function [st,t,f] = st(timeseries,minfreq,maxfreq,samplingrate,freqsamplingrate)
% This is the S transform wrapper that holds default values for the function.
TRUE = 1;
FALSE = 0;
%%% DEFAULT PARAMETERS [change these for your particular application]
verbose = TRUE;
removeedge= FALSE;
analytic_signal = FALSE;
factor = 1;
%%% END of DEFAULT PARAMETERS
if verbose disp(' '),end % i like a line left blank
if nargin == 0
if verbose disp('No parameters inputted.'),end
st_help
t=0;,st=-1;,f=0;
return
end
% Change to column vector
if size(timeseries,2) > size(timeseries,1)
timeseries=timeseries';
end
% Make sure it is a 1-dimensional array
if size(timeseries,2) > 1
error('Please enter a *vector* of data, not matrix')
return
elseif (size(timeseries)==[1 1]) == 1
error('Please enter a *vector* of data, not a scalar')
return
end
% use defaults for input variables
if nargin == 1
minfreq = 0;
maxfreq = fix(length(timeseries)/2);
samplingrate=1;
freqsamplingrate=1;
elseif nargin==2
maxfreq = fix(length(timeseries)/2);
samplingrate=1;
freqsamplingrate=1;
[ minfreq,maxfreq,samplingrate,freqsamplingrate] = check_input(minfreq,maxfreq,samplingrate,freqsamplingrate,verbose,timeseries);
elseif nargin==3
samplingrate=1;
freqsamplingrate=1;
[ minfreq,maxfreq,samplingrate,freqsamplingrate] = check_input(minfreq,maxfreq,samplingrate,freqsamplingrate,verbose,timeseries);
elseif nargin==4
freqsamplingrate=1;
[ minfreq,maxfreq,samplingrate,freqsamplingrate] = check_input(minfreq,maxfreq,samplingrate,freqsamplingrate,verbose,timeseries);
elseif nargin == 5
[ minfreq,maxfreq,samplingrate,freqsamplingrate] = check_input(minfreq,maxfreq,samplingrate,freqsamplingrate,verbose,timeseries);
else
if verbose disp('Error in input arguments: using defaults'),end
minfreq = 0;
maxfreq = fix(length(timeseries)/2);
samplingrate=1;
freqsamplingrate=1;
end
if verbose
disp(sprintf('Minfreq = %d',minfreq))
disp(sprintf('Maxfreq = %d',maxfreq))
disp(sprintf('Sampling Rate (time domain) = %d',samplingrate))
disp(sprintf('Sampling Rate (freq. domain) = %d',freqsamplingrate))
disp(sprintf('The length of the timeseries is %d points',length(timeseries)))
disp(' ')
end
%END OF INPUT VARIABLE CHECK
% If you want to "hardwire" minfreq & maxfreq & samplingrate & freqsamplingrate do it here
% calculate the sampled time and frequency values from the two sampling rates
t = (0:length(timeseries)-1)*samplingrate;
spe_nelements =ceil((maxfreq - minfreq+1)/freqsamplingrate) ;
f = (minfreq + [0:spe_nelements-1]*freqsamplingrate)/(samplingrate*length(timeseries));
if verbose disp(sprintf('The number of frequency voices is %d',spe_nelements)),end
% The actual S Transform function is here:
st = strans(timeseries,minfreq,maxfreq,samplingrate,freqsamplingrate,verbose,removeedge,analytic_signal,factor);
% this function is below, thus nicely encapsulated
%WRITE switch statement on nargout
% if 0 then plot amplitude spectrum
if nargout==0
if verbose disp('Plotting pseudocolor image'),end
pcolor(t,f,abs(st))
end
return
function st = strans(timeseries,minfreq,maxfreq,samplingrate,freqsamplingrate,verbose,removeedge,analytic_signal,factor);
% Compute the length of the data.
