def __init__(self, constraintSdifPath):
self.sdifFile = pysdif.SdifFile(os.path.expanduser(constraintSdifPath),
'r')
sc = self.sdifFile.get_stream_IDs()
self.numConstraints = len(sc)
self.constraints = {}
self.operatorLookup = {
'and ': 'self.andOMP',
'or ': 'self.orOMP',
'xor ': 'self.xorOMP',
'nand ': 'self.nandOMP',
'nor ': 'self.norOMP',
'xnor ': 'self.xnorOMP',
'b ': 'self.biasOMP',
'w ': 'self.weightOMP'
}
#obtain the full constraint expression
for nvt in self.sdifFile.get_NVTs():
if 'Fullconstraint' in nvt.keys():
self.fullConstraintString = nvt['Fullconstraint']
break
print(self.fullConstraintString)
#initialize the OMPursuiConstraintObjects
for i, constraint in enumerate(sc):
C = OMPursuitConstraint(constraint.treeway)
self.constraints[i + 1] = C
self.setConstraintValuesAndTimes()
def writeModelSdif(self, path):
iterationIndices = self.ompModel.parameterArray.argsort(order='mtime')
self.ompModel.parameterArray.sort(order='mtime')
f = pysdif.SdifFile('%s' % os.path.expanduser(path), 'w')
f.add_NVT({
'Date': time.asctime(time.localtime()),
'Tablename': 'FileInfo',
'Author': 'OM-Pursuit v0.1 - G. Boyes, M. Schumacher'
})
f.add_frame_type('XSGR', 'XSGR soundgrain-data')
f.add_frame_type(
'XGLB',
'XDUR duration, XCRP Corpus-ID, XMDC Midi-cent, XVEL Midi-velocity, XNRM Signal-norm'
)
f.add_matrix_type('XDUR', 'Duration')
f.add_matrix_type('XCRP', 'Corpus-ID')
f.add_matrix_type('XMDC', 'Midi-cent')
f.add_matrix_type('XVEL', 'Midi-velocity')
f.add_matrix_type('XNRM', 'Signal-norm')
#the amplitude is 1./ norm * mp-coef
f.add_matrix_type(
'XSGR', 'Amplitude-coefficient, MP-coefficient, Iteration-index')
#add the stream references from the dictionary
for ref in self.ompDictionary.sdifFile.get_stream_IDs():
f.add_streamID(ref.numid, ref.source, ref.treeway)
#add the global data for the soundgrains in the model
normLkp = {}
for key in (set(self.ompDictionary.soundgrains.keys())
& set(np.unique(self.ompModel.parameterArray['mindex']))):
sg = self.ompDictionary.soundgrains[key]
for mkey in sg.globalValues:
frame = f.new_frame('XGLB', 0.0, key)
frame.add_matrix(mkey,
np.array([[float(sg.globalValues[mkey])]]))
frame.write()
frame = f.new_frame('XGLB', 0.0, key)
frame.add_matrix('XNRM', np.array([[sg.norm]]))
normLkp[key] = sg.norm
frame.write()
#add the time-varying analysis data
for i, row in enumerate(self.ompModel.parameterArray):
frame = f.new_frame('XSGR', row['mtime'], row['mindex'])
frame.add_matrix(
'XSGR',
np.array([[1.0 / normLkp[row['mindex']] * row['mcoef']],
[row['mcoef']], [iterationIndices[i]]]))
frame.write()
f.close()
def read_sdif(infile):
s = pysdif.SdifFile(infile)
sig = s.signature
if sig == b"RBEP":
return _read_rbep(s)
elif sig == b"1TRK":
return _read_1trck(s)
else:
raise IOError(f"Sdiffile with unknown signature: {sig}")
def readSdif(self, sdif_in):
import pysdif
sdif_file = pysdif.SdifFile(sdif_in)
for frame in sdif_file:
P = Polygon()
P.readFrame(frame)
self.polygons.append(P)
def getSoundfiles(self, file_list, midiinfosdif):
"""Add specific audio files in the directory to a Corpus instance"""
import pysdif
sdiff = pysdif.SdifFile(midiinfosdif)
midiinfo = sdiff.get_NVTs()
midiinfo_ = {}
for mi in midiinfo:
if mi["TableName"] == "velocity":
midiinfo_["velocity"] = mi
elif mi["TableName"] == "midicent":
midiinfo_["midicent"] = mi
# get only the soundfiles, avoid anything else in the dir
self.fileDescriptors = np.zeros(
len(file_list),
dtype=[
("file_index", int),
("length", int),
("sampleRate", int),
("norm", float),
("midicent", int),
("velocity", int),
],
)
d = [q for q in os.listdir(self.directory) if q[0] != "."]
