Remove temp file

diff --git a/timeside/analyzer/irit_speech.py~ b/timeside/analyzer/irit_speech.py~
deleted file mode 100644 (file)
index 8f0edc4..0000000
--- a/timeside/analyzer/irit_speech.py~
+++ /dev/null
@@ -1,83 +0,0 @@
-# -*- coding: utf-8 -*-
-#
-# Copyright (c) 2013 Maxime Le Coz <lecoz@irit.fr>
-
-# This file is part of TimeSide.
-
-# TimeSide 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.
-
-# TimeSide 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 TimeSide.  If not, see <http://www.gnu.org/licenses/>.
-
-# Author: Maxime Le Coz <lecoz@irit.fr>
-
-from timeside.core import Processor, implements, interfacedoc, FixedSizeInputAdapter
-from timeside.analyzer.core import *
-from timeside.api import IValueAnalyzer
-
-class IRITSpeech(Processor):
-    implements(IValueAnalyzer)
-
-    @interfacedoc
-    def setup(self, channels=None, samplerate=None, blocksize=None, totalframes=None):
-        super(AubioPitch, self).setup(channels, samplerate, blocksize, totalframes)
-        self.win_s = 2048
-        self.hop_s = self.win_s / 2
-        self.p = pitch("default", self.win_s, self.hop_s, samplerate)
-        self.p.set_unit("freq")
-        self.block_read = 0
-        self.pitches = []
-
-    @staticmethod
-    @interfacedoc
-    def id():
-        return "aubio_pitch_analyzer"
-
-    @staticmethod
-    @interfacedoc
-    def name():
-        return "f0 (aubio)"
-
-    @staticmethod
-    @interfacedoc
-    def unit():
-        return ""
-
-    def __str__(self):
-        return "pitch values"
-
-    def process(self, frames, eod=False):
-        for samples in downsample_blocking(frames, self.hop_s):
-            #time = self.block_read * self.hop_s * 1. / self.samplerate()
-            self.pitches += [self.p(samples)[0]]
-            self.block_read += 1
-        return frames, eod
-
-    def results(self):
-
-        #container = AnalyzerResultContainer()
-
-        self.pitches = numpy.array(self.pitches)
-
-        pitch = AnalyzerResult(id = "aubio_pitch", name = "f0 (aubio)", unit = "Hz")
-        pitch.value = self.pitches
-        #container.add_result(pitch)
-
-        pitch_mean = AnalyzerResult(id = "aubio_pitch_mean", name = "f0 mean (aubio)", unit = "Hz")
-        pitch_mean.value = numpy.mean(self.pitches)
-        #container.add_result(pitch_mean)
-
-        pitch_median = AnalyzerResult(id = "aubio_pitch_median", name = "f0 median (aubio)", unit = "Hz")
-        pitch_median.value = numpy.median(self.pitches)
-        #container.add_result(pitch_median)
-
-        #return container
-        return AnalyzerResultContainer([pitch, pitch_mean, pitch_median])

diff --git a/timeside/analyzer/irit_speech_4hz.pyc b/timeside/analyzer/irit_speech_4hz.pyc
deleted file mode 100644 (file)
index eed34b4..0000000
Binary files a/timeside/analyzer/irit_speech_4hz.pyc and /dev/null differ

diff --git a/timeside/analyzer/irit_speech_entropy.pyc b/timeside/analyzer/irit_speech_entropy.pyc
deleted file mode 100644 (file)
index 387de1a..0000000
Binary files a/timeside/analyzer/irit_speech_entropy.pyc and /dev/null differ

diff --git a/timeside/analyzer/irit_speech_entropy.py~ b/timeside/analyzer/irit_speech_entropy.py~
deleted file mode 100644 (file)
index a37fadf..0000000
--- a/timeside/analyzer/irit_speech_entropy.py~
+++ /dev/null
@@ -1,88 +0,0 @@
-# -*- coding: utf-8 -*-
-#
-# Copyright (c) 2013 Maxime Le Coz <lecoz@irit.fr>
-
-# This file is part of TimeSide.
-
-# TimeSide 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.
-
-# TimeSide 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 TimeSide.  If not, see <http://www.gnu.org/licenses/>.
-
-# Author: Maxime Le Coz <lecoz@irit.fr>
-
-from timeside.core import Processor, implements, interfacedoc, FixedSizeInputAdapter
-from timeside.analyzer.core import *
-from timeside.api import IValueAnalyzer
-from numpy import histogram,log,sqrt,min,max,sum,exp,array,zeros,var
-from scipy.ndimage.morphology import binary_opening
-from matplotlib import pylab
-
-class IRITSpeechEntropy(Processor):
-    implements(IValueAnalyzer)
-
-    @interfacedoc
-    def setup(self, channels=None, samplerate=None, blocksize=None, totalframes=None):
-        super(IRITSpeechEntropy, self).setup(channels, samplerate, blocksize, totalframes)
-        self.entropyValue = []
-        self.threshold = 0.4
-        self.smoothLen = 5
-        self.w_hop = 1024
-        self.modulLen = 1
-    @staticmethod
-    @interfacedoc
-    def id():
-        return "irit_speech_entropy"
-
-    @staticmethod
-    @interfacedoc
-    def name():
-        return "Speech entropy (IRIT)"
-
-    @staticmethod
-    @interfacedoc
-    def unit():
-        return ""
-
-    def __str__(self):
-        return "Speech confidences indexes"
-
-    def process(self, frames, eod=False):
-               
-        for samples in downsample_blocking(frames, self.w_hop):
-            self.entropyValue.append(entropy(samples))
-        return frames, eod        
-      
-    def results(self):
-
-        entropyValue = numpy.array(self.entropyValue)
-        w = self.modulLen*self.samplerate()/self.w_hop
-        modulentropy = computeModulation(entr,w,withLog=False)
-        confEntropy=  array(modulentropy-self.threshold)/self.threshold
-        confEntropy[confEntropy>1] = 1
-        
-        conf = AnalyzerResult(id = "irit_entropy_confidence", name = "entropy (IRIT)", unit = "?")
-        conf.value = confEntropy
-        
-        binaryEntropy = modulentropy > self.threshold
-        binaryEntropy = binary_opening(binaryEntropy,[1]*(self.smoothLen*2))
-        
-        convert = {False:'NonSpeech',True:'Speech'}
-               segList = segmentFromValues(binaryEntropy)
-        segmentsEntropy =[]
-        for s in segList : 
-            segmentsEntropy.append((s[0]*self.w_hop/float(self.samplerate()),s[1]*self.w_hop/float(self.samplerate()),convert[s[2]])) 
-        
-        segs = AnalyzerResult(id = "irit_entropy_segments", name = "seg entropy (IRIT)", unit = "s")
-        segs.value = segmentsEntropy
-
-      
-        return AnalyzerResultContainer([conf, segs])