function out=crqad(varargin)
% CRQAD Computes and plots the diagonalwise CRQA measures.
% Y=CRQAD(X [,Y] [,param1,param2,...])
% Recurrence quantification analysis of diagonals in the
% cross recurrence plot of the vectors X and Y as well as
% X and -Y. The output is a structure (see below).
%
% The input vectors can be multi-column vectors, where
% each column will be used as a component of the
% phase-space vector. However, if the first column is
% monotonically increasing, it will be used as an
% time scale for plotting.
%
% Y=CRQAD(X,M,T,E,W,LMIN) computes the recurrence
% quantification analysis of the recurrence plot
% of X by using the dimension M, delay T, the
% size of neighbourhood E, for the diagonals within
% the range [-W,W] around the main diagonal. Variable LMIN
% sets the minimal length of what should be considered
% to be a diagonal line.
%
% Parameters: dimension M, delay T, the size of
% neighbourhood E and the range size W are the first
% five numbers after the data series; if W is empty,
% the whole plot will be calculated. Further parameters
% can be used to switch between various methods of finding
% the neighbours of the phasespace trajectory, to suppress
% the normalization of the data and to suppress the GUI
% (useful in order to use this programme by other programmes).
%
% Methods of finding the neighbours.
% maxnorm - Maximum norm.
% euclidean - Euclidean norm.
% minnorm - Minimum norm.
% nrmnorm - Euclidean norm between normalized vectors
% (all vectors have the length one).
% maxnorm - Maximum norm, fixed recurrence rate.
% fan - Fixed amount of nearest neighbours.
% inter - Interdependent neighbours.
% omatrix - Order matrix.
% opattern - Order patterns recurrence plot.
%
% Normalization of the data series.
% normalize - Normalization of the data.
% nonormalize - No normalization of the data.
%
% Parameters not needed to be specified.
%
% Output:
% Y.RRp = RRp
% Y.RRm = RRm
% Y.DETp = DETp
% Y.DETm = DETm
% Y.Lp = Lp
% Y.Lm = Lm
%
% Examples: a = sin(0:.1:80) + randn(1,801);
% b = sin(0:.1:80) + randn(1,801);
% crqad(a,b,3,15,.1,100,'fan')
%
% See also CRQA, CRQAD_BIG, CRP, CRP2, CRP_BIG, DL, TT, RPDE.
%
% References:
% Marwan, N., Kurths, J.:
% Nonlinear analysis of bivariate data with cross recurrence plots,
% Phys. Lett. A, 302, 2002.
% Copyright (c) 2008-2009
% Norbert Marwan, Potsdam Institute for Climate Impact Research, Germany
% http://www.pik-potsdam.de
%
% Copyright (c) 2002-2008
% Norbert Marwan, Potsdam University, Germany
% http://www.agnld.uni-potsdam.de
%
% $Date$
% $Revision$
%
% $Log$
% Revision 2.10 2010/06/30 12:03:02 marwan
% Help text modified
%
% Revision 2.9 2009/03/24 08:35:19 marwan
% corrected XCF calculation
%
% Revision 2.8 2007/07/18 17:18:44 marwan
% integer values in the arguments supported
%
% Revision 2.7 2007/05/15 17:33:13 marwan
% new neighbourhood criterion: fixed RR
%
% Revision 2.6 2006/10/24 14:16:16 marwan
% minor change: sigma in title line of RP shown only for normalised data
%
% Revision 2.5 2006/07/04 14:03:57 marwan
% axis-error
%
% Revision 2.4 2005/03/16 11:19:02 marwan
% help text modified
%
% Revision 2.3 2004/11/12 08:40:46 marwan
% order patterns recurrence plot added
%
% Revision 2.2 2004/11/10 07:05:55 marwan
% initial import
%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% programme properties
global props
init_properties
lmin_default=2;
w=[]; method='max'; method_n=1; t=1; m=1; e=.1;
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% check the input
error(nargchk(1,10,nargin));
if nargout>1, error('Too many output arguments'), end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% splash the GPL
splash_gpl('crp');
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% check and read the input
varargin{11}=[];
% transform any int to double
intclasses = {'uint8';'uint16';'uint32';'uint64';'int8';'int16';'int32';'int64'};
flagClass = [];
for i = 1:length(intclasses)
i_int=find(cellfun('isclass',varargin,intclasses{i}));
if ~isempty(i_int)
for j = 1:length(i_int)
varargin{i_int(j)} = double(varargin{i_int(j)});
end
flagClass = [flagClass; i_int(:)];
end
end
if ~isempty(flagClass)
disp(['Warning: Input arguments at position [',num2str(flagClass'),'] contain integer values']);
disp(['(now converted to double).'])