indices = [[i for i in range(len(d)) if d[i] == f][0]
for f in file_list]
i = 0
for ind, f in enumerate(file_list):
if not any([
os.path.splitext(f)[1].lower() == p
for p in [".aif", ".wav", ".aiff", ".au"]
]):
continue
x = self.readAudio(self.directory + "/" + f)
self.fileDescriptors["file_index"][i] = indices[ind]
self.fileDescriptors["length"][i] = len(x[0])
self.fileDescriptors["sampleRate"][i] = x[1]
self.fileDescriptors["norm"][i] = linalg.norm(x[0])
self.fileDescriptors["midicent"][i] = midiinfo_["midicent"][f]
self.fileDescriptors["velocity"][i] = midiinfo_["velocity"][f]
i += 1
self.soundfiles[indices[ind]] = f
self.fileDescriptors = self.fileDescriptors[0:i]
def __init__(self, path):
self.sdifFile = pysdif.SdifFile(os.path.expanduser(path), 'r')
sc = self.sdifFile.get_stream_IDs()
self.constraints = {}
self.numConstraints = len(sc)
#initialize the appropriate objects
for i, constraint in enumerate(sc):
C = OMPAnalysisConstraint(constraint.treeway)
self.constraints[i + 1] = C
self.setConstraintValuesAndTimes()
def getAllSoundfiles(self, midiinfosdif):
"""Add all of the sound files in the directory to a Corpus instance"""
import pysdif
sdiff = pysdif.SdifFile(midiinfosdif)
midiinfo = sdiff.get_NVTs()
midiinfo_ = {}
for mi in midiinfo:
if mi["TableName"] == "velocity":
midiinfo_["velocity"] = mi
elif mi["TableName"] == "midicent":
midiinfo_["midicent"] = mi
# get only the soundfiles, avoid anything else in the dir
d = [q for q in os.listdir(self.directory) if q[0] != "."]
self.fileDescriptors = np.zeros(
len(d),
dtype=[
("file_index", int),
("length", int),
("sampleRate", int),
("norm", float),
("midicent", int),
("velocity", int),
],
)
i = 0
k = 0
for ind, val in enumerate(d):
if not any([
os.path.splitext(val)[1].lower() == p
for p in [".aif", ".wav", ".aiff", ".au"]
]):
continue
x = self.readAudio(self.directory + "/" + val)
self.fileDescriptors["file_index"][i] = k
self.fileDescriptors["length"][i] = len(x[0])
self.fileDescriptors["sampleRate"][i] = x[1]
self.fileDescriptors["norm"][i] = linalg.norm(x[0])
self.fileDescriptors["midicent"][i] = midiinfo_["midicent"][val]
self.fileDescriptors["velocity"][i] = midiinfo_["velocity"][val]
i += 1
k += 1
self.soundfiles[k] = val
self.fileDescriptors = self.fileDescriptors[0:i]
def __init__(self, sdifPath):
sdifFile = pysdif.SdifFile(os.path.expanduser(sdifPath), 'r')
self.times = []
for frame in sdifFile:
'''
if frame.signature == 'XXXX':
for matrix in frame:
self.times.append(matrix.get_data()[0])
else:
self.times.append(frame.time)'''
self.times.append(frame.time)
self.times = np.array(self.times)
self.times = self.times[np.argwhere(
self.times >= 0.0).flatten()] #sanity check
def makeFile():
f = pysdif.SdifFile('testStreamSdif.sdif', 'w')
f.add_streamID(0, 'a_source', 'a_tree')
f.add_streamID(1, 'another_source', 'another_tree')
f.add_frame_type('XFXX', 'XMXX anXMXX')
f.add_matrix_type('XMXX', 'value')
for n in range(100):
if n < 50:
q = 0
else:
q = 1
