replace 4-spaces by tab

bmarechal
1 parent 183c460e4e
Showing 8 changed files with 1688 additions and 1680 deletions Side-by-side Diff
allan.m
allan_cov.m
allan_modified.m
allan_overlap.m
allanplot.m
allanplot_cov.m
dsplot.m
psdplot.m
@@ -5,33 +5,33 @@
 % Inputs:
 % DATA should be a structure and have the following fields:
 %  DATA.freq or DATA.phase
-%               A vector of fractional frequency measurements (df/f) in
-%                DATA.freq *or* phase offset data (seconds) in DATA.phase .
-%               If frequency data is not present, it will be generated by
-%                differentiating the phase data.
-%               If both fields are present, then DATA.freq will be used.
-%               Note: for general-purpose calculations of Allan deviation,
-%                (i.e. a two-sample variance) use DATA.freq .
+%			   A vector of fractional frequency measurements (df/f) in
+%				DATA.freq *or* phase offset data (seconds) in DATA.phase .
+%			   If frequency data is not present, it will be generated by
+%				differentiating the phase data.
+%			   If both fields are present, then DATA.freq will be used.
+%			   Note: for general-purpose calculations of Allan deviation,
+%				(i.e. a two-sample variance) use DATA.freq .
 %
 %  DATA.rate or DATA.time
-%               The sampling rate in Hertz (DATA.rate) or a vector of
-%               timestamps for each measurement in seconds (DATA.time).
-%               DATA.rate is used if both fields are present.
-%               If DATA.rate == 0, then the timestamps are used.
+%			   The sampling rate in Hertz (DATA.rate) or a vector of
+%			   timestamps for each measurement in seconds (DATA.time).
+%			   DATA.rate is used if both fields are present.
+%			   If DATA.rate == 0, then the timestamps are used.
 %
 %  DATA.units (optional)
-%               The units for the data. If present, the string DATA.units
-%               is added to the plot y-axis label.
+%			   The units for the data. If present, the string DATA.units
+%			   is added to the plot y-axis label.
 %
 % TAU is an array of tau values for computing Allan deviation.
-%     TAU values must be divisible by 1/DATA.rate (data points cannot be
-%     grouped in fractional quantities!) and invalid values are ignored.
-%     Leave empty to use default values.
+%	 TAU values must be divisible by 1/DATA.rate (data points cannot be
+%	 grouped in fractional quantities!) and invalid values are ignored.
+%	 Leave empty to use default values.
 % NAME is an optional label that is added to the plot titles.
 % VERBOSE sets the level of status messages:
-%     0 = silent & no data plots;
-%     1 = status messages & minimum plots;
-%     2 = all messages and plots (default)
+%	 0 = silent & no data plots;
+%	 1 = status messages & minimum plots;
+%	 2 = all messages and plots (default)
 %
 % Outputs:
 % RETVAL is the array of Allan deviation values at each TAU.
@@ -46,8 +46,8 @@
 % To compute the Allan deviation for the data in the variable "lt":
 % >> lt
 % lt = 
-%     freq: [1x86400 double]
-%     rate: 0.5
+%	 freq: [1x86400 double]
+%	 rate: 0.5
 %
 % Use:
 %
  
  
@@ -94,16 +94,16 @@
 %
 %
 % M.A. Hopcroft
-%      mhopeng at gmail dot com
+%	  mhopeng at gmail dot com
 %
 % I welcome your comments and feedback!
 %
 % MH Mar2014
 % v2.24 fix bug related to generating freq data from phase with timestamps
-%       (thanks to S. David-Grignot for finding the bug)
+%	   (thanks to S. David-Grignot for finding the bug)
 % MH Oct2010
 % v2.22 tau truncation to integer groups; tau sort
-%       plotting bugfix
+%	   plotting bugfix
 % v2.20 sychronize updates across allan, allan_overlap, allan_modified
 % v2.16 add TAU as output, fixed unusual error with dsplot v1.1
 % v2.14 update plotting behaviour, default tau values
  
  
  
  
  
  
  
  
  
@@ -113,53 +113,53 @@
  
 % MH Jun2010
 % v2.12 bugfix for rate data row/col orientation
-%       add DATA.units for plotting
-%       use dsplot.m for plotting
+%	   add DATA.units for plotting
+%	   use dsplot.m for plotting
 %
 % MH MAR2010
 % v2.1  minor interface and bugfixes
-%       update data consistency check
+%	   update data consistency check
 %
 % MH FEB2010
 % v2.0  Consistent code behaviour for all "allan_x.m" functions:
-%       accept phase data
-%       verbose levels
+%	   accept phase data
+%	   verbose levels
 %
 %
 % MH JAN2010
 % v1.84  code cleanup
 % v1.82  typos in comments and code cleanup
-%        tau bin plotting changed for performance improvement
+%		tau bin plotting changed for performance improvement
 % v1.8   Performance improvements:
-%        vectorize code for rate data
-%        logical indexing for irregular rate data
+%		vectorize code for rate data
+%		logical indexing for irregular rate data
 % MH APR2008
 % v1.62  loglog plot option
 % v1.61  improve error handling, plotting
-%        fix bug in regular data calc for high-rate data
-%        fix bug in timestamp data calc for large starting gap
-%         (thanks to C. B. Ruiz for identifying these bugs)
-%        uses timestamps for DATA.rate=0
-%        progress indicator for large timestamp data processing
+%		fix bug in regular data calc for high-rate data
+%		fix bug in timestamp data calc for large starting gap
+%		 (thanks to C. B. Ruiz for identifying these bugs)
+%		uses timestamps for DATA.rate=0
+%		progress indicator for large timestamp data processing
 % MH JUN2007
 % v1.54 Improve data plotting and optional bin plotting
 % MH FEB2007
 % v1.5  use difference from median for plotting
-%       added MAD calculation for outlier detection
+%	   added MAD calculation for outlier detection
 % MH JAN2007
 % v1.48 plotting typos fixes
 % MH DEC2006
 % v1.46 hack to plot error bars
 % v1.44 further validation (Riley 1000-pt)
-%       plot mean and std
+%	   plot mean and std
 % MH NOV2006
 % v1.42 typo fix comments
 % v1.4  fix irregular rate algorithm
-%       irregular algorithm rejects tau less than max gap in time data
-%       validate both algorithms using test data from NBS Monograph 140
+%	   irregular algorithm rejects tau less than max gap in time data
+%	   validate both algorithms using test data from NBS Monograph 140
 % v1.3  fix time calc if data.time not present
-%       add error bars (not possible due to bug in MATLAB R14SP3)
-%       remove offset calculation
+%	   add error bars (not possible due to bug in MATLAB R14SP3)
+%	   remove offset calculation
 % v1.24 improve feedback
 % MH SEP2006
 % v1.22 updated comments
  
@@ -184,25 +184,25 @@
  
 %% Data consistency checks
 if ~(isfield(data,'phase') || isfield(data,'freq'))
-    error('Either ''phase'' or ''freq'' must be present in DATA. See help file for details. [con0]');
+	error('Either ''phase'' or ''freq'' must be present in DATA. See help file for details. [con0]');
 end
 if isfield(data,'time')
-    if isfield(data,'phase') && (length(data.phase) ~= length(data.time))
-        if isfield(data,'freq') && (length(data.freq) ~= length(data.time))
-            error('The time and freq vectors are not the same length. See help for details. [con2]');
-        else
-            error('The time and phase vectors are not the same length. See help for details. [con1]');
-        end
-    end
-    if isfield(data,'phase') && (any(isnan(data.phase)) || any(isinf(data.phase)))
-        error('The phase vector contains invalid elements (NaN/Inf). [con3]');
-    end
-    if isfield(data,'freq') && (any(isnan(data.freq)) || any(isinf(data.freq)))
-        error('The freq vector contains invalid elements (NaN/Inf). [con4]');
-    end
-    if isfield(data,'time') && (any(isnan(data.time)) || any(isinf(data.time)))
-        error('The time vector contains invalid elements (NaN/Inf). [con5]');
-    end
+	if isfield(data,'phase') && (length(data.phase) ~= length(data.time))
+		if isfield(data,'freq') && (length(data.freq) ~= length(data.time))
+			error('The time and freq vectors are not the same length. See help for details. [con2]');
+		else
+			error('The time and phase vectors are not the same length. See help for details. [con1]');
+		end
+	end
+	if isfield(data,'phase') && (any(isnan(data.phase)) || any(isinf(data.phase)))
+		error('The phase vector contains invalid elements (NaN/Inf). [con3]');
+	end
+	if isfield(data,'freq') && (any(isnan(data.freq)) || any(isinf(data.freq)))
+		error('The freq vector contains invalid elements (NaN/Inf). [con4]');
+	end
+	if isfield(data,'time') && (any(isnan(data.time)) || any(isinf(data.time)))
+		error('The time vector contains invalid elements (NaN/Inf). [con5]');
+	end
 end
  
 % sort tau vector
  
  
  
  
  
@@ -211,34 +211,34 @@
  
 %% Basic statistical tests on the data set
 if ~isfield(data,'freq')
-    if isfield(data,'rate') && data.rate ~= 0
-        data.freq=diff(data.phase).*data.rate;
-    elseif isfield(data,'time')
-        data.freq=diff(data.phase)./diff(data.time);
-    end
-    if verbose >= 1, fprintf(1,'allan: Fractional frequency data generated from phase data (M=%g).\n',length(data.freq)); end
-    data.time(1)=[]; % make time stamps correspond to freq data 
+	if isfield(data,'rate') && data.rate ~= 0
+		data.freq=diff(data.phase).*data.rate;
+	elseif isfield(data,'time')
+		data.freq=diff(data.phase)./diff(data.time);
+	end
+	if verbose >= 1, fprintf(1,'allan: Fractional frequency data generated from phase data (M=%g).\n',length(data.freq)); end
+	data.time(1)=[]; % make time stamps correspond to freq data 
 end
 if size(data.freq,2) > size(data.freq,1), data.freq=data.freq'; end % ensure columns
-    
+	
 s.numpoints=length(data.freq);
 s.max=max(data.freq);
 s.min=min(data.freq);
 s.mean=mean(data.freq);
 s.median=median(data.freq);
 if isfield(data,'time')
-    if size(data.time,2) > size(data.time,1), data.time=data.time'; end % ensure columns
-    s.linear=polyfit(data.time(1:length(data.freq)),data.freq,1);
+	if size(data.time,2) > size(data.time,1), data.time=data.time'; end % ensure columns
+	s.linear=polyfit(data.time(1:length(data.freq)),data.freq,1);
 elseif isfield(data,'rate') && data.rate ~= 0;
-    s.linear=polyfit((1/data.rate:1/data.rate:length(data.freq)/data.rate)',data.freq,1);
+	s.linear=polyfit((1/data.rate:1/data.rate:length(data.freq)/data.rate)',data.freq,1);
 else
-    error('Either "time" or "rate" must be present in DATA. Type "help allan" for details. [err1]');
+	error('Either "time" or "rate" must be present in DATA. Type "help allan" for details. [err1]');
 end
 s.std=std(data.freq);
  
 if verbose >= 2
-    fprintf(1,'allan: input data statistics:\n');
-    disp(s);
+	fprintf(1,'allan: input data statistics:\n');
+	disp(s);
 end
  
  
  
@@ -249,10 +249,10 @@
 % Screen for outliers using 5x Median Absolute Deviation (MAD) criteria
 s.MAD = median(abs(medianfreq)/0.6745);
 if verbose >= 2
-    fprintf(1, 'allan: 5x MAD value for outlier detection: %g\n',5*s.MAD);
+	fprintf(1, 'allan: 5x MAD value for outlier detection: %g\n',5*s.MAD);
 end
 if verbose >= 1 && any(abs(medianfreq) > 5*s.MAD)
-    fprintf(1, 'allan: NOTE: There appear to be outliers in the frequency data. See plot.\n');
+	fprintf(1, 'allan: NOTE: There appear to be outliers in the frequency data. See plot.\n');
 end
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
@@ -263,199 +263,199 @@
 %  If there is a regular interval between measurements, calculation is much
 %   easier/faster
 if isfield(data,'rate') && data.rate > 0 % if data rate was given
-    if verbose >= 1, fprintf(1, 'allan: regular data (%g data points @ %g Hz)\n',length(data.freq),data.rate); end
-    
-    % string for plot title
-    name=[name ' (' num2str(data.rate) ' Hz)'];
-    
-    % what is the time interval between data points?
-    tmstep = 1/data.rate;
+	if verbose >= 1, fprintf(1, 'allan: regular data (%g data points @ %g Hz)\n',length(data.freq),data.rate); end
+	
+	% string for plot title
+	name=[name ' (' num2str(data.rate) ' Hz)'];
+	
+	% what is the time interval between data points?
+	tmstep = 1/data.rate;
  
-    % Is there time data? Just for curiosity/plotting, does not impact calculation
-    if isfield(data,'time')
-        % adjust time data to remove any starting gap; first time step
-        %  should not be zero for comparison with freq data
-        dtime=data.time-data.time(1)+mean(diff(data.time));
-        if verbose >= 2
-            fprintf(1,'allan: End of timestamp data: %g sec.\n',dtime(end));
-            if (data.rate - 1/mean(diff(dtime))) > 1e-6
-                fprintf(1,'allan: NOTE: data.rate (%f Hz) does not match average timestamped sample rate (%f Hz)\n',data.rate,1/mean(diff(dtime)));
-            end
-        end
-    else
-        % create time axis data using rate (for plotting only)
-        dtime=(tmstep:tmstep:length(data.freq)*tmstep)'; % column oriented
-    end
+	% Is there time data? Just for curiosity/plotting, does not impact calculation
+	if isfield(data,'time')
+		% adjust time data to remove any starting gap; first time step
+		%  should not be zero for comparison with freq data
+		dtime=data.time-data.time(1)+mean(diff(data.time));
+		if verbose >= 2
+			fprintf(1,'allan: End of timestamp data: %g sec.\n',dtime(end));
+			if (data.rate - 1/mean(diff(dtime))) > 1e-6
+				fprintf(1,'allan: NOTE: data.rate (%f Hz) does not match average timestamped sample rate (%f Hz)\n',data.rate,1/mean(diff(dtime)));
+			end
+		end
+	else
+		% create time axis data using rate (for plotting only)
+		dtime=(tmstep:tmstep:length(data.freq)*tmstep)'; % column oriented
+	end
  
-    % check the range of tau values and truncate if necessary
-    % find halfway point of time record
-    halftime = round(tmstep*length(data.freq)/2);
-    % truncate tau to appropriate values
-    tau = tau(tau >= tmstep & tau <= halftime);
-    if verbose >= 2, fprintf(1, 'allan: allowable tau range: %g to %g sec. (1/rate to total_time/2)\n',tmstep,halftime); end  
-    
-    % save the freq data for the loop
-    dfreq=data.freq;
-    % find the number of data points in each tau group
-    m = data.rate.*tau;
-    % only integer values allowed (no fractional groups of points)
-    %tau = tau(m-round(m)<1e-8); % numerical precision issues (v2.1)
-    tau = tau(m==round(m));  % The round() test is only correct for values < 2^53
-    %m = m(m-round(m)<1e-8); % change to round(m) for integer test v2.22
-    m = m(m==round(m));
-    %m=round(m);
-    
-    if verbose >= 1, fprintf(1,'allan: calculating Allan deviation...\n       '); end
-    
-    % calculate the Allan deviation for each value of tau
-    k=0; tic;
-    for i = tau
-        if verbose >= 2, fprintf(1,'%g ',i); end
-        k=k+1;
+	% check the range of tau values and truncate if necessary
+	% find halfway point of time record
+	halftime = round(tmstep*length(data.freq)/2);
+	% truncate tau to appropriate values
+	tau = tau(tau >= tmstep & tau <= halftime);
+	if verbose >= 2, fprintf(1, 'allan: allowable tau range: %g to %g sec. (1/rate to total_time/2)\n',tmstep,halftime); end  
+	
+	% save the freq data for the loop
+	dfreq=data.freq;
+	% find the number of data points in each tau group
+	m = data.rate.*tau;
+	% only integer values allowed (no fractional groups of points)
+	%tau = tau(m-round(m)<1e-8); % numerical precision issues (v2.1)
+	tau = tau(m==round(m));  % The round() test is only correct for values < 2^53
+	%m = m(m-round(m)<1e-8); % change to round(m) for integer test v2.22
+	m = m(m==round(m));
+	%m=round(m);
+	
+	if verbose >= 1, fprintf(1,'allan: calculating Allan deviation...\n	   '); end
+	
+	% calculate the Allan deviation for each value of tau
+	k=0; tic;
+	for i = tau
+		if verbose >= 2, fprintf(1,'%g ',i); end
+		k=k+1;
  
-        % truncate frequency set to an even multiple of this tau value
-        freq=dfreq(1:end-rem(length(dfreq),m(k)));
-        % group the data into tau-length groups or bins
-        f = reshape(freq,m(k),[]); % Vectorize!     
-        % find average in each "tau group", y_k (each colummn of f)
-        fa=mean(f,1);
-        % first finite difference
-        fd=diff(fa);
-        % calculate two-sample variance for this tau
-        M=length(fa);
-        sm(k)=sqrt(0.5/(M-1)*(sum(fd.^2)));
+		% truncate frequency set to an even multiple of this tau value
+		freq=dfreq(1:end-rem(length(dfreq),m(k)));
+		% group the data into tau-length groups or bins
+		f = reshape(freq,m(k),[]); % Vectorize!	 
+		% find average in each "tau group", y_k (each colummn of f)
+		fa=mean(f,1);
+		% first finite difference
+		fd=diff(fa);
+		% calculate two-sample variance for this tau
+		M=length(fa);
+		sm(k)=sqrt(0.5/(M-1)*(sum(fd.^2)));
  
-        % estimate error bars
-        sme(k)=sm(k)/sqrt(M+1);
-        
-        if TAUBIN == 1
-            % save the binning points for plotting
-            fs(k,1:length(freq)/m(k))=m(k):m(k):length(freq); fval{k}=mean(f,1);
-        end
-        
-    end % repeat for each value of tau
-    
-    if verbose >= 2, fprintf(1,'\n'); end
-    calctime=toc; if verbose >= 2, fprintf(1,'allan: Elapsed time for calculation: %e seconds\n',calctime); end
-    
-       
-    
+		% estimate error bars
+		sme(k)=sm(k)/sqrt(M+1);
+		
+		if TAUBIN == 1
+			% save the binning points for plotting
+			fs(k,1:length(freq)/m(k))=m(k):m(k):length(freq); fval{k}=mean(f,1);
+		end
+		
+	end % repeat for each value of tau
+	
+	if verbose >= 2, fprintf(1,'\n'); end
+	calctime=toc; if verbose >= 2, fprintf(1,'allan: Elapsed time for calculation: %e seconds\n',calctime); end
+	
+	   
+	
 %% Irregular data (timestamp)   
 elseif isfield(data,'time')
-    % the interval between measurements is irregular
-    %  so we must group the data by time
-    if verbose >= 1, fprintf(1, 'allan: irregular rate data (no fixed sample rate)\n'); end
-    
-    % string for plot title
-    name=[name ' (timestamp)'];
-    
-    % adjust time to remove any initial offset or zero
-    dtime=data.time-data.time(1)+mean(diff(data.time));
-    %dtime=data.time;
-    % where is the maximum gap in time record?
-    gap_pos=find(diff(dtime)==max(diff(dtime)));
-    % what is average data spacing?
-    avg_gap = mean(diff(dtime));
-    
-    if verbose >= 2
-        fprintf(1, 'allan: WARNING: irregular timestamp data (no fixed sample rate).\n');
-        fprintf(1, '       Calculation time may be long and the results subject to interpretation.\n');
-        fprintf(1, '       You are advised to estimate using an average sample rate (%g Hz) instead of timestamps.\n',1/avg_gap);
-        fprintf(1, '       Continue at your own risk! (press any key to continue)\n');
-        pause;
-    end
-    
-    if verbose >= 1
-        fprintf(1, 'allan: End of timestamp data: %g sec\n',dtime(end));
-    	fprintf(1, '       Average rate: %g Hz (%g sec/measurement)\n',1/avg_gap,avg_gap);
-        if max(diff(dtime)) ~= 1/mean(diff(dtime))
-            fprintf(1, '       Max. gap: %g sec at position %d\n',max(diff(dtime)),gap_pos(1));
-        end
-        if max(diff(dtime)) > 5*avg_gap
-            fprintf(1, '       WARNING: Max. gap in time record is suspiciously large (>5x the average interval).\n');
-        end        
-    end
+	% the interval between measurements is irregular
+	%  so we must group the data by time
+	if verbose >= 1, fprintf(1, 'allan: irregular rate data (no fixed sample rate)\n'); end
+	
+	% string for plot title
+	name=[name ' (timestamp)'];
+	
+	% adjust time to remove any initial offset or zero
+	dtime=data.time-data.time(1)+mean(diff(data.time));
+	%dtime=data.time;
+	% where is the maximum gap in time record?
+	gap_pos=find(diff(dtime)==max(diff(dtime)));
+	% what is average data spacing?
+	avg_gap = mean(diff(dtime));
+	
+	if verbose >= 2
+		fprintf(1, 'allan: WARNING: irregular timestamp data (no fixed sample rate).\n');
+		fprintf(1, '	   Calculation time may be long and the results subject to interpretation.\n');
+		fprintf(1, '	   You are advised to estimate using an average sample rate (%g Hz) instead of timestamps.\n',1/avg_gap);
+		fprintf(1, '	   Continue at your own risk! (press any key to continue)\n');
+		pause;
+	end
+	
+	if verbose >= 1
+		fprintf(1, 'allan: End of timestamp data: %g sec\n',dtime(end));
+		fprintf(1, '	   Average rate: %g Hz (%g sec/measurement)\n',1/avg_gap,avg_gap);
+		if max(diff(dtime)) ~= 1/mean(diff(dtime))
+			fprintf(1, '	   Max. gap: %g sec at position %d\n',max(diff(dtime)),gap_pos(1));
+		end
+		if max(diff(dtime)) > 5*avg_gap
+			fprintf(1, '	   WARNING: Max. gap in time record is suspiciously large (>5x the average interval).\n');
+		end		
+	end
  
  
-    % find halfway point
-    halftime = fix(dtime(end)/2);
-    % truncate tau to appropriate values
-    tau = tau(tau >= max(diff(dtime)) & tau <= halftime);
-    if isempty(tau)
-        error('allan: ERROR: no appropriate tau values (> %g s, < %g s)\n',max(diff(dtime)),halftime);
-    end
-    
-    % save the freq data for the loop
-    dfreq=data.freq;
-    dtime=dtime(1:length(dfreq));
+	% find halfway point
+	halftime = fix(dtime(end)/2);
+	% truncate tau to appropriate values
+	tau = tau(tau >= max(diff(dtime)) & tau <= halftime);
+	if isempty(tau)
+		error('allan: ERROR: no appropriate tau values (> %g s, < %g s)\n',max(diff(dtime)),halftime);
+	end
+	
+	% save the freq data for the loop
+	dfreq=data.freq;
+	dtime=dtime(1:length(dfreq));
  
-    if verbose >= 1, fprintf(1,'allan: calculating Allan deviation...\n'); end
+	if verbose >= 1, fprintf(1,'allan: calculating Allan deviation...\n'); end
  