end
i_double=find(cellfun('isclass',varargin,'double'));
i_char=find(cellfun('isclass',varargin,'char'));
nogui=0;
if nargin & isnumeric(varargin{1})
% check the text input parameters for method, gui
check_meth={'ma','eu','mi','nr','rr','fa','in','om','op','di'}; % maxnorm, euclidean, nrmnorm, fan, distance
check_gui={'gui','nog','sil'}; % gui, nogui, silent
temp_meth=0;
temp_gui=0;
if ~isempty(i_char)
for i=1:length(i_char),
varargin{i_char(i)}(4)='0';
temp_gui=temp_gui+strcmpi(varargin{i_char(i)}(1:3),check_gui');
temp_meth=temp_meth+strcmpi(varargin{i_char(i)}(1:2),check_meth');
end
method_n=min(find(temp_meth));
nogui=min(find(temp_gui))-1;
for i=1:length(i_char); temp2(i,:)=varargin{i_char(i)}(1:3); end
i_char(strmatch(check_gui(find(temp_gui)),temp2))=[];
if isempty(nogui), nogui=0; end
if isempty(method_n), method_n=1; end
if nogui>2, nogui=1; end
if method_n>length(check_meth), method0=length(check_meth); end
method=check_meth{method_n};
else
nogui=0;
if nargout
nogui=1;
action='compute';
end
end
if nogui==0
action='init';
else
action='compute';
end
% get the parameters for creating RP
if max(size(varargin{1}))<=3
error('To less values in data X.')
end
x=double(varargin{1});
if isempty(varargin{2}) | ~isnumeric(varargin{2}), y=x; else
y=double(varargin{2}); end
if sum(double(diff(x(:,1))<=0)), embed_flag=0; end
if (isnumeric(varargin{2}) & max(size(varargin{2}))==1) | ~isnumeric(varargin{2})
y=x;
if ~isempty(varargin{i_double(2)}), m=varargin{i_double(2)}(1); else m=1; end
if ~isempty(varargin{i_double(3)}), t=varargin{i_double(3)}(1); else t=1; end
if ~isempty(varargin{i_double(4)}), e=varargin{i_double(4)}(1); else e=.1; end
if ~isempty(varargin{i_double(5)}), w=varargin{i_double(5)}(1); else w=varargin{i_double(5)}; end
if ~isempty(varargin{i_double(6)}), lmin=varargin{i_double(6)}(1); else lmin=lmin_default; end
else
if ~isempty(varargin{i_double(3)}), m=varargin{i_double(3)}(1); else m=1; end
if ~isempty(varargin{i_double(4)}), t=varargin{i_double(4)}(1); else t=1; end
if ~isempty(varargin{i_double(5)}), e=varargin{i_double(5)}(1); else e=.1; end
if ~isempty(varargin{i_double(6)}), w=varargin{i_double(6)}(1); else w=varargin{i_double(6)}; end
if ~isempty(varargin{i_double(7)}), lmin=varargin{i_double(7)}(1); else lmin=lmin_default; end
end
else
error('No valid arguments.')
