MIRtoolbox: purgedata(c) - File Exchange

Code covered by the BSD License

Highlights from
MIRtoolbox

aiffread(filePath,indexRange) AIFFREAD Read AIFF (Audio Interchange File Format) sound file.
center(x)
combinepeaks(p,v,thr) dedicated function for (Klapuri, 99) that creates a curve made of burst
convolve2(x, m, shape, tol) CONVOLVE2 Two dimensional convolution.
demo1pitch.m
demo2timbre
demo3tempo To get familiar with tempo estimation from audio using the MIR Toolbox.
demo4segmentation To get familiar with some approaches of segmentation of audio files
demo5export Example of use of the export function.
demo6curves(file) Example of use of curve analysis tools, such as moment estimations.
demo7tonality.m
displot(x,y,xlab,ylab,t,fp,pp... graphical display of any data (except mirscalar data) computed by MIRToolbox
fcoefs=MakeERBFilters(fs,numC... function [fcoefs]=MakeERBFilters(fs,numChannels,lowFreq)
haspeaks(d)
hwr(x) Half-Wave Rectifier
isamir(x,class)
mirattacks(orig,varargin)
mirattackslope(orig,varargin) a = mirattackslope(x) estimates the average slope of each note attack.
mirattacktime.m
mirauditory(x,varargin) Produces the output based on an auditory modelling, of the signal x,
mirbeatspectrum(orig,varargin) n = mirbeatspectrum(m) evaluates the beat spectrum.
mirbrightness(x,varargin) b = mirbrightness(s) calculates the spectral brightness, i.e. the amount
mircentroid(x,varargin) c = mircentroid(x) calculates the centroid (or center of gravity) of x.
mirchunklim(lim) c = mirchunklim returns the maximal chunk size.
mircluster(a,varargin) c = mircluster(a,f) clusters the segments in the audio sequence(s)
mircompute(algo,varargin)
mirdist(x,y,dist) d = mirdist(x,y) evaluates the distance between x and y.
mirentropy(x,varargin) h = mirentropy(a) calculates the relative entropy of a.
mirerror(operator,message)
mireval(d,file,single,export) mireval(d,filename) applies the mirdesign object d to the audio file
mirevalparallel(a,sr,w,single... Function in separate M file, because the "parfor" command is not
mireventdensity(x,varargin) e = mireventdensity(x) estimate the mean frequency of events (i.e., how
mirexport(f,varargin) mirexport(filename,...) exports statistical information related to
mirfeatures(x,varargin) f = mirfeatures(x) computes a large set of features from one or several
mirfilterbank(orig,varargin) b = mirfilterbank(x) performs a filterbank decomposition of an audio
mirflatness(orig,varargin) f = mirflatness(x) calculates the flatness of x, which can be either:
mirfluctuation(orig,varargin) f = mirfluctuation(x) calculates the fluctuation strength, indicating the
mirflux(orig,varargin) f = mirflux(x) measures distance between successive frames.
mirframe(x,varargin) f = mirframe(x) creates the frame decomposition of the audio signal x.
mirframenow(x,option)
mirfunction(method,x,varg,nou... Meta function called by all MIRtoolbox functions.
mirgetdata(x,varargin) d = mirgetdata(x) return the data contained in the object x in a
mirgetrange(x)
mirhcdf(orig,varargin) df = mirhcdf(x) calculates the Harmonic Change Detection Function
mirinharmonicity(orig,varargi... ih = mirinharmonicity(x) estimates the inharmonicity of x, i.e., the
mirkey(orig,varargin)
mirkurtosis(orig,varargin) k = mirkurtosis(x) calculates the kurtosis of x, indicating whether
mirlength(orig,varargin) mirlength(x) indicates the temporal length of x.
mirlowenergy(x,varargin) p = mirlowenergy(f) computes the percentage of frames showing a RMS
mirmap(predics_ref,ratings_re... mirmap(predictors_file, ratings_file) performs a statistical mapping
mirmean(f,varargin) m = mirmean(f) returns the mean along frames of the feature f
mirmode(x,varargin) m = mirmode(a) estimates the mode. A value of 0 indicates a complete
mirnovelty(orig,varargin) n = mirnovelty(m) evaluates the novelty score from a similarity matrix.
mironsets(x,varargin) o = mironsets(x) shows a temporal curve where peaks relate to the
miroptions(method,orig,specif... The options are determined during the bottom-up process design (see below).
mirparallel(s) mirparallel(1) toggles on parallel processing: (BETA)
mirpeaks(orig,varargin)
mirplay(a,varargin) mirplay(a) plays audio signal, envelope, or pitches.