-    k=0; tic;
-    for i = tau
-        if verbose >= 2, fprintf(1,'%d ',i); end
-        
-        k=k+1; fa=[]; %f=[];
-        km=0;
-        
-        % truncate data set to an even multiple of this tau value
-        freq=dfreq(dtime <= dtime(end)-rem(dtime(end),i));
-        time=dtime(dtime <= dtime(end)-rem(dtime(end),i));
-        %freq=dfreq;
-        %time=dtime;
-        
-        % break up the data into groups of tau length in sec
-        while i*km < time(end)
-            km=km+1;
-                        
-            % progress bar
-            if verbose >= 2
-                if rem(km,100)==0, fprintf(1,'.'); end
-                if rem(km,1000)==0, fprintf(1,'%g/%g\n',km,round(time(end)/i)); end
-            end
+	k=0; tic;
+	for i = tau
+		if verbose >= 2, fprintf(1,'%d ',i); end
+		
+		k=k+1; fa=[]; %f=[];
+		km=0;
+		
+		% truncate data set to an even multiple of this tau value
+		freq=dfreq(dtime <= dtime(end)-rem(dtime(end),i));
+		time=dtime(dtime <= dtime(end)-rem(dtime(end),i));
+		%freq=dfreq;
+		%time=dtime;
+		
+		% break up the data into groups of tau length in sec
+		while i*km < time(end)
+			km=km+1;
+						
+			% progress bar
+			if verbose >= 2
+				if rem(km,100)==0, fprintf(1,'.'); end
+				if rem(km,1000)==0, fprintf(1,'%g/%g\n',km,round(time(end)/i)); end
+			end
  
-            f = freq(i*(km-1) < time & time <= i*km);
-            f = f(~isnan(f)); % make sure values are valid
-            
-            if ~isempty(f)
-                fa(km)=mean(f);
-            else
-                fa(km)=0;
-            end
+			f = freq(i*(km-1) < time & time <= i*km);
+			f = f(~isnan(f)); % make sure values are valid
+			
+			if ~isempty(f)
+				fa(km)=mean(f);
+			else
+				fa(km)=0;
+			end
  
-            if TAUBIN == 1 % WARNING: this has a significant impact on performance
-                % save the binning points for plotting
-                %if find(time <= i*km) > 0
-                    fs(k,km)=max(time(time <= i*km));
-                %else
-                if isempty(fs(k,km))
-                    fs(k,km)=0;
-                end
-                fval{k}=fa;
-            end % save tau bin plot points
-            
-        end
-        
-        if verbose >= 2, fprintf(1,'\n'); end
+			if TAUBIN == 1 % WARNING: this has a significant impact on performance
+				% save the binning points for plotting
+				%if find(time <= i*km) > 0
+					fs(k,km)=max(time(time <= i*km));
+				%else
+				if isempty(fs(k,km))
+					fs(k,km)=0;
+				end
+				fval{k}=fa;
+			end % save tau bin plot points
+			
+		end
+		
+		if verbose >= 2, fprintf(1,'\n'); end
  
-        % first finite difference of the averaged results
-        fd=diff(fa);
-        % calculate Allan deviation for this tau
-        M=length(fa);
-        sm(k)=sqrt(0.5/(M-1)*(sum(fd.^2)));
+		% first finite difference of the averaged results
+		fd=diff(fa);
+		% calculate Allan deviation for this tau
+		M=length(fa);
+		sm(k)=sqrt(0.5/(M-1)*(sum(fd.^2)));
  
-        % estimate error bars
-        sme(k)=sm(k)/sqrt(M+1);
-        
+		% estimate error bars
+		sme(k)=sm(k)/sqrt(M+1);
+		
  
-    end
+	end
  
-    if verbose == 2, fprintf(1,'\n'); end
-    calctime=toc; if verbose >= 2, fprintf(1,'allan: Elapsed time for calculation: %e seconds\n',calctime); end
-    
+	if verbose == 2, fprintf(1,'\n'); end
+	calctime=toc; if verbose >= 2, fprintf(1,'allan: Elapsed time for calculation: %e seconds\n',calctime); end
+	
  
 else
-    error('allan: WARNING: no DATA.rate or DATA.time! Type "help allan" for more information. [err2]');
+	error('allan: WARNING: no DATA.rate or DATA.time! Type "help allan" for more information. [err2]');
 end
  
  
  
  
  
  
  
  
  
@@ -463,113 +463,113 @@
 %% Plotting
  
 if verbose >= 2 % show all data
-    
-    % plot the frequency data, centered on median
-    if size(dtime,2) > size(dtime,1), dtime=dtime'; end % this should not be necessary, but dsplot 1.1 is a little bit brittle
-    try
-        % dsplot makes a new figure
-        hd=dsplot(dtime,medianfreq);
-    catch ME
-        figure;
-        if length(dtime) ~= length(medianfreq)
-            fprintf(1,'allan: Warning: length of time axis (%d) is not equal to data array (%d)\n',length(dtime),length(medianfreq));
-        end
-        hd=plot(dtime,medianfreq);
-        if verbose >= 1, fprintf(1,'allan: Note: Install dsplot.m for improved plotting of large data sets (File Exchange File ID: #15850).\n'); end
-        if verbose >= 2, fprintf(1,'             (Message: %s)\n',ME.message); end
-    end
-    set(hd,'Marker','.','LineStyle','none','Color','b'); % equivalent to '.-'
-    hold on;
+	
+	% plot the frequency data, centered on median
+	if size(dtime,2) > size(dtime,1), dtime=dtime'; end % this should not be necessary, but dsplot 1.1 is a little bit brittle
+	try
+		% dsplot makes a new figure
+		hd=dsplot(dtime,medianfreq);
+	catch ME
+		figure;
+		if length(dtime) ~= length(medianfreq)
+			fprintf(1,'allan: Warning: length of time axis (%d) is not equal to data array (%d)\n',length(dtime),length(medianfreq));
+		end
+		hd=plot(dtime,medianfreq);
+		if verbose >= 1, fprintf(1,'allan: Note: Install dsplot.m for improved plotting of large data sets (File Exchange File ID: #15850).\n'); end
+		if verbose >= 2, fprintf(1,'			 (Message: %s)\n',ME.message); end
+	end
+	set(hd,'Marker','.','LineStyle','none','Color','b'); % equivalent to '.-'
+	hold on;
  
-    % show center (0)
-    plot(xlim,[0 0],':k');
-    % show 5x Median Absolute Deviation (MAD) values
-    hm=plot(xlim,[5*s.MAD 5*s.MAD],'-r');
-    plot(xlim,[-5*s.MAD -5*s.MAD],'-r');
-    % show linear fit line
-    hf=plot(xlim,polyval(s.linear,xlim)-s.median,'-g');
-    title(['Data: ' name],'FontSize',FontSize+2,'FontName',FontName);
-    %set(get(gca,'Title'),'Interpreter','none');
-    xlabel('Time [sec]','FontSize',FontSize,'FontName',FontName);
-    if isfield(data,'units')
-        ylabel(['data - median(data) [' data.units ']'],'FontSize',FontSize,'FontName',FontName);
-    else
-        ylabel('freq - median(freq)','FontSize',FontSize,'FontName',FontName);
-    end
-    set(gca,'FontSize',FontSize,'FontName',FontName);
-    legend([hd hm hf],{'data (centered on median)','5x MAD outliers',['Linear Fit (' num2str(s.linear(1),'%g') ')']},'FontSize',max(10,FontSize-2));
-    % tighten up
-    xlim([dtime(1) dtime(end)]);
+	% show center (0)
+	plot(xlim,[0 0],':k');
+	% show 5x Median Absolute Deviation (MAD) values
+	hm=plot(xlim,[5*s.MAD 5*s.MAD],'-r');
+	plot(xlim,[-5*s.MAD -5*s.MAD],'-r');
+	% show linear fit line
+	hf=plot(xlim,polyval(s.linear,xlim)-s.median,'-g');
+	title(['Data: ' name],'FontSize',FontSize+2,'FontName',FontName);
+	%set(get(gca,'Title'),'Interpreter','none');
+	xlabel('Time [sec]','FontSize',FontSize,'FontName',FontName);
+	if isfield(data,'units')
+		ylabel(['data - median(data) [' data.units ']'],'FontSize',FontSize,'FontName',FontName);
+	else
+		ylabel('freq - median(freq)','FontSize',FontSize,'FontName',FontName);
+	end
+	set(gca,'FontSize',FontSize,'FontName',FontName);
+	legend([hd hm hf],{'data (centered on median)','5x MAD outliers',['Linear Fit (' num2str(s.linear(1),'%g') ')']},'FontSize',max(10,FontSize-2));
+	% tighten up
+	xlim([dtime(1) dtime(end)]);
  
  
-    % Optional tau bin (y_k samples) plot
-    if TAUBIN == 1
-        % plot the tau divisions on the data plot
-        rfs=size(fs,1);
-        colororder=get(gca,'ColorOrder');
-        axis tight; kc=2;
-        %ap=axis;
-        for j=1:rfs
-            kc=kc+1; if rem(kc,length(colororder))==1, kc=2; end
-            %for b=1:max(find(fs(j,:))); % new form of "find" in r2009a
-            for b=1:find(fs(j,:), 1, 'last' );
-                % plot the tau division boundaries
-                %plot([fs(j,b) fs(j,b)],[ap(3)*1.1 ap(4)*1.1],'-','Color',colororder(kc,:));
-                % plot tau group y values
-                if b == 1
-                    plot([dtime(1) fs(j,b)],[fval{j}(b)-s.median fval{j}(b)-s.median],'-','Color',colororder(kc,:),'LineWidth',4);
-                else
-                    plot([fs(j,b-1) fs(j,b)],[fval{j}(b)-s.median fval{j}(b)-s.median],'-','Color',colororder(kc,:),'LineWidth',4);
-                end
-            end
-        end
-        axis auto
-    end % End optional bin plot
-    
+	% Optional tau bin (y_k samples) plot
+	if TAUBIN == 1
+		% plot the tau divisions on the data plot
+		rfs=size(fs,1);
+		colororder=get(gca,'ColorOrder');
+		axis tight; kc=2;
+		%ap=axis;
+		for j=1:rfs
+			kc=kc+1; if rem(kc,length(colororder))==1, kc=2; end
+			%for b=1:max(find(fs(j,:))); % new form of "find" in r2009a
+			for b=1:find(fs(j,:), 1, 'last' );
+				% plot the tau division boundaries
+				%plot([fs(j,b) fs(j,b)],[ap(3)*1.1 ap(4)*1.1],'-','Color',colororder(kc,:));
+				% plot tau group y values
+				if b == 1
+					plot([dtime(1) fs(j,b)],[fval{j}(b)-s.median fval{j}(b)-s.median],'-','Color',colororder(kc,:),'LineWidth',4);
+				else
+					plot([fs(j,b-1) fs(j,b)],[fval{j}(b)-s.median fval{j}(b)-s.median],'-','Color',colororder(kc,:),'LineWidth',4);
+				end
+			end
+		end
+		axis auto
+	end % End optional bin plot
+	
 end % end plot raw data
  
  
 if verbose >= 1 % show ADEV results
  
-    % plot Allan deviation results
-    if ~isempty(sm)
-        figure
+	% plot Allan deviation results
+	if ~isempty(sm)
+		figure
  
-        % Choose loglog or semilogx plot here    #PLOTLOG
-        %semilogx(tau,sm,'.-b','LineWidth',plotlinewidth,'MarkerSize',24);
-        loglog(tau,sm,'.-b','LineWidth',plotlinewidth,'MarkerSize',24);
+		% Choose loglog or semilogx plot here	#PLOTLOG
+		%semilogx(tau,sm,'.-b','LineWidth',plotlinewidth,'MarkerSize',24);
+		loglog(tau,sm,'.-b','LineWidth',plotlinewidth,'MarkerSize',24);
  
-        % in R14SP3, there is a bug that screws up the error bars on a semilog plot.
-        %  When this is fixed in a future release, uncomment below to use normal errorbars
-        %errorbar(tau,sm,sme,'.-b'); set(gca,'XScale','log');
-        % this is a hack to approximate the error bars
-        hold on; plot([tau; tau],[sm+sme; sm-sme],'-k','LineWidth',max(plotlinewidth-1,2));
+		% in R14SP3, there is a bug that screws up the error bars on a semilog plot.
+		%  When this is fixed in a future release, uncomment below to use normal errorbars
+		%errorbar(tau,sm,sme,'.-b'); set(gca,'XScale','log');
+		% this is a hack to approximate the error bars
+		hold on; plot([tau; tau],[sm+sme; sm-sme],'-k','LineWidth',max(plotlinewidth-1,2));
  
-        grid on;
-        title(['Allan Deviation: ' name],'FontSize',FontSize+2,'FontName',FontName);
-        %set(get(gca,'Title'),'Interpreter','none');
-        xlabel('\tau [sec]','FontSize',FontSize,'FontName',FontName);
-        if isfield(data,'units')
-            ylabel(['\sigma_y(\tau) [' data.units ']'],'FontSize',FontSize,'FontName',FontName);
-        else
-            ylabel('\sigma_y(\tau)','FontSize',FontSize,'FontName',FontName);
-        end
-        set(gca,'FontSize',FontSize,'FontName',FontName);
-        % expand the x axis a little bit so that the errors bars look nice
-        adax = axis;
-        axis([adax(1)*0.9 adax(2)*1.1 adax(3) adax(4)]);
-        
-        % display the minimum value
-        fprintf(1,'allan: Minimum ADEV value: %g at tau = %g seconds\n',min(sm),tau(sm==min(sm)));
-        
-    elseif verbose >= 1
-        fprintf(1,'allan: WARNING: no values calculated.\n');
-        fprintf(1,'       Check that TAU > 1/DATA.rate and TAU values are divisible by 1/DATA.rate\n');
-        fprintf(1,'Type "help allan" for more information.\n\n');
-    end
+		grid on;
+		title(['Allan Deviation: ' name],'FontSize',FontSize+2,'FontName',FontName);
+		%set(get(gca,'Title'),'Interpreter','none');
+		xlabel('\tau [sec]','FontSize',FontSize,'FontName',FontName);
+		if isfield(data,'units')
+			ylabel(['\sigma_y(\tau) [' data.units ']'],'FontSize',FontSize,'FontName',FontName);
+		else
+			ylabel('\sigma_y(\tau)','FontSize',FontSize,'FontName',FontName);
+		end
+		set(gca,'FontSize',FontSize,'FontName',FontName);
+		% expand the x axis a little bit so that the errors bars look nice
+		adax = axis;
+		axis([adax(1)*0.9 adax(2)*1.1 adax(3) adax(4)]);
+		
+		% display the minimum value
+		fprintf(1,'allan: Minimum ADEV value: %g at tau = %g seconds\n',min(sm),tau(sm==min(sm)));
+		
+	elseif verbose >= 1
+		fprintf(1,'allan: WARNING: no values calculated.\n');
+		fprintf(1,'	   Check that TAU > 1/DATA.rate and TAU values are divisible by 1/DATA.rate\n');
+		fprintf(1,'Type "help allan" for more information.\n\n');
+	end
  
 end % end plot ADEV data
-    
+	
 retval = sm;
 errorb = sme;
  
@@ -5,33 +5,33 @@
 % Inputs:
 % DATA should be a structure and have the following fields:
 %  DATA.freq or DATA.phase
-%               A vector of fractional frequency measurements (df/f) in
-%                DATA.freq *or* phase offset data (seconds) in DATA.phase .
-%               If frequency data is not present, it will be generated by
-%                differentiating the phase data.
-%               If both fields are present, then DATA.freq will be used.
-%               Note: for general-purpose calculations of Allan deviation,
-%                (i.e. a two-sample variance) use DATA.freq .
+%			   A vector of fractional frequency measurements (df/f) in
+%				DATA.freq *or* phase offset data (seconds) in DATA.phase .
+%			   If frequency data is not present, it will be generated by
+%				differentiating the phase data.
+%			   If both fields are present, then DATA.freq will be used.
+%			   Note: for general-purpose calculations of Allan deviation,
+%				(i.e. a two-sample variance) use DATA.freq .
 %
 %  DATA.rate or DATA.time
-%               The sampling rate in Hertz (DATA.rate) or a vector of
-%               timestamps for each measurement in seconds (DATA.time).
-%               DATA.rate is used if both fields are present.
-%               If DATA.rate == 0, then the timestamps are used.
+%			   The sampling rate in Hertz (DATA.rate) or a vector of
+%			   timestamps for each measurement in seconds (DATA.time).
+%			   DATA.rate is used if both fields are present.
+%			   If DATA.rate == 0, then the timestamps are used.
 %
 %  DATA.units (optional)
-%               The units for the data. If present, the string DATA.units
-%               is added to the plot y-axis label.
+%			   The units for the data. If present, the string DATA.units
+%			   is added to the plot y-axis label.
 %
 % TAU is an array of tau values for computing Allan deviation.
-%     TAU values must be divisible by 1/DATA.rate (data points cannot be
-%     grouped in fractional quantities!) and invalid values are ignored.
-%     Leave empty to use default values.
+%	 TAU values must be divisible by 1/DATA.rate (data points cannot be
+%	 grouped in fractional quantities!) and invalid values are ignored.
+%	 Leave empty to use default values.
 % NAME is an optional label that is added to the plot titles.
 % VERBOSE sets the level of status messages:
-%     0 = silent & no data plots;
-%     1 = status messages & minimum plots;
-%     2 = all messages and plots (default)
+%	 0 = silent & no data plots;
+%	 1 = status messages & minimum plots;
+%	 2 = all messages and plots (default)
 %
 % Outputs:
 % RETVAL is the array of Allan deviation values at each TAU.
@@ -46,8 +46,8 @@
 % To compute the Allan deviation for the data in the variable "lt":
 % >> lt
 % lt = 
-%     freq: [1x86400 double]
-%     rate: 0.5
+%	 freq: [1x86400 double]
+%	 rate: 0.5
 %
 % Use:
 %
  
  
@@ -94,16 +94,16 @@
 %
 %
 % M.A. Hopcroft
-%      mhopeng at gmail dot com
+%	  mhopeng at gmail dot com
 %
 % I welcome your comments and feedback!
 %
 % MH Mar2014
 % v2.24 fix bug related to generating freq data from phase with timestamps
-%       (thanks to S. David-Grignot for finding the bug)
+%	   (thanks to S. David-Grignot for finding the bug)
 % MH Oct2010
 % v2.22 tau truncation to integer groups; tau sort
-%       plotting bugfix
+%	   plotting bugfix
 % v2.20 sychronize updates across allan, allan_overlap, allan_modified
 % v2.16 add TAU as output, fixed unusual error with dsplot v1.1
 % v2.14 update plotting behaviour, default tau values
  
  
  
  
  
  
  
  
  
@@ -113,53 +113,53 @@
  
 % MH Jun2010
 % v2.12 bugfix for rate data row/col orientation
-%       add DATA.units for plotting
-%       use dsplot.m for plotting
+%	   add DATA.units for plotting
+%	   use dsplot.m for plotting
 %
 % MH MAR2010
 % v2.1  minor interface and bugfixes
-%       update data consistency check
+%	   update data consistency check
 %
 % MH FEB2010
 % v2.0  Consistent code behaviour for all "allan_x.m" functions:
-%       accept phase data
-%       verbose levels
+%	   accept phase data
+%	   verbose levels
 %
 %
 % MH JAN2010
 % v1.84  code cleanup
 % v1.82  typos in comments and code cleanup
-%        tau bin plotting changed for performance improvement
+%		tau bin plotting changed for performance improvement
 % v1.8   Performance improvements:
-%        vectorize code for rate data
-%        logical indexing for irregular rate data
+%		vectorize code for rate data
+%		logical indexing for irregular rate data
 % MH APR2008
 % v1.62  loglog plot option
 % v1.61  improve error handling, plotting
-%        fix bug in regular data calc for high-rate data
-%        fix bug in timestamp data calc for large starting gap
-%         (thanks to C. B. Ruiz for identifying these bugs)
-%        uses timestamps for DATA.rate=0
-%        progress indicator for large timestamp data processing
+%		fix bug in regular data calc for high-rate data
+%		fix bug in timestamp data calc for large starting gap
+%		 (thanks to C. B. Ruiz for identifying these bugs)
+%		uses timestamps for DATA.rate=0
+%		progress indicator for large timestamp data processing
 % MH JUN2007
 % v1.54 Improve data plotting and optional bin plotting
 % MH FEB2007
 % v1.5  use difference from median for plotting
-%       added MAD calculation for outlier detection
+%	   added MAD calculation for outlier detection
 % MH JAN2007
 % v1.48 plotting typos fixes
 % MH DEC2006
 % v1.46 hack to plot error bars
 % v1.44 further validation (Riley 1000-pt)
-%       plot mean and std
+%	   plot mean and std
 % MH NOV2006
 % v1.42 typo fix comments
 % v1.4  fix irregular rate algorithm
-%       irregular algorithm rejects tau less than max gap in time data
-%       validate both algorithms using test data from NBS Monograph 140
+%	   irregular algorithm rejects tau less than max gap in time data
+%	   validate both algorithms using test data from NBS Monograph 140
 % v1.3  fix time calc if data.time not present
-%       add error bars (not possible due to bug in MATLAB R14SP3)
-%       remove offset calculation
+%	   add error bars (not possible due to bug in MATLAB R14SP3)
+%	   remove offset calculation
 % v1.24 improve feedback
 % MH SEP2006
 % v1.22 updated comments
  
@@ -184,25 +184,25 @@
  
 %% Data consistency checks
 if ~(isfield(data,'phase') || isfield(data,'freq'))
-    error('Either ''phase'' or ''freq'' must be present in DATA. See help file for details. [con0]');
+	error('Either ''phase'' or ''freq'' must be present in DATA. See help file for details. [con0]');
 end
 if isfield(data,'time')
-    if isfield(data,'phase') && (length(data.phase) ~= length(data.time))
-        if isfield(data,'freq') && (length(data.freq) ~= length(data.time))
-            error('The time and freq vectors are not the same length. See help for details. [con2]');
-        else
-            error('The time and phase vectors are not the same length. See help for details. [con1]');
-        end
-    end
-    if isfield(data,'phase') && (any(isnan(data.phase)) || any(isinf(data.phase)))
-        error('The phase vector contains invalid elements (NaN/Inf). [con3]');
-    end
-    if isfield(data,'freq') && (any(isnan(data.freq)) || any(isinf(data.freq)))
-        error('The freq vector contains invalid elements (NaN/Inf). [con4]');
-    end
-    if isfield(data,'time') && (any(isnan(data.time)) || any(isinf(data.time)))
-        error('The time vector contains invalid elements (NaN/Inf). [con5]');
-    end
+	if isfield(data,'phase') && (length(data.phase) ~= length(data.time))
+		if isfield(data,'freq') && (length(data.freq) ~= length(data.time))
+			error('The time and freq vectors are not the same length. See help for details. [con2]');
+		else
+			error('The time and phase vectors are not the same length. See help for details. [con1]');
+		end
+	end
+	if isfield(data,'phase') && (any(isnan(data.phase)) || any(isinf(data.phase)))
+		error('The phase vector contains invalid elements (NaN/Inf). [con3]');
+	end
+	if isfield(data,'freq') && (any(isnan(data.freq)) || any(isinf(data.freq)))
+		error('The freq vector contains invalid elements (NaN/Inf). [con4]');
+	end
+	if isfield(data,'time') && (any(isnan(data.time)) || any(isinf(data.time)))
+		error('The time vector contains invalid elements (NaN/Inf). [con5]');
+	end
 end
  
 % sort tau vector
  
  
  
  
  
