primera_parte.py

tp/scripts/primera_parte.py (3389B)
Line numbers
   1 from utils import *
   2 from data import *
   3 
   4 ############################## Primera Parte ###################################
   5 
   6 def time_domain_cancion1():
   7     ### grafico completo
   8     time_plot(file1_fs, file1_data, file1_path)
   9 
  10     ### porciones cuasi-periodicas 'cancion1'
  11     time_plot(file1_fs, file1_data, "cancion1_0_248s_a_0_256s",
  12                t=0.248, dt=0.008, a=0.24978, da=0.003)
  13 
  14     time_plot(file1_fs, file1_data, "cancion1_0_520s_a_0_528s",
  15                t=0.520, dt=0.008, a=0.5208, da=0.003)
  16 
  17     ### salida de filtro 'cancion1'
  18     save_to_wav(file1_fs, file1_filter1_output, "file1_filter1_output.wav")
  19     save_to_wav(file1_fs, file1_filter2_output, "file1_filter2_output.wav")
  20 
  21     ### grafico comparando la muestra 1 original y filtrada 1
  22     data_arr = [normalize(file1_data), normalize(file1_filter1_output)]
  23     leg_arr = ['Señal de audio', 'Señal de audio filtrada']
  24 
  25     time_plot_multiple(file1_fs, data_arr, leg_arr,
  26                        "cancion1_filter1_output_compare")
  27 
  28     time_plot_multiple(file1_fs, data_arr, leg_arr,
  29                        "cancion1_filter1_output_compare_0_248_a_0_256",
  30                        t=0.248, dt=0.008)
  31 
  32     ### grafico comparando la muestra 1 original y filtrada 2
  33     data_arr = [normalize(file1_data), normalize(file1_filter2_output)]
  34     leg_arr = ['Señal de audio', 'Señal de audio filtrada']
  35 
  36     time_plot_multiple(file1_fs, data_arr, leg_arr,
  37                        "cancion1_filter2_output_compare")
  38     time_plot_multiple(file1_fs, data_arr, leg_arr,
  39                        "cancion1_filter2_output_compare_0_248_a_0_256",
  40                        t=0.248, dt=0.008)
  41 
  42 def time_domain_cancion2():
  43     ### grafico completo
  44     time_plot(file2_fs, file2_data, "cancion2", t=6)
  45 
  46     ### porciones cuasi-periodicas 'cancion2'
  47     time_plot(file2_fs, file2_data, "cancion2_14_72s_a_14_73s", t=14.720, dt=0.01)
  48     time_plot(file2_fs, file2_data, "cancion2_26_57s_a_26_58s", t=26.570, dt=0.01)
  49 
  50     save_to_wav(file2_fs, file2_filter1_output, "file2_filter1_output.wav")
  51     save_to_wav(file2_fs, file2_filter2_output, "file2_filter2_output.wav")
  52 
  53     ### grafico comparando la muestra 2 original y filtrada 2
  54     data_arr = [normalize(file2_data), normalize(file2_filter1_output)]
  55     leg_arr = ['Señal original', 'Señal filtrada']
  56 
  57     time_plot_multiple(file2_fs, data_arr, leg_arr,
  58                        "cancion2_6s_filter1_output_compare", t=6)
  59     time_plot_multiple(file2_fs, data_arr, leg_arr,
  60                        "cancion2_6s_filter1_output_compare_26_57_a_26_58",
  61                        t=26.57, dt=0.01)
  62 
  63     ### grafico comparando la muestra 2 original y filtrada 2
  64     data_arr = [normalize(file2_data), normalize(file2_filter2_output)]
  65     leg_arr = ['Señal original', 'Señal filtrada']
  66 
  67     time_plot_multiple(file2_fs, data_arr, leg_arr,
  68                        "cancion2_6s_filter2_output_compare", t=6)
  69     time_plot_multiple(file2_fs, data_arr, leg_arr,
  70                        "cancion2_6s_filter2_output_compare_26_57_a_26_58",
  71                        t=26.57, dt=0.01)
  72 
  73 def time_domain_music_instruments():
  74     ### grafico de los instrumentos musicales
  75     time_plot(a4_flauta_fs, a4_flauta_data, "a4_flauta", t=0.25, dt=0.010)
  76     time_plot(a4_clarinete_fs, a4_clarinete_data, "a4_clarinete", t=0.25, dt=0.010)
  77     time_plot(a4_violin_fs, a4_violin_data, "a4_violin", t=0.25, dt=0.010)
  78 
  79
TB065
