_Zxx = np.array([])
+    global_f = np.array([])
+    global_t = np.array([])
+    current_time = offset
+    k = 0
+    while(current_time <= songlen):
+        subprocess.run(["ffmpeg", "-ss", str(current_time), "-t", str(increment), "-i", song_name, "crop.wav"]) 
+
+        sample_rate, audio_data = wavfile.read('crop.wav')
+        size = audio_data.size
+
+        subprocess.run(["clear"])
+        subprocess.run(["rm", "crop.wav"])
+
+        # do stuff here
+        #f, t, Zxx = signal.stft(audio_data, sample_rate, nperseg=1000)
+        f, t, Zxx = signal.spectrogram(audio_data, fs=sample_rate, nfft=size)
+        leng = len(f)
+
+        f, Zxx = f[:leng//to_cut], Zxx[:leng//to_cut]
+
+        #print(len(Zxx))
+        #print(len(Zxx[0]))
+
+        #convert to mel 
+        '''
+        for i in range(len(Zxx)):
+            for j in range(len(Zxx[i])):
+                Zxx[i][j] *= 1127*np.log(1+f[i]/700)'''
+
+        t = np.array([current_time + x for x in t])
+
+        if(k == 0):
+            global_f = f
+            global_t = t
+            global_Zxx = Zxx
+        else:
+            global_Zxx = np.concatenate((global_Zxx, Zxx), axis=1)
+            global_t = np.concatenate((global_t, t))
+
+        #print(len(global_t))
+        
+        k += 1
+        current_time = offset + k*increment
+
+        print("Completion rate : ", np.round(100*(current_time-offset)/(songlen-offset), 4), "%")
+    
+    if(display):
+        plt.pcolormesh(global_t, global_f, np.abs(global_Zxx), shading='gouraud')
+        # print(len(global_Zxx), len(global_Zxx[0]))
+        # 88 192 = 2500
+        # 70 192 = 2000
+        plt.title('STFT Magnitude')
+        plt.ylabel('Frequency [Hz]')
+        plt.xlabel('Time [sec]')
+        plt.show()
+
+    return global_t, global_f, np.abs(global_Zxx)
+
+def write_to_file(t, flist, maxlist, filename):
+    file = open(filename, 'w')
+    file.writelines('time,frequency,maxvalue\n')
+    for i in range(len(t)):
+        file.writelines(str(np.round(t[i], 3)))
+        file.writelines(',')
+        file.writelines(str(np.round(flist[i], 1)))
+        file.writelines(',')
+        file.writelines(str(np.round(maxlist[i], 0)))
+        file.writelines('\n')
+    #close(file)
+
+def plot_max(time, freq, Zxx, save):
+    fres = [0 for x in range(len(time))]
+    maxres = [0 for x in range(len(time))]
+    for t in range(len(time)):
+        subprocess.run(["clear"])
+        print(t, "/", len(time))
+        for f in range(len(Zxx)):
+            if(maxres[t] < Zxx[f][t]):
+                maxres[t] = Zxx[f][t]
+                fres[t] = freq[f]
+
+    if(save):
+        write_to_file(time, fres, maxres, 'output.csv')
+
+    '''
+    plt.plot(time, fres, 'r')
+    plt.grid()
+    plt.xlabel("Time")
+    plt.ylabel("Maximum frequencies")
+
+    plt.plot(time, maxres, 'g')
+    plt.grid()
+    plt.xlabel("Time")
+    plt.ylabel("Maximun values")
+
+    plt.show()'''
+
+    fig, (ax1, ax2) = plt.subplots(2)
+    fig.suptitle('Top : time and frequencies\nBottom : time and max values')
+    ax1.plot(time, fres)
+    ax2.plot(time, maxres)
+
+    plt.show()
+
+t, f, Zxx = fct("worlds_end_3.wav", 160.889, 0.032, 170.889, 3000, False)
+#t, f, Zxx = fct("changing.wav", 0, 0.05, 3.9, 5000)
+#fct("worlds_end_3.wav", 75, (60/178)/4, 75+2, 2500)
+
+plot_max(t, f, Zxx, True)
+
+
+print("Program finished with return 0")