comparison notebooks/test_music_segments.ipynb @ 6:a35bd818d8e9 branch-tests

notebook to test music segments
author Maria Panteli <m.x.panteli@gmail.com>
date Mon, 11 Sep 2017 14:22:17 +0100
parents
children 46b2c713cc73
comparison
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5:543744ed1ae7 6:a35bd818d8e9
1 {
2 "cells": [
3 {
4 "cell_type": "code",
5 "execution_count": 1,
6 "metadata": {
7 "collapsed": true
8 },
9 "outputs": [],
10 "source": [
11 "import numpy as np\n",
12 "import pickle"
13 ]
14 },
15 {
16 "cell_type": "code",
17 "execution_count": 2,
18 "metadata": {
19 "collapsed": true
20 },
21 "outputs": [],
22 "source": [
23 "filenames = ['/import/c4dm-04/mariap/train_data_melodia_8.pickle', \n",
24 " '/import/c4dm-04/mariap/val_data_melodia_8.pickle', \n",
25 " '/import/c4dm-04/mariap/test_data_melodia_8.pickle']"
26 ]
27 },
28 {
29 "cell_type": "code",
30 "execution_count": null,
31 "metadata": {
32 "collapsed": true
33 },
34 "outputs": [],
35 "source": [
36 "all_Yaudio = []\n",
37 "for filename in filenames:\n",
38 " _, Y, Yaudio = pickle.load(open(filename), 'rb')\n",
39 " all_Yaudio.append(Yaudio)\n",
40 "all_Yaudio = np.concatenate(all_Yaudio)"
41 ]
42 },
43 {
44 "cell_type": "code",
45 "execution_count": 3,
46 "metadata": {
47 "collapsed": false
48 },
49 "outputs": [
50 {
51 "ename": "NameError",
52 "evalue": "name 'all_Yaudio' is not defined",
53 "output_type": "error",
54 "traceback": [
55 "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
56 "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)",
57 "\u001b[0;32m<ipython-input-3-4107ada442c0>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0muniq_audio\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0muniq_counts\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0munique\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mall_Yaudio\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mreturn_counts\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mTrue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
58 "\u001b[0;31mNameError\u001b[0m: name 'all_Yaudio' is not defined"
59 ]
60 }
61 ],
62 "source": [
63 "uniq_audio, uniq_counts = np.unique(all_Yaudio, return_counts=True)"
64 ]
65 },
66 {
67 "cell_type": "markdown",
68 "metadata": {},
69 "source": [
70 "## Stats on audio files with very few music frames (after the speech/music discrimination)"
71 ]
72 },
73 {
74 "cell_type": "code",
75 "execution_count": 4,
76 "metadata": {
77 "collapsed": false
78 },
79 "outputs": [
80 {
81 "ename": "NameError",
82 "evalue": "name 'uniq_counts' is not defined",
83 "output_type": "error",
84 "traceback": [
85 "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
86 "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)",
87 "\u001b[0;32m<ipython-input-4-700ed156399c>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[0mmin_n_frames\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;36m10\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0mn_short_files\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mwhere\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0muniq_counts\u001b[0m\u001b[0;34m<\u001b[0m\u001b[0mmin_n_frames\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mshape\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 3\u001b[0m \u001b[0;32mprint\u001b[0m \u001b[0;34m'%d files out of %d have less than %d frames'\u001b[0m \u001b[0;34m%\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mn_short_files\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0muniq_counts\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmin_n_frames\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
88 "\u001b[0;31mNameError\u001b[0m: name 'uniq_counts' is not defined"
89 ]
90 }
91 ],
92 "source": [
93 "min_n_frames = 10\n",
94 "n_short_files = np.where(uniq_counts<min_n_frames)[0].shape\n",
95 "print '%d files out of %d have less than %d frames' % (n_short_files, len(uniq_counts), min_n_frames)"
96 ]
97 },
98 {
99 "cell_type": "markdown",
100 "metadata": {},
101 "source": [
102 "## Stats on average duration of the music segments for all tracks"
103 ]
104 },
105 {
106 "cell_type": "code",
107 "execution_count": 5,
108 "metadata": {
109 "collapsed": false
110 },
111 "outputs": [
112 {
113 "ename": "SyntaxError",