frame = f.new_frame('XFXX', n, q)
for m in range(4):
frame.add_matrix('XMXX', np.array([[float(m)]]))
frame.write()
f.close()
def _write_sdif_1trc(partials: List[np.ndarray],
outfile: str,
labels: U[List[int], np.ndarray] = None,
fadetime=0.) -> None:
if labels:
logger.warn(
"labels are not supported (at the moment) when writing to 1TRC sdif"
)
import pysdif
sdif = pysdif.SdifFile(outfile, "w")
sdif.add_NVT({'creator': 'pysdif3'})
#sdif.add_matrix_type("1TRC", "Index, Frequency, Amplitude, Phase")
#sdif.add_frame_type("1TRC", ["1TRC SinusoidalTracks"])
frametimes = _get_frame_times(partials)
partials = [partial_sample_at(p, frametimes) for p in partials]
allbps = []
for i, partial in enumerate(partials):
partialidx = np.ones(shape=(len(partial), ), dtype=float) * i
bps = np.column_stack((partial, partialidx))
allbps.append(bps)
bparray = np.row_stack(allbps)
bparray = bparray[bparray[:, 0].argsort()]
seen = set()
startidx = 0
for i in range(len(bparray)):
row = bparray[i]
# t f a p b i
# 1trc: i f a p
idx = int(row[5])
if idx not in seen:
seen.add(idx)
else:
data = bparray[startidx:i]
t0 = data[0, 0]
frame = data[:, (5, 1, 2, 3)]
if not frame.flags.c_contiguous:
frame = np.ascontiguousarray(frame)
sdif.new_frame_one_matrix("1TRC", t0, "1TRC", frame)
startidx = i
seen.clear()
seen.add(idx)
def sdif2array(self, sdif_in, type_string_list):
"""Make an SDIF file into a python dictionary of ndarrays separated by matrix type
sdif_in := SDIF file to read
type_string_list := SDIF matrix types to be extracted (these need to be defined in pydbm.data.Type.sdifTypes)"""
import pysdif
sdif_file = pysdif.SdifFile(sdif_in)
data = [[] for k in type_string_list]
for frame in sdif_file:
for matrix in frame:
for ind, ts in enumerate(type_string_list):
if matrix.signature == ts:
data[ind].append(
(frame.time, matrix.get_data().copy()))
num = [sum([len(p[1]) for p in data[k]]) for k in range(len(data))]
S = dict(
zip(
(type_string_list[k] for k in range(len(data))),
(np.zeros(num[k], dtype=self.sdifTypes[type_string_list[k]])
for k in range(len(data))),
))
for indx, d in enumerate(data):
c = 0
for i in range(len(d)):
if len(d[i][1]) == 0:
continue
tim = d[i][0]
for q in range(len(d[i][1])):
r = [k for k in d[i][1][q]]
r.insert(0, tim)
S[type_string_list[indx]][c] = tuple(r)
c += 1
return S
def __init__(self, sdifPath, downsampleFactor):
#obtain the sdif file object
self.sdifFile = pysdif.SdifFile(os.path.expanduser(sdifPath), 'r')
#obtain the references to the streams in sdifFile
self.streamRefs = self.sdifFile.get_stream_IDs()
#the number of sound references
self.numRefs = len(self.streamRefs)
self.sdifTypes = {}
#assign a lookup for soundgrains
self.soundgrains = {}
for i, sg in enumerate(self.streamRefs):
self.soundgrains[sg.numid] = OMPursuitSoundgrain(
sg.source, downsampleFactor)
self.soundgrains[sg.numid].corpusID = eval(sg.treeway)
#build the descriptor object (holds the raw data, might not need this as an attibute at a later stage...)