end
Nx=length(x); Ny=length(y);
if size(x,1)<size(x,2), x=x'; end
if size(y,1)<size(y,2), y=y'; end
if size(x,2)>=2
xscale=x(:,1);
if ~isempty(find(diff(xscale)<0)), embed_flag=0;end
else
xscale=(1:length(x))';
end
if size(y,2)>=2
yscale=y(:,1);
if ~isempty(find(diff(yscale)<0)), embed_flag=0;end
else
yscale=(1:length(y))';
end
if max(size(x))~=max(size(y)),
if ~nogui, errordlg('Data must have the same length.','Check Data'), else error('Data must have the same length.'), end
end
if e<0,
e=1;
if ~nogui
warndlg('The threshold size E can not be negative and is now set to 1.','Check Data')
h=findobj('Tag','crqa_eps');
set(h(1),'String',str2num(e))
else
disp('The threshold size E can not be negative and is now set to 1.'),
end
end
if t<1,
t=1;
if ~nogui
warndlg('The delay T can not be smaller than one and is now set to 1.','Check Data')
h=findobj('Tag','crqa_maxLag');
set(h(1),'String',str2num(t))
else
disp('The delay T can not be smaller than one and is now set to 1.')
end
end
if isempty(w), w=.5*Nx; wstep=1; end
% if w<2,
% w=2;
% if ~nogui, warndlg('The window size W exceeds the valid range.','Check Data')
% else, disp('The window size W exceeds the valid range.'), end
% end
if w>Nx,
w=Nx; wstep=1;;
if ~nogui, warndlg('The window size W exceeds the valid range.','Check Data')
else, disp('The window size W exceeds the valid range.'), end
end
t=round(t); m=round(m); w=round(w);% wstep=round(wstep);
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% compute
flag=1;
x1=x; x2=y;
if length(method)>1 & strcmpi(method(1:2),'di')
disp('Warning: RQA from distance plot not possible!')
return
end
warning off
if size(x1,1)<size(x1,2), x1=x1'; end
if size(x2,1)<size(x2,2), x2=x2'; end
x=crp2(x1,x2,m,t,e,method,'sil','nor');
warning off
N=size(x);
x3=zeros(2*N(2)+N(1),N(2));
x3(N(2)+1:N(2)+N(1),1:N(2))=x;
N3=size(x3);
i2=repmat(((1:1+N(2))+N(1)+N(2))',1,N(2));
i4=i2+repmat((2*N(2)+N(1)+1)*[0:N(2)-1],size(i2,1),1);
i4(:,end)=[]; i4=reshape(i4,size(i4,1)*size(i4,2),1);
x3(i4)=[]; x3(end)=[];
x4=(reshape(x3,N(1)+N(2),N(2)))'; x4(end+1,:)=0;
i=1; clear DET L RR
for j=-w:w, clear z z0 z1
if sum(x4(:,N(2)+1+j))==N(2), l1=N(2);else
z=diff(x4(:,N(2)+1+j));
if ~isempty(find(~(z-1))) & any(~(z-1))
z0(:,1)=find(~(z-1));
else
z0(1:N(2))=0;
end
if ~isempty(find(~(z+1))) & any(~(z+1))
z1=find(~(z+1));
else
z1(1:N(2))=0;
end
% some brutforce corrections
adjustlength = min(length(z0), length(z1));
z0 = z0(1:adjustlength);
z1 = z1(1:adjustlength);
if z0(1)>z1(1)
z0(2:end+1,1)=z0(1:end);z0(1)=0;
if length(z0)>length(z1), z0(end)=[]; end
end
l=sort(z1-z0); l1=l(find(l>lmin));
end
