ref: deb1fd481a56f1ef979ff1d70b0e6ac6252a13ab
dir: /python.old/aubio/onsetcompare.py/
"""Copyright (C) 2004 Paul Brossier <piem@altern.org>
print aubio.__LICENSE__ for the terms of use
"""
__LICENSE__ = """\
Copyright (C) 2004-2009 Paul Brossier <piem@aubio.org>
This file is part of aubio.
aubio 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 3 of the License, or
(at your option) any later version.
aubio 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 aubio. If not, see <http://www.gnu.org/licenses/>.
"""
""" 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 numpy 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