#TODO: some of the frame types in the definition may not have data associated, so the table references should be built when reading the SDIF
self.descriptorLookup = {}
for i in range(1, self.numRefs + 1):
self.descriptorLookup[i] = {}
for ft in self.sdifFile.get_frame_types():
self.descriptorLookup[i][ft.signature] = {}
for component in ft.components:
self.descriptorLookup[i][ft.signature][
component.signature] = {}
self.descriptorLookup[i][ft.signature][
component.signature]['name'] = component.name
self.descriptorLookup[i][ft.signature][
component.signature]['num'] = component.num
self.descriptorLookup[i][ft.signature][
component.signature]['values'] = []
self.descriptorLookup[i][ft.signature][
component.signature]['time'] = []
for g in self.soundgrains.values():
g.globalValues = {}
#read the descriptor values from the sdif and fill the lookup table
for frame in self.sdifFile:
for matrix in frame:
if frame.signature == 'XGLB':
self.soundgrains[frame.id].globalValues[
matrix.signature] = (matrix.get_data()[0])[0]
else:
self.descriptorLookup[frame.id][frame.signature][
matrix.signature]['values'].append(
(matrix.get_data()[0]))
self.descriptorLookup[frame.id][frame.signature][
matrix.signature]['time'].append(frame.time)
#if matrix.signature not in self.sdifTypes.keys():
#self.sdifTypes[matrix.signature] = matrix.desc
#get the dimension in order to build the ndarrays
maxy = [0, 0]
for i, matsig in enumerate(['1DSC', '1WMN']):
for k in range(1, self.numRefs + 1):
for key in self.descriptorLookup[k][matsig].keys():
n = len(self.descriptorLookup[k][matsig][key]['time'])
if n > maxy[i]:
maxy[i] = n
dtype = [(d, float) for d in self.descriptorLookup[1]['1WMN'].keys()
if len(self.descriptorLookup[1]['1WMN'][d]['values']) > 0]
dtype.append(('XCRP', int))
dtype.append(('XDUR', float))
dtype.append(('time', float))
allGlbs = []
for sgs in self.soundgrains.values():
for key in sgs.globalValues.keys():
if key not in allGlbs:
allGlbs.append(key)
if 'XMDC' in allGlbs:
dtype.append(('XMDC', int))
if 'XVEL' in allGlbs:
dtype.append(('XVEL', int))
for i in range(1, self.numRefs + 1):
for q, ys in enumerate(maxy):
if q == 0:
self.soundgrains[i].shortTimeDescriptors = np.zeros(
ys, dtype=dtype)
dummyArray = self.soundgrains[i].shortTimeDescriptors
dummyString = '1DSC'
else:
self.soundgrains[i].averagedDescriptors = np.zeros(
ys, dtype=dtype)
dummyArray = self.soundgrains[i].averagedDescriptors
dummyString = '1WMN'
for j in range(ys):
checkTime = True
for key in [d[0] for d in dtype]:
if key not in ['time', 'XCRP', 'XDUR', 'XMDC', 'XVEL']:
if len(self.descriptorLookup[i][dummyString][key]
['values']) > j:
dummyArray[j][key] = self.descriptorLookup[i][
dummyString][key]['values'][j]
if checkTime:
checkTime = False
dummyArray[j][
'time'] = self.descriptorLookup[i][
dummyString][key]['time'][j]
elif key in ['XCRP', 'XDUR', 'XMDC', 'XVEL']:
try:
dummyArray[j][key] = self.soundgrains[
i].globalValues[key]
except KeyError:
dummyArray[j][key] = 0
self.indices = set(self.soundgrains.keys(
)) #store the set of indices to apply the constriant operations later
def writeSDIF(self, outpath, labeled=True):
"""Generate an sdif from a soundgrain analysis books"""
import pysdif
f = pysdif.SdifFile("%s" % outpath, "w")
f.add_NVT({
"TableName": "FileInfo",
"date": time.asctime(time.localtime()),
"sample rate": self.sampleRate,
})
uc = np.unique(self.atoms["corpus_index"])
f.add_NVT(