mirpulseclarity(orig,varargin) r = mirpulseclarity(x) estimates the rhythmic clarity, indicating the
mirread(extract,orig,load,fol... Read the audio file ORIG, at temporal position indicated by EXTRACT. If
mirregularity(orig,varargin) i = mirregularity(x) calculates the irregularity of a spectrum, i.e.,
mirrms(x,varargin) e = mirrms(x) calculates the root mean square energy.
mirrolloff(x,varargin) r = mirrolloff(s) calculates the spectral roll-off in Hz.
mirroughness(x,varargin) r = mirroughness(x) calculates the roughness, or sensory dissonance,
mirsave(d,varargin) mirsave(d) saves temporal data d in a file.
mirsegment(x,varargin) f = mirsegment(a) segments an audio signal. It can also be the name of an
mirskewness(orig,varargin)
mirspread(orig,varargin) S = mirspread(x) calculates the spread of x, which can be either:
mirstat(f,varargin) stat = mirstat(f) returns basic statistics of the feature f as a
mirstd(f,varargin) m = mirstd(f) returns the standard deviation along frames of the feature f
mirsum(orig,varargin) s = mirsum(f) sums the envelope of the multi-channel object f.
mirsummary(varargin) mirsummary is the same function as mirsum.
mirtempo(x,varargin)
mirtest(audio) Version 1.0
mirtimes(a,b)
mirtype(x)
mirverbose(s) mirverbose(0) toggles off the display by MIRtoolbox of minor informations
mirwaitbar(s) mirwaitbar(0) toggles off the display by MIRtoolbox of waitbar windows.
mirzerocross(orig,varargin) mirzeroscross(x) computes the sign-changes rate along the signal x,
mp3read(FILE,N,MONO,DOWNSAMP,... MP3READ Read MP3 audio file via use of external binaries.
mp3write(D,SR,NBITS,FILE,OPTI... MP3WRITE Write MP3 file by use of external binary
mtimescell(x,varargin)
netlabgmminit(mix, x, options) GMMINIT Initialises Gaussian mixture model from data
netlabkmeans(centres, data, o... KMEANS Trains a k means cluster model.
nthoutput(orig,varargin)
num2col(k);
peaksegments(func,d,p,varargi...
pluscell(x,varargin)
purgedata(c)
surfplot(varargin) SURFPLOT Pseudocolor (checkerboard) plot.
uncell(x,lvl)
miraudio(orig,varargin)
mirautocor(orig,varargin) a = mirautocor(x) computes the autocorrelation function related to x.
mircepstrum(orig,varargin) s = mircepstrum(x) computes the cepstrum, which indicates
mirchromagram.m
mirclassify(a,da,t,dt,varargi... c = mirclassify(test,features_test,train,features_train) classifies the
mirdata(orig,varargin)
mirdesign(orig,argin,option,p...
miremotion(orig,varargin) Predicts emotion along three dimensions and five basic concepts.
mirenvelope(orig,varargin) e = mirenvelope(x) extracts the envelope of x, showing the global shape
mirhisto(x,varargin) h = mirhisto(x) constructs the histogram from x. The elements of x are
mirkeysom(orig,varargin) ks = mirkeysom(x) projects a chromagram on a self-organizing map.
mirkeystrength(orig,varargin) ks = mirkeystrength(x) computes the key strength, i.e., the probability
mirmatrix(orig,varargin) Simple numerical matrix object used to display for instance correlation
mirmfcc(orig,varargin) c = mirmfcc(a) finds the Mel frequency cepstral coefficients (ceps),
mirmidi(orig,varargin) m = mirmidi(x) converts into a MIDI sequence.
mirpattern(orig,varargin)
mirpitch(orig,varargin) p = mirpitch(x) evaluates the pitch frequencies (in Hz).
mirquery(varargin)
mirscalar(orig,varargin) s = mirscalar(x,n) creates a scalar object
mirsimatrix(orig,varargin) m = mirsimatrix(x) computes the similarity matrix resulting from the
mirspectrum(orig,varargin) s = mirspectrum(x) computes the spectrum of the audio signal x, showing
mirstruct(varargin)
mirtemporal(orig,varargin) t = mirtemporal(x) creates a temporal object from signal x.
mirtonalcentroid(orig,varargi... c = mirtonalcentroid(x) calculates the 6-dimensional tonal centroid
Contents.m
demo0grandbuffet.m
mirdemo.m
tutorial.m
View all files

from MIRtoolbox by Olivier Lartillot
An innovative environment, on top of Matlab, for music and audio analysis

purgedata(c)

function c = purgedata(c)

d = get(c,'Data');
l = length(d);
empty = cell(1,l);
for i = 1:l
    empty{i} = cell(1,length(d{i}));
end
c = set(c,'PeakPos',empty,'PeakVal',empty,...
          'PeakPrecisePos',{},'PeakPreciseVal',{},'PeakMode',empty);
          %,...'Tmp',[]);

Highlights from MIRtoolbox

Highlights from
MIRtoolbox