def plot_simmat(simmat, labfile=''):
"""
Plot a similarity matrix
"""
# postprocess simmat
simmat2 = copy.deepcopy(simmat)
if False:
allvals = np.sort(simmat2.flatten())
medianval = allvals[int(allvals.shape[0] / 2)]
simmat2[np.where(simmat2 > medianval)] = medianval
# plot
import pylab as P
P.figure()
args2 = {'interpolation': 'nearest', 'cmap': P.cm.gray, 'aspect': 'auto'}
P.imshow(simmat2, **args2)
P.colorbar()
P.hold(True)
# we have labfile?
if labfile != '':
startbeats, stopbeats, labels = DUMMY.read_lab_file(labfile)
for sb in startbeats:
pos = sb
assert pos <= simmat.shape[1], 'wrong pos for lab data'
point_size = 30
P.scatter(pos, pos, s=point_size, c='r', marker='o')
P.scatter(pos, 0, s=point_size, c='r', marker='o')
P.scatter(0, pos, s=point_size, c='r', marker='o')
P.hold(False)
# diff
simmat_diff = np.diff(simmat2)
P.figure()
args2 = {'interpolation': 'nearest', 'cmap': P.cm.gray, 'aspect': 'auto'}
P.imshow(simmat_diff, **args2)
P.colorbar()
P.hold(True)
# we have labfile?
if labfile != '':
startbeats, stopbeats, labels = DUMMY.read_lab_file(labfile)
for sb in startbeats:
pos = sb - 1
assert pos <= simmat.shape[1], 'wrong pos for lab data'
point_size = 30
P.scatter(pos, pos, s=point_size, c='r', marker='o')
P.scatter(pos, 0, s=point_size, c='r', marker='o')
P.scatter(0, pos, s=point_size, c='r', marker='o')
P.hold(False)
# show
P.show()
def plot_simmat(simmat,labfile=''):
"""
Plot a similarity matrix
"""
# postprocess simmat
simmat2 = copy.deepcopy(simmat)
if False:
allvals = np.sort(simmat2.flatten())
medianval = allvals[int(allvals.shape[0]/2)]
simmat2[np.where(simmat2>medianval)] = medianval
# plot
import pylab as P
P.figure()
args2 = {'interpolation':'nearest','cmap':P.cm.gray,'aspect':'auto'}
P.imshow(simmat2,**args2)
P.colorbar()
P.hold(True)
# we have labfile?
if labfile != '':
startbeats,stopbeats,labels = DUMMY.read_lab_file(labfile)
for sb in startbeats:
pos = sb
assert pos <= simmat.shape[1],'wrong pos for lab data'
point_size = 30
P.scatter(pos,pos,s=point_size,c='r',marker='o')
P.scatter(pos,0,s=point_size,c='r',marker='o')
P.scatter(0,pos,s=point_size,c='r',marker='o')
P.hold(False)
# diff
simmat_diff = np.diff(simmat2)
P.figure()
args2 = {'interpolation':'nearest','cmap':P.cm.gray,'aspect':'auto'}
P.imshow(simmat_diff,**args2)
P.colorbar()
P.hold(True)
