source: python/aubio/onsetcompare.py @ 1e7ef7c

"""Copyright (C) 2004 Paul Brossier <piem@altern.org>
print aubio.__LICENSE__ for the terms of use
"""

__LICENSE__ = """\
     Copyright (C) 2004 Paul Brossier <piem@altern.org>

     This program is free software; you can redistribute it and/or modify
     it under the terms of the GNU General Public License as published by
     the Free Software Foundation; either version 2 of the License, or
     (at your option) any later version.

     This program is distributed in the hope that it will be useful,
     but WITHOUT ANY WARRANTY; without even the implied warranty of
     MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
     GNU General Public License for more details.

     You should have received a copy of the GNU General Public License
     along with this program; if not, write to the Free Software
     Foundation, Inc., 675 Mass Ave, Cambridge, MA 02139, USA.
"""            

""" this file contains routines to compare two lists of onsets or notes.
it somewhat implements the Receiver Operating Statistic (ROC).
see http://en.wikipedia.org/wiki/Receiver_operating_characteristic
"""

def onset_roc(ltru, lexp, eps):
    """ compute differences between two lists 
          orig = hits + missed + merged 
          expc = hits + bad + doubled
        returns orig, missed, merged, expc, bad, doubled 
    """
    orig, expc = len(ltru), len(lexp)
    # if lexp is empty
    if expc == 0 : return orig,orig,0,0,0,0
    missed, bad, doubled, merged = 0, 0, 0, 0
    # find missed and doubled ones first
    for x in ltru:
        correspond = 0
        for y in lexp:
            if abs(x-y) <= eps:    correspond += 1
        if correspond == 0:        missed += 1
        elif correspond > 1:       doubled += correspond - 1 
    # then look for bad and merged ones
    for y in lexp:
        correspond = 0
        for x in ltru:
            if abs(x-y) <= eps:    correspond += 1
        if correspond == 0:        bad += 1
        elif correspond > 1:       merged += correspond - 1
    # check consistancy of the results
    assert ( orig - missed - merged == expc - bad - doubled)
    return orig, missed, merged, expc, bad, doubled 

def onset_diffs(ltru, lexp, eps):
    """ compute differences between two lists 
          orig = hits + missed + merged 
          expc = hits + bad + doubled
        returns orig, missed, merged, expc, bad, doubled 
    """
    orig, expc = len(ltru), len(lexp)
    # if lexp is empty
    l = []
    if expc == 0 : return l 
    # find missed and doubled ones first
    for x in ltru:
        correspond = 0
        for y in lexp:
            if abs(x-y) <= eps:    l.append(y-x) 
    # return list of diffs
    return l 

def onset_rocloc(ltru, lexp, eps):
    """ compute differences between two lists 
          orig = hits + missed + merged 
          expc = hits + bad + doubled
        returns orig, missed, merged, expc, bad, doubled 
    """
    orig, expc = len(ltru), len(lexp)
    l = []
    labs = []
    mean = 0
    # if lexp is empty
    if expc == 0 : return orig,orig,0,0,0,0,l,mean
    missed, bad, doubled, merged = 0, 0, 0, 0
    # find missed and doubled ones first
    for x in ltru:
        correspond = 0
        for y in lexp:
            if abs(x-y) <= eps:    correspond += 1
        if correspond == 0:        missed += 1
        elif correspond > 1:       doubled += correspond - 1 
    # then look for bad and merged ones
    for y in lexp:
        correspond = 0
        for x in ltru:
            if abs(x-y) <= eps:    
                correspond += 1
                l.append(y-x) 
                labs.append(abs(y-x))
        if correspond == 0:        bad += 1
        elif correspond > 1:       merged += correspond - 1
    # check consistancy of the results
    assert ( orig - missed - merged == expc - bad - doubled)
    return orig, missed, merged, expc, bad, doubled, l, labs

def notes_roc (la, lb, eps):
    from numarray import transpose, add, resize 
    """ creates a matrix of size len(la)*len(lb) then look for hit and miss
    in it within eps tolerance windows """
    gdn,fpw,fpg,fpa,fdo,fdp = 0,0,0,0,0,0
    m = len(la)
    n = len(lb)
    x =           resize(la[:][0],(n,m))
    y = transpose(resize(lb[:][0],(m,n)))
    teps =  (abs(x-y) <= eps[0]) 
    x =           resize(la[:][1],(n,m))
    y = transpose(resize(lb[:][1],(m,n)))
    tpitc = (abs(x-y) <= eps[1]) 
    res = teps * tpitc
    res = add.reduce(res,axis=0)
    for i in range(len(res)) :
        if res[i] > 1:
            gdn+=1
            fdo+=res[i]-1
        elif res [i] == 1:
            gdn+=1
    fpa = n - gdn - fpa
    return gdn,fpw,fpg,fpa,fdo,fdp

def load_onsets(filename) :
    """ load onsets targets / candidates files in arrays """
    l = [];
    
    f = open(filename,'ro')
    while 1:
        line = f.readline().split()
        if not line : break
        l.append(float(line[0]))
    
    return l