114 "evalue": "invalid syntax (<ipython-input-5-2c4ab0e943a6>, line 1)",
115 "output_type": "error",
116 "traceback": [
117 "\u001b[0;36m File \u001b[0;32m\"<ipython-input-5-2c4ab0e943a6>\"\u001b[0;36m, line \u001b[0;32m1\u001b[0m\n\u001b[0;31m print 'mean %f' np.mean(uniq_counts)\u001b[0m\n\u001b[0m ^\u001b[0m\n\u001b[0;31mSyntaxError\u001b[0m\u001b[0;31m:\u001b[0m invalid syntax\n"
118 ]
119 }
120 ],
121 "source": [
122 "sr = 2.0 # with 8-second window and 0.5-second hop size the sampling rate is 2 about 2 samples per second\n",
123 "print 'mean %f' % np.mean(uniq_counts)\n",
124 "print 'median %f' % np.median(uniq_counts)\n",
125 "print 'std %f' % np.std(uniq_counts)\n",
126 "print 'mean duration %f' % (np.mean(uniq_counts) / sr)"
127 ]
128 },
129 {
130 "cell_type": "markdown",
131 "metadata": {},
132 "source": [
133 "## Stats on average duration of the music segments for the British Library tracks"
134 ]
135 },
136 {
137 "cell_type": "code",
138 "execution_count": 7,
139 "metadata": {
140 "collapsed": false
141 },
142 "outputs": [
143 {
144 "ename": "NameError",
145 "evalue": "name 'uniq_audio' is not defined",
146 "output_type": "error",
147 "traceback": [
148 "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
149 "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)",
150 "\u001b[0;32m<ipython-input-7-4ebf50436e4a>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[0;31m#British library tracks start with 'D:/Audio/...'\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0midx_BL_tracks\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0marray\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mi\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mi\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mrange\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0muniq_audio\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0muniq_audio\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msplit\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'D:/'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m>\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 3\u001b[0m \u001b[0msr\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;36m2.0\u001b[0m \u001b[0;31m# with 8-second window and 0.5-second hop size the sampling rate is 2 about 2 samples per second\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 4\u001b[0m \u001b[0;32mprint\u001b[0m \u001b[0;34m'mean %f'\u001b[0m \u001b[0;34m%\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmean\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0muniq_counts\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0midx_BL_tracks\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 5\u001b[0m \u001b[0;32mprint\u001b[0m \u001b[0;34m'median %f'\u001b[0m \u001b[0;34m%\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmedian\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0muniq_counts\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0midx_BL_tracks\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
151 "\u001b[0;31mNameError\u001b[0m: name 'uniq_audio' is not defined"
152 ]
153 }
154 ],
155 "source": [
156 "#British library tracks start with 'D:/Audio/...'\n",
157 "idx_BL_tracks = np.array([i for i in range(len(uniq_audio)) if len(uniq_audio[i].split('D:/'))>1])\n",
158 "sr = 2.0 # with 8-second window and 0.5-second hop size the sampling rate is 2 about 2 samples per second\n",
159 "print 'mean %f' % np.mean(uniq_counts[idx_BL_tracks])\n",
160 "print 'median %f' % np.median(uniq_counts[idx_BL_tracks])\n",
161 "print 'std %f' % np.std(uniq_counts[idx_BL_tracks])\n",
162 "print 'mean duration %f' % (np.mean(uniq_counts[idx_BL_tracks]) / sr)"
163 ]
164 },
165 {
166 "cell_type": "code",
167 "execution_count": null,
168 "metadata": {
169 "collapsed": true
170 },
171 "outputs": [],
172 "source": []
173 }
174 ],
175 "metadata": {
176 "kernelspec": {
177 "display_name": "Python 2",
178 "language": "python",
179 "name": "python2"
180 },
181 "language_info": {
182 "codemirror_mode": {
183 "name": "ipython",
184 "version": 2
185 },
186 "file_extension": ".py",
187 "mimetype": "text/x-python",
188 "name": "python",
189 "nbconvert_exporter": "python",
190 "pygments_lexer": "ipython2",
191 "version": "2.7.12"
192 }
193 },
194 "nbformat": 4,
195 "nbformat_minor": 0
196 }