248 lines
6.1 KiB
Text
248 lines
6.1 KiB
Text
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{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Analyse non paramétrique du signal de la flute\n",
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"\n",
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"Nous allons commencer par afficher le signals\n",
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"\n",
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"/TODO mettre des labels X/Y avec unités et des titres à toutes les figure"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"metadata": {},
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"outputs": [],
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"source": [
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"using WAV\n",
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"\n",
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"s, fs = wavread(\"../myson.wav\");\n",
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"s = vec(s);\n",
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"t = (0 : 1 : size(s)[1]-1)/fs;\n",
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"fs = floor(Int, fs);\n",
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"\n",
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"t_s = 10 #s\n",
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"trame_period = 0.005 #s\n",
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"\n",
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"floor_freq = 10 #Hz\n",
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"ceil_freq = 60 #Hz\n",
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"\n",
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"number_trame = 50 # trames on each side of t_s\n",
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"overlap = 0.0001;#s\n",
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"\n",
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"N_fft = 2^18- 1; #number points fft"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"using Plots\n",
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"plot(t, s, title=\"Son bizarre\",label=[\"Signal\"])"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Regardons des trames. La taille de trame reste classique : de l'ordre de 20ms.\n",
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"\n",
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"/TODO attention Gabor\n",
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"\n",
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"/TODO FFT avec gros nombre"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"#using LinearAlgebra\n",
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"\n",
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"#plot(t_trame, s_trame)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"using FFTW\n",
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"\n",
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"i_s = floor(Int, t_s*fs+1)\n",
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"i_e = floor(Int, i_s+trame_period*fs)\n",
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"t_trame = t[i_s:i_e]\n",
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"s_trame = s[i_s:i_e]\n",
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"\n",
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"# Fourier Transform of it \n",
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"s_pad = zeros(N_fft)\n",
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"s_pad[1:size(s_trame,1), 1:size(s_trame,2)]=s_trame\n",
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"F = fft(s_pad) |> fftshift\n",
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"freqs = fftfreq(N_fft, fs) |> fftshift\n",
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"\n",
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"# plots \n",
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"time_domain = plot(t_trame, s_trame, title = \"Signal\")\n",
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"freq_domain = plot(freqs, abs.(F), title = \"Spectrum\", xlim=(-1000, +1000)) \n",
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"plot(time_domain, freq_domain, layout = 2)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"i_s = floor(Int, t_s*fs-number_trame*trame_period*fs+1)\n",
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"i_e = floor(Int, i_s+2*number_trame*trame_period*fs)\n",
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"t_trame = t[i_s:i_e]\n",
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"s_trame = s[i_s:i_e]\n",
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"\n",
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"# Fourier Transform of it \n",
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"s_pad = zeros(N_fft)\n",
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"s_pad[1:size(s_trame,1), 1:size(s_trame,2)]=s_trame\n",
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"F = fft(s_pad) |> fftshift\n",
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"freqs = fftfreq(N_fft, fs) |> fftshift\n",
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"\n",
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"# plots \n",
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"time_domain = plot(t_trame, s_trame, title = \"Signal\")\n",
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"freq_domain = plot(freqs, abs.(F), title = \"Spectrum\", xlim=(-1000, +1000)) \n",
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"plot(time_domain, freq_domain, layout = 2)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"On cherche maintenant la fréquence du fondamental. Comme il s'agit d'un instrument à vent, on choisit notre interval de fréquence."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"using WORLD\n",
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"\n",
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"f0, timeaxis = harvest(s, fs, HarvestOption(floor_freq, ceil_freq, trame_period));#floor and ceil freq, period\n",
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"plot(timeaxis, f0)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"On observe des vibratos, par exemple un gros vibrato vers 5s, un \"fa\". La fréquence du son ne correspond pas exactement à la fréquence du fondamental. On a une modulation de fréquence.\n",
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"\n",
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"/TODO étudier cette modulation de fréquence\n",
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"\n",
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"Regardons un zoom sur un vibrato. \n",
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"\n",
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"/TODO fft du petit bout de signal"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"\n",
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"i_s = floor(Int, t_s*fs-number_trame*trame_period*fs+1)\n",
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"i_e = floor(Int, i_s+2*number_trame*trame_period*fs)\n",
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"t_trame = t[i_s:i_e]\n",
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"s_trame = s[i_s:i_e]\n",
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"\n",
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"f0, timeaxis = harvest(s_trame, fs, HarvestOption(floor_freq, ceil_freq, trame_period));#floor and ceil freq, period\n",
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"plot(timeaxis.+t_trame[1], f0)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"On va s'intéresser maintenant au spectrogramme.\n",
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"\n",
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"\\TODO On choisit une fenêtre XXXX car XXX"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"using DSP, PyPlot\n",
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"\n",
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"println(floor(Int, trame_period*fs), floor(Int, overlap*fs))\n",
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"S = spectrogram(s, floor(Int, trame_period*fs), floor(Int, overlap*fs); fs=fs, window=hanning)\n",
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"t = time(S)\n",
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"f = freq(S)\n",
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"imshow(reverse(log10.(power(S)), dims=1), extent=[first(t), last(t), first(f), last(f)], aspect=\"auto\")"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Zoom sur notre vibrato que l'on voit un peu"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"S = spectrogram(s_trame, floor(Int, trame_period*fs), floor(Int, overlap*fs); fs=fs, window=hanning)\n",
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"t = time(S)\n",
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"f = freq(S)\n",
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"imshow(reverse(log10.(power(S)), dims=1), extent=[first(t).+t_trame[1], last(t).+t_trame[1], first(f), last(f)], aspect=\"auto\")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": []
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": []
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Julia 1.2.0",
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"language": "julia",
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"name": "julia-1.2"
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},
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"language_info": {
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"file_extension": ".jl",
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"mimetype": "application/julia",
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"name": "julia",
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"version": "1.2.0"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 4
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}
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