def tempo_search(db, Key, tempo):
"""
::
Static tempo-invariant search
Returns search results for query resampled over a range of tempos.
"""
if not db.configCheck():
print "Failed configCheck in query spec."
print db.configQuery
return None
prop = 1. / tempo # the proportion of original samples required for new tempo
qconf = db.configQuery.copy()
X = db.retrieve_datum(Key)
P = db.retrieve_datum(Key, powers=True)
X_m = pylab.mat(X.mean(0))
X_resamp = pylab.array(
adb.resample_vector(X - pylab.mat(pylab.ones(X.shape[0])).T * X_m,
prop))
X_resamp += pylab.mat(pylab.ones(X_resamp.shape[0])).T * X_m
P_resamp = pylab.array(adb.resample_vector(P, prop))
seqStart = int(pylab.around(qconf['seqStart'] * prop))
qconf['seqStart'] = seqStart
seqLength = int(pylab.around(qconf['seqLength'] * prop))
qconf['seqLength'] = seqLength
tmpconf = db.configQuery
db.configQuery = qconf
res = db.query_data(featData=X_resamp, powerData=P_resamp)
res_resorted = adb.sort_search_result(res.rawData)
db.configQuery = tmpconf
return res_resorted
def tempo_search(db, Key, tempo):
"""
::
Static tempo-invariant search
Returns search results for query resampled over a range of tempos.
"""
if not db.configCheck():
print "Failed configCheck in query spec."
print db.configQuery
return None
prop = 1.0 / tempo # the proportion of original samples required for new tempo
qconf = db.configQuery.copy()
X = db.retrieve_datum(Key)
P = db.retrieve_datum(Key, powers=True)
X_m = pylab.mat(X.mean(0))
X_resamp = pylab.array(adb.resample_vector(X - pylab.mat(pylab.ones(X.shape[0])).T * X_m, prop))
X_resamp += pylab.mat(pylab.ones(X_resamp.shape[0])).T * X_m
P_resamp = pylab.array(adb.resample_vector(P, prop))
seqStart = int(pylab.around(qconf["seqStart"] * prop))
qconf["seqStart"] = seqStart
seqLength = int(pylab.around(qconf["seqLength"] * prop))
qconf["seqLength"] = seqLength
tmpconf = db.configQuery
db.configQuery = qconf
res = db.query_data(featData=X_resamp, powerData=P_resamp)
res_resorted = adb.sort_search_result(res.rawData)
db.configQuery = tmpconf
return res_resorted
def asDCM(self):
"""Return the rotation matrix of the (normalized) quaternion
http://www.x-io.co.uk/res/doc/madgwick_internal_report.pdf"""
qw, qx, qy, qz = self.q
##http://www.rossprogrammproduct.com/translations/Matrix%20and%20Quaternion%20FAQ.htm#Q54
return mat([[1-2*(qy**2+qz**2), 2*(qx*qy-qz*qw),2*(qx*qz+qy*qw)],
[2*(qx*qy+qz*qw), 1-2*(qx**2+qz**2), 2*(qy*qz-qx*qw)],
[2*(qx*qz-qy*qw), 2*(qy*qz+qx*qw), 1-2*(qx**2+qy**2)]])
def _cqft(self):
"""
::
Constant-Q Fourier transform.
"""
if not self._have_power:
if not self._power():
return False
fp = self._check_feature_params()
if fp['intensify']:
self._cqft_intensified()
else:
self._make_log_freq_map()
self.CQFT=pylab.array(pylab.sqrt(pylab.mat(self.Q)*pylab.mat(pylab.absolute(self.STFT)**2)))
self._is_intensified=False
self._have_cqft=True
if fp['verbosity']:
print "Extracted CQFT: intensified=%d" %self._is_intensified
return True
def _cqft(self):
"""
::
Constant-Q Fourier transform.
"""
if not self._power():
return False
fp = self._check_feature_params()
if self.intensify:
self._cqft_intensified()
else:
self._make_log_freq_map()
self.CQFT=P.sqrt(P.array(P.mat(self.Q)*P.mat(P.absolute(self.STFT)**2)))
self._is_intensified=False
self._have_cqft=True
if self.verbosity:
print "Extracted CQFT: intensified=%d" %self._is_intensified
self.inverse=self.icqft
self.X=self.CQFT
return True
def _cqft(self):
"""
::
Constant-Q Fourier transform.
"""
if not self._power():
return False
fp = self._check_feature_params()
if self.intensify:
self._cqft_intensified()
else:
self._make_log_freq_map()
self.CQFT=P.sqrt(P.array(P.mat(self.Q)*P.mat(P.absolute(self.STFT)**2)))
self._is_intensified=False
self._have_cqft=True
if self.verbosity:
print "Extracted CQFT: intensified=%d" %self._is_intensified
self.inverse=self.icqft
self.X=self.CQFT
return True
def asMatrix(self):
return mat(self.q)
def asMatrix(self):
return mat(self.q)
