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# Copyright (c) 2009 John Glover, National University of Ireland, Maynooth
#
# This program 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 2 of the License, or
# (at your option) any later version.
#
# This program 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 this program; if not, write to the Free Software
# Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
import simpl
import pysndobj
import numpy as np
class SndObjPeakDetection(simpl.PeakDetection):
"Sinusoidal peak detection using the SndObj library (Instantaneous Frequency)"
def __init__(self):
simpl.PeakDetection.__init__(self)
self._input = pysndobj.SndObj()
self._input.SetVectorSize(self.frame_size)
self._window = pysndobj.HammingTable(self.frame_size, 0.5)
self._ifgram = pysndobj.IFGram(self._window, self._input, 1,
self.frame_size, self.hop_size)
self._threshold = 0.003
self._analysis = pysndobj.SinAnal(self._ifgram, self._threshold,
self.max_peaks)
# properties
threshold = property(lambda self: self.get_threshold(),
lambda self, x: self.set_threshold(x))
def set_frame_size(self, frame_size):
"Set the analysis frame size"
self._input.SetVectorSize(frame_size)
if self.window_type == "hamming":
self._window = pysndobj.HammingTable(frame_size, 0.5)
elif self.window_type >=0 and self.window_type <= 1:
self._window = pysndobj.HammingTable(frame_size, self.window_type)
self._ifgram.Connect("window", self._window)
self._ifgram.Set("fft size", frame_size)
self._frame_size = frame_size
def set_hop_size(self, hop_size):
self._ifgram.Set("hop size", hop_size)
self._hop_size = hop_size
def set_max_peaks(self, max_peaks):
"Set the maximum number of peaks detected"
self._analysis.Set("max tracks", max_peaks)
self._max_peaks = max_peaks
def set_window_type(self, window_type):
"Set the analysis window type"
if window_type == "hamming":
self._window = pysndobj.HammingTable(self.frame_size, 0.5)
elif window_type >=0 and window_type <= 1:
self._window = pysndobj.HammingTable(self.frame_size, window_type)
else:
raise Exception("UnknownWindowType")
self._ifgram.Connect("window", self._window)
self._window_type = window_type
def get_threshold(self):
return self._threshold
def set_threshold(self, threshold):
self._analysis.Set("threshold", threshold)
self._threshold = threshold
def find_peaks_in_frame(self, frame):
"Find and return all spectral peaks in a given frame of audio"
current_peaks = []
self._input.PushIn(frame)
self._input.DoProcess()
self._ifgram.DoProcess()
num_peaks_found = self._analysis.FindPeaks()
# loop through analysis output and create peak objects
for i in range(num_peaks_found):
p = simpl.Peak()
p.amplitude = self._analysis.Output(i*3)
p.frequency = self._analysis.Output((i*3)+1)
p.phase = self._analysis.Output((i*3)+2)
if not current_peaks:
current_peaks.append(p)
else:
if np.abs(p.frequency - current_peaks[-1].frequency) > self._min_peak_separation:
current_peaks.append(p)
else:
if p.amplitude > current_peaks[-1].amplitude:
current_peaks.remove(current_peaks[-1])
current_peaks.append(p)
return current_peaks
class SndObjPartialTracking(simpl.PartialTracking):
"Partial tracking using the algorithm from the Sound Object Library"
def __init__(self):
simpl.PartialTracking.__init__(self)
self._threshold = 0.003 # todo: property
self._num_bins = 1025 # todo: property
self._analysis = pysndobj.SinAnal(pysndobj.SndObj(), self._num_bins,
self._threshold, self.max_partials)
def set_max_partials(self, num_partials):
self._analysis.Set("max tracks", num_partials)
self._max_partials = num_partials
def update_partials(self, frame, frame_number):
"Streamable (real-time) partial-tracking."
frame_partials = []
# load Peak amplitudes, frequencies and phases into arrays
num_peaks = len(frame)
amps = simpl.zeros(num_peaks)
freqs = simpl.zeros(num_peaks)
phases = simpl.zeros(num_peaks)
for i in range(num_peaks):
peak = frame[i]
amps[i] = peak.amplitude
freqs[i] = peak.frequency
phases[i] = peak.phase
# set peaks in SndObj SinAnal object
self._analysis.SetPeaks(amps, freqs, phases)
# call SndObj partial tracking
self._analysis.PartialTracking()
# form Partial objects
num_partials = self._analysis.GetTracks()
for i in range(num_partials):
peak = simpl.Peak()
peak.amplitude = self._analysis.Output(i*3)
peak.frequency = self._analysis.Output((i*3)+1)
peak.phase = self._analysis.Output((i*3)+2)
id = self._analysis.GetTrackID(i)
# if this is a continuing partial, create a peak and append it
if id >= 0 and id <= len(self.partials) - 1:
self.partials[id].add_peak(peak)
# if not, make a new partial
else:
partial = simpl.Partial()
partial.starting_frame = frame_number
partial.add_peak(peak)
self.partials.append(partial)
frame_partials.append(peak)
return frame_partials
class SimplSndObjAnalysisWrapper(pysndobj.SinAnal):
"""An object that takes simpl Peaks and presents them as SndObj analysis
data to the SndObj synthesis objects."""
def __init__(self):
pysndobj.SinAnal.__init__(self)
self.peaks = []
def GetTracks(self):
return len(self.peaks)
def GetTrackID(self, partial_number):
if partial_number < len(self.peaks):
return self.peaks[partial_number].partial_id
else:
# TODO: what should this return if no matching partial found?
return 0
def Output(self, position):
peak = int(position) / 3
if peak > len(self.peaks):
# TODO: what should this return if no matching partial found?
return 0.0
data_field = int(position) % 3
if data_field is 0:
return self.peaks[peak].amplitude
elif data_field is 1:
return self.peaks[peak].frequency
elif data_field is 2:
return self.peaks[peak].phase
class SndObjSynthesis(simpl.Synthesis):
"Sinusoidal resynthesis using the SndObj library"
def __init__(self, synthesis_type='adsyn'):
simpl.Synthesis.__init__(self)
self._analysis = SimplSndObjAnalysisWrapper()
self._table = pysndobj.HarmTable(10000, 1, 1, 0.25)
if synthesis_type == 'adsyn':
self._synth = pysndobj.AdSyn(self._analysis, self.max_partials,
self._table, 1, 1, self.hop_size)
elif synthesis_type == 'sinsyn':
self._synth = pysndobj.SinSyn(self._analysis, self.max_partials,
self._table, 1, self.hop_size)
else:
raise Exception("UnknownSynthesisType")
self._current_frame = simpl.zeros(self.hop_size)
def set_hop_size(self, hop_size):
self._synth.SetVectorSize(hop_size)
self._hop_size = hop_size
self._current_frame = simpl.zeros(hop_size)
def set_max_partials(self, num_partials):
self._synth.Set('max tracks', num_partials)
self._max_partials = num_partials
def synth_frame(self, peaks):
"Synthesises a frame of audio, given a list of peaks from tracks"
self._analysis.peaks = peaks
if len(peaks) > self._max_partials:
self.max_partials = len(peaks)
self._synth.DoProcess()
self._synth.PopOut(self._current_frame)
return self._current_frame
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