n=length(timeseries);
original = timeseries;
if removeedge
if verbose disp('Removing trend with polynomial fit'),end
ind = [0:n-1]';
r = polyfit(ind,timeseries,2);
fit = polyval(r,ind) ;
timeseries = timeseries - fit;
if verbose disp('Removing edges with 5% hanning taper'),end
sh_len = floor(length(timeseries)/10);
wn = hanning(sh_len);
if(sh_len==0)
sh_len=length(timeseries);
wn = 1&[1:sh_len];
end
% make sure wn is a column vector, because timeseries is
if size(wn,2) > size(wn,1)
wn=wn';
end
timeseries(1:floor(sh_len/2),1) = timeseries(1:floor(sh_len/2),1).*wn(1:floor(sh_len/2),1);
timeseries(length(timeseries)-floor(sh_len/2):n,1) = timeseries(length(timeseries)-floor(sh_len/2):n,1).*wn(sh_len-floor(sh_len/2):sh_len,1);
end
% If vector is real, do the analytic signal
if analytic_signal
if verbose disp('Calculating analytic signal (using Hilbert transform)'),end
% this version of the hilbert transform is different than hilbert.m
% This is correct!
ts_spe = fft(real(timeseries));
h = [1; 2*ones(fix((n-1)/2),1); ones(1-rem(n,2),1); zeros(fix((n-1)/2),1)];
ts_spe(:) = ts_spe.*h(:);
timeseries = ifft(ts_spe);
end
% Compute FFT's
tic;vector_fft=fft(timeseries);tim_est=toc;
vector_fft=[vector_fft,vector_fft];
tim_est = tim_est*ceil((maxfreq - minfreq+1)/freqsamplingrate) ;
if verbose disp(sprintf('Estimated time is %f',tim_est)),end
% Preallocate the STOutput matrix
st=zeros(ceil((maxfreq - minfreq+1)/freqsamplingrate),n);
% Compute the mean
% Compute S-transform value for 1 ... ceil(n/2+1)-1 frequency points
if verbose disp('Calculating S transform...'),end
if minfreq == 0
st(1,:) = mean(timeseries)*(1&[1:1:n]);
else
st(1,:)=ifft(vector_fft(minfreq+1:minfreq+n).*g_window(n,minfreq,factor));
end
%the actual calculation of the ST
% Start loop to increment the frequency point
for banana=freqsamplingrate:freqsamplingrate:(maxfreq-minfreq)
st(banana/freqsamplingrate+1,:)=ifft(vector_fft(minfreq+banana+1:minfreq+banana+n).*g_window(n,minfreq+banana,factor));
end % a fruit loop! aaaaa ha ha ha ha ha ha ha ha ha ha
% End loop to increment the frequency point
if verbose disp('Finished Calculation'),end
%%% end strans function
%------------------------------------------------------------------------
function gauss=g_window(length,freq,factor)
vector(1,:)=[0:length-1];
vector(2,:)=[-length:-1];
vector=vector.^2;
vector=vector*(-factor*2*pi^2/freq^2);
% Compute the Gaussion window
gauss=sum(exp(vector));
%-----------------------------------------------------------------------
%^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^%
function [ minfreq,maxfreq,samplingrate,freqsamplingrate] = check_input(minfreq,maxfreq,samplingrate,freqsamplingrate,verbose,timeseries)
% this checks numbers, and replaces them with defaults if invalid
% if the parameters are passed as an array, put them into the appropriate variables
s = size(minfreq);
l = max(s);
if l > 1
if verbose disp('Array of inputs accepted.'),end
temp=minfreq;
minfreq = temp(1);;
if l > 1 maxfreq = temp(2);,end;
if l > 2 samplingrate = temp(3);,end;
if l > 3 freqsamplingrate = temp(4);,end;
if l > 4
if verbose disp('Ignoring extra input parameters.'),end
end;
end
if minfreq < 0 | minfreq > fix(length(timeseries)/2);
minfreq = 0;
if verbose disp('Minfreq < 0 or > Nyquist. Setting minfreq = 0.'),end
end
if maxfreq > length(timeseries)/2 | maxfreq < 0
maxfreq = fix(length(timeseries)/2);
if verbose disp(sprintf('Maxfreq < 0 or > Nyquist. Setting maxfreq = %d',maxfreq)),end
end
if minfreq > maxfreq
temporary = minfreq;
minfreq = maxfreq;
maxfreq = temporary;
clear temporary;
if verbose disp('Swapping maxfreq <=> minfreq.'),end
end
if samplingrate <0
samplingrate = abs(samplingrate);
if verbose disp('Samplingrate <0. Setting samplingrate to its absolute value.'),end
end
if freqsamplingrate < 0 % check 'what if freqsamplingrate > maxfreq - minfreq' case
freqsamplingrate = abs(freqsamplingrate);
if verbose disp('Frequency Samplingrate negative, taking absolute value'),end
end
% bloody odd how you don't end a function
%^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^%
function st_help
