def eval(self, inputdata, ftru, mode="roc", vmode=""):
from aubio.txtfile import read_datafile
from aubio.onsetcompare import onset_roc, onset_diffs, onset_rocloc
ltru = read_datafile(ftru, depth=0)
lres = []
for i in range(len(inputdata)):
lres.append(inputdata[i][0] * self.params.step)
if vmode == "verbose":
print "Running with mode %s" % self.params.onsetmode,
print " and threshold %f" % self.params.threshold,
print " on file", self.input
# print ltru; print lres
if mode == "local":
l = onset_diffs(ltru, lres, self.params.tol)
mean = 0
for i in l:
mean += i
if len(l):
mean = "%.3f" % (mean / len(l))
else:
mean = "?0"
return l, mean
elif mode == "roc":
self.orig, self.missed, self.merged, self.expc, self.bad, self.doubled = onset_roc(
ltru, lres, self.params.tol
)
elif mode == "rocloc":
self.v = {}
self.v["orig"], self.v["missed"], self.v["Tm"], self.v["expc"], self.v["bad"], self.v["Td"], self.v[
"l"
], self.v["labs"] = onset_rocloc(ltru, lres, self.params.tol)
def eval(self,inputdata,ftru,mode='roc',vmode=''):
from aubio.txtfile import read_datafile
from aubio.onsetcompare import onset_roc, onset_diffs, onset_rocloc
ltru = read_datafile(ftru,depth=0)
lres = []
for i in range(len(inputdata)): lres.append(inputdata[i][0]*self.params.step)
if vmode=='verbose':
print "Running with mode %s" % self.params.onsetmode,
print " and threshold %f" % self.params.threshold,
print " on file", self.input
#print ltru; print lres
if mode == 'local':
l = onset_diffs(ltru,lres,self.params.tol)
mean = 0
for i in l: mean += i
if len(l): mean = "%.3f" % (mean/len(l))
else: mean = "?0"
return l, mean
elif mode == 'roc':
self.orig, self.missed, self.merged, \
self.expc, self.bad, self.doubled = \
onset_roc(ltru,lres,self.params.tol)
elif mode == 'rocloc':
self.v = {}
self.v['orig'], self.v['missed'], self.v['Tm'], \
self.v['expc'], self.v['bad'], self.v['Td'], \
self.v['l'], self.v['labs'] = \
onset_rocloc(ltru,lres,self.params.tol)
def plot(self, onsets, ofunc, wplot, oplots, nplot=False):
import Gnuplot, Gnuplot.funcutils
import aubio.txtfile
import os.path
from numpy import arange, array, ones
from aubio.onsetcompare import onset_roc
x1, y1, y1p = [], [], []
oplot = []
if self.params.onsetmode in ('mkl', 'kl'): ofunc[0:10] = [0] * 10
self.lenofunc = len(ofunc)
self.maxofunc = max(ofunc)
# onset detection function
downtime = arange(len(ofunc)) * self.params.step
oplot.append(
Gnuplot.Data(downtime,
ofunc,
with_='lines',
title=self.params.onsetmode))
# detected onsets
if not nplot:
for i in onsets:
x1.append(i[0] * self.params.step)
y1.append(self.maxofunc)
y1p.append(-self.maxofunc)
#x1 = array(onsets)*self.params.step
#y1 = self.maxofunc*ones(len(onsets))
if x1:
oplot.append(Gnuplot.Data(x1, y1, with_='impulses'))
wplot.append(Gnuplot.Data(x1, y1p, with_='impulses'))
oplots.append((oplot, self.params.onsetmode, self.maxofunc))
# check if ground truth datafile exists
datafile = self.input.replace('.wav', '.txt')
if datafile == self.input: datafile = ""
if not os.path.isfile(datafile):
self.title = "" #"(no ground truth)"
else:
t_onsets = aubio.txtfile.read_datafile(datafile)
x2 = array(t_onsets).resize(len(t_onsets))
y2 = self.maxofunc * ones(len(t_onsets))
wplot.append(Gnuplot.Data(x2, y2, with_='impulses'))
tol = 0.050
orig, missed, merged, expc, bad, doubled = \
onset_roc(x2,x1,tol)
self.title = "GD %2.3f%% FP %2.3f%%" % \
((100*float(orig-missed-merged)/(orig)),
(100*float(bad+doubled)/(orig)))
def plot(self, onsets, ofunc, wplot, oplots, nplot=False):
import Gnuplot, Gnuplot.funcutils
import aubio.txtfile
import os.path
from numpy import arange, array, ones
from aubio.onsetcompare import onset_roc
x1, y1, y1p = [], [], []
oplot = []
if self.params.onsetmode in ("mkl", "kl"):
ofunc[0:10] = [0] * 10
self.lenofunc = len(ofunc)
self.maxofunc = max(ofunc)
# onset detection function
downtime = arange(len(ofunc)) * self.params.step
oplot.append(Gnuplot.Data(downtime, ofunc, with_="lines", title=self.params.onsetmode))
# detected onsets
if not nplot:
for i in onsets:
x1.append(i[0] * self.params.step)
y1.append(self.maxofunc)
y1p.append(-self.maxofunc)
# x1 = array(onsets)*self.params.step
# y1 = self.maxofunc*ones(len(onsets))
if x1:
oplot.append(Gnuplot.Data(x1, y1, with_="impulses"))
wplot.append(Gnuplot.Data(x1, y1p, with_="impulses"))
oplots.append((oplot, self.params.onsetmode, self.maxofunc))
# check if ground truth datafile exists
datafile = self.input.replace(".wav", ".txt")
if datafile == self.input:
datafile = ""
if not os.path.isfile(datafile):
self.title = "" # "(no ground truth)"
else:
t_onsets = aubio.txtfile.read_datafile(datafile)
x2 = array(t_onsets).resize(len(t_onsets))
y2 = self.maxofunc * ones(len(t_onsets))
wplot.append(Gnuplot.Data(x2, y2, with_="impulses"))
tol = 0.050
orig, missed, merged, expc, bad, doubled = onset_roc(x2, x1, tol)
self.title = "GD %2.3f%% FP %2.3f%%" % (
(100 * float(orig - missed - merged) / (orig)),
(100 * float(bad + doubled) / (orig)),
)
# check if ground truth datafile exists
datafile = self.input.replace('.wav','.txt')
if datafile == self.input: datafile = ""
if not os.path.isfile(datafile):
self.title = "" #"(no ground truth)"
else:
t_onsets = aubio.txtfile.read_datafile(datafile)
x2 = numarray.array(t_onsets).resize(len(t_onsets))
y2 = self.maxofunc*numarray.ones(len(t_onsets))
wplot.append(Gnuplot.Data(x2,y2,with='impulses'))
tol = 0.050
orig, missed, merged, expc, bad, doubled = \
onset_roc(x2,x1,tol)
self.title = "GD %2.3f%% FP %2.3f%%" % \
((100*float(orig-missed-merged)/(orig)),
(100*float(bad+doubled)/(orig)))
def plotplot(self,wplot,oplots,outplot=None,extension=None,xsize=1.,ysize=1.,spectro=False):
from aubio.gnuplot import gnuplot_create, audio_to_array, make_audio_plot, audio_to_spec
import re
# prepare the plot
g = gnuplot_create(outplot=outplot, extension=extension)
g('set title \'%s\'' % (re.sub('.*/','',self.input)))
if spectro:
g('set size %f,%f' % (xsize,1.3*ysize) )
else:
g('set size %f,%f' % (xsize,ysize) )