# we have labfile?
if labfile != '':
startbeats,stopbeats,labels = DUMMY.read_lab_file(labfile)
for sb in startbeats:
pos = sb - 1
assert pos <= simmat.shape[1],'wrong pos for lab data'
point_size = 30
P.scatter(pos,pos,s=point_size,c='r',marker='o')
P.scatter(pos,0,s=point_size,c='r',marker='o')
P.scatter(0,pos,s=point_size,c='r',marker='o')
P.hold(False)
# show
P.show()
def maxes_beattimes_segs_from_audiofile(wavfile):
"""
Utility function
From a given eavfile:
- computes the fingerprint maxes
- gets the corresponding en beat times
- gets the corresponding annotated segments
RETURN:
signal, sampling rate, maxes, beatstarts, duration, segstarts, labels
"""
# fingerprint it
wav = LANDMARKS.AUDIOLAB.wavread(wavfile)
L,S,T,maxes = LANDMARKS.find_landmarks(wav[0],wav[1])
# find the EN matfile
relwavfile = os.path.relpath(wavfile,start=_audio_dir)
enmatfile = os.path.join(_enfeats_dir,relwavfile+'.mat')
assert os.path.exists(enmatfile),'can not find matfile %s' % enmatfile
mat = sio.loadmat(enmatfile)
btstart = mat['btstart']
try:
duration = mat['duration'][0][0] # must be some bug in encoding
except TypeError:
duration = mat['duration']
# get the segments
labfile = enmatfile+'.lab'
assert os.path.exists(labfile),'can not find labfile %s' % labfile
segstarts, segstops, labels = DUMMY.read_lab_file(labfile)
# done, return
return wav[0], wav[1], maxes, btstart, duration, segstarts, labels
def maxes_beattimes_segs_from_audiofile(wavfile):
"""
Utility function
From a given eavfile:
- computes the fingerprint maxes
- gets the corresponding en beat times
- gets the corresponding annotated segments
RETURN:
signal, sampling rate, maxes, beatstarts, duration, segstarts, labels
"""
# fingerprint it
wav = LANDMARKS.AUDIOLAB.wavread(wavfile)
L, S, T, maxes = LANDMARKS.find_landmarks(wav[0], wav[1])
# find the EN matfile
relwavfile = os.path.relpath(wavfile, start=_audio_dir)
enmatfile = os.path.join(_enfeats_dir, relwavfile + '.mat')
assert os.path.exists(enmatfile), 'can not find matfile %s' % enmatfile
mat = sio.loadmat(enmatfile)
btstart = mat['btstart']
try:
duration = mat['duration'][0][0] # must be some bug in encoding
except TypeError:
duration = mat['duration']
# get the segments
labfile = enmatfile + '.lab'
assert os.path.exists(labfile), 'can not find labfile %s' % labfile
segstarts, segstops, labels = DUMMY.read_lab_file(labfile)
# done, return
return wav[0], wav[1], maxes, btstart, duration, segstarts, labels
def plot_simmat(data, winsize=1, overlap=0, dist=euclidean_dist, labfile=''):
"""
Similat to build_simmat, but plot it, and can add labfile information
"""
# get simmat
simmat = build_simmat(data, winsize=winsize, overlap=overlap, dist=dist)
# PLOT IT
import pylab as P
P.figure()
args2 = {'interpolation': 'nearest', 'cmap': P.cm.gray, 'aspect': 'auto'}
P.imshow(simmat, **args2)
# we have labfile?
if labfile != '':
P.hold(True)
startbeats, stopbeats, labels = DUMMY.read_lab_file(labfile)
for sb in startbeats:
pos = int((sb - winsize) / (winsize - overlap)) + 1
assert pos <= simmat.shape[1], 'wrong pos for lab data'
point_size = 30
P.scatter(pos, pos, s=point_size, c='r', marker='o')
P.scatter(pos, 0, s=point_size, c='r', marker='o')
P.scatter(0, pos, s=point_size, c='r', marker='o')
P.hold(False)
P.show()
# plot first derivative
P.figure()
simmat_diff = np.diff(simmat)
simmat_diff = simmat_diff * simmat_diff
P.imshow(simmat_diff, **args2)
# we have labfile?
if labfile != '':
P.hold(True)
startbeats, stopbeats, labels = DUMMY.read_lab_file(labfile)
for sb in startbeats:
pos = int((sb - winsize) / (winsize - overlap)) + 1 - 1
assert pos <= simmat.shape[1], 'wrong pos for lab data'
point_size = 30
P.scatter(pos, pos, s=point_size, c='r', marker='o')
P.scatter(pos, 0, s=point_size, c='r', marker='o')
P.scatter(0, pos, s=point_size, c='r', marker='o')
P.hold(False)
P.show()
# done, return simmat
return simmat
def plot_simmat(data,winsize=1,overlap=0,dist=euclidean_dist,labfile=''):
"""
Similat to build_simmat, but plot it, and can add labfile information
"""
# get simmat
simmat = build_simmat(data,winsize=winsize,overlap=overlap,dist=dist)
# PLOT IT
import pylab as P
P.figure()
args2 = {'interpolation':'nearest','cmap':P.cm.gray,'aspect':'auto'}
P.imshow(simmat,**args2)