@@ -211,34 +211,34 @@
  
 %% Basic statistical tests on the data set
 if ~isfield(data,'freq')
-    if isfield(data,'rate') && data.rate ~= 0
-        data.freq=diff(data.phase).*data.rate;
-    elseif isfield(data,'time')
-        data.freq=diff(data.phase)./diff(data.time);
-    end
-    if verbose >= 1, fprintf(1,'allan: Fractional frequency data generated from phase data (M=%g).\n',length(data.freq)); end
-    data.time(1)=[]; % make time stamps correspond to freq data 
+	if isfield(data,'rate') && data.rate ~= 0
+		data.freq=diff(data.phase).*data.rate;
+	elseif isfield(data,'time')
+		data.freq=diff(data.phase)./diff(data.time);
+	end
+	if verbose >= 1, fprintf(1,'allan: Fractional frequency data generated from phase data (M=%g).\n',length(data.freq)); end
+	data.time(1)=[]; % make time stamps correspond to freq data 
 end
 if size(data.freq,2) > size(data.freq,1), data.freq=data.freq'; end % ensure columns
-    
+	
 s.numpoints=length(data.freq);
 s.max=max(data.freq);
 s.min=min(data.freq);
 s.mean=mean(data.freq);
 s.median=median(data.freq);
 if isfield(data,'time')
-    if size(data.time,2) > size(data.time,1), data.time=data.time'; end % ensure columns
-    s.linear=polyfit(data.time(1:length(data.freq)),data.freq,1);
+	if size(data.time,2) > size(data.time,1), data.time=data.time'; end % ensure columns
+	s.linear=polyfit(data.time(1:length(data.freq)),data.freq,1);
 elseif isfield(data,'rate') && data.rate ~= 0;
-    s.linear=polyfit((1/data.rate:1/data.rate:length(data.freq)/data.rate)',data.freq,1);
+	s.linear=polyfit((1/data.rate:1/data.rate:length(data.freq)/data.rate)',data.freq,1);
 else
-    error('Either "time" or "rate" must be present in DATA. Type "help allan" for details. [err1]');
+	error('Either "time" or "rate" must be present in DATA. Type "help allan" for details. [err1]');
 end
 s.std=std(data.freq);
  
 if verbose >= 2
-    fprintf(1,'allan: input data statistics:\n');
-    disp(s);
+	fprintf(1,'allan: input data statistics:\n');
+	disp(s);
 end
  
  
  
@@ -249,10 +249,10 @@
 % Screen for outliers using 5x Median Absolute Deviation (MAD) criteria
 s.MAD = median(abs(medianfreq)/0.6745);
 if verbose >= 2
-    fprintf(1, 'allan: 5x MAD value for outlier detection: %g\n',5*s.MAD);
+	fprintf(1, 'allan: 5x MAD value for outlier detection: %g\n',5*s.MAD);
 end
 if verbose >= 1 && any(abs(medianfreq) > 5*s.MAD)
-    fprintf(1, 'allan: NOTE: There appear to be outliers in the frequency data. See plot.\n');
+	fprintf(1, 'allan: NOTE: There appear to be outliers in the frequency data. See plot.\n');
 end
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
@@ -263,204 +263,204 @@
 %  If there is a regular interval between measurements, calculation is much
 %   easier/faster
 if isfield(data,'rate') && data.rate > 0 % if data rate was given
-    if verbose >= 1, fprintf(1, 'allan: regular data (%g data points @ %g Hz)\n',length(data.freq),data.rate); end
-    
-    % string for plot title
-    name=[name ' (' num2str(data.rate) ' Hz)'];
-    
-    % what is the time interval between data points?
-    tmstep = 1/data.rate;
+	if verbose >= 1, fprintf(1, 'allan: regular data (%g data points @ %g Hz)\n',length(data.freq),data.rate); end
+	
+	% string for plot title
+	name=[name ' (' num2str(data.rate) ' Hz)'];
+	
+	% what is the time interval between data points?
+	tmstep = 1/data.rate;
  
-    % Is there time data? Just for curiosity/plotting, does not impact calculation
-    if isfield(data,'time')
-        % adjust time data to remove any starting gap; first time step
-        %  should not be zero for comparison with freq data
-        dtime=data.time-data.time(1)+mean(diff(data.time));
-        if verbose >= 2
-            fprintf(1,'allan: End of timestamp data: %g sec.\n',dtime(end));
-            if (data.rate - 1/mean(diff(dtime))) > 1e-6
-                fprintf(1,'allan: NOTE: data.rate (%f Hz) does not match average timestamped sample rate (%f Hz)\n',data.rate,1/mean(diff(dtime)));
-            end
-        end
-    else
-        % create time axis data using rate (for plotting only)
-        dtime=(tmstep:tmstep:length(data.freq)*tmstep)'; % column oriented
-    end
+	% Is there time data? Just for curiosity/plotting, does not impact calculation
+	if isfield(data,'time')
+		% adjust time data to remove any starting gap; first time step
+		%  should not be zero for comparison with freq data
+		dtime=data.time-data.time(1)+mean(diff(data.time));
+		if verbose >= 2
+			fprintf(1,'allan: End of timestamp data: %g sec.\n',dtime(end));
+			if (data.rate - 1/mean(diff(dtime))) > 1e-6
+				fprintf(1,'allan: NOTE: data.rate (%f Hz) does not match average timestamped sample rate (%f Hz)\n',data.rate,1/mean(diff(dtime)));
+			end
+		end
+	else
+		% create time axis data using rate (for plotting only)
+		dtime=(tmstep:tmstep:length(data.freq)*tmstep)'; % column oriented
+	end
  
-    % check the range of tau values and truncate if necessary
-    % find halfway point of time record
-    halftime = round(tmstep*length(data.freq)/2);
-    % truncate tau to appropriate values
-    tau = tau(tau >= tmstep & tau <= halftime);
-    if verbose >= 2, fprintf(1, 'allan: allowable tau range: %g to %g sec. (1/rate to total_time/2)\n',tmstep,halftime); end  
-    
-    % save the freq data for the loop
-    dfreq=data.freq;
-    dfreq2=data.freq2;
-    % find the number of data points in each tau group
-    m = data.rate.*tau;
-    % only integer values allowed (no fractional groups of points)
-    %tau = tau(m-round(m)<1e-8); % numerical precision issues (v2.1)
-    tau = tau(m==round(m));  % The round() test is only correct for values < 2^53
-    %m = m(m-round(m)<1e-8); % change to round(m) for integer test v2.22
-    m = m(m==round(m));
-    %m=round(m);
-    
-    if verbose >= 1, fprintf(1,'allan: calculating Allan deviation...\n       '); end
-    
-    % calculate the Allan deviation for each value of tau
-    k=0; tic;
-    for i = tau
-        if verbose >= 2, fprintf(1,'%g ',i); end
-        k=k+1;
+	% check the range of tau values and truncate if necessary
+	% find halfway point of time record
+	halftime = round(tmstep*length(data.freq)/2);
+	% truncate tau to appropriate values
+	tau = tau(tau >= tmstep & tau <= halftime);
+	if verbose >= 2, fprintf(1, 'allan: allowable tau range: %g to %g sec. (1/rate to total_time/2)\n',tmstep,halftime); end  
+	
+	% save the freq data for the loop
+	dfreq=data.freq;
+	dfreq2=data.freq2;
+	% find the number of data points in each tau group
+	m = data.rate.*tau;
+	% only integer values allowed (no fractional groups of points)
+	%tau = tau(m-round(m)<1e-8); % numerical precision issues (v2.1)
+	tau = tau(m==round(m));  % The round() test is only correct for values < 2^53
+	%m = m(m-round(m)<1e-8); % change to round(m) for integer test v2.22
+	m = m(m==round(m));
+	%m=round(m);
+	
+	if verbose >= 1, fprintf(1,'allan: calculating Allan deviation...\n	   '); end
+	
+	% calculate the Allan deviation for each value of tau
+	k=0; tic;
+	for i = tau
+		if verbose >= 2, fprintf(1,'%g ',i); end
+		k=k+1;
  
-        % truncate frequency set to an even multiple of this tau value
-        freq=dfreq(1:end-rem(length(dfreq),m(k)));
-        freq2=dfreq2(1:end-rem(length(dfreq2),m(k)));
-        % group the data into tau-length groups or bins
-        f = reshape(freq,m(k),[]); % Vectorize!     
-        f2 = reshape(freq2,m(k),[]); % Vectorize!     
-        % find average in each "tau group", y_k (each colummn of f)
-        fa=mean(f,1);
-        fa2=mean(f2,1);
-        % first finite difference
-        fd=diff(fa);
-        fd2=diff(fa2);
-        % calculate two-sample variance for this tau
-        M=length(fa);
-        sm(k)=sqrt(0.5/(M-1)*(abs(sum(fd.*fd2))));
+		% truncate frequency set to an even multiple of this tau value
+		freq=dfreq(1:end-rem(length(dfreq),m(k)));
+		freq2=dfreq2(1:end-rem(length(dfreq2),m(k)));
+		% group the data into tau-length groups or bins
+		f = reshape(freq,m(k),[]); % Vectorize!	 
+		f2 = reshape(freq2,m(k),[]); % Vectorize!	 
+		% find average in each "tau group", y_k (each colummn of f)
+		fa=mean(f,1);
+		fa2=mean(f2,1);
+		% first finite difference
+		fd=diff(fa);
+		fd2=diff(fa2);
+		% calculate two-sample variance for this tau
+		M=length(fa);
+		sm(k)=sqrt(0.5/(M-1)*(abs(sum(fd.*fd2))));
  
-        % estimate error bars
-        sme(k)=sm(k)/sqrt(M+1);
-        
-        if TAUBIN == 1
-            % save the binning points for plotting
-            fs(k,1:length(freq)/m(k))=m(k):m(k):length(freq); fval{k}=mean(f,1);
-        end
-        
-    end % repeat for each value of tau
-    
-    if verbose >= 2, fprintf(1,'\n'); end
-    calctime=toc; if verbose >= 2, fprintf(1,'allan: Elapsed time for calculation: %e seconds\n',calctime); end
-    
-       
-    
+		% estimate error bars
+		sme(k)=sm(k)/sqrt(M+1);
+		
+		if TAUBIN == 1
+			% save the binning points for plotting
+			fs(k,1:length(freq)/m(k))=m(k):m(k):length(freq); fval{k}=mean(f,1);
+		end
+		
+	end % repeat for each value of tau
+	
+	if verbose >= 2, fprintf(1,'\n'); end
+	calctime=toc; if verbose >= 2, fprintf(1,'allan: Elapsed time for calculation: %e seconds\n',calctime); end
+	
+	   
+	
 %% Irregular data (timestamp)   
 elseif isfield(data,'time')
-    % the interval between measurements is irregular
-    %  so we must group the data by time
-    if verbose >= 1, fprintf(1, 'allan: irregular rate data (no fixed sample rate)\n'); end
-    
-    % string for plot title
-    name=[name ' (timestamp)'];
-    
-    % adjust time to remove any initial offset or zero
-    dtime=data.time-data.time(1)+mean(diff(data.time));
-    %dtime=data.time;
-    % where is the maximum gap in time record?
-    gap_pos=find(diff(dtime)==max(diff(dtime)));
-    % what is average data spacing?
-    avg_gap = mean(diff(dtime));
-    
-    if verbose >= 2
-        fprintf(1, 'allan: WARNING: irregular timestamp data (no fixed sample rate).\n');
-        fprintf(1, '       Calculation time may be long and the results subject to interpretation.\n');
-        fprintf(1, '       You are advised to estimate using an average sample rate (%g Hz) instead of timestamps.\n',1/avg_gap);
-        fprintf(1, '       Continue at your own risk! (press any key to continue)\n');
-        pause;
-    end
-    
-    if verbose >= 1
-        fprintf(1, 'allan: End of timestamp data: %g sec\n',dtime(end));
-    	fprintf(1, '       Average rate: %g Hz (%g sec/measurement)\n',1/avg_gap,avg_gap);
-        if max(diff(dtime)) ~= 1/mean(diff(dtime))
-            fprintf(1, '       Max. gap: %g sec at position %d\n',max(diff(dtime)),gap_pos(1));
-        end
-        if max(diff(dtime)) > 5*avg_gap
-            fprintf(1, '       WARNING: Max. gap in time record is suspiciously large (>5x the average interval).\n');
-        end        
-    end
+	% the interval between measurements is irregular
+	%  so we must group the data by time
+	if verbose >= 1, fprintf(1, 'allan: irregular rate data (no fixed sample rate)\n'); end
+	
+	% string for plot title
+	name=[name ' (timestamp)'];
+	
+	% adjust time to remove any initial offset or zero
+	dtime=data.time-data.time(1)+mean(diff(data.time));
+	%dtime=data.time;
+	% where is the maximum gap in time record?
+	gap_pos=find(diff(dtime)==max(diff(dtime)));
+	% what is average data spacing?
+	avg_gap = mean(diff(dtime));
+	
+	if verbose >= 2
+		fprintf(1, 'allan: WARNING: irregular timestamp data (no fixed sample rate).\n');
+		fprintf(1, '	   Calculation time may be long and the results subject to interpretation.\n');
+		fprintf(1, '	   You are advised to estimate using an average sample rate (%g Hz) instead of timestamps.\n',1/avg_gap);
+		fprintf(1, '	   Continue at your own risk! (press any key to continue)\n');
+		pause;
+	end
+	
+	if verbose >= 1
+		fprintf(1, 'allan: End of timestamp data: %g sec\n',dtime(end));
+		fprintf(1, '	   Average rate: %g Hz (%g sec/measurement)\n',1/avg_gap,avg_gap);
+		if max(diff(dtime)) ~= 1/mean(diff(dtime))
+			fprintf(1, '	   Max. gap: %g sec at position %d\n',max(diff(dtime)),gap_pos(1));
+		end
+		if max(diff(dtime)) > 5*avg_gap
+			fprintf(1, '	   WARNING: Max. gap in time record is suspiciously large (>5x the average interval).\n');
+		end		
+	end
  
  
-    % find halfway point
-    halftime = fix(dtime(end)/2);
-    % truncate tau to appropriate values
-    tau = tau(tau >= max(diff(dtime)) & tau <= halftime);
-    if isempty(tau)
-        error('allan: ERROR: no appropriate tau values (> %g s, < %g s)\n',max(diff(dtime)),halftime);
-    end
-    
-    % save the freq data for the loop
-    dfreq=data.freq;
-    dtime=dtime(1:length(dfreq));
+	% find halfway point
+	halftime = fix(dtime(end)/2);
+	% truncate tau to appropriate values
+	tau = tau(tau >= max(diff(dtime)) & tau <= halftime);
+	if isempty(tau)
+		error('allan: ERROR: no appropriate tau values (> %g s, < %g s)\n',max(diff(dtime)),halftime);
+	end
+	
+	% save the freq data for the loop
+	dfreq=data.freq;
+	dtime=dtime(1:length(dfreq));
  
-    if verbose >= 1, fprintf(1,'allan: calculating Allan deviation...\n'); end
+	if verbose >= 1, fprintf(1,'allan: calculating Allan deviation...\n'); end
  
-    k=0; tic;
-    for i = tau
-        if verbose >= 2, fprintf(1,'%d ',i); end
-        
-        k=k+1; fa=[]; %f=[];
-        km=0;
-        
-        % truncate data set to an even multiple of this tau value
-        freq=dfreq(dtime <= dtime(end)-rem(dtime(end),i));
-        time=dtime(dtime <= dtime(end)-rem(dtime(end),i));
-        %freq=dfreq;
-        %time=dtime;
-        
-        % break up the data into groups of tau length in sec
-        while i*km < time(end)
-            km=km+1;
-                        
-            % progress bar
-            if verbose >= 2
-                if rem(km,100)==0, fprintf(1,'.'); end
-                if rem(km,1000)==0, fprintf(1,'%g/%g\n',km,round(time(end)/i)); end
-            end
+	k=0; tic;
+	for i = tau
+		if verbose >= 2, fprintf(1,'%d ',i); end
+		
+		k=k+1; fa=[]; %f=[];
+		km=0;
+		
+		% truncate data set to an even multiple of this tau value
+		freq=dfreq(dtime <= dtime(end)-rem(dtime(end),i));
+		time=dtime(dtime <= dtime(end)-rem(dtime(end),i));
+		%freq=dfreq;
+		%time=dtime;
+		
+		% break up the data into groups of tau length in sec
+		while i*km < time(end)
+			km=km+1;
+						
+			% progress bar
+			if verbose >= 2
+				if rem(km,100)==0, fprintf(1,'.'); end
+				if rem(km,1000)==0, fprintf(1,'%g/%g\n',km,round(time(end)/i)); end
+			end
  
-            f = freq(i*(km-1) < time & time <= i*km);
-            f = f(~isnan(f)); % make sure values are valid
-            
-            if ~isempty(f)
-                fa(km)=mean(f);
-            else
-                fa(km)=0;
-            end
+			f = freq(i*(km-1) < time & time <= i*km);
+			f = f(~isnan(f)); % make sure values are valid
+			
+			if ~isempty(f)
+				fa(km)=mean(f);
+			else
+				fa(km)=0;
+			end
  
-            if TAUBIN == 1 % WARNING: this has a significant impact on performance
-                % save the binning points for plotting
-                %if find(time <= i*km) > 0
-                    fs(k,km)=max(time(time <= i*km));
-                %else
-                if isempty(fs(k,km))
-                    fs(k,km)=0;
-                end
-                fval{k}=fa;
-            end % save tau bin plot points
-            
-        end
-        
-        if verbose >= 2, fprintf(1,'\n'); end
+			if TAUBIN == 1 % WARNING: this has a significant impact on performance
+				% save the binning points for plotting
+				%if find(time <= i*km) > 0
+					fs(k,km)=max(time(time <= i*km));
+				%else
+				if isempty(fs(k,km))
+					fs(k,km)=0;
+				end
+				fval{k}=fa;
+			end % save tau bin plot points
+			
+		end
+		
+		if verbose >= 2, fprintf(1,'\n'); end
  
-        % first finite difference of the averaged results
-        fd=diff(fa);
-        % calculate Allan deviation for this tau
-        M=length(fa);
-        sm(k)=sqrt(0.5/(M-1)*(sum(fd.^2)));
+		% first finite difference of the averaged results
+		fd=diff(fa);
+		% calculate Allan deviation for this tau
+		M=length(fa);
+		sm(k)=sqrt(0.5/(M-1)*(sum(fd.^2)));
  
-        % estimate error bars
-        sme(k)=sm(k)/sqrt(M+1);
-        
+		% estimate error bars
+		sme(k)=sm(k)/sqrt(M+1);
+		
  
-    end
+	end
  
-    if verbose == 2, fprintf(1,'\n'); end
-    calctime=toc; if verbose >= 2, fprintf(1,'allan: Elapsed time for calculation: %e seconds\n',calctime); end
-    
+	if verbose == 2, fprintf(1,'\n'); end
+	calctime=toc; if verbose >= 2, fprintf(1,'allan: Elapsed time for calculation: %e seconds\n',calctime); end
+	
  
 else
-    error('allan: WARNING: no DATA.rate or DATA.time! Type "help allan" for more information. [err2]');
+	error('allan: WARNING: no DATA.rate or DATA.time! Type "help allan" for more information. [err2]');
 end
  
  
  
  
  
  
  
  
  
@@ -468,113 +468,113 @@
 %% Plotting
  
 if verbose >= 2 % show all data
-    
-    % plot the frequency data, centered on median
-    if size(dtime,2) > size(dtime,1), dtime=dtime'; end % this should not be necessary, but dsplot 1.1 is a little bit brittle
-    try
-        % dsplot makes a new figure
-        hd=dsplot(dtime,medianfreq);
-    catch ME
-        figure;
-        if length(dtime) ~= length(medianfreq)
-            fprintf(1,'allan: Warning: length of time axis (%d) is not equal to data array (%d)\n',length(dtime),length(medianfreq));
-        end
-        hd=plot(dtime,medianfreq);
-        if verbose >= 1, fprintf(1,'allan: Note: Install dsplot.m for improved plotting of large data sets (File Exchange File ID: #15850).\n'); end
-        if verbose >= 2, fprintf(1,'             (Message: %s)\n',ME.message); end
-    end
-    set(hd,'Marker','.','LineStyle','none','Color','b'); % equivalent to '.-'
-    hold on;
+	
+	% plot the frequency data, centered on median
+	if size(dtime,2) > size(dtime,1), dtime=dtime'; end % this should not be necessary, but dsplot 1.1 is a little bit brittle
+	try
+		% dsplot makes a new figure
+		hd=dsplot(dtime,medianfreq);
+	catch ME
+		figure;
+		if length(dtime) ~= length(medianfreq)
+			fprintf(1,'allan: Warning: length of time axis (%d) is not equal to data array (%d)\n',length(dtime),length(medianfreq));
+		end
+		hd=plot(dtime,medianfreq);
+		if verbose >= 1, fprintf(1,'allan: Note: Install dsplot.m for improved plotting of large data sets (File Exchange File ID: #15850).\n'); end
+		if verbose >= 2, fprintf(1,'			 (Message: %s)\n',ME.message); end
+	end
+	set(hd,'Marker','.','LineStyle','none','Color','b'); % equivalent to '.-'
+	hold on;
  
-    % show center (0)
-    plot(xlim,[0 0],':k');
-    % show 5x Median Absolute Deviation (MAD) values
-    hm=plot(xlim,[5*s.MAD 5*s.MAD],'-r');
-    plot(xlim,[-5*s.MAD -5*s.MAD],'-r');
-    % show linear fit line
-    hf=plot(xlim,polyval(s.linear,xlim)-s.median,'-g');
-    title(['Data: ' name],'FontSize',FontSize+2,'FontName',FontName);
-    %set(get(gca,'Title'),'Interpreter','none');
-    xlabel('Time [sec]','FontSize',FontSize,'FontName',FontName);
-    if isfield(data,'units')
-        ylabel(['data - median(data) [' data.units ']'],'FontSize',FontSize,'FontName',FontName);
-    else
-        ylabel('freq - median(freq)','FontSize',FontSize,'FontName',FontName);
-    end
-    set(gca,'FontSize',FontSize,'FontName',FontName);
-    legend([hd hm hf],{'data (centered on median)','5x MAD outliers',['Linear Fit (' num2str(s.linear(1),'%g') ')']},'FontSize',max(10,FontSize-2));
-    % tighten up
-    xlim([dtime(1) dtime(end)]);
+	% show center (0)
+	plot(xlim,[0 0],':k');
+	% show 5x Median Absolute Deviation (MAD) values
+	hm=plot(xlim,[5*s.MAD 5*s.MAD],'-r');
+	plot(xlim,[-5*s.MAD -5*s.MAD],'-r');
+	% show linear fit line
+	hf=plot(xlim,polyval(s.linear,xlim)-s.median,'-g');
+	title(['Data: ' name],'FontSize',FontSize+2,'FontName',FontName);
+	%set(get(gca,'Title'),'Interpreter','none');
+	xlabel('Time [sec]','FontSize',FontSize,'FontName',FontName);
+	if isfield(data,'units')
+		ylabel(['data - median(data) [' data.units ']'],'FontSize',FontSize,'FontName',FontName);
+	else
+		ylabel('freq - median(freq)','FontSize',FontSize,'FontName',FontName);
+	end
+	set(gca,'FontSize',FontSize,'FontName',FontName);
+	legend([hd hm hf],{'data (centered on median)','5x MAD outliers',['Linear Fit (' num2str(s.linear(1),'%g') ')']},'FontSize',max(10,FontSize-2));
+	% tighten up
+	xlim([dtime(1) dtime(end)]);
  