dict([("TableName", "CorpusDirectories")] + zip(
[str(k) for k in uc],
[
C.directory
for C in [self.SoundDatabase.corpora[c] for c in uc]
],
)))
for c in uc:
ainds = np.where(self.atoms["corpus_index"] == c)[0]
finds = self.atoms["file_index"][ainds]
f.add_NVT(
dict([("TableName", "Corpus-%i" % c)] + zip(
[str(k) for k in finds],
[
self.SoundDatabase.corpora[c].soundfiles[k]
for k in finds
],
)))
f.add_frame_type("XADS", "XSGM NewXSGM, XSLM NewXSLM")
self.atoms.sort(order="onset")
f.add_matrix_type(
"XSGM",
"onset, duration, corpus_index, file_index, norm, mag, molecule")
f.add_matrix_type(
"XSLM",
"onset, duration, corpus_index, file_index, norm, midicent, velocity, mag, molecule",
)
n = 0
while n < len(self.atoms["onset"]):
t = self.atoms["onset"][n]
frame = f.new_frame("XADS", t / float(self.sampleRate))
c = 0
for ind in np.where(self.atoms["onset"] == t)[0]:
N = self.atoms[ind]
if not labeled:
frame.add_matrix(
"XSGM",
np.array([[
N["onset"],
N["duration"],
N["corpus_index"],
N["file_index"],
N["norm"],
N["mag"],
N["molecule"],
]]),
)
else:
frame.add_matrix(
"XSLM",
np.array([[
N["onset"],
N["duration"],
N["corpus_index"],
N["file_index"],
N["norm"],
N["midicent"],
N["velocity"],
N["mag"],
N["molecule"],
]]),
)
c += 1
frame.write()
n += c
f.close()
def _write_sdif_rbep(partials: List[np.ndarray],
outfile: str,
labels: U[List[int], np.ndarray] = None) -> None:
"""
Args:
partials: the partials to write
outfile: the path of the sdif file to generate
labels: if given, a list of integers with the same size as the partials,
one label per partial
"""
import pysdif
sdif = pysdif.SdifFile(outfile, "w")
sdif.add_NVT({'creator': 'pysdif3'})
sdif.add_matrix_type(
"RBEP", "Index, Frequency, Amplitude, Phase, Bandwidth, Offset")
if labels:
sdif.add_matrix_type("RBEL", "Index, Label")
sdif.add_frame_type("RBEP", ["RBEP ReassignedBandEnhancedPartials"])
if labels:
sdif.add_frame_type("RBEL", ["RBEL PartialLabels"])
if isinstance(labels, list):
assert len(labels) == len(partials)
labelframe = np.asarray(labels, dtype=float)
elif isinstance(labels, np.ndarray):
assert len(labels.shape) == 1 and labels.shape[0] == len(partials)
labelframe = labels
else:
raise TypeError(
f"Expected a list of ints or a numpy array, got {type(labels)}"
)
sdif.new_frame_one_matrix("RBEL", 0, "RBEL", labelframe)
allbps = []
for i, partial in enumerate(partials):
partialidx = np.ones(shape=(len(partial), ), dtype=float) * i
bps = np.column_stack((partial, partialidx))
allbps.append(bps)
bparray = np.row_stack(allbps)
bparray = bparray[bparray[:, 0].argsort()]
seen = set()
startidx = 0
for i in range(len(bparray)):
# print(i, len(bparray))
row = bparray[i]
# t f a p b i
# rbep: i f a p b offset
idx = int(row[5])
if idx not in seen:
seen.add(idx)
else:
data = bparray[startidx:i]
times = data[:, 0]
t0 = times[0]
offsets = times - t0
rbepframe = data.copy()
rbepframe[:, 0] = data[:, 5]
rbepframe[:, 5] = offsets
# rbepframe = np.column_stack((data[:, (5, 1, 2, 3, 4)], offsets))
if not rbepframe.flags.c_contiguous:
rbepframe = np.ascontiguousarray(rbepframe)
sdif.new_frame_one_matrix("RBEP", t0, "RBEP", rbepframe)
startidx = i
seen.clear()
seen.add(idx)
def readFile():
f = pysdif.SdifFile('testStreamSdif.sdif', 'r')
for frame in f:
print(frame.id)
for matrix in frame:
print(matrix.get_data())
def write_rbep(outfile, matrices, labels, rbep=True, **kws):
# TODO: save labels
matrices = aslist(matrices)
assert isinstance(outfile, str)
