source: python/aubio/onsetcompare.py @ 437fa65

feature/autosinkfeature/cnnfeature/cnn_orgfeature/constantqfeature/crepefeature/crepe_orgfeature/pitchshiftfeature/pydocstringsfeature/timestretchfix/ffmpeg5pitchshiftsamplertimestretchyinfft+
Last change on this file since 437fa65 was 9cf2833, checked in by Paul Brossier <piem@altern.org>, 20 years ago

evaluate doubled detection
evaluate doubled detection

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File size: 3.6 KB
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[96fb8ad]1"""Copyright (C) 2004 Paul Brossier <piem@altern.org>
2print aubio.__LICENSE__ for the terms of use
3"""
4
5__LICENSE__ = """\
6     Copyright (C) 2004 Paul Brossier <piem@altern.org>
7
8     This program is free software; you can redistribute it and/or modify
9     it under the terms of the GNU General Public License as published by
10     the Free Software Foundation; either version 2 of the License, or
11     (at your option) any later version.
12
13     This program is distributed in the hope that it will be useful,
14     but WITHOUT ANY WARRANTY; without even the implied warranty of
15     MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
16     GNU General Public License for more details.
17
18     You should have received a copy of the GNU General Public License
19     along with this program; if not, write to the Free Software
20     Foundation, Inc., 675 Mass Ave, Cambridge, MA 02139, USA.
21"""           
22
23""" this file contains routines to compare two lists of onsets or notes.
24it somewhat implements the Receiver Operating Statistic (ROC).
25see http://en.wikipedia.org/wiki/Receiver_operating_characteristic
26"""
27
28from numarray import *
29
[9cf2833]30def onset_roc(ltru, lexp, eps):
31    """ compute differences between two lists
32          orig = hits + missed + merged
33          expc = hits + bad + doubled
34        returns orig, missed, merged, expc, bad, doubled
35    """
36    orig, expc = len(ltru), len(lexp)
37    # if lexp is empty
38    if expc == 0 : return orig,orig,0,0,0,0
39    missed, bad, doubled, merged = 0, 0, 0, 0
40    # find missed and doubled ones first
41    for x in ltru:
[96fb8ad]42        correspond = 0
[9cf2833]43        for y in lexp:
44            if abs(x-y) <= eps:    correspond += 1
45        if correspond == 0:        missed += 1
46        elif correspond > 1:       doubled += correspond - 1 
47    # then look for bad and merged ones
48    for y in lexp:
[96fb8ad]49        correspond = 0
[9cf2833]50        for x in ltru:
51            if abs(x-y) <= eps:    correspond += 1
52        if correspond == 0:        bad += 1
53        elif correspond > 1:       merged += correspond - 1
54    # check consistancy of the results
55    assert ( orig - missed - merged == expc - bad - doubled)
56    return orig, missed, merged, expc, bad, doubled
57
58def onset_diffs(ltru, lexp, eps):
59    """ compute differences between two lists
60          orig = hits + missed + merged
61          expc = hits + bad + doubled
62        returns orig, missed, merged, expc, bad, doubled
63    """
64    orig, expc = len(ltru), len(lexp)
65    # if lexp is empty
66    l = []
67    if expc == 0 : return l
68    # find missed and doubled ones first
69    for x in ltru:
70        correspond = 0
71        for y in lexp:
72            if abs(x-y) <= eps:    l.append(y-x) 
73    # return list of diffs
74    return l
75
[96fb8ad]76def notes_roc (la, lb, eps):
77    """ creates a matrix of size len(la)*len(lb) then look for hit and miss
78    in it within eps tolerance windows """
79    gdn,fpw,fpg,fpa,fdo,fdp = 0,0,0,0,0,0
80    m = len(la)
81    n = len(lb)
82    x =           resize(la[:,0],(n,m))
83    y = transpose(resize(lb[:,0],(m,n)))
84    teps =  (abs(x-y) <= eps[0]) 
85    x =           resize(la[:,1],(n,m))
86    y = transpose(resize(lb[:,1],(m,n)))
87    tpitc = (abs(x-y) <= eps[1]) 
88    res = teps * tpitc
89    res = add.reduce(res,axis=0)
90    for i in range(len(res)) :
91        if res[i] > 1:
92            gdn+=1
93            fdo+=res[i]-1
94        elif res [i] == 1:
95            gdn+=1
96    fpa = n - gdn - fpa
97    return gdn,fpw,fpg,fpa,fdo,fdp
98
99def load_onsets(filename) :
100    """ load onsets targets / candidates files in arrays """
101    l = [];
102   
103    f = open(filename,'ro')
104    while 1:
105        line = f.readline().split()
106        if not line : break
107        l.append(float(line[0]))
108   
109    return l
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