  
-    % Optional tau bin (y_k samples) plot
-    if TAUBIN == 1
-        % plot the tau divisions on the data plot
-        rfs=size(fs,1);
-        colororder=get(gca,'ColorOrder');
-        axis tight; kc=2;
-        %ap=axis;
-        for j=1:rfs
-            kc=kc+1; if rem(kc,length(colororder))==1, kc=2; end
-            %for b=1:max(find(fs(j,:))); % new form of "find" in r2009a
-            for b=1:find(fs(j,:), 1, 'last' );
-                % plot the tau division boundaries
-                %plot([fs(j,b) fs(j,b)],[ap(3)*1.1 ap(4)*1.1],'-','Color',colororder(kc,:));
-                % plot tau group y values
-                if b == 1
-                    plot([dtime(1) fs(j,b)],[fval{j}(b)-s.median fval{j}(b)-s.median],'-','Color',colororder(kc,:),'LineWidth',4);
-                else
-                    plot([fs(j,b-1) fs(j,b)],[fval{j}(b)-s.median fval{j}(b)-s.median],'-','Color',colororder(kc,:),'LineWidth',4);
-                end
-            end
-        end
-        axis auto
-    end % End optional bin plot
-    
+	% Optional tau bin (y_k samples) plot
+	if TAUBIN == 1
+		% plot the tau divisions on the data plot
+		rfs=size(fs,1);
+		colororder=get(gca,'ColorOrder');
+		axis tight; kc=2;
+		%ap=axis;
+		for j=1:rfs
+			kc=kc+1; if rem(kc,length(colororder))==1, kc=2; end
+			%for b=1:max(find(fs(j,:))); % new form of "find" in r2009a
+			for b=1:find(fs(j,:), 1, 'last' );
+				% plot the tau division boundaries
+				%plot([fs(j,b) fs(j,b)],[ap(3)*1.1 ap(4)*1.1],'-','Color',colororder(kc,:));
+				% plot tau group y values
+				if b == 1
+					plot([dtime(1) fs(j,b)],[fval{j}(b)-s.median fval{j}(b)-s.median],'-','Color',colororder(kc,:),'LineWidth',4);
+				else
+					plot([fs(j,b-1) fs(j,b)],[fval{j}(b)-s.median fval{j}(b)-s.median],'-','Color',colororder(kc,:),'LineWidth',4);
+				end
+			end
+		end
+		axis auto
+	end % End optional bin plot
+	
 end % end plot raw data
  
  
 if verbose >= 1 % show ADEV results
  
-    % plot Allan deviation results
-    if ~isempty(sm)
-        figure
+	% plot Allan deviation results
+	if ~isempty(sm)
+		figure
  
-        % Choose loglog or semilogx plot here    #PLOTLOG
-        %semilogx(tau,sm,'.-b','LineWidth',plotlinewidth,'MarkerSize',24);
-        loglog(tau,sm,'.-b','LineWidth',plotlinewidth,'MarkerSize',24);
+		% Choose loglog or semilogx plot here	#PLOTLOG
+		%semilogx(tau,sm,'.-b','LineWidth',plotlinewidth,'MarkerSize',24);
+		loglog(tau,sm,'.-b','LineWidth',plotlinewidth,'MarkerSize',24);
  
-        % in R14SP3, there is a bug that screws up the error bars on a semilog plot.
-        %  When this is fixed in a future release, uncomment below to use normal errorbars
-        %errorbar(tau,sm,sme,'.-b'); set(gca,'XScale','log');
-        % this is a hack to approximate the error bars
-        hold on; plot([tau; tau],[sm+sme; sm-sme],'-k','LineWidth',max(plotlinewidth-1,2));
+		% in R14SP3, there is a bug that screws up the error bars on a semilog plot.
+		%  When this is fixed in a future release, uncomment below to use normal errorbars
+		%errorbar(tau,sm,sme,'.-b'); set(gca,'XScale','log');
+		% this is a hack to approximate the error bars
+		hold on; plot([tau; tau],[sm+sme; sm-sme],'-k','LineWidth',max(plotlinewidth-1,2));
  
-        grid on;
-        title(['Allan Deviation: ' name],'FontSize',FontSize+2,'FontName',FontName);
-        %set(get(gca,'Title'),'Interpreter','none');
-        xlabel('\tau [sec]','FontSize',FontSize,'FontName',FontName);
-        if isfield(data,'units')
-            ylabel(['\sigma_y(\tau) [' data.units ']'],'FontSize',FontSize,'FontName',FontName);
-        else
-            ylabel('\sigma_y(\tau)','FontSize',FontSize,'FontName',FontName);
-        end
-        set(gca,'FontSize',FontSize,'FontName',FontName);
-        % expand the x axis a little bit so that the errors bars look nice
-        adax = axis;
-        axis([adax(1)*0.9 adax(2)*1.1 adax(3) adax(4)]);
-        
-        % display the minimum value
-        fprintf(1,'allan: Minimum ADEV value: %g at tau = %g seconds\n',min(sm),tau(sm==min(sm)));
-        
-    elseif verbose >= 1
-        fprintf(1,'allan: WARNING: no values calculated.\n');
-        fprintf(1,'       Check that TAU > 1/DATA.rate and TAU values are divisible by 1/DATA.rate\n');
-        fprintf(1,'Type "help allan" for more information.\n\n');
-    end
+		grid on;
+		title(['Allan Deviation: ' name],'FontSize',FontSize+2,'FontName',FontName);
+		%set(get(gca,'Title'),'Interpreter','none');
+		xlabel('\tau [sec]','FontSize',FontSize,'FontName',FontName);
+		if isfield(data,'units')
+			ylabel(['\sigma_y(\tau) [' data.units ']'],'FontSize',FontSize,'FontName',FontName);
+		else
+			ylabel('\sigma_y(\tau)','FontSize',FontSize,'FontName',FontName);
+		end
+		set(gca,'FontSize',FontSize,'FontName',FontName);
+		% expand the x axis a little bit so that the errors bars look nice
+		adax = axis;
+		axis([adax(1)*0.9 adax(2)*1.1 adax(3) adax(4)]);
+		
+		% display the minimum value
+		fprintf(1,'allan: Minimum ADEV value: %g at tau = %g seconds\n',min(sm),tau(sm==min(sm)));
+		
+	elseif verbose >= 1
+		fprintf(1,'allan: WARNING: no values calculated.\n');
+		fprintf(1,'	   Check that TAU > 1/DATA.rate and TAU values are divisible by 1/DATA.rate\n');
+		fprintf(1,'Type "help allan" for more information.\n\n');
+	end
  
 end % end plot ADEV data
-    
+	
 retval = sm;
 errorb = sme;
  
@@ -6,24 +6,24 @@
 % Inputs:
 % DATA should be a struct and have the following fields:
 %  DATA.freq or DATA.phase
-%               A vector of fractional frequency measurements (df/f) in
-%               DATA.freq *or* phase offset data (seconds) in DATA.phase
-%               If phase data is not present, it will be generated by
-%               integrating the fractional frequency data.
-%               If both fields are present, then DATA.phase will be used.
+%			   A vector of fractional frequency measurements (df/f) in
+%			   DATA.freq *or* phase offset data (seconds) in DATA.phase
+%			   If phase data is not present, it will be generated by
+%			   integrating the fractional frequency data.
+%			   If both fields are present, then DATA.phase will be used.
 %
 %  DATA.rate or DATA.time
-%               The sampling rate in Hertz (DATA.rate) or a vector of
-%               timestamps for each measurement in seconds (DATA.time).
-%               DATA.rate is used if both fields are present.
-%               If DATA.rate == 0, then the timestamps are used.
+%			   The sampling rate in Hertz (DATA.rate) or a vector of
+%			   timestamps for each measurement in seconds (DATA.time).
+%			   DATA.rate is used if both fields are present.
+%			   If DATA.rate == 0, then the timestamps are used.
 %
 % TAU is an array of tau values for computing Allan deviation.
-%     TAU values must be divisible by 1/DATA.rate (data points cannot be
-%     grouped in fractional quantities!). Invalid values are ignored.
+%	 TAU values must be divisible by 1/DATA.rate (data points cannot be
+%	 grouped in fractional quantities!). Invalid values are ignored.
 % NAME is an optional label that is added to the plot titles.
 % VERBOSE sets the level of status messages:
-%     0 = silent & no data plots; 1 = status messages; 2 = all messages
+%	 0 = silent & no data plots; 1 = status messages; 2 = all messages
 %
 % Outputs:
 % RETVAL is the array of modified Allan deviation values at each TAU.
@@ -38,8 +38,8 @@
 % To compute the modified Allan deviation for the data in the variable "lt":
 % >> lt
 % lt = 
-%     freq: [1x86400 double]
-%     rate: 0.5
+%	 freq: [1x86400 double]
+%	 rate: 0.5
 %
 % Use:
 %
  
  
  
  
@@ -83,25 +83,25 @@
 %
 %
 % M.A. Hopcroft
-%      mhopeng at gmail dot com
+%	  mhopeng at gmail dot com
 %
 % I welcome your comments and feedback!
 %
 % MH Mar2014
 % v1.24 fix bug related to generating freq data from phase with timestamps
-%       (thanks to S. David-Grignot for finding the bug)
+%	   (thanks to S. David-Grignot for finding the bug)
 % MH Oct2010
 % v1.22 tau truncation to integer groups; tau sort
-%       plotting bugfix
+%	   plotting bugfix
 % v1.20 update to match allan.m (dsplot.m, columns)
-%       discard tau values with timestamp irregularities
+%	   discard tau values with timestamp irregularities
 %
  
 versionstr = 'allan_modified v1.24';
  
 % MH MAR2010
 % v1.1  bugfixes for irregular sample rates
-%       update consistency check
+%	   update consistency check
 %
 % MH FEB2010
 % v1.0  based on allan_overlap v2.0
  
@@ -125,25 +125,25 @@
  
 %% Data consistency checks
 if ~(isfield(data,'phase') || isfield(data,'freq'))
-    error('Either ''phase'' or ''freq'' must be present in DATA. See help file for details. [con0]');
+	error('Either ''phase'' or ''freq'' must be present in DATA. See help file for details. [con0]');
 end
 if isfield(data,'time')
-    if isfield(data,'phase') && (length(data.phase) ~= length(data.time))
-        if isfield(data,'freq') && (length(data.freq) ~= length(data.time))
-            error('The time and freq vectors are not the same length. See help for details. [con2]');
-        else
-            error('The time and phase vectors are not the same length. See help for details. [con1]');
-        end
-    end
-    if isfield(data,'phase') && (any(isnan(data.phase)) || any(isinf(data.phase)))
-        error('The phase vector contains invalid elements (NaN/Inf). [con3]');
-    end
-    if isfield(data,'freq') && (any(isnan(data.freq)) || any(isinf(data.freq)))
-        error('The freq vector contains invalid elements (NaN/Inf). [con4]');
-    end
-    if isfield(data,'time') && (any(isnan(data.time)) || any(isinf(data.time)))
-        error('The time vector contains invalid elements (NaN/Inf). [con5]');
-    end
+	if isfield(data,'phase') && (length(data.phase) ~= length(data.time))
+		if isfield(data,'freq') && (length(data.freq) ~= length(data.time))
+			error('The time and freq vectors are not the same length. See help for details. [con2]');
+		else
+			error('The time and phase vectors are not the same length. See help for details. [con1]');
+		end
+	end
+	if isfield(data,'phase') && (any(isnan(data.phase)) || any(isinf(data.phase)))
+		error('The phase vector contains invalid elements (NaN/Inf). [con3]');
+	end
+	if isfield(data,'freq') && (any(isnan(data.freq)) || any(isinf(data.freq)))
+		error('The freq vector contains invalid elements (NaN/Inf). [con4]');
+	end
+	if isfield(data,'time') && (any(isnan(data.time)) || any(isinf(data.time)))
+		error('The time vector contains invalid elements (NaN/Inf). [con5]');
+	end
 end
  
 % sort tau vector
@@ -152,12 +152,12 @@
  
 %% Basic statistical tests on the data set
 if ~isfield(data,'freq')
-    if isfield(data,'rate') && data.rate ~= 0
-        data.freq=diff(data.phase).*data.rate;
-    elseif isfield(data,'time')
-        data.freq=diff(data.phase)./diff(data.time);
-    end
-    if verbose >= 1, fprintf(1,'allan_modified: Fractional frequency data generated from phase data (M=%g).\n',length(data.freq)); end
+	if isfield(data,'rate') && data.rate ~= 0
+		data.freq=diff(data.phase).*data.rate;
+	elseif isfield(data,'time')
+		data.freq=diff(data.phase)./diff(data.time);
+	end
+	if verbose >= 1, fprintf(1,'allan_modified: Fractional frequency data generated from phase data (M=%g).\n',length(data.freq)); end
 end
 if size(data.freq,2) > size(data.freq,1), data.freq=data.freq'; end % ensure columns
  
  
  
  
@@ -167,18 +167,18 @@
 s.mean=mean(data.freq);
 s.median=median(data.freq);
 if isfield(data,'time')
-    if size(data.time,2) > size(data.time,1), data.time=data.time'; end % ensure columns
-    s.linear=polyfit(data.time(1:length(data.freq)),data.freq,1);
+	if size(data.time,2) > size(data.time,1), data.time=data.time'; end % ensure columns
+	s.linear=polyfit(data.time(1:length(data.freq)),data.freq,1);
 elseif isfield(data,'rate') && data.rate ~= 0;
-    s.linear=polyfit((1/data.rate:1/data.rate:length(data.freq)/data.rate)',data.freq,1);
+	s.linear=polyfit((1/data.rate:1/data.rate:length(data.freq)/data.rate)',data.freq,1);
 else
-    error('Either "time" or "rate" must be present in DATA. Type "help allan_modified" for details. [err1]');
+	error('Either "time" or "rate" must be present in DATA. Type "help allan_modified" for details. [err1]');
 end
 s.std=std(data.freq);
  
 if verbose >= 2
-    fprintf(1,'allan_modified: fractional frequency data statistics:\n');
-    disp(s);
+	fprintf(1,'allan_modified: fractional frequency data statistics:\n');
+	disp(s);
 end
  
 % scale to median for plotting
@@ -188,7 +188,7 @@
 % Screen for outliers using 5x Median Absolute Deviation (MAD) criteria
 MAD = median(abs(medianfreq)/0.6745);
 if verbose >= 1 && any(abs(medianfreq) > 5*MAD)
-    fprintf(1, 'allan_modified: NOTE: There appear to be outliers in the frequency data. See plot.\n');
+	fprintf(1, 'allan_modified: NOTE: There appear to be outliers in the frequency data. See plot.\n');
 end
  
 %%%%
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
@@ -198,279 +198,279 @@
 %   If there is a regular interval between measurements, calculation is much
 %   easier/faster
 if isfield(data,'rate') && data.rate > 0 % if data rate was given
-    if verbose >= 1
-        fprintf(1, 'allan_modified: regular data ');
-        if isfield(data,'freq')
-            fprintf(1, '(%g freq data points @ %g Hz)\n',length(data.freq),data.rate);
-        elseif isfield(data,'phase')
-            fprintf(1, '(%g phase data points @ %g Hz)\n',length(data.phase),data.rate);
-        else
-            error('\n phase or freq data missing [err10]');
-        end
-    end
-    
-    % string for plot title
-    name=[name ' (' num2str(data.rate) ' Hz)'];
+	if verbose >= 1
+		fprintf(1, 'allan_modified: regular data ');
+		if isfield(data,'freq')
+			fprintf(1, '(%g freq data points @ %g Hz)\n',length(data.freq),data.rate);
+		elseif isfield(data,'phase')
+			fprintf(1, '(%g phase data points @ %g Hz)\n',length(data.phase),data.rate);
+		else
+			error('\n phase or freq data missing [err10]');
+		end
+	end
+	
+	% string for plot title
+	name=[name ' (' num2str(data.rate) ' Hz)'];
  
-    % what is the time interval between data points?
-    tmstep = 1/data.rate;
-    
-    % Is there time data? Just for curiosity/plotting, does not impact calculation
-    if isfield(data,'time')
-        % adjust time data to remove any starting gap; first time step
-        %  should not be zero for comparison with freq data
-        dtime=data.time-data.time(1)+mean(diff(data.time));
-        dtime=dtime(1:length(medianfreq)); % equalize the data vector lengths for plotting (v1.1)
-        if verbose >= 2
-            fprintf(1,'allan_modified: End of timestamp data: %g sec.\n',dtime(end));
-            if (data.rate - 1/mean(diff(dtime))) > 1e-6
-                fprintf(1,'allan_modified: NOTE: data.rate (%f Hz) does not match average timestamped sample rate (%f Hz)\n',data.rate,1/mean(diff(dtime)));
-            end
-        end
-    else
-        % create time axis data using rate (for plotting only)
-        dtime=(tmstep:tmstep:length(data.freq)*tmstep);
-    end
-    
-    
-    % is phase data present? If not, generate it
-    if ~isfield(data,'phase')
-        nfreq=data.freq-s.mean;
-        dphase=zeros(1,length(nfreq)+1);
-        dphase(2:end) = cumsum(nfreq).*tmstep;
-        if verbose >= 1, fprintf(1,'allan_modified: phase data generated from fractional frequency data (N=%g).\n',length(dphase)); end
-    else
-        dphase=data.phase;
-    end
+	% what is the time interval between data points?
+	tmstep = 1/data.rate;
+	
+	% Is there time data? Just for curiosity/plotting, does not impact calculation
+	if isfield(data,'time')
+		% adjust time data to remove any starting gap; first time step
+		%  should not be zero for comparison with freq data
+		dtime=data.time-data.time(1)+mean(diff(data.time));
+		dtime=dtime(1:length(medianfreq)); % equalize the data vector lengths for plotting (v1.1)
+		if verbose >= 2
+			fprintf(1,'allan_modified: End of timestamp data: %g sec.\n',dtime(end));
+			if (data.rate - 1/mean(diff(dtime))) > 1e-6
+				fprintf(1,'allan_modified: NOTE: data.rate (%f Hz) does not match average timestamped sample rate (%f Hz)\n',data.rate,1/mean(diff(dtime)));
+			end
+		end
+	else
+		% create time axis data using rate (for plotting only)
+		dtime=(tmstep:tmstep:length(data.freq)*tmstep);
+	end
+	
+	
+	% is phase data present? If not, generate it
+	if ~isfield(data,'phase')
+		nfreq=data.freq-s.mean;
+		dphase=zeros(1,length(nfreq)+1);
+		dphase(2:end) = cumsum(nfreq).*tmstep;
+		if verbose >= 1, fprintf(1,'allan_modified: phase data generated from fractional frequency data (N=%g).\n',length(dphase)); end
+	else
+		dphase=data.phase;
+	end
  
-    
-    % check the range of tau values and truncate if necessary
-    % find halfway point of time record
-    halftime = round(tmstep*length(data.freq)/2);
-    % truncate tau to appropriate values
-    tau = tau(tau >= tmstep & tau <= halftime);
-    if verbose >= 2, fprintf(1, 'allan_modified: allowable tau range: %g to %g sec. (1/rate to total_time/2)\n',tmstep,halftime); end
+	
+	% check the range of tau values and truncate if necessary
+	% find halfway point of time record
+	halftime = round(tmstep*length(data.freq)/2);
+	% truncate tau to appropriate values
+	tau = tau(tau >= tmstep & tau <= halftime);
+	if verbose >= 2, fprintf(1, 'allan_modified: allowable tau range: %g to %g sec. (1/rate to total_time/2)\n',tmstep,halftime); end
  
-    % find the number of data points in each tau group
-    % number of samples
-    N=length(dphase);
-    m = data.rate.*tau;
-    % only integer values allowed (no fractional groups of points)
-    %tau = tau(m-round(m)<1e-8); % numerical precision issues (v1.1)
-    tau = tau(m==round(m));  % The round() test is only correct for values < 2^53
-    %m = m(m-round(m)<1e-8); % change to round(m) for integer test v1.22
-    m = m(m==round(m));
-    %m=round(m);
-    
-    if verbose >= 1, fprintf(1,'allan_modified: calculating modified Allan deviation...\n       '); end
-    
-    
-    % calculate the modified Allan deviation for each value of tau
-    k=0; tic;
-    for i = tau
-        k=k+1;
-        pa=[];
-        if verbose >= 2, fprintf(1,'%d ',i); end
-        
-        mphase = dphase;
-            
-        % calculate overlapping "phase averages" (x_k)
-        for p=1:m(k)
-            
-            % truncate frequency set length to an even multiple of this tau value
-            mphase=mphase(1:end-rem(length(mphase),m(k)));
-            % group phase values
-            mp=reshape(mphase,m(k),[]);
-            % find average in each "tau group" (each column of mp)
-            pa(p,:)=mean(mp,1);
-            % shift data vector by -1 and repeat
-            mphase=circshift(dphase,(size(dphase)>1)*-p);
-            
-        end
-            
-        % create "modified" y_k freq values
-        mfreq=diff(pa,1,2)./i;
-        mfreq=reshape(mfreq,1,[]);
-        
-        % calculate modified frequency differences
-        mfreqd=reshape(mfreq,m(k),[]); % Vectorize!
-        mfreqd=diff(mfreqd,1,2);
-        mfreqd=reshape(mfreqd,1,[]);
-        
-       
-        % calculate two-sample variance for this tau
-        sm(k)=sqrt((1/(2*(N-3*m(k)+1)))*(sum(mfreqd(1:N-3*m(k)+1).^2)));
+	% find the number of data points in each tau group
+	% number of samples
+	N=length(dphase);
+	m = data.rate.*tau;
+	% only integer values allowed (no fractional groups of points)
+	%tau = tau(m-round(m)<1e-8); % numerical precision issues (v1.1)
+	tau = tau(m==round(m));  % The round() test is only correct for values < 2^53
+	%m = m(m-round(m)<1e-8); % change to round(m) for integer test v1.22
+	m = m(m==round(m));
+	%m=round(m);
+	
+	if verbose >= 1, fprintf(1,'allan_modified: calculating modified Allan deviation...\n	   '); end
+	
+	
+	% calculate the modified Allan deviation for each value of tau
+	k=0; tic;
+	for i = tau
+		k=k+1;
+		pa=[];
+		if verbose >= 2, fprintf(1,'%d ',i); end
+		
+		mphase = dphase;
+			
+		% calculate overlapping "phase averages" (x_k)
+		for p=1:m(k)
+			
+			% truncate frequency set length to an even multiple of this tau value
+			mphase=mphase(1:end-rem(length(mphase),m(k)));
+			% group phase values
+			mp=reshape(mphase,m(k),[]);
+			% find average in each "tau group" (each column of mp)
+			pa(p,:)=mean(mp,1);
+			% shift data vector by -1 and repeat
+			mphase=circshift(dphase,(size(dphase)>1)*-p);
+			
+		end
+			
+		% create "modified" y_k freq values
+		mfreq=diff(pa,1,2)./i;
+		mfreq=reshape(mfreq,1,[]);
+		
+		% calculate modified frequency differences
+		mfreqd=reshape(mfreq,m(k),[]); % Vectorize!
+		mfreqd=diff(mfreqd,1,2);
+		mfreqd=reshape(mfreqd,1,[]);
+		
+	   
+		% calculate two-sample variance for this tau
+		sm(k)=sqrt((1/(2*(N-3*m(k)+1)))*(sum(mfreqd(1:N-3*m(k)+1).^2)));
  
-        % estimate error bars
-        sme(k)=sm(k)/sqrt(N-3*m(k)+1);
+		% estimate error bars
+		sme(k)=sm(k)/sqrt(N-3*m(k)+1);
  
-        
-    end % repeat for each value of tau
-    
-    if verbose >= 2, fprintf(1,'\n'); end
-    calctime=toc; if verbose >= 2, fprintf(1,'allan_modified: Elapsed time for calculation: %g seconds\n',calctime); end
+		
+	end % repeat for each value of tau
+	
+	if verbose >= 2, fprintf(1,'\n'); end
+	calctime=toc; if verbose >= 2, fprintf(1,'allan_modified: Elapsed time for calculation: %g seconds\n',calctime); end
  