assert isinstance(matrices, list)
assert isinstance(matrices[0], np.ndarray)
assert isinstance(labels, list) or labels is None
assert isinstance(rbep, bool)
logger.debug("opening %s" % outfile)
sdif = pysdif.SdifFile(outfile, "w")
logger.debug("adding type")
sdif.add_predefined_frametype(b"RBEP")
numbps = [len(m) for m in matrices]
sumbps = sum(numbps)
# alltimes = np.concatenate([p.times for p in spectrum])
alltimes = np.concatenate([m[:, 0] for m in matrices])
# allidx = np.concatenate([np.full((n,), i, dtype=int) for i, n in enumerate(numbps)])
maxbps = max(numbps)
indices = np.arange(maxbps, dtype=int)
allidx = np.empty((sumbps, ), dtype=int)
pos = 0
for i, n in enumerate(numbps):
allidx[pos:pos + n] = i
pos += n
allbpidx = np.concatenate([indices[:n] for n in numbps])
sortidx = np.argsort(alltimes)
t0 = alltimes[sortidx[0]]
sorted_idx = allidx[sortidx]
sorted_bpidx = allbpidx[sortidx]
N = len(matrices)
frametime = t0
present0 = array.array("b", [0]) * N
present = present0[:]
rowidx = -1
bigmatrix = np.zeros((N, 6), dtype=float)
for i in range(sortidx.shape[0]):
idx = sorted_idx[i]
bpidx = sorted_bpidx[i]
# rbep: index freq amp phase bw offset
# 1trc: index freq amp phase
arr = matrices[idx]
t = arr[bpidx, 0]
if present[idx]:
matrix = bigmatrix[:rowidx + 1]
sdif.new_frame_one_matrix("RBEP", frametime, "RBEP", matrix)
frametime = t
rowidx = 0
present[:] = present0
else:
present[idx] = 1
rowidx += 1
assert rowidx < N
bigmatrix[rowidx, 0] = idx
bigmatrix[rowidx, 1] = arr[bpidx, 1]
bigmatrix[rowidx, 2] = arr[bpidx, 2]
bigmatrix[rowidx, 3] = arr[bpidx, 3]
bigmatrix[rowidx, 4] = arr[bpidx, 4]
bigmatrix[rowidx, 5] = t - frametime
matrix = bigmatrix[:rowidx + 1]
sdif.new_frame_one_matrix("RBEP", frametime, "RBEP", matrix)
sdif.close()
def writeSDIF(self, outpath):
"""Generate an SDIF file from a sequence of decomposition book"""
import pysdif
f = pysdif.SdifFile("%s" % outpath, "w")
f.add_NVT({
"date": time.asctime(time.localtime()),
"sample rate": self.sampleRate
})
f.add_frame_type(
"XBOK", "XGAM NewXGAM, XFOM NewXFOM, XGMM NewXGMM, XDMM NewXDMM")
self.atoms.sort(order="onset")
f.add_matrix_type(
"XGAM", "index, onset, scale, omega, chirp, mag, phase, norm")
f.add_matrix_type(
"XFOM",
"index, onset, scale, omega, chirp, rise, decay, mag, phase, norm")
f.add_matrix_type(
"XGMM",
"index, onset, scale, omega, chirp, order, bandwidth, mag, phase, norm",
)
f.add_matrix_type(
"XDMM",
"index, onset, scale, omega, chirp, damp, mag, phase, norm")
n = 0
while n < self.num:
t = self.atoms["onset"][n]
frame = f.new_frame("XBOK", t / float(self.sampleRate))
c = 0
for ind in np.where(self.atoms["onset"] == t)[0]:
N = self.atoms[ind]
if N["type"] == "gabor":
frame.add_matrix(
"XGAM",
np.array([[
N["index"],
N["onset"],
N["duration"],
N["omega"],
N["chirp"],
N["mag"],
N["phase"],
N["norm"],
]]),
)
elif N["type"] == "FOF":
frame.add_matrix(
"XFOM",
np.array([[
N["index"],
N["onset"],
N["duration"],
N["omega"],
N["chirp"],
N["rise"],
N["decay"],
N["mag"],
N["phase"],
N["norm"],
]]),
)
elif N["type"] == "gamma":
frame.add_matrix(
"XGMM",
np.array([[
N["index"],
N["onset"],
N["duration"],
N["omega"],
N["chirp"],
N["order"],
N["bandwidth"],
N["mag"],
N["phase"],
N["norm"],
]]),
)
elif N["type"] == "damped":
frame.add_matrix(
"XDMM",
np.array([[
N["index"],
N["onset"],
N["duration"],
N["omega"],
N["chirp"],
N["damp"],
N["mag"],
N["phase"],
N["norm"],
]]),
)
c += 1
frame.write()
n += c
f.close()