# we have labfile?
if labfile != '':
P.hold(True)
startbeats,stopbeats,labels = DUMMY.read_lab_file(labfile)
for sb in startbeats:
pos = int((sb - winsize) / (winsize - overlap)) + 1
assert pos <= simmat.shape[1],'wrong pos for lab data'
point_size = 30
P.scatter(pos,pos,s=point_size,c='r',marker='o')
P.scatter(pos,0,s=point_size,c='r',marker='o')
P.scatter(0,pos,s=point_size,c='r',marker='o')
P.hold(False)
P.show()
# plot first derivative
P.figure()
simmat_diff = np.diff(simmat)
simmat_diff = simmat_diff * simmat_diff
P.imshow(simmat_diff,**args2)
# we have labfile?
if labfile != '':
P.hold(True)
startbeats,stopbeats,labels = DUMMY.read_lab_file(labfile)
for sb in startbeats:
pos = int((sb - winsize) / (winsize - overlap)) + 1 - 1
assert pos <= simmat.shape[1],'wrong pos for lab data'
point_size = 30
P.scatter(pos,pos,s=point_size,c='r',marker='o')
P.scatter(pos,0,s=point_size,c='r',marker='o')
P.scatter(0,pos,s=point_size,c='r',marker='o')
P.hold(False)
P.show()
# done, return simmat
return simmat
def plot_maxes_beats_segs(maxes,maxessecs,btstart,labfile=''):
"""
Plot the maxes for the whole songs, indicates beats and segs
"""
import pylab as P
P.figure()
P.hold(True)
P.scatter(maxessecs,list(maxes[1,:]),c='b')
#for bs in list(btstart.flatten()):
# P.axvline(x=bs,color='r')
if labfile != '':
startbeats,stopbeats,labels = DUMMY.read_lab_file(labfile)
for sb in startbeats:
pos = btstart[0,sb]
P.axvline(x=pos,color='g')
P.hold(False)
P.show()
def plot_nearby_diff(beatfeats,labfile='',dist=dist_avg_closest_pair):
"""
plot difference between nearby beats
"""
dists = map(lambda k: dist(beatfeats[k-1],beatfeats[k+1]),range(1,len(beatfeats)-1))
# plot
import pylab as P
P.plot(dists)
P.hold(True)
if labfile != '':
startbeats,stopbeats,labels = DUMMY.read_lab_file(labfile)
for sb in startbeats:
pos = sb
point_size = 30
P.scatter(pos,0,s=point_size,c='r',marker='o')
P.hold(False)
P.show()
def plot_maxes_beats_segs(maxes, maxessecs, btstart, labfile=''):
"""
Plot the maxes for the whole songs, indicates beats and segs
"""
import pylab as P
P.figure()
P.hold(True)
P.scatter(maxessecs, list(maxes[1, :]), c='b')
#for bs in list(btstart.flatten()):
# P.axvline(x=bs,color='r')
if labfile != '':
startbeats, stopbeats, labels = DUMMY.read_lab_file(labfile)
for sb in startbeats:
pos = btstart[0, sb]
P.axvline(x=pos, color='g')
P.hold(False)
P.show()
def plot_nearby_diff(beatfeats, labfile='', dist=dist_avg_closest_pair):
"""
plot difference between nearby beats
"""
dists = map(lambda k: dist(beatfeats[k - 1], beatfeats[k + 1]),
range(1,
len(beatfeats) - 1))
# plot
import pylab as P
P.plot(dists)
P.hold(True)
if labfile != '':
startbeats, stopbeats, labels = DUMMY.read_lab_file(labfile)
for sb in startbeats:
pos = sb
point_size = 30
P.scatter(pos, 0, s=point_size, c='r', marker='o')
P.hold(False)
P.show()