-       
-    
+	   
+	
 %% Irregular data (timestamp)   
 elseif isfield(data,'time')
-    % the interval between measurements is irregular
-    %  so we must group the data by time
-    if verbose >= 1, fprintf(1, 'allan_modified: irregular rate data (no fixed sample rate)\n'); end
-    
-    % string for plot title
-    name=[name ' (timestamp)'];
-    
-    % adjust time to remove any initial offset
-    dtime=data.time-data.time(1)+mean(diff(data.time));
-    %dtime=data.time-data.time(1);
-    % where is the maximum gap in time record?
-    gap_pos=find(diff(dtime)==max(diff(dtime)));
-    % what is average data spacing?
-    avg_gap = mean(diff(dtime));
-    
-    if verbose >= 2
-        fprintf(1, 'allan_modified: WARNING: irregular timestamp data (no fixed sample rate).\n');
-        fprintf(1, '       Calculation time may be long and the results subject to interpretation.\n');
-        fprintf(1, '       You are advised to estimate using an average sample rate (%g Hz) instead of timestamps.\n',1/avg_gap);
-        fprintf(1, '       Continue at your own risk! (press any key to continue)\n');
-        pause;
-    end
-    
-    if verbose >= 1
-        fprintf(1, 'allan_modified: End of timestamp data: %g sec\n',dtime(end));
-    	fprintf(1, '       Average sample rate: %g Hz (%g sec/measurement)\n',1/avg_gap,avg_gap);
-        if max(diff(dtime)) ~= 1/mean(diff(dtime))
-            fprintf(1, '       Max. gap in time record: %g sec at position %d\n',max(diff(dtime)),gap_pos(1));
-        end
-        if max(diff(dtime)) > 5*avg_gap
-            fprintf(1, '       WARNING: Max. gap in time record is suspiciously large (>5x the average interval).\n');
-        end
-    end
+	% the interval between measurements is irregular
+	%  so we must group the data by time
+	if verbose >= 1, fprintf(1, 'allan_modified: irregular rate data (no fixed sample rate)\n'); end
+	
+	% string for plot title
+	name=[name ' (timestamp)'];
+	
+	% adjust time to remove any initial offset
+	dtime=data.time-data.time(1)+mean(diff(data.time));
+	%dtime=data.time-data.time(1);
+	% where is the maximum gap in time record?
+	gap_pos=find(diff(dtime)==max(diff(dtime)));
+	% what is average data spacing?
+	avg_gap = mean(diff(dtime));
+	
+	if verbose >= 2
+		fprintf(1, 'allan_modified: WARNING: irregular timestamp data (no fixed sample rate).\n');
+		fprintf(1, '	   Calculation time may be long and the results subject to interpretation.\n');
+		fprintf(1, '	   You are advised to estimate using an average sample rate (%g Hz) instead of timestamps.\n',1/avg_gap);
+		fprintf(1, '	   Continue at your own risk! (press any key to continue)\n');
+		pause;
+	end
+	
+	if verbose >= 1
+		fprintf(1, 'allan_modified: End of timestamp data: %g sec\n',dtime(end));
+		fprintf(1, '	   Average sample rate: %g Hz (%g sec/measurement)\n',1/avg_gap,avg_gap);
+		if max(diff(dtime)) ~= 1/mean(diff(dtime))
+			fprintf(1, '	   Max. gap in time record: %g sec at position %d\n',max(diff(dtime)),gap_pos(1));
+		end
+		if max(diff(dtime)) > 5*avg_gap
+			fprintf(1, '	   WARNING: Max. gap in time record is suspiciously large (>5x the average interval).\n');
+		end
+	end
  
-    % is phase data present? If not, generate it
-    if ~isfield(data,'phase')
-        nfreq=data.freq-s.mean;
-        % NOTE: uncommenting the following two lines will artificially
-        % allow the code to give equivalent results for validation data
-        % sets using fixed rate data and timestamped data by adding a
-        % "phantom" data point for frequency integration. Use of this
-        % phantom point can skew the results of calculations on real data.
-        %nfreq(end+1)=0; % phantom freq point, with average value
-        %dtime(end+1)=dtime(end)+avg_gap; % phantom average time step
-        dphase=zeros(1,length(nfreq));
-        dphase(2:end) = cumsum(nfreq(1:end-1)).*diff(dtime);
-        if verbose >= 1, fprintf(1,'allan_modified: Phase data generated from fractional frequency data (N=%g).\n',length(dphase)); end
-    else
-        dphase=data.phase;
-    end
+	% is phase data present? If not, generate it
+	if ~isfield(data,'phase')
+		nfreq=data.freq-s.mean;
+		% NOTE: uncommenting the following two lines will artificially
+		% allow the code to give equivalent results for validation data
+		% sets using fixed rate data and timestamped data by adding a
+		% "phantom" data point for frequency integration. Use of this
+		% phantom point can skew the results of calculations on real data.
+		%nfreq(end+1)=0; % phantom freq point, with average value
+		%dtime(end+1)=dtime(end)+avg_gap; % phantom average time step
+		dphase=zeros(1,length(nfreq));
+		dphase(2:end) = cumsum(nfreq(1:end-1)).*diff(dtime);
+		if verbose >= 1, fprintf(1,'allan_modified: Phase data generated from fractional frequency data (N=%g).\n',length(dphase)); end
+	else
+		dphase=data.phase;
+	end
  
-    % find halfway point
-    halftime = fix(dtime(end)/2);
-    % truncate tau to appropriate values
-    tau = tau(tau >= max(diff(dtime)) & tau <= halftime);
-    if isempty(tau)
-        error('allan_modified: ERROR: no appropriate tau values (> %g s, < %g s)\n',max(diff(dtime)),halftime);
-    end
+	% find halfway point
+	halftime = fix(dtime(end)/2);
+	% truncate tau to appropriate values
+	tau = tau(tau >= max(diff(dtime)) & tau <= halftime);
+	if isempty(tau)
+		error('allan_modified: ERROR: no appropriate tau values (> %g s, < %g s)\n',max(diff(dtime)),halftime);
+	end
  
-%     % save the freq data for the loop
-%     dfreq=data.freq;
-    
-    % number of samples
-    N=length(dphase);
-    m=round(tau./mean(diff(dtime)));
-    
-    if verbose >= 1, fprintf(1,'allan_modified: calculating modified Allan deviation...\n'); end
+%	 % save the freq data for the loop
+%	 dfreq=data.freq;
+	
+	% number of samples
+	N=length(dphase);
+	m=round(tau./mean(diff(dtime)));
+	
+	if verbose >= 1, fprintf(1,'allan_modified: calculating modified Allan deviation...\n'); end
  
-    k=0; tic;
-    for i = tau
-        
-        k=k+1; pa=[];
-        
-        mphase = dphase; time = dtime;
+	k=0; tic;
+	for i = tau
+		
+		k=k+1; pa=[];
+		
+		mphase = dphase; time = dtime;
  
-        if verbose >= 2, fprintf(1,'%d ',i); end
-        
-        % calculate overlapping "phase averages" (x_k)
-        %for j = 1:i
-        for j = 1:m(k) % (v1.1)
-            km=0;
-            %fprintf(1,'j: %d ',j);
-            
-            % (v1.1) truncating not correct for overlapping samples
-            % truncate data set to an even multiple of this tau value
-            %mphase = mphase(time <= time(end)-rem(time(end),i));
-            %time = time(time <= time(end)-rem(time(end),i));
-            
-        
-            % break up the data into overlapping groups of tau length
-            while i*km < time(end)
-                km=km+1;
+		if verbose >= 2, fprintf(1,'%d ',i); end
+		
+		% calculate overlapping "phase averages" (x_k)
+		%for j = 1:i
+		for j = 1:m(k) % (v1.1)
+			km=0;
+			%fprintf(1,'j: %d ',j);
+			
+			% (v1.1) truncating not correct for overlapping samples
+			% truncate data set to an even multiple of this tau value
+			%mphase = mphase(time <= time(end)-rem(time(end),i));
+			%time = time(time <= time(end)-rem(time(end),i));
+			
+		
+			% break up the data into overlapping groups of tau length
+			while i*km < time(end)
+				km=km+1;
  
-                % progress bar
-                if verbose >= 2
-                    if rem(km,100)==0, fprintf(1,'.'); end
-                    if rem(km,1000)==0, fprintf(1,'%g/%g\n',km,round(time(end)/i)); end
-                end
+				% progress bar
+				if verbose >= 2
+					if rem(km,100)==0, fprintf(1,'.'); end
+					if rem(km,1000)==0, fprintf(1,'%g/%g\n',km,round(time(end)/i)); end
+				end
  
-                mp = mphase(i*(km-1) < (time) & (time) <= i*km);
+				mp = mphase(i*(km-1) < (time) & (time) <= i*km);
  
-                if ~isempty(mp)
-                    pa(j,km)=mean(mp);
-                else
-                    pa(j,km)=0;
-                end
+				if ~isempty(mp)
+					pa(j,km)=mean(mp);
+				else
+					pa(j,km)=0;
+				end
  
-            end
-                        
-            % shift data vector by -1 and repeat
-            mphase=circshift(dphase,(size(mphase)>1)*-j);
-            mphase(end-j+1:end)=[];
-            time=circshift(dtime,(size(time)>1)*-j);
-            time(end-j+1:end)=[];
-            time=time-time(1)+avg_gap; % remove time offset
-            
-        end        
+			end
+						
+			% shift data vector by -1 and repeat
+			mphase=circshift(dphase,(size(mphase)>1)*-j);
+			mphase(end-j+1:end)=[];
+			time=circshift(dtime,(size(time)>1)*-j);
+			time(end-j+1:end)=[];
+			time=time-time(1)+avg_gap; % remove time offset
+			
+		end		
  
-        % create "modified" y_k freq values
-        mfreq=diff(pa,1,2)./i;
-        mfreq=reshape(mfreq,1,[]);
-        
-        % calculate modified frequency differences
-        mfreqd=reshape(mfreq,m(k),[]); % Vectorize!
-        mfreqd=diff(mfreqd,1,2);
-        mfreqd=reshape(mfreqd,1,[]);
+		% create "modified" y_k freq values
+		mfreq=diff(pa,1,2)./i;
+		mfreq=reshape(mfreq,1,[]);
+		
+		% calculate modified frequency differences
+		mfreqd=reshape(mfreq,m(k),[]); % Vectorize!
+		mfreqd=diff(mfreqd,1,2);
+		mfreqd=reshape(mfreqd,1,[]);
  
-        % calculate two-sample variance for this tau
-        %  only the first N-3*m(k)+1 samples are valid
-        if length(mfreqd) >= N-3*m(k)+1
-            sm(k)=sqrt((1/(2*(N-3*m(k)+1)))*(sum(mfreqd(1:N-3*m(k)+1).^2)));
+		% calculate two-sample variance for this tau
+		%  only the first N-3*m(k)+1 samples are valid
+		if length(mfreqd) >= N-3*m(k)+1
+			sm(k)=sqrt((1/(2*(N-3*m(k)+1)))*(sum(mfreqd(1:N-3*m(k)+1).^2)));
  
-            % estimate error bars
-            sme(k)=sm(k)/sqrt(N);
-            
-            if verbose >= 2, fprintf(1,'\n'); end
-        else
-            if verbose >=2, fprintf(1,' tau=%g dropped due to timestamp irregularities\n',tau(k)); end
-            sm(k)=0; sme(k)=0;
-        end            
-        
+			% estimate error bars
+			sme(k)=sm(k)/sqrt(N);
+			
+			if verbose >= 2, fprintf(1,'\n'); end
+		else
+			if verbose >=2, fprintf(1,' tau=%g dropped due to timestamp irregularities\n',tau(k)); end
+			sm(k)=0; sme(k)=0;
+		end			
+		
  
-    end
+	end
  
-    if verbose >= 2, fprintf(1,'\n'); end
-    calctime=toc; if verbose >= 2, fprintf(1,'allan_modified: Elapsed time for calculation: %g seconds\n',calctime); end
-    
-    % remove any points that were dropped
-    tau(sm==0)=[];
-    sm(sm==0)=[];
-    sme(sme==0)=[];
-    
-    % modify time vector for plotting
-    dtime=dtime(1:length(medianfreq));
+	if verbose >= 2, fprintf(1,'\n'); end
+	calctime=toc; if verbose >= 2, fprintf(1,'allan_modified: Elapsed time for calculation: %g seconds\n',calctime); end
+	
+	% remove any points that were dropped
+	tau(sm==0)=[];
+	sm(sm==0)=[];
+	sme(sme==0)=[];
+	
+	% modify time vector for plotting
+	dtime=dtime(1:length(medianfreq));
  
 else
-    error('allan_modified: WARNING: no DATA.rate or DATA.time! Type "help allan_modified" for more information. [err2]');
+	error('allan_modified: WARNING: no DATA.rate or DATA.time! Type "help allan_modified" for more information. [err2]');
 end
  
  
  
@@ -478,41 +478,41 @@
 %% Plotting
  
 if verbose >= 2 % show all data
-    
-    % plot the frequency data, centered on median
-    if size(dtime,2) > size(dtime,1), dtime=dtime'; end % this should not be necessary, but dsplot 1.1 is a little bit brittle
-    try
-        % dsplot makes a new figure
-        hd=dsplot(dtime,medianfreq);
-    catch ME
-        figure;
-        hd=plot(dtime,medianfreq);
-        if verbose >= 1, fprintf(1,'allan_modified: Note: Install dsplot.m for improved plotting of large data sets (File Exchange File ID: #15850).\n'); end
-        if verbose >= 2, fprintf(1,'             (Message: %s)\n',ME.message); end
-    end
-    set(hd,'Marker','.','LineStyle','none','Color','b'); % equivalent to '.-'
-    hold on;
+	
+	% plot the frequency data, centered on median
+	if size(dtime,2) > size(dtime,1), dtime=dtime'; end % this should not be necessary, but dsplot 1.1 is a little bit brittle
+	try
+		% dsplot makes a new figure
+		hd=dsplot(dtime,medianfreq);
+	catch ME
+		figure;
+		hd=plot(dtime,medianfreq);
+		if verbose >= 1, fprintf(1,'allan_modified: Note: Install dsplot.m for improved plotting of large data sets (File Exchange File ID: #15850).\n'); end
+		if verbose >= 2, fprintf(1,'			 (Message: %s)\n',ME.message); end
+	end
+	set(hd,'Marker','.','LineStyle','none','Color','b'); % equivalent to '.-'
+	hold on;
  
-    fx = xlim;
-    % plot([fx(1) fx(2)],[s.median s.median],'-k');
-    plot([fx(1) fx(2)],[0 0],':k');
-    % show 5x Median Absolute deviation (MAD) values
-    hm=plot([fx(1) fx(2)],[5*MAD 5*MAD],'-r');
-    plot([fx(1) fx(2)],[-5*MAD -5*MAD],'-r');
-    % show linear fit line
-    hf=plot(xlim,polyval(s.linear,xlim)-s.median,'-g');    
-    title(['Data: ' name],'FontSize',FontSize+2,'FontName',FontName);
-    %set(get(gca,'Title'),'Interpreter','none');
-    xlabel('Time [sec]','FontSize',FontSize,'FontName',FontName);
-    if isfield(data,'units')
-        ylabel(['data - median(data) [' data.units ']'],'FontSize',FontSize,'FontName',FontName);
-    else
-        ylabel('freq - median(freq)','FontSize',FontSize,'FontName',FontName);
-    end
-    set(gca,'FontSize',FontSize,'FontName',FontName);
-    legend([hd hm hf],{'data (centered on median)','5x MAD outliers',['Linear Fit (' num2str(s.linear(1),'%g') ')']},'FontSize',max(10,FontSize-2));
-    % tighten up
-    xlim([dtime(1) dtime(end)]);
+	fx = xlim;
+	% plot([fx(1) fx(2)],[s.median s.median],'-k');
+	plot([fx(1) fx(2)],[0 0],':k');
+	% show 5x Median Absolute deviation (MAD) values
+	hm=plot([fx(1) fx(2)],[5*MAD 5*MAD],'-r');
+	plot([fx(1) fx(2)],[-5*MAD -5*MAD],'-r');
+	% show linear fit line
+	hf=plot(xlim,polyval(s.linear,xlim)-s.median,'-g');	
+	title(['Data: ' name],'FontSize',FontSize+2,'FontName',FontName);
+	%set(get(gca,'Title'),'Interpreter','none');
+	xlabel('Time [sec]','FontSize',FontSize,'FontName',FontName);
+	if isfield(data,'units')
+		ylabel(['data - median(data) [' data.units ']'],'FontSize',FontSize,'FontName',FontName);
+	else
+		ylabel('freq - median(freq)','FontSize',FontSize,'FontName',FontName);
+	end
+	set(gca,'FontSize',FontSize,'FontName',FontName);
+	legend([hd hm hf],{'data (centered on median)','5x MAD outliers',['Linear Fit (' num2str(s.linear(1),'%g') ')']},'FontSize',max(10,FontSize-2));
+	% tighten up
+	xlim([dtime(1) dtime(end)]);
  
  
 end % end plot raw data
  
  
  
  
@@ -520,41 +520,41 @@
  
 if verbose >= 1 % show analysis results
  
-    % plot Allan deviation results
-    if ~isempty(sm)
-        figure
+	% plot Allan deviation results
+	if ~isempty(sm)
+		figure
  
-        % Choose loglog or semilogx plot here    #PLOTLOG
-        %semilogx(tau,sm,'.-b','LineWidth',plotlinewidth,'MarkerSize',24);
-        loglog(tau,sm,'.-b','LineWidth',plotlinewidth,'MarkerSize',24);
+		% Choose loglog or semilogx plot here	#PLOTLOG
+		%semilogx(tau,sm,'.-b','LineWidth',plotlinewidth,'MarkerSize',24);
+		loglog(tau,sm,'.-b','LineWidth',plotlinewidth,'MarkerSize',24);
  
-        % in R14SP3, there is a bug that screws up the error bars on a semilog plot.
-        %  When this is fixed, uncomment below to use normal errorbars
-        %errorbar(tau,sm,sme,'.-b'); set(gca,'XScale','log');
-        % this is a hack to approximate the error bars
-        hold on; plot([tau; tau],[sm+sme; sm-sme],'-k','LineWidth',max(plotlinewidth-1,2));
+		% in R14SP3, there is a bug that screws up the error bars on a semilog plot.
+		%  When this is fixed, uncomment below to use normal errorbars
+		%errorbar(tau,sm,sme,'.-b'); set(gca,'XScale','log');
+		% this is a hack to approximate the error bars
+		hold on; plot([tau; tau],[sm+sme; sm-sme],'-k','LineWidth',max(plotlinewidth-1,2));
  
-        grid on;
-        title(['Modified Allan Deviation: ' name],'FontSize',FontSize+2,'FontName',FontName);
-        %set(get(gca,'Title'),'Interpreter','none');
-        xlabel('\tau [sec]','FontSize',FontSize,'FontName',FontName);
-        ylabel('Modified \sigma_y(\tau)','FontSize',FontSize,'FontName',FontName);
-        set(gca,'FontSize',FontSize,'FontName',FontName);
-        % expand the x axis a little bit so that the errors bars look nice
-        adax = axis;
-        axis([adax(1)*0.9 adax(2)*1.1 adax(3) adax(4)]);
-        
-        % display the minimum value
-        fprintf(1,'allan: Minimum modified ADEV value: %g at tau = %g seconds\n',min(sm),tau(sm==min(sm)));        
-        
-    elseif verbose >= 1
-        fprintf(1,'allan_modified: WARNING: no values calculated.\n');
-        fprintf(1,'       Check that TAU > 1/DATA.rate and TAU values are divisible by 1/DATA.rate\n');
-        fprintf(1,'Type "help allan_modified" for more information.\n\n');
-    end
+		grid on;
+		title(['Modified Allan Deviation: ' name],'FontSize',FontSize+2,'FontName',FontName);
+		%set(get(gca,'Title'),'Interpreter','none');
+		xlabel('\tau [sec]','FontSize',FontSize,'FontName',FontName);
+		ylabel('Modified \sigma_y(\tau)','FontSize',FontSize,'FontName',FontName);
+		set(gca,'FontSize',FontSize,'FontName',FontName);
+		% expand the x axis a little bit so that the errors bars look nice
+		adax = axis;
+		axis([adax(1)*0.9 adax(2)*1.1 adax(3) adax(4)]);
+		
+		% display the minimum value
+		fprintf(1,'allan: Minimum modified ADEV value: %g at tau = %g seconds\n',min(sm),tau(sm==min(sm)));		
+		
+	elseif verbose >= 1
+		fprintf(1,'allan_modified: WARNING: no values calculated.\n');
+		fprintf(1,'	   Check that TAU > 1/DATA.rate and TAU values are divisible by 1/DATA.rate\n');
+		fprintf(1,'Type "help allan_modified" for more information.\n\n');
+	end
  
 end % end plot analysis
-        
+		
 retval = sm;
 errorb = sme;
  
@@ -6,24 +6,24 @@
 % Inputs:
 % DATA should be a struct and have the following fields:
 %  DATA.freq or DATA.phase
-%               A vector of fractional frequency measurements (df/f) in
-%               DATA.freq *or* phase offset data (seconds) in DATA.phase
-%               If phase data is not present, it will be generated by
-%                integrating the fractional frequency data.
-%               If both fields are present, then DATA.phase will be used.
+%			   A vector of fractional frequency measurements (df/f) in
+%			   DATA.freq *or* phase offset data (seconds) in DATA.phase
+%			   If phase data is not present, it will be generated by
+%				integrating the fractional frequency data.
+%			   If both fields are present, then DATA.phase will be used.
 %
 %  DATA.rate or DATA.time
-%               The sampling rate in Hertz (DATA.rate) or a vector of
-%                timestamps for each measurement in seconds (DATA.time).
-%               DATA.rate is used if both fields are present.
-%               If DATA.rate == 0, then the timestamps are used.
+%			   The sampling rate in Hertz (DATA.rate) or a vector of
+%				timestamps for each measurement in seconds (DATA.time).
+%			   DATA.rate is used if both fields are present.
+%			   If DATA.rate == 0, then the timestamps are used.
 %
 % TAU is an array of tau values for computing Allan deviation.
-%     TAU values must be divisible by 1/DATA.rate (data points cannot be
-%     grouped in fractional quantities!). Invalid values are ignored.
+%	 TAU values must be divisible by 1/DATA.rate (data points cannot be
+%	 grouped in fractional quantities!). Invalid values are ignored.
 % NAME is an optional label that is added to the plot titles.
 % VERBOSE sets the level of status messages:
-%     0 = silent & no data plots; 1 = status messages; 2 = all messages 
+%	 0 = silent & no data plots; 1 = status messages; 2 = all messages 
 %
 % Outputs:
 % RETVAL is the array of overlapping Allan deviation values at each TAU.
@@ -38,8 +38,8 @@
 % To compute the overlapping Allan deviation for the data in the variable "lt":
 % >> lt
 % lt = 
-%     freq: [1x86400 double]
-%     rate: 0.5
+%	 freq: [1x86400 double]
+%	 rate: 0.5
 %
 % Use:
 %
  
  
  
  
  
@@ -89,34 +89,34 @@
 %
 %
 % M.A. Hopcroft
-%      mhopeng at gmail dot com
+%	  mhopeng at gmail dot com
 %
 % I welcome your comments and feedback!
 %
 % MH Mar2014
 % v2.24 fix bug related to generating freq data from phase with timestamps
-%       (thanks to S. David-Grignot for finding the bug)
+%	   (thanks to S. David-Grignot for finding the bug)
 % MH Oct2010
 % v2.22 tau truncation to integer groups; tau sort
-%       plotting bugfix
+%	   plotting bugfix
 % v2.20 update to match allan.m (dsplot.m, columns)
-%       discard tau values with timestamp irregularities
+%	   discard tau values with timestamp irregularities
  
 versionstr = 'allan_overlap v2.24';
  
 %
 % MH MAR2010
 % v2.1  bugfixes for irregular sample rates
-%        (thanks to Ryad Ben-El-Kezadri for feedback and testing)
-%       handle empty rate field
-%       fix integer comparisons for fractional sample rates
-%       update consistency check
+%		(thanks to Ryad Ben-El-Kezadri for feedback and testing)
+%	   handle empty rate field
+%	   fix integer comparisons for fractional sample rates
+%	   update consistency check
 %
 % MH FEB2010
 % v2.0  use phase data for calculation- much faster
-%       Consistent code behaviour for all "allan_x.m" functions:
-%       accept phase data
-%       verbose levels
+%	   Consistent code behaviour for all "allan_x.m" functions:
+%	   accept phase data
+%	   verbose levels
 %
 % MH JAN2010
 % v1.0  based on allan v1.84
  
@@ -140,25 +140,25 @@
  
 %% Data consistency checks v2.1
 if ~(isfield(data,'phase') || isfield(data,'freq'))
-    error('Either ''phase'' or ''freq'' must be present in DATA. See help file for details. [con0]');
+	error('Either ''phase'' or ''freq'' must be present in DATA. See help file for details. [con0]');
 end
 if isfield(data,'time')
-    if isfield(data,'phase') && (length(data.phase) ~= length(data.time))
-        if isfield(data,'freq') && (length(data.freq) ~= length(data.time))
-            error('The time and freq vectors are not the same length. See help for details. [con2]');
-        else
-            error('The time and phase vectors are not the same length. See help for details. [con1]');
-        end
-    end
-    if isfield(data,'phase') && (any(isnan(data.phase)) || any(isinf(data.phase)))
-        error('The phase vector contains invalid elements (NaN/Inf). [con3]');
-    end
-    if isfield(data,'freq') && (any(isnan(data.freq)) || any(isinf(data.freq)))
-        error('The freq vector contains invalid elements (NaN/Inf). [con4]');
-    end
-    if isfield(data,'time') && (any(isnan(data.time)) || any(isinf(data.time)))
-        error('The time vector contains invalid elements (NaN/Inf). [con5]');
-    end
+	if isfield(data,'phase') && (length(data.phase) ~= length(data.time))
+		if isfield(data,'freq') && (length(data.freq) ~= length(data.time))
+			error('The time and freq vectors are not the same length. See help for details. [con2]');
+		else
+			error('The time and phase vectors are not the same length. See help for details. [con1]');
+		end
+	end
+	if isfield(data,'phase') && (any(isnan(data.phase)) || any(isinf(data.phase)))
+		error('The phase vector contains invalid elements (NaN/Inf). [con3]');
+	end
+	if isfield(data,'freq') && (any(isnan(data.freq)) || any(isinf(data.freq)))
+		error('The freq vector contains invalid elements (NaN/Inf). [con4]');
+	end
+	if isfield(data,'time') && (any(isnan(data.time)) || any(isinf(data.time)))
+		error('The time vector contains invalid elements (NaN/Inf). [con5]');
+	end
 end
  
 % sort tau vector
  
  
  
  
  
@@ -166,33 +166,33 @@
  
 %% Basic statistical tests on the data set
 if ~isfield(data,'freq')
-    if isfield(data,'rate') && data.rate ~= 0
-        data.freq=diff(data.phase).*data.rate;
-    elseif isfield(data,'time')
-        data.freq=diff(data.phase)./diff(data.time);
-    end
-    if verbose >= 1, fprintf(1,'allan_overlap: Fractional frequency data generated from phase data (M=%g).\n',length(data.freq)); end
+	if isfield(data,'rate') && data.rate ~= 0
+		data.freq=diff(data.phase).*data.rate;
+	elseif isfield(data,'time')
+		data.freq=diff(data.phase)./diff(data.time);
+	end
+	if verbose >= 1, fprintf(1,'allan_overlap: Fractional frequency data generated from phase data (M=%g).\n',length(data.freq)); end
 end
 if size(data.freq,2) > size(data.freq,1), data.freq=data.freq'; end % ensure columns
-    
+	
 s.numpoints=length(data.freq);
 s.max=max(data.freq);
 s.min=min(data.freq);
 s.mean=mean(data.freq);
 s.median=median(data.freq);
 if isfield(data,'time')
-    if size(data.time,2) > size(data.time,1), data.time=data.time'; end % ensure columns
-    s.linear=polyfit(data.time(1:length(data.freq)),data.freq,1);
+	if size(data.time,2) > size(data.time,1), data.time=data.time'; end % ensure columns
+	s.linear=polyfit(data.time(1:length(data.freq)),data.freq,1);
 elseif isfield(data,'rate') && data.rate ~= 0;
-    s.linear=polyfit((1/data.rate:1/data.rate:length(data.freq)/data.rate)',data.freq,1);
+	s.linear=polyfit((1/data.rate:1/data.rate:length(data.freq)/data.rate)',data.freq,1);
 else
-    error('Either "time" or "rate" must be present in DATA. Type "help allan_overlap" for details. [err1]');
+	error('Either "time" or "rate" must be present in DATA. Type "help allan_overlap" for details. [err1]');
 end
 s.std=std(data.freq);
  
 if verbose >= 2
-    fprintf(1,'allan_overlap: fractional frequency data statistics:\n');
-    disp(s);
+	fprintf(1,'allan_overlap: fractional frequency data statistics:\n');
+	disp(s);
 end
  
  
@@ -203,7 +203,7 @@
 % Screen for outliers using 5x Median Absolute Deviation (MAD) criteria
 MAD = median(abs(medianfreq)/0.6745);
 if verbose >= 1 && any(abs(medianfreq) > 5*MAD)
-    fprintf(1, 'allan_overlap: NOTE: There appear to be outliers in the frequency data. See plot.\n');
+	fprintf(1, 'allan_overlap: NOTE: There appear to be outliers in the frequency data. See plot.\n');
 end
  
 %%%%
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
@@ -213,250 +213,250 @@
 %   If there is a regular interval between measurements, calculation is much
 %   easier/faster
 if isfield(data,'rate') && data.rate > 0 % if data rate was given
-    if verbose >= 1
-        fprintf(1, 'allan_overlap: regular data ');
-        if isfield(data,'freq')
-            fprintf(1, '(%g freq data points @ %g Hz)\n',length(data.freq),data.rate);
-        elseif isfield(data,'phase')
-            fprintf(1, '(%g phase data points @ %g Hz)\n',length(data.phase),data.rate);
-        else
-            error('\n phase or freq data missing [err10]');
-        end
-    end
+	if verbose >= 1
+		fprintf(1, 'allan_overlap: regular data ');
+		if isfield(data,'freq')
+			fprintf(1, '(%g freq data points @ %g Hz)\n',length(data.freq),data.rate);
+		elseif isfield(data,'phase')
+			fprintf(1, '(%g phase data points @ %g Hz)\n',length(data.phase),data.rate);
+		else
+			error('\n phase or freq data missing [err10]');
+		end
+	end
  
-    % string for plot title
-    name=[name ' (' num2str(data.rate) ' Hz)'];
+	% string for plot title
+	name=[name ' (' num2str(data.rate) ' Hz)'];
  
-    % what is the time interval between data points?
-    tmstep = 1/data.rate;      
-    
-    % Is there time data? Just for curiosity/plotting, does not impact calculation
-    if isfield(data,'time')
-        % adjust time data to remove any starting gap; first time step
-        %  should not be zero for comparison with freq data
-        dtime=data.time-data.time(1)+mean(diff(data.time)); 
-        dtime=dtime(1:length(medianfreq)); % equalize the data vector lengths for plotting (v2.1)
-        if verbose >= 2
-            fprintf(1,'allan_overlap: End of timestamp data: %g sec.\n',dtime(end));
-            if (data.rate - 1/mean(diff(dtime))) > 1e-6
-                fprintf(1,'allan_overlap: NOTE: data.rate (%f Hz) does not match average timestamped sample rate (%f Hz)\n',data.rate,1/mean(diff(dtime)));
-            end
-        end
-    else
-        % create time axis data using rate (for plotting only)
-        dtime=(tmstep:tmstep:length(data.freq)*tmstep);
-    end
+	% what is the time interval between data points?
+	tmstep = 1/data.rate;	  
+	
+	% Is there time data? Just for curiosity/plotting, does not impact calculation
+	if isfield(data,'time')
+		% adjust time data to remove any starting gap; first time step
+		%  should not be zero for comparison with freq data
+		dtime=data.time-data.time(1)+mean(diff(data.time)); 
+		dtime=dtime(1:length(medianfreq)); % equalize the data vector lengths for plotting (v2.1)
+		if verbose >= 2
+			fprintf(1,'allan_overlap: End of timestamp data: %g sec.\n',dtime(end));
+			if (data.rate - 1/mean(diff(dtime))) > 1e-6
+				fprintf(1,'allan_overlap: NOTE: data.rate (%f Hz) does not match average timestamped sample rate (%f Hz)\n',data.rate,1/mean(diff(dtime)));
+			end
+		end
+	else
+		% create time axis data using rate (for plotting only)
+		dtime=(tmstep:tmstep:length(data.freq)*tmstep);
+	end
  
  
-    % is phase data present? If not, generate it
-    if ~isfield(data,'phase')
-        nfreq=data.freq-s.mean;
-        dphase=zeros(1,length(nfreq)+1);
-        dphase(2:end) = cumsum(nfreq)./data.rate;
-        if verbose >= 1, fprintf(1,'allan_overlap: phase data generated from fractional frequency data (N=%g).\n',length(dphase)); end
-    else
-        dphase=data.phase;
-    end
-    
-    % check the range of tau values and truncate if necessary
-    % find halfway point of time record
-    halftime = round(tmstep*length(data.freq)/2);
-    % truncate tau to appropriate values
-    tau = tau(tau >= tmstep & tau <= halftime);
-    if verbose >= 2, fprintf(1, 'allan_overlap: allowable tau range: %g to %g sec. (1/rate to total_time/2)\n',tmstep,halftime); end
-    
-    % number of samples
-    N=length(dphase);
-    % number of samples per tau period
-    m = data.rate.*tau;
-    % only integer values allowed for m (no fractional groups of points)
-    %tau = tau(m-round(m)<1e-8); % numerical precision issues (v2.1)
-    tau = tau(m==round(m));  % The round() test is only correct for values < 2^53
-    %m = m(m-round(m)<1e-8); % change to round(m) for integer test v2.22
-    m = m(m==round(m));
-    %m=round(m);
-    %fprintf(1,'m: %.50f\n',m)
-        
-    if verbose >= 1, fprintf(1,'allan_overlap: calculating overlapping Allan deviation...\n       '); end
-    
-    % calculate the Allan deviation for each value of tau
-    k=0; tic;
-    for i = tau
-        k=k+1;
-        if verbose >= 2, fprintf(1,'%d ',i); end
+	% is phase data present? If not, generate it
+	if ~isfield(data,'phase')
+		nfreq=data.freq-s.mean;
+		dphase=zeros(1,length(nfreq)+1);
+		dphase(2:end) = cumsum(nfreq)./data.rate;
+		if verbose >= 1, fprintf(1,'allan_overlap: phase data generated from fractional frequency data (N=%g).\n',length(dphase)); end
+	else
+		dphase=data.phase;
+	end
+	
+	% check the range of tau values and truncate if necessary
+	% find halfway point of time record
+	halftime = round(tmstep*length(data.freq)/2);
+	% truncate tau to appropriate values
+	tau = tau(tau >= tmstep & tau <= halftime);
+	if verbose >= 2, fprintf(1, 'allan_overlap: allowable tau range: %g to %g sec. (1/rate to total_time/2)\n',tmstep,halftime); end
+	
+	% number of samples
+	N=length(dphase);
+	% number of samples per tau period
+	m = data.rate.*tau;
+	% only integer values allowed for m (no fractional groups of points)
+	%tau = tau(m-round(m)<1e-8); % numerical precision issues (v2.1)
+	tau = tau(m==round(m));  % The round() test is only correct for values < 2^53
+	%m = m(m-round(m)<1e-8); % change to round(m) for integer test v2.22
+	m = m(m==round(m));
+	%m=round(m);
+	%fprintf(1,'m: %.50f\n',m)
+		
+	if verbose >= 1, fprintf(1,'allan_overlap: calculating overlapping Allan deviation...\n	   '); end
+	
+	% calculate the Allan deviation for each value of tau
+	k=0; tic;
+	for i = tau
+		k=k+1;
+		if verbose >= 2, fprintf(1,'%d ',i); end
  
  
-        % pad phase data set length to an even multiple of this tau value
-        mphase=zeros(ceil(length(dphase)./m(k))*m(k),1);
-        mphase(1:N)=dphase;
-        % group phase values
-        mp=reshape(mphase,m(k),[]);
-        % compute second differences of phase values (x_k+m - x_k)
-        md1=diff(mp,1,2);
-        md2=diff(md1,1,2);
-        md1=reshape(md2,1,[]);
-        
-        % compute overlapping ADEV from phase values
-        %  only the first N-2*m(k) samples are valid
-        sm(k)=sqrt((1/(2*(N-2*m(k))*i^2))*sum(md1(1:N-2*m(k)).^2));
-        
-        % estimate error bars
-        sme(k)=sm(k)/sqrt(N-2*m(k));
-        
+		% pad phase data set length to an even multiple of this tau value
+		mphase=zeros(ceil(length(dphase)./m(k))*m(k),1);
+		mphase(1:N)=dphase;
+		% group phase values
+		mp=reshape(mphase,m(k),[]);
+		% compute second differences of phase values (x_k+m - x_k)
+		md1=diff(mp,1,2);
+		md2=diff(md1,1,2);
+		md1=reshape(md2,1,[]);
+		
+		% compute overlapping ADEV from phase values
+		%  only the first N-2*m(k) samples are valid
+		sm(k)=sqrt((1/(2*(N-2*m(k))*i^2))*sum(md1(1:N-2*m(k)).^2));
+		
+		% estimate error bars
+		sme(k)=sm(k)/sqrt(N-2*m(k));
+		
  
-    end % repeat for each value of tau
-    
-    if verbose >= 2, fprintf(1,'\n'); end
-    calctime=toc; if verbose >= 2, fprintf(1,'allan_overlap: Elapsed time for calculation: %g seconds\n',calctime); end
+	end % repeat for each value of tau
+	
+	if verbose >= 2, fprintf(1,'\n'); end
+	calctime=toc; if verbose >= 2, fprintf(1,'allan_overlap: Elapsed time for calculation: %g seconds\n',calctime); end
  
-        
-    
-%% Irregular data, no fixed interval    
+		
+	
+%% Irregular data, no fixed interval	
 elseif isfield(data,'time')
-    % the interval between measurements is irregular
-    %  so we must group the data by time
-    if verbose >= 1, fprintf(1, 'allan_overlap: irregular rate data (no fixed sample rate)\n'); end
+	% the interval between measurements is irregular
+	%  so we must group the data by time
+	if verbose >= 1, fprintf(1, 'allan_overlap: irregular rate data (no fixed sample rate)\n'); end
  
-    
-    % string for plot title
-    name=[name ' (timestamp)'];
-    
+	
+	% string for plot title
+	name=[name ' (timestamp)'];
+	
  
-    % adjust time to remove any starting offset
-    dtime=data.time-data.time(1)+mean(diff(data.time));
-    
-    % save the freq data for the loop
-    dfreq=data.freq;
-    dtime=dtime(1:length(dfreq));
-    
-    dfdtime=diff(dtime); % only need to do this once (v2.1)
-    % where is the maximum gap in time record?
-    gap_pos=find(dfdtime==max(dfdtime));
-    % what is average data spacing?
-    avg_gap = mean(dfdtime);
-    s.avg_rate = 1/avg_gap; % save avg rate for user (v2.1)
-    
-    if verbose >= 2
-        fprintf(1, 'allan_overlap: WARNING: irregular timestamp data (no fixed sample rate).\n');
-        fprintf(1, '       Calculation time may be long and the results subject to interpretation.\n');
-        fprintf(1, '       You are advised to estimate using an average sample rate (%g Hz) instead of timestamps.\n',1/avg_gap);
-        fprintf(1, '       Continue at your own risk! (press any key to continue)\n');
-        pause;
-    end
-    
-    if verbose >= 1
-        fprintf(1, 'allan_overlap: End of timestamp data: %g sec\n',dtime(end));
-    	fprintf(1, '       Average rate: %g Hz (%g sec/measurement)\n',1/avg_gap,avg_gap);
-        if max(diff(dtime)) ~= 1/mean(diff(dtime))
-            fprintf(1, '       Max. gap in time record: %g sec at position %d\n',max(dfdtime),gap_pos(1));
-        end
-        if max(diff(dtime)) > 5*avg_gap
-            fprintf(1, '       WARNING: Max. gap in time record is suspiciously large (>5x the average interval).\n');
-        end
-    end
-    
+	% adjust time to remove any starting offset
+	dtime=data.time-data.time(1)+mean(diff(data.time));
+	
+	% save the freq data for the loop
+	dfreq=data.freq;
+	dtime=dtime(1:length(dfreq));
+	
+	dfdtime=diff(dtime); % only need to do this once (v2.1)
+	% where is the maximum gap in time record?
+	gap_pos=find(dfdtime==max(dfdtime));
+	% what is average data spacing?
+	avg_gap = mean(dfdtime);
+	s.avg_rate = 1/avg_gap; % save avg rate for user (v2.1)
+	
+	if verbose >= 2
+		fprintf(1, 'allan_overlap: WARNING: irregular timestamp data (no fixed sample rate).\n');
+		fprintf(1, '	   Calculation time may be long and the results subject to interpretation.\n');
+		fprintf(1, '	   You are advised to estimate using an average sample rate (%g Hz) instead of timestamps.\n',1/avg_gap);
+		fprintf(1, '	   Continue at your own risk! (press any key to continue)\n');
+		pause;
+	end
+	
+	if verbose >= 1
+		fprintf(1, 'allan_overlap: End of timestamp data: %g sec\n',dtime(end));
+		fprintf(1, '	   Average rate: %g Hz (%g sec/measurement)\n',1/avg_gap,avg_gap);
+		if max(diff(dtime)) ~= 1/mean(diff(dtime))
+			fprintf(1, '	   Max. gap in time record: %g sec at position %d\n',max(dfdtime),gap_pos(1));
+		end
+		if max(diff(dtime)) > 5*avg_gap
+			fprintf(1, '	   WARNING: Max. gap in time record is suspiciously large (>5x the average interval).\n');
+		end
+	end
+	
  
-    % find halfway point
-    halftime = fix(dtime(end)/2);
-    % truncate tau to appropriate values
-    tau = tau(tau >= max(dfdtime) & tau <= halftime);
-    if isempty(tau)
-        error('allan_overlap: ERROR: no appropriate tau values (> %g s, < %g s)\n',max(dfdtime),halftime);
-    end
-    
+	% find halfway point
+	halftime = fix(dtime(end)/2);
+	% truncate tau to appropriate values
+	tau = tau(tau >= max(dfdtime) & tau <= halftime);
+	if isempty(tau)
+		error('allan_overlap: ERROR: no appropriate tau values (> %g s, < %g s)\n',max(dfdtime),halftime);
+	end
+	
  
-    % number of samples
-    M=length(dfreq);
-    % number of samples per tau period
-    m=round(tau./avg_gap);
+	% number of samples
+	M=length(dfreq);
+	% number of samples per tau period
+	m=round(tau./avg_gap);
  
-    if verbose >= 1, fprintf(1,'allan_overlap: calculating overlapping Allan deviation...\n'); end
+	if verbose >= 1, fprintf(1,'allan_overlap: calculating overlapping Allan deviation...\n'); end
  
-    k=0; tic;
-    for i = tau
-        k=k+1;
-        fa=[];
+	k=0; tic;
+	for i = tau
+		k=k+1;
+		fa=[];
  
-        if verbose >= 2, fprintf(1,'%d ',i); end
-        
-        freq = dfreq; time = dtime;
-       
-        
-        % compute overlapping samples (y_k) for this tau
-        %for j = 1:i
-        for j = 1:m(k) % (v2.1)
-            km=0;
-            %fprintf(1,'j: %d ',j);
+		if verbose >= 2, fprintf(1,'%d ',i); end
+		
+		freq = dfreq; time = dtime;
+	   
+		
+		% compute overlapping samples (y_k) for this tau
+		%for j = 1:i
+		for j = 1:m(k) % (v2.1)
+			km=0;
+			%fprintf(1,'j: %d ',j);
  
-            % (v2.1) truncating not correct for overlapping samples
-            % truncate data set to an even multiple of this tau value
-            %freq = freq(time <= time(end)-rem(time(end),i));
-            %time = time(time <= time(end)-rem(time(end),i));
-                        
-            % break up the data into overlapping groups of tau length
-            while i*km <= time(end)
-                km=km+1;
-                %i*km
+			% (v2.1) truncating not correct for overlapping samples
+			% truncate data set to an even multiple of this tau value
+			%freq = freq(time <= time(end)-rem(time(end),i));
+			%time = time(time <= time(end)-rem(time(end),i));
+						
+			% break up the data into overlapping groups of tau length
+			while i*km <= time(end)
+				km=km+1;
+				%i*km
  
-                % progress bar
-                if verbose >= 2
-                    if rem(km,100)==0, fprintf(1,'.'); end
-                    if rem(km,1000)==0, fprintf(1,'%g/%g\n',km,round(time(end)/i)); end
-                end
+				% progress bar
+				if verbose >= 2
+					if rem(km,100)==0, fprintf(1,'.'); end
+					if rem(km,1000)==0, fprintf(1,'%g/%g\n',km,round(time(end)/i)); end
+				end
  
-                f = freq(i*(km-1) < (time) & (time) <= i*km);
+				f = freq(i*(km-1) < (time) & (time) <= i*km);
  
-                if ~isempty(f)
-                    fa(j,km)=mean(f);
-                else
-                    fa(j,km)=0;
-                end
+				if ~isempty(f)
+					fa(j,km)=mean(f);
+				else
+					fa(j,km)=0;
+				end
  
-            end
-            %fa
-            
-            % shift data vector by -1 and repeat
-            freq=circshift(dfreq,(size(freq)>1)*-j);
-            freq(end-j+1:end)=[];
-            time=circshift(dtime,(size(time)>1)*-j);
-            time(end-j+1:end)=[];
-            time=time-time(1)+avg_gap; % remove time offset
-            
-        end
-        
-        % compute second differences of fractional frequency values (y_k+m - y_k)
-        fd1=diff(fa,1,2);
-        fd1=reshape(fd1,1,[]);
-        % compute overlapping ADEV from fractional frequency values
-        %  only the first M-2*m(k)+1 samples are valid
-        if length(fd1) >= M-2*m(k)+1
-            sm(k)=sqrt((1/(2*(M-2*m(k)+1)))*sum(fd1(1:M-2*m(k)+1).^2));
+			end
+			%fa
+			
+			% shift data vector by -1 and repeat
+			freq=circshift(dfreq,(size(freq)>1)*-j);
+			freq(end-j+1:end)=[];
+			time=circshift(dtime,(size(time)>1)*-j);
+			time(end-j+1:end)=[];
+			time=time-time(1)+avg_gap; % remove time offset
+			
+		end
+		
+		% compute second differences of fractional frequency values (y_k+m - y_k)
+		fd1=diff(fa,1,2);
+		fd1=reshape(fd1,1,[]);
+		% compute overlapping ADEV from fractional frequency values
+		%  only the first M-2*m(k)+1 samples are valid
+		if length(fd1) >= M-2*m(k)+1
+			sm(k)=sqrt((1/(2*(M-2*m(k)+1)))*sum(fd1(1:M-2*m(k)+1).^2));
  
-            % estimate error bars
-            sme(k)=sm(k)/sqrt(M+1);
-            
-            if verbose >= 2, fprintf(1,'\n'); end
-            
-        else
-            if verbose >=2, fprintf(1,' tau=%g dropped due to timestamp irregularities\n',tau(k)); end
-            sm(k)=0; sme(k)=0;
-        end
-        
+			% estimate error bars
+			sme(k)=sm(k)/sqrt(M+1);
+			
+			if verbose >= 2, fprintf(1,'\n'); end
+			
+		else
+			if verbose >=2, fprintf(1,' tau=%g dropped due to timestamp irregularities\n',tau(k)); end
+			sm(k)=0; sme(k)=0;
+		end
+		
  
-    end
+	end
  
-    if verbose >= 2, fprintf(1,'\n'); end
-    calctime=toc; if verbose >= 1, fprintf(1,'allan_overlap: Elapsed time for calculation: %g seconds\n',calctime); end
+	if verbose >= 2, fprintf(1,'\n'); end
+	calctime=toc; if verbose >= 1, fprintf(1,'allan_overlap: Elapsed time for calculation: %g seconds\n',calctime); end
  
-    % remove any points that were dropped
-    tau(sm==0)=[];
-    sm(sm==0)=[];
-    sme(sme==0)=[];
+	% remove any points that were dropped
+	tau(sm==0)=[];
+	sm(sm==0)=[];
+	sme(sme==0)=[];
  
  
  
 else
-    error('allan_overlap: WARNING: no DATA.rate or DATA.time! Type "help allan" for more information. [err2]');
+	error('allan_overlap: WARNING: no DATA.rate or DATA.time! Type "help allan" for more information. [err2]');
 end
  
  
  
  
  
  
  
  
  
@@ -464,83 +464,83 @@
 %% Plotting
  
 if verbose >= 2 % show all data
-    
-    % plot the frequency data, centered on median
-    if size(dtime,2) > size(dtime,1), dtime=dtime'; end % this should not be necessary, but dsplot 1.1 is a little bit brittle
-    try
-        % dsplot makes a new figure
-        hd=dsplot(dtime,medianfreq);
-    catch ME
-        figure;
-        hd=plot(dtime,medianfreq);
-        if verbose >= 1, fprintf(1,'allan_overlap: Note: Install dsplot.m for improved plotting of large data sets (File Exchange File ID: #15850).\n'); end
-        if verbose >= 2, fprintf(1,'             (Message: %s)\n',ME.message); end
-    end
-    set(hd,'Marker','.','LineStyle','none','Color','b'); % equivalent to '.-'
-    hold on;
+	
+	% plot the frequency data, centered on median
+	if size(dtime,2) > size(dtime,1), dtime=dtime'; end % this should not be necessary, but dsplot 1.1 is a little bit brittle
+	try
+		% dsplot makes a new figure
+		hd=dsplot(dtime,medianfreq);
+	catch ME
+		figure;
+		hd=plot(dtime,medianfreq);
+		if verbose >= 1, fprintf(1,'allan_overlap: Note: Install dsplot.m for improved plotting of large data sets (File Exchange File ID: #15850).\n'); end
+		if verbose >= 2, fprintf(1,'			 (Message: %s)\n',ME.message); end
+	end
+	set(hd,'Marker','.','LineStyle','none','Color','b'); % equivalent to '.-'
+	hold on;
  
-    fx = xlim;
-    % plot([fx(1) fx(2)],[s.median s.median],'-k');
-    plot([fx(1) fx(2)],[0 0],':k');
-    % show 5x Median Absolute deviation (MAD) values
-    hm=plot([fx(1) fx(2)],[5*MAD 5*MAD],'-r');
-    plot([fx(1) fx(2)],[-5*MAD -5*MAD],'-r');
-    % show linear fit line
-    hf=plot(xlim,polyval(s.linear,xlim)-s.median,'-g');    
-    title(['Data: ' name],'FontSize',FontSize+2,'FontName','Arial');
-    %set(get(gca,'Title'),'Interpreter','none');
-    xlabel('Time [sec]','FontSize',FontSize,'FontName',FontName);
-    if isfield(data,'units')
-        ylabel(['data - median(data) [' data.units ']'],'FontSize',FontSize,'FontName',FontName);
-    else
-        ylabel('freq - median(freq)','FontSize',FontSize,'FontName',FontName);
-    end
-    set(gca,'FontSize',FontSize,'FontName',FontName);
-    legend([hd hm hf],{'data (centered on median)','5x MAD outliers',['Linear Fit (' num2str(s.linear(1),'%g') ')']},'FontSize',max(10,FontSize-2));
-    % tighten up
-    xlim([dtime(1) dtime(end)]);
+	fx = xlim;
+	% plot([fx(1) fx(2)],[s.median s.median],'-k');
+	plot([fx(1) fx(2)],[0 0],':k');
+	% show 5x Median Absolute deviation (MAD) values
+	hm=plot([fx(1) fx(2)],[5*MAD 5*MAD],'-r');
+	plot([fx(1) fx(2)],[-5*MAD -5*MAD],'-r');
+	% show linear fit line
+	hf=plot(xlim,polyval(s.linear,xlim)-s.median,'-g');	
+	title(['Data: ' name],'FontSize',FontSize+2,'FontName','Arial');
+	%set(get(gca,'Title'),'Interpreter','none');
+	xlabel('Time [sec]','FontSize',FontSize,'FontName',FontName);
+	if isfield(data,'units')
+		ylabel(['data - median(data) [' data.units ']'],'FontSize',FontSize,'FontName',FontName);
+	else
+		ylabel('freq - median(freq)','FontSize',FontSize,'FontName',FontName);
+	end
+	set(gca,'FontSize',FontSize,'FontName',FontName);
+	legend([hd hm hf],{'data (centered on median)','5x MAD outliers',['Linear Fit (' num2str(s.linear(1),'%g') ')']},'FontSize',max(10,FontSize-2));
+	% tighten up
+	xlim([dtime(1) dtime(end)]);
  
-    
+	
 end % end plot raw data
  
  
 if verbose >= 1 % show analysis results
  
-    % plot Allan deviation results
-    if ~isempty(sm)
-        figure
+	% plot Allan deviation results
+	if ~isempty(sm)
+		figure
  
-        % Choose loglog or semilogx plot here    #PLOTLOG
-        %semilogx(tau,sm,'.-b','LineWidth',plotlinewidth,'MarkerSize',24);
-        loglog(tau,sm,'.-b','LineWidth',plotlinewidth,'MarkerSize',24);
+		% Choose loglog or semilogx plot here	#PLOTLOG
+		%semilogx(tau,sm,'.-b','LineWidth',plotlinewidth,'MarkerSize',24);
+		loglog(tau,sm,'.-b','LineWidth',plotlinewidth,'MarkerSize',24);
  
-        % in R14SP3, there is a bug that screws up the error bars on a semilog plot.
-        %  When this is fixed, uncomment below to use normal errorbars
-        %errorbar(tau,sm,sme,'.-b'); set(gca,'XScale','log');
-        % this is a hack to approximate the error bars
-        hold on; plot([tau; tau],[sm+sme; sm-sme],'-k','LineWidth',max(plotlinewidth-1,2));
+		% in R14SP3, there is a bug that screws up the error bars on a semilog plot.
+		%  When this is fixed, uncomment below to use normal errorbars
+		%errorbar(tau,sm,sme,'.-b'); set(gca,'XScale','log');
+		% this is a hack to approximate the error bars
+		hold on; plot([tau; tau],[sm+sme; sm-sme],'-k','LineWidth',max(plotlinewidth-1,2));
  
-        grid on;
-        title(['Overlapping Allan Deviation: ' name],'FontSize',FontSize+2,'FontName',FontName);
-        %set(get(gca,'Title'),'Interpreter','none');
-        xlabel('\tau [sec]','FontSize',FontSize,'FontName','Arial');
-        ylabel(' Overlapping \sigma_y(\tau)','FontSize',FontSize,'FontName',FontName);
-        set(gca,'FontSize',FontSize,'FontName',FontName);
-        % expand the x axis a little bit so that the errors bars look nice
-        adax = axis;
-        axis([adax(1)*0.9 adax(2)*1.1 adax(3) adax(4)]);
-        
-        % display the minimum value
-        fprintf(1,'allan: Minimum overlapping ADEV value: %g at tau = %g seconds\n',min(sm),tau(sm==min(sm)));        
-        
-    elseif verbose >= 1
-        fprintf(1,'allan_overlap: WARNING: no values calculated.\n');
-        fprintf(1,'       Check that TAU > 1/DATA.rate and TAU values are divisible by 1/DATA.rate\n');
-        fprintf(1,'Type "help allan_overlap" for more information.\n\n');
-    end
-    
+		grid on;
+		title(['Overlapping Allan Deviation: ' name],'FontSize',FontSize+2,'FontName',FontName);
+		%set(get(gca,'Title'),'Interpreter','none');
+		xlabel('\tau [sec]','FontSize',FontSize,'FontName','Arial');
+		ylabel(' Overlapping \sigma_y(\tau)','FontSize',FontSize,'FontName',FontName);
+		set(gca,'FontSize',FontSize,'FontName',FontName);
+		% expand the x axis a little bit so that the errors bars look nice
+		adax = axis;
+		axis([adax(1)*0.9 adax(2)*1.1 adax(3) adax(4)]);
+		
+		% display the minimum value
+		fprintf(1,'allan: Minimum overlapping ADEV value: %g at tau = %g seconds\n',min(sm),tau(sm==min(sm)));		
+		
+	elseif verbose >= 1
+		fprintf(1,'allan_overlap: WARNING: no values calculated.\n');
+		fprintf(1,'	   Check that TAU > 1/DATA.rate and TAU values are divisible by 1/DATA.rate\n');
+		fprintf(1,'Type "help allan_overlap" for more information.\n\n');
+	end
+	
 end % end plot analysis
-        
+		
 retval = sm;
 errorb = sme;
  
@@ -5,25 +5,33 @@
 mult = eval(argv(){3});
  
 if length(col) == length(mult)
-    figure
-    hold all
-    grid on
-    cc = 'bkcgmry';
-    for i = [1:length(col)]
-        data.freq = load(filename)(:,col(i)).*mult(i);
-        if eval(argv(){4})(i) == 1
-            printf(strcat(filename, ' col', num2str(col(i)), ' drift removed\n\n'))
-            data.freq = detrend(data.freq);
-        end
-        data.rate = 1;
-        [ad, S, err, tau] = allan(data, 2.^[0:nextpow2(length(data.freq))-3]./data.rate, strcat(strsplit(filename, '/'){end}, num2str(i)), 0);
-        loglogerr(tau, ad, err, strcat(cc(mod(i, length(cc))), '-s'))
-        leg{i} = strcat(filename, ' col', num2str(col(i)));
-        axis(10.^ceil(log10([tau(1), tau(end)])))
-        hold on
-    end
-    legend(leg)
-    input("Press to continue...");
+	figure
+	hold all
+	grid on
+	cc = 'bkcgmry';
+	for i = [1:length(col)]
+		data.freq = load(filename)(:,col(i)).*mult(i);
+		if nargin == 4
+			if eval(argv(){4})(i) == 1
+				printf(strcat(filename, ' col', num2str(col(i)), ' drift removed\n\n'))
+				data.freq = detrend(data.freq);
+			elseif eval(argv(){4})(i) == 2
+				printf(strcat(filename, ' col', num2str(col(i)), ' relative ad\n\n'))
+                data.freq = data.freq./mean(data.freq);
+            elseif eval(argv(){4})(i) == 3
+                printf(strcat(filename, ' col', num2str(col(i)), ' drift removed relative ad\n\n'))
+                data.freq = detrend(data.freq./mean(data.freq));
+			end
+		endif
+		data.rate = 1;
+		[ad, S, err, tau] = allan(data, 2.^[0:nextpow2(length(data.freq))-3]./data.rate, strcat(strsplit(filename, '/'){end}, num2str(i)), 0);
+		loglogerr(tau, ad, err, strcat(cc(mod(i, length(cc))), '-s'))
+		leg{i} = strcat(filename, ' col', num2str(col(i)));
+		axis(10.^ceil(log10([tau(1), tau(end)])))
+		hold on
+	end
+	legend(leg)
+	input("Press to continue...");
 end
 exit
@@ -7,32 +7,32 @@
 mult2 = eval(argv(){5});
  
 if length(col1) == length(mult1)
-    figure
-    hold all
-    grid on
-    cc = 'bkcgmry';
-    for i = [1:length(col1)]
-        data.freq = load(filename)(:,col1(i)).*mult1(i);
-        data.freq2 = load(filename)(:,col2(i)).*mult2(i);
-        data.freq = data.freq(1:min(length(data.freq), length(data.freq2)));
-        data.freq2 = data.freq2(1:min(length(data.freq), length(data.freq2)));
-        if eval(argv(){end-1}) == 1
-            printf('\ndata1 drift removed\n\n')
-            data.freq = detrend(data.freq);
-        end
-        if eval(argv(){end}) == 1
-            printf('\ndata2 drift removed\n\n')
-            data.freq2 = detrend(data.freq2);
-        end
-        data.rate = 1;
-        [ad, S, err, tau] = allan_cov(data, 2.^[0:nextpow2(length(data.freq))-3]./data.rate, strcat(strsplit(filename, '/'){end}, num2str(i)), 0);
-        loglogerr(tau, ad, err, strcat(cc(mod(i, length(cc))), '-s'))
-        leg{i} = strcat(filename, ' cov col', num2str(col1(i)), ' col', num2str(col2(i)));
-        axis(10.^ceil(log10([tau(1), tau(end)])))
-        hold on
-    end
-    legend(leg)
-    input("Press to continue...");
+	figure
+	hold all
+	grid on
+	cc = 'bkcgmry';
+	for i = [1:length(col1)]
+		data.freq = load(filename)(:,col1(i)).*mult1(i);
+		data.freq2 = load(filename)(:,col2(i)).*mult2(i);
+		data.freq = data.freq(1:min(length(data.freq), length(data.freq2)));
+		data.freq2 = data.freq2(1:min(length(data.freq), length(data.freq2)));
+		if eval(argv(){end-1}) == 1
+			printf('\ndata1 drift removed\n\n')
+			data.freq = detrend(data.freq);
+		end
+		if eval(argv(){end}) == 1
+			printf('\ndata2 drift removed\n\n')
+			data.freq2 = detrend(data.freq2);
+		end
+		data.rate = 1;
+		[ad, S, err, tau] = allan_cov(data, 2.^[0:nextpow2(length(data.freq))-3]./data.rate, strcat(strsplit(filename, '/'){end}, num2str(i)), 0);
+		loglogerr(tau, ad, err, strcat(cc(mod(i, length(cc))), '-s'))
+		leg{i} = strcat(filename, ' cov col', num2str(col1(i)), ' col', num2str(col2(i)));
+		axis(10.^ceil(log10([tau(1), tau(end)])))
+		hold on
+	end
+	legend(leg)
+	input("Press to continue...");
 end
 exit
@@ -6,9 +6,9 @@
 %
 %   DSPLOT(X, Y) plots Y versus X by downsampling if there are large number
 %   of elements. X and Y needs to obey the following:
-%     1. X must be a monotonically increasing vector.
-%     2. If Y is a vector, it must be the same size as X.
-%     3. If Y is a matrix, one of the dimensions must line up with X.
+%	 1. X must be a monotonically increasing vector.
+%	 2. If Y is a vector, it must be the same size as X.
+%	 3. If Y is a matrix, one of the dimensions must line up with X.
 %
 %   DSPLOT(Y) plots the columns of Y versus their index.
 %
@@ -58,9 +58,9 @@
 %  Version:
 %   v1.0 - first version (Aug 1, 2007)
 %   v1.1 - added CreateFcn for the figure so that when the figure is saved
-%          and re-loaded, the zooming and panning works. Also added a menu
-%          item for saving out the original data back to the base
-%          workspace. (Aug 10, 2007)
+%		  and re-loaded, the zooming and panning works. Also added a menu
+%		  item for saving out the original data back to the base
+%		  workspace. (Aug 10, 2007)
 %
 %  Jiro Doke
 %  August 1, 2007
  
@@ -101,13 +101,13 @@
 % orientation.
 if numSignals > size(y, 1)
   s = input(sprintf('Are you sure you want to plot %d lines? (y/n) ', ...
-    numSignals), 's');
+	numSignals), 's');
   if ~strcmpi(s, 'y')
-    disp('Canceled. You may want to transpose the matrix.');
-    if nargout == 1
-      hL = [];
-    end
-    return;
+	disp('Canceled. You may want to transpose the matrix.');
+	if nargout == 1
+	  hL = [];
+	end
+	return;
   end
 end
  
@@ -120,7 +120,7 @@
  
 % Always create new figure because it messes around with zoom, pan,
 % datacursors.
-hFig    = figure;
+hFig	= figure;
 figName = '';
  
 % Create template plot using NaNs
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
@@ -147,173 +147,173 @@
  
 %--------------------------------------------------------------------------
   function myExportFcn(varargin)
-    % This callback allows for extracting the actual data from the figure.
-    % This means that if you save this figure and load it back later, you
-    % can get back the data.
-    
-    % Determine the variable name
-    allVarNames = evalin('base', 'who');
-    newVarName = genvarname('dsplotData', allVarNames);
-    
-    % X
-    if ~noXVar
-      if varTranspose
-        dat.x = x';
-      else
-        dat.x = x;
-      end
-    end
-    
-    % Y
-    if varTranspose
-      dat.y = y';
-    else
-      dat.y = y;
-    end
-    
-    assignin('base', newVarName, dat);
-    
-    msgbox(sprintf('Data saved to the base workspace as ''%s''.', ...
-      newVarName), 'Saved', 'modal');
-    
+	% This callback allows for extracting the actual data from the figure.
+	% This means that if you save this figure and load it back later, you
+	% can get back the data.
+	
+	% Determine the variable name
+	allVarNames = evalin('base', 'who');
+	newVarName = genvarname('dsplotData', allVarNames);
+	
+	% X
+	if ~noXVar
+	  if varTranspose
+		dat.x = x';
+	  else
+		dat.x = x;
+	  end
+	end
+	
+	% Y
+	if varTranspose
+	  dat.y = y';
+	else
+	  dat.y = y;
+	end
+	
+	assignin('base', newVarName, dat);
+	
+	msgbox(sprintf('Data saved to the base workspace as ''%s''.', ...
+	  newVarName), 'Saved', 'modal');
+	
   end
  
 %--------------------------------------------------------------------------
   function mycreatefcn(varargin)
-    % This callback defines the custom zoom/pan functions. It is defined as
-    % the CreateFcn of the figure, so it allows for saving and reloading of
-    % the figure.
+	% This callback defines the custom zoom/pan functions. It is defined as
+	% the CreateFcn of the figure, so it allows for saving and reloading of
+	% the figure.
  
-    if nargin > 0
-      hFig = varargin{1};
-    end
-    hLine = findobj(hFig, 'type', 'axes');
-    hLine(strmatch('legend', get(hLine, 'tag'))) = [];
-    hLine = get(hLine, 'Children');
-    
-    % Create Zoom, Pan, Datacursor objects
-    hZoom = zoom(hFig);
-    hPan  = pan(hFig);
-    hDc   = datacursormode(hFig);
-    set(hZoom, 'ActionPostCallback', @mypostcallback);
-    set(hPan , 'ActionPostCallback', @mypostcallback);
-    set(hDc  , 'UpdateFcn'         , @myDCupdatefcn);
+	if nargin > 0
+	  hFig = varargin{1};
+	end
+	hLine = findobj(hFig, 'type', 'axes');
+	hLine(strmatch('legend', get(hLine, 'tag'))) = [];
+	hLine = get(hLine, 'Children');
+	
+	% Create Zoom, Pan, Datacursor objects
+	hZoom = zoom(hFig);
+	hPan  = pan(hFig);
+	hDc   = datacursormode(hFig);
+	set(hZoom, 'ActionPostCallback', @mypostcallback);
+	set(hPan , 'ActionPostCallback', @mypostcallback);
+	set(hDc  , 'UpdateFcn'		 , @myDCupdatefcn);
  
   end
  
 %--------------------------------------------------------------------------
   function mypostcallback(obj, evd) %#ok
-    % This callback that gets called when the mouse is released after
-    % zooming or panning.
+	% This callback that gets called when the mouse is released after
+	% zooming or panning.
  
-    % single or double-click
-    switch get(hFig, 'SelectionType')
-      case {'normal', 'alt'}
-        updateLines(xlim(evd.Axes));
+	% single or double-click
+	switch get(hFig, 'SelectionType')
+	  case {'normal', 'alt'}
+		updateLines(xlim(evd.Axes));
  
-      case 'open'
-        updateLines([min(x), max(x)]);
+	  case 'open'
+		updateLines([min(x), max(x)]);
  
-    end
+	end
  
   end
  
 %--------------------------------------------------------------------------
   function updateLines(rng)
-    % This helper function is for determining the points to plot on the
-    % screen based on which portion is visible in the current limits.
+	% This helper function is for determining the points to plot on the
+	% screen based on which portion is visible in the current limits.
  
-    % find indeces inside the range
-    id = find(x >= rng(1) & x <= rng(2));
+	% find indeces inside the range
+	id = find(x >= rng(1) & x <= rng(2));
  
-    % if there are more points than we want
-    if length(id) > numPoints / numSignals
+	% if there are more points than we want
+	if length(id) > numPoints / numSignals
  
-      % see how many outlier points are in this range
-      blah = iOutliers > id(1) & iOutliers < id(end);
+	  % see how many outlier points are in this range
+	  blah = iOutliers > id(1) & iOutliers < id(end);
  
-      % determine indeces of points to plot. 
-      idid = round(linspace(id(1), id(end), round(numPoints/numSignals)))';
+	  % determine indeces of points to plot. 
+	  idid = round(linspace(id(1), id(end), round(numPoints/numSignals)))';
  
-      x2 = cell(numSignals, 1);
-      y2 = x2;
-      for iSignals = 1:numSignals
-        % add outlier points
-        ididid = unique([idid; iOutliers(blah & jOutliers == iSignals)]);
-        x2{iSignals} = x(ididid);
-        y2{iSignals} = y(ididid, iSignals);
-      end
+	  x2 = cell(numSignals, 1);
+	  y2 = x2;
+	  for iSignals = 1:numSignals
+		% add outlier points
+		ididid = unique([idid; iOutliers(blah & jOutliers == iSignals)]);
+		x2{iSignals} = x(ididid);
+		y2{iSignals} = y(ididid, iSignals);
+	  end
  
-      if debugMode
-        figName = ['downsampled - ', sprintf('%d, ', cellfun('length', y2))];
-      else
-        figName = 'downsampled';
-      end
+	  if debugMode
+		figName = ['downsampled - ', sprintf('%d, ', cellfun('length', y2))];
+	  else
+		figName = 'downsampled';
+	  end
  
-    else % no need to down sample
-      figName = 'true';
+	else % no need to down sample
+	  figName = 'true';
  
-      x2 = repmat({x(id)}, numSignals, 1);
-      y2 = mat2cell(y(id, :), length(id), ones(1, numSignals))';
+	  x2 = repmat({x(id)}, numSignals, 1);
+	  y2 = mat2cell(y(id, :), length(id), ones(1, numSignals))';
  
-    end
+	end
  
-    % Update plot
-    set(hLine, {'xdata', 'ydata'} , [x2, y2]);
-    set(hFig, 'Name', figName);
+	% Update plot
+	set(hLine, {'xdata', 'ydata'} , [x2, y2]);
+	set(hFig, 'Name', figName);
  
   end
  
 %--------------------------------------------------------------------------
   function txt = myDCupdatefcn(empt, event_obj) %#ok
-    % This function displays appropriate data cursor message based on the
-    % display type
+	% This function displays appropriate data cursor message based on the
+	% display type
  
-    pos = get(event_obj,'Position');
-    switch figName
-      case 'true'
-        txt = {['X: ',num2str(pos(1))],...
-          ['Y: ',num2str(pos(2))]};
-      otherwise
-        txt = {['X: ',num2str(pos(1))],...
-          ['Y: ',num2str(pos(2))], ...
-          'Warning: Downsampled', ...
-          'May not be accurate'};
-    end
+	pos = get(event_obj,'Position');
+	switch figName
+	  case 'true'
+		txt = {['X: ',num2str(pos(1))],...
+		  ['Y: ',num2str(pos(2))]};
+	  otherwise
+		txt = {['X: ',num2str(pos(1))],...
+		  ['Y: ',num2str(pos(2))], ...
+		  'Warning: Downsampled', ...
+		  'May not be accurate'};
+	end
   end
  
 %--------------------------------------------------------------------------
   function myErrorCheck
-    % Do some error checking on the input arguments.
+	% Do some error checking on the input arguments.
  
-    if ~isa(numPoints, 'double') || numel(numPoints) > 1 || numPoints < 500
-      error('Third argument must be a scalar greater than 500');
-    end
-    if ~isnumeric(x) || ~isnumeric(y)
-      error('Arguments must be numeric');
-    end
-    if length(size(x)) > 2 || length(size(y)) > 2
-      error('Only 2-D data accepted');
-    end
-    
-    % If only one input, create index vector X
-    if isempty(x)
-      if ismember(1, size(y))
-        x = reshape(1:numel(y), size(y));
-      else
-        x = (1:size(y, 1))';
-      end
-    end
-    
-    if ~ismember(1, size(x))
-      error('First argument has to be a vector');
-    end
-    if ~isequal(size(x, 1), size(y, 1)) && ~isequal(size(x, 2), size(y, 2))
-      error('One of the dimensions of the two arguments must match');
-    end
-    if any(diff(x) <= 0)
-      error('The first argument has to be a monotonically increasing vector');
-    end
+	if ~isa(numPoints, 'double') || numel(numPoints) > 1 || numPoints < 500
+	  error('Third argument must be a scalar greater than 500');
+	end
+	if ~isnumeric(x) || ~isnumeric(y)
+	  error('Arguments must be numeric');
+	end
+	if length(size(x)) > 2 || length(size(y)) > 2
+	  error('Only 2-D data accepted');
+	end
+	
+	% If only one input, create index vector X
+	if isempty(x)
+	  if ismember(1, size(y))
+		x = reshape(1:numel(y), size(y));
+	  else
+		x = (1:size(y, 1))';
+	  end
+	end
+	
+	if ~ismember(1, size(x))
+	  error('First argument has to be a vector');
+	end
+	if ~isequal(size(x, 1), size(y, 1)) && ~isequal(size(x, 2), size(y, 2))
+	  error('One of the dimensions of the two arguments must match');
+	end
+	if any(diff(x) <= 0)
+	  error('The first argument has to be a monotonically increasing vector');
+	end
   end
  
 end
@@ -5,20 +5,20 @@
 mult = eval(argv(){3});
  
 if length(col) == length(mult)
-    figure
-    hold all
-    grid on
-    cc = 'bkcgmry';
-    for i = [1:length(col)]
-        data.freq = load(filename)(:,col(i)).*mult(i);
-        data.rate = 1;
-        [p, f] = pwelch(data.freq, [], 0.95, [], data.rate.*mult(i), 'onesided');
-        semilogx(f, 10*log10(p), cc(mod(i, length(cc))))
-        leg{i} = strcat(filename, ' col', num2str(col(i)));
-        hold on
-    end
-    legend(leg)
-    input("Press to continue...");
+	figure
+	hold all
+	grid on
+	cc = 'bkcgmry';
+	for i = [1:length(col)]
+		data.freq = load(filename)(:,col(i)).*mult(i);
+		data.rate = 1;
+		[p, f] = pwelch(data.freq, [], 0.95, [], data.rate.*mult(i), 'onesided');
+		semilogx(f, 10*log10(p), cc(mod(i, length(cc))))
+		leg{i} = strcat(filename, ' col', num2str(col(i)));
+		hold on
+	end
+	legend(leg)
+	input("Press to continue...");
 end
 exit
...	...	@@ -5,25 +5,33 @@
5	5	mult = eval(argv(){3});
6	6
7	7	if length(col) == length(mult)
8		- figure
9		- hold all
10		- grid on
11		- cc = 'bkcgmry';
12		- for i = [1:length(col)]
13		- data.freq = load(filename)(:,col(i)).*mult(i);
14		- if eval(argv(){4})(i) == 1
15		- printf(strcat(filename, ' col', num2str(col(i)), ' drift removed\n\n'))
16		- data.freq = detrend(data.freq);
17		- end
18		- data.rate = 1;
19		- [ad, S, err, tau] = allan(data, 2.^[0:nextpow2(length(data.freq))-3]./data.rate, strcat(strsplit(filename, '/'){end}, num2str(i)), 0);
20		- loglogerr(tau, ad, err, strcat(cc(mod(i, length(cc))), '-s'))
21		- leg{i} = strcat(filename, ' col', num2str(col(i)));
22		- axis(10.^ceil(log10([tau(1), tau(end)])))
23		- hold on
24		- end
25		- legend(leg)
26		- input("Press to continue...");
	8	+ figure
	9	+ hold all
	10	+ grid on
	11	+ cc = 'bkcgmry';
	12	+ for i = [1:length(col)]
	13	+ data.freq = load(filename)(:,col(i)).*mult(i);
	14	+ if nargin == 4
	15	+ if eval(argv(){4})(i) == 1
	16	+ printf(strcat(filename, ' col', num2str(col(i)), ' drift removed\n\n'))
	17	+ data.freq = detrend(data.freq);
	18	+ elseif eval(argv(){4})(i) == 2
	19	+ printf(strcat(filename, ' col', num2str(col(i)), ' relative ad\n\n'))
	20	+ data.freq = data.freq./mean(data.freq);
	21	+ elseif eval(argv(){4})(i) == 3
	22	+ printf(strcat(filename, ' col', num2str(col(i)), ' drift removed relative ad\n\n'))
	23	+ data.freq = detrend(data.freq./mean(data.freq));
	24	+ end
	25	+ endif
	26	+ data.rate = 1;
	27	+ [ad, S, err, tau] = allan(data, 2.^[0:nextpow2(length(data.freq))-3]./data.rate, strcat(strsplit(filename, '/'){end}, num2str(i)), 0);
	28	+ loglogerr(tau, ad, err, strcat(cc(mod(i, length(cc))), '-s'))
	29	+ leg{i} = strcat(filename, ' col', num2str(col(i)));
	30	+ axis(10.^ceil(log10([tau(1), tau(end)])))
	31	+ hold on
	32	+ end
	33	+ legend(leg)
	34	+ input("Press to continue...");
27	35	end
28	36	exit
...	...	@@ -7,32 +7,32 @@
7	7	mult2 = eval(argv(){5});
8	8
9	9	if length(col1) == length(mult1)
10		- figure
11		- hold all
12		- grid on
13		- cc = 'bkcgmry';
14		- for i = [1:length(col1)]
15		- data.freq = load(filename)(:,col1(i)).*mult1(i);
16		- data.freq2 = load(filename)(:,col2(i)).*mult2(i);
17		- data.freq = data.freq(1:min(length(data.freq), length(data.freq2)));
18		- data.freq2 = data.freq2(1:min(length(data.freq), length(data.freq2)));
19		- if eval(argv(){end-1}) == 1
20		- printf('\ndata1 drift removed\n\n')
21		- data.freq = detrend(data.freq);
22		- end
23		- if eval(argv(){end}) == 1
24		- printf('\ndata2 drift removed\n\n')
25		- data.freq2 = detrend(data.freq2);
26		- end
27		- data.rate = 1;
28		- [ad, S, err, tau] = allan_cov(data, 2.^[0:nextpow2(length(data.freq))-3]./data.rate, strcat(strsplit(filename, '/'){end}, num2str(i)), 0);
29		- loglogerr(tau, ad, err, strcat(cc(mod(i, length(cc))), '-s'))
30		- leg{i} = strcat(filename, ' cov col', num2str(col1(i)), ' col', num2str(col2(i)));
31		- axis(10.^ceil(log10([tau(1), tau(end)])))
32		- hold on
33		- end
34		- legend(leg)
35		- input("Press to continue...");
	10	+ figure
	11	+ hold all
	12	+ grid on
	13	+ cc = 'bkcgmry';
	14	+ for i = [1:length(col1)]
	15	+ data.freq = load(filename)(:,col1(i)).*mult1(i);
	16	+ data.freq2 = load(filename)(:,col2(i)).*mult2(i);
	17	+ data.freq = data.freq(1:min(length(data.freq), length(data.freq2)));
	18	+ data.freq2 = data.freq2(1:min(length(data.freq), length(data.freq2)));
	19	+ if eval(argv(){end-1}) == 1
	20	+ printf('\ndata1 drift removed\n\n')
	21	+ data.freq = detrend(data.freq);
	22	+ end
	23	+ if eval(argv(){end}) == 1
	24	+ printf('\ndata2 drift removed\n\n')
	25	+ data.freq2 = detrend(data.freq2);
	26	+ end
	27	+ data.rate = 1;
	28	+ [ad, S, err, tau] = allan_cov(data, 2.^[0:nextpow2(length(data.freq))-3]./data.rate, strcat(strsplit(filename, '/'){end}, num2str(i)), 0);
	29	+ loglogerr(tau, ad, err, strcat(cc(mod(i, length(cc))), '-s'))
	30	+ leg{i} = strcat(filename, ' cov col', num2str(col1(i)), ' col', num2str(col2(i)));
	31	+ axis(10.^ceil(log10([tau(1), tau(end)])))
	32	+ hold on
	33	+ end
	34	+ legend(leg)
	35	+ input("Press to continue...");
36	36	end
37	37	exit
...	...	@@ -6,9 +6,9 @@
6	6	%
7	7	% DSPLOT(X, Y) plots Y versus X by downsampling if there are large number
8	8	% of elements. X and Y needs to obey the following:
9		-% 1. X must be a monotonically increasing vector.
10		-% 2. If Y is a vector, it must be the same size as X.
11		-% 3. If Y is a matrix, one of the dimensions must line up with X.
	9	+% 1. X must be a monotonically increasing vector.
	10	+% 2. If Y is a vector, it must be the same size as X.
	11	+% 3. If Y is a matrix, one of the dimensions must line up with X.
12	12	%
13	13	% DSPLOT(Y) plots the columns of Y versus their index.
14	14	%
...	...	@@ -58,9 +58,9 @@
58	58	% Version:
59	59	% v1.0 - first version (Aug 1, 2007)
60	60	% v1.1 - added CreateFcn for the figure so that when the figure is saved
61		-% and re-loaded, the zooming and panning works. Also added a menu
62		-% item for saving out the original data back to the base
63		-% workspace. (Aug 10, 2007)
	61	+% and re-loaded, the zooming and panning works. Also added a menu
	62	+% item for saving out the original data back to the base
	63	+% workspace. (Aug 10, 2007)
64	64	%
65	65	% Jiro Doke
66	66	% August 1, 2007
67	67
...	...	@@ -101,13 +101,13 @@
101	101	% orientation.
102	102	if numSignals > size(y, 1)
103	103	s = input(sprintf('Are you sure you want to plot %d lines? (y/n) ', ...
104		- numSignals), 's');
	104	+ numSignals), 's');
105	105	if ~strcmpi(s, 'y')
106		- disp('Canceled. You may want to transpose the matrix.');
107		- if nargout == 1
108		- hL = [];
109		- end
110		- return;
	106	+ disp('Canceled. You may want to transpose the matrix.');
	107	+ if nargout == 1
	108	+ hL = [];
	109	+ end
	110	+ return;
111	111	end
112	112	end
113	113
...	...	@@ -120,7 +120,7 @@
120	120
121	121	% Always create new figure because it messes around with zoom, pan,
122	122	% datacursors.
123		-hFig = figure;
	123	+hFig = figure;
124	124	figName = '';
125	125
126	126	% Create template plot using NaNs
127	127
128	128
129	129
130	130
131	131
132	132
133	133
134	134
135	135
136	136
137	137
138	138
139	139
140	140
141	141
142	142
143	143
144	144
145	145
146	146
147	147
...	...	@@ -147,173 +147,173 @@
147	147
148	148	%--------------------------------------------------------------------------
149	149	function myExportFcn(varargin)
150		- % This callback allows for extracting the actual data from the figure.
151		- % This means that if you save this figure and load it back later, you
152		- % can get back the data.
153		-
154		- % Determine the variable name
155		- allVarNames = evalin('base', 'who');
156		- newVarName = genvarname('dsplotData', allVarNames);
157		-
158		- % X
159		- if ~noXVar
160		- if varTranspose
161		- dat.x = x';
162		- else
163		- dat.x = x;
164		- end
165		- end
166		-
167		- % Y
168		- if varTranspose
169		- dat.y = y';
170		- else
171		- dat.y = y;
172		- end
173		-
174		- assignin('base', newVarName, dat);
175		-
176		- msgbox(sprintf('Data saved to the base workspace as ''%s''.', ...
177		- newVarName), 'Saved', 'modal');
178		-
	150	+ % This callback allows for extracting the actual data from the figure.
	151	+ % This means that if you save this figure and load it back later, you
	152	+ % can get back the data.
	153	+
	154	+ % Determine the variable name
	155	+ allVarNames = evalin('base', 'who');
	156	+ newVarName = genvarname('dsplotData', allVarNames);
	157	+
	158	+ % X
	159	+ if ~noXVar
	160	+ if varTranspose
	161	+ dat.x = x';
	162	+ else
	163	+ dat.x = x;
	164	+ end
	165	+ end
	166	+
	167	+ % Y
	168	+ if varTranspose
	169	+ dat.y = y';
	170	+ else
	171	+ dat.y = y;
	172	+ end
	173	+
	174	+ assignin('base', newVarName, dat);
	175	+
	176	+ msgbox(sprintf('Data saved to the base workspace as ''%s''.', ...
	177	+ newVarName), 'Saved', 'modal');
	178	+
179	179	end
180	180
181	181	%--------------------------------------------------------------------------
182	182	function mycreatefcn(varargin)
183		- % This callback defines the custom zoom/pan functions. It is defined as
184		- % the CreateFcn of the figure, so it allows for saving and reloading of
185		- % the figure.
	183	+ % This callback defines the custom zoom/pan functions. It is defined as
	184	+ % the CreateFcn of the figure, so it allows for saving and reloading of
	185	+ % the figure.
186	186
187		- if nargin > 0
188		- hFig = varargin{1};
189		- end
190		- hLine = findobj(hFig, 'type', 'axes');
191		- hLine(strmatch('legend', get(hLine, 'tag'))) = [];
192		- hLine = get(hLine, 'Children');
193		-
194		- % Create Zoom, Pan, Datacursor objects
195		- hZoom = zoom(hFig);
196		- hPan = pan(hFig);
197		- hDc = datacursormode(hFig);
198		- set(hZoom, 'ActionPostCallback', @mypostcallback);
199		- set(hPan , 'ActionPostCallback', @mypostcallback);
200		- set(hDc , 'UpdateFcn' , @myDCupdatefcn);
	187	+ if nargin > 0
	188	+ hFig = varargin{1};
	189	+ end
	190	+ hLine = findobj(hFig, 'type', 'axes');
	191	+ hLine(strmatch('legend', get(hLine, 'tag'))) = [];
	192	+ hLine = get(hLine, 'Children');
	193	+
	194	+ % Create Zoom, Pan, Datacursor objects
	195	+ hZoom = zoom(hFig);
	196	+ hPan = pan(hFig);
	197	+ hDc = datacursormode(hFig);
	198	+ set(hZoom, 'ActionPostCallback', @mypostcallback);
	199	+ set(hPan , 'ActionPostCallback', @mypostcallback);
	200	+ set(hDc , 'UpdateFcn' , @myDCupdatefcn);
201	201
202	202	end
203	203
204	204	%--------------------------------------------------------------------------
205	205	function mypostcallback(obj, evd) %#ok
206		- % This callback that gets called when the mouse is released after
207		- % zooming or panning.
	206	+ % This callback that gets called when the mouse is released after
	207	+ % zooming or panning.
208	208
209		- % single or double-click
210		- switch get(hFig, 'SelectionType')
211		- case {'normal', 'alt'}
212		- updateLines(xlim(evd.Axes));
	209	+ % single or double-click
	210	+ switch get(hFig, 'SelectionType')
	211	+ case {'normal', 'alt'}
	212	+ updateLines(xlim(evd.Axes));
213	213
214		- case 'open'
215		- updateLines([min(x), max(x)]);
	214	+ case 'open'
	215	+ updateLines([min(x), max(x)]);
216	216
217		- end
	217	+ end
218	218
219	219	end
220	220
221	221	%--------------------------------------------------------------------------
222	222	function updateLines(rng)
223		- % This helper function is for determining the points to plot on the
224		- % screen based on which portion is visible in the current limits.
	223	+ % This helper function is for determining the points to plot on the
	224	+ % screen based on which portion is visible in the current limits.
225	225
226		- % find indeces inside the range
227		- id = find(x >= rng(1) & x <= rng(2));
	226	+ % find indeces inside the range
	227	+ id = find(x >= rng(1) & x <= rng(2));
228	228
229		- % if there are more points than we want
230		- if length(id) > numPoints / numSignals
	229	+ % if there are more points than we want
	230	+ if length(id) > numPoints / numSignals
231	231
232		- % see how many outlier points are in this range
233		- blah = iOutliers > id(1) & iOutliers < id(end);
	232	+ % see how many outlier points are in this range
	233	+ blah = iOutliers > id(1) & iOutliers < id(end);
234	234
235		- % determine indeces of points to plot.
236		- idid = round(linspace(id(1), id(end), round(numPoints/numSignals)))';
	235	+ % determine indeces of points to plot.
	236	+ idid = round(linspace(id(1), id(end), round(numPoints/numSignals)))';
237	237
238		- x2 = cell(numSignals, 1);
239		- y2 = x2;
240		- for iSignals = 1:numSignals
241		- % add outlier points
242		- ididid = unique([idid; iOutliers(blah & jOutliers == iSignals)]);
243		- x2{iSignals} = x(ididid);
244		- y2{iSignals} = y(ididid, iSignals);
245		- end
	238	+ x2 = cell(numSignals, 1);
	239	+ y2 = x2;
	240	+ for iSignals = 1:numSignals
	241	+ % add outlier points
	242	+ ididid = unique([idid; iOutliers(blah & jOutliers == iSignals)]);
	243	+ x2{iSignals} = x(ididid);
	244	+ y2{iSignals} = y(ididid, iSignals);
	245	+ end
246	246
247		- if debugMode
248		- figName = ['downsampled - ', sprintf('%d, ', cellfun('length', y2))];
249		- else
250		- figName = 'downsampled';
251		- end
	247	+ if debugMode
	248	+ figName = ['downsampled - ', sprintf('%d, ', cellfun('length', y2))];
	249	+ else
	250	+ figName = 'downsampled';
	251	+ end
252	252
253		- else % no need to down sample
254		- figName = 'true';
	253	+ else % no need to down sample
	254	+ figName = 'true';
255	255
256		- x2 = repmat({x(id)}, numSignals, 1);
257		- y2 = mat2cell(y(id, :), length(id), ones(1, numSignals))';
	256	+ x2 = repmat({x(id)}, numSignals, 1);
	257	+ y2 = mat2cell(y(id, :), length(id), ones(1, numSignals))';
258	258
259		- end
	259	+ end
260	260
261		- % Update plot
262		- set(hLine, {'xdata', 'ydata'} , [x2, y2]);
263		- set(hFig, 'Name', figName);
	261	+ % Update plot
	262	+ set(hLine, {'xdata', 'ydata'} , [x2, y2]);
	263	+ set(hFig, 'Name', figName);
264	264
265	265	end
266	266
267	267	%--------------------------------------------------------------------------
268	268	function txt = myDCupdatefcn(empt, event_obj) %#ok
269		- % This function displays appropriate data cursor message based on the
270		- % display type
	269	+ % This function displays appropriate data cursor message based on the
	270	+ % display type
271	271
272		- pos = get(event_obj,'Position');
273		- switch figName
274		- case 'true'
275		- txt = {['X: ',num2str(pos(1))],...
276		- ['Y: ',num2str(pos(2))]};
277		- otherwise
278		- txt = {['X: ',num2str(pos(1))],...
279		- ['Y: ',num2str(pos(2))], ...
280		- 'Warning: Downsampled', ...
281		- 'May not be accurate'};
282		- end
	272	+ pos = get(event_obj,'Position');
	273	+ switch figName
	274	+ case 'true'
	275	+ txt = {['X: ',num2str(pos(1))],...
	276	+ ['Y: ',num2str(pos(2))]};
	277	+ otherwise
	278	+ txt = {['X: ',num2str(pos(1))],...
	279	+ ['Y: ',num2str(pos(2))], ...
	280	+ 'Warning: Downsampled', ...
	281	+ 'May not be accurate'};
	282	+ end
283	283	end
284	284
285	285	%--------------------------------------------------------------------------
286	286	function myErrorCheck
287		- % Do some error checking on the input arguments.
	287	+ % Do some error checking on the input arguments.
288	288
289		- if ~isa(numPoints, 'double') \|\| numel(numPoints) > 1 \|\| numPoints < 500
290		- error('Third argument must be a scalar greater than 500');
291		- end
292		- if ~isnumeric(x) \|\| ~isnumeric(y)
293		- error('Arguments must be numeric');
294		- end
295		- if length(size(x)) > 2 \|\| length(size(y)) > 2
296		- error('Only 2-D data accepted');
297		- end
298		-
299		- % If only one input, create index vector X
300		- if isempty(x)
301		- if ismember(1, size(y))
302		- x = reshape(1:numel(y), size(y));
303		- else
304		- x = (1:size(y, 1))';
305		- end
306		- end
307		-
308		- if ~ismember(1, size(x))
309		- error('First argument has to be a vector');
310		- end
311		- if ~isequal(size(x, 1), size(y, 1)) && ~isequal(size(x, 2), size(y, 2))
312		- error('One of the dimensions of the two arguments must match');
313		- end
314		- if any(diff(x) <= 0)
315		- error('The first argument has to be a monotonically increasing vector');
316		- end
	289	+ if ~isa(numPoints, 'double') \|\| numel(numPoints) > 1 \|\| numPoints < 500
	290	+ error('Third argument must be a scalar greater than 500');
	291	+ end
	292	+ if ~isnumeric(x) \|\| ~isnumeric(y)
	293	+ error('Arguments must be numeric');
	294	+ end
	295	+ if length(size(x)) > 2 \|\| length(size(y)) > 2
	296	+ error('Only 2-D data accepted');
	297	+ end
	298	+
	299	+ % If only one input, create index vector X
	300	+ if isempty(x)
	301	+ if ismember(1, size(y))
	302	+ x = reshape(1:numel(y), size(y));
	303	+ else
	304	+ x = (1:size(y, 1))';
	305	+ end
	306	+ end
	307	+
	308	+ if ~ismember(1, size(x))
	309	+ error('First argument has to be a vector');
	310	+ end
	311	+ if ~isequal(size(x, 1), size(y, 1)) && ~isequal(size(x, 2), size(y, 2))
	312	+ error('One of the dimensions of the two arguments must match');
	313	+ end
	314	+ if any(diff(x) <= 0)
	315	+ error('The first argument has to be a monotonically increasing vector');
	316	+ end
317	317	end
318	318
319	319	end
...	...	@@ -5,20 +5,20 @@
5	5	mult = eval(argv(){3});
6	6
7	7	if length(col) == length(mult)
8		- figure
9		- hold all
10		- grid on
11		- cc = 'bkcgmry';
12		- for i = [1:length(col)]
13		- data.freq = load(filename)(:,col(i)).*mult(i);
14		- data.rate = 1;
15		- [p, f] = pwelch(data.freq, [], 0.95, [], data.rate.*mult(i), 'onesided');
16		- semilogx(f, 10*log10(p), cc(mod(i, length(cc))))
17		- leg{i} = strcat(filename, ' col', num2str(col(i)));
18		- hold on
19		- end
20		- legend(leg)
21		- input("Press to continue...");
	8	+ figure
	9	+ hold all
	10	+ grid on
	11	+ cc = 'bkcgmry';
	12	+ for i = [1:length(col)]
	13	+ data.freq = load(filename)(:,col(i)).*mult(i);
	14	+ data.rate = 1;
	15	+ [p, f] = pwelch(data.freq, [], 0.95, [], data.rate.*mult(i), 'onesided');
	16	+ semilogx(f, 10*log10(p), cc(mod(i, length(cc))))
	17	+ leg{i} = strcat(filename, ' col', num2str(col(i)));
	18	+ hold on
	19	+ end
	20	+ legend(leg)
	21	+ input("Press to continue...");
22	22	end
23	23	exit