DET(i)=sum(l1)/sum(x4(:,N(2)+1+j));
L(i)=mean(l1);
RR(i)=sum(x4(:,N(2)+1+j))/(N(2)-abs(j));
i=i+1;
end
L(find(isnan(L)))=0;
RR(find(isnan(RR)))=0;
DET(find(isnan(DET)))=0;
if nargout, XCF=xcf(x1,x2,w,1); end
if ~nargout
subplot(2,2,1)
clim=1;
xcf(x1(:,1),x2(:,1),w)
set(gca,'fonta','i')
xlabel('Lag'), axis([-w w -clim clim])
ylabel('Cross Correlation')
h=text(0,0,'A','fontw','b');set(h,'un','pi'),set(h,'pos',[9,16,0])
switch flag
case 1
subplot(2,2,2), plot([-w:w],RR,'k','linew',.7),
set(gca,'fonta','i'),axis([-w w 0 1])
xlabel('Lag'),ylabel('Recurrence Rate'),grid on
h=text(0,0,'B','fontw','b');set(h,'un','pi'),set(h,'pos',[9,16,0])
subplot(2,2,3), plot([-w:w],DET,'k','linew',.7),
set(gca,'fonta','i'),xlabel('Lag')
axis([-w w 0 1]),ylabel('Determinism'),grid on
h=text(0,0,'C','fontw','b');set(h,'un','pi'),set(h,'pos',[9,16,0])
subplot(2,2,4), plot([-w:w],L,'k','linew',.7),
set(gca,'fonta','i'),xlabel('Lag')
axis([-w w 0 max([max(L) 1])]),ylabel('Averaged Line Length'),grid on
h=text(0,0,'D','fontw','b');set(h,'un','pi'),set(h,'pos',[9,16,0])
case 2
subplot(2,2,2), plot([-w:w],smooth(RR,5,5),'k','linew',.7),
set(gca,'fonta','i'),axis([-w w 0 1])
xlabel('Lag'),ylabel('Recurrence Rate'),grid on
h=text(0,0,'B','fontw','b');set(h,'un','pi'),set(h,'pos',[9,16,0])
subplot(2,2,3), plot([-w:w],smooth(DET,5,5),'k','linew',.7),
set(gca,'fonta','i'),xlabel('Lag')
axis([-w w 0 1]),ylabel('Determinism'),grid on
h=text(0,0,'C','fontw','b');set(h,'un','pi'),set(h,'pos',[9,16,0])
subplot(2,2,4), plot([-w:w],smooth(L,5,5),'k','linew',.7),
set(gca,'fonta','i'),xlabel('Lag')
axis([-w w 0 max(L)]),ylabel('Averaged Line Length'),grid on
h=text(0,0,'D','fontw','b');set(h,'un','pi'),set(h,'pos',[9,16,0])
end
else
out.XCF=XCF';
out.RRp=RR;
out.DETp=DET;
out.Lp=L;
end
x=crp2(x1,-x2,m,t,e,method,'sil');
warning off
N=size(x);
x3=zeros(2*N(2)+N(1),N(2));
x3(N(2)+1:N(2)+N(1),1:N(2))=x;
N3=size(x3);
i2=repmat(((1:1+N(2))+N(1)+N(2))',1,N(2));
i4=i2+repmat((2*N(2)+N(1)+1)*[0:N(2)-1],size(i2,1),1);
i4(:,end)=[]; i4=reshape(i4,size(i4,1)*size(i4,2),1);
x3(i4)=[]; x3(end)=[];
x4=(reshape(x3,N(1)+N(2),N(2)))'; x4(end+1,:)=0;
i=1; clear DET L RR
for j=-w:w, clear z z0 z1
if sum(x4(:,N(2)+1+j))==N(2), l1=N(2);else
z=diff(x4(:,N(2)+1+j));
if ~isempty(find(~(z-1))),z0(:,1)=find(~(z-1));else,z0(1:N(2))=0;end,
if ~isempty(find(~(z+1))),z1=find(~(z+1));else,z1(1:N(2))=0;end
if z0(1)>z1(1)
z0(2:end+1,1)=z0(1:end);z0(1)=0;
if length(z0)>length(z1), z0(end)=[]; end
end
l=sort(z1-z0); l1=l(find(l>lmin));
end
DET(i)=sum(l1)/sum(x4(:,N(2)+1+j));
L(i)=mean(l1);
RR(i)=sum(x4(:,N(2)+1+j))/(N(2)-abs(j));
i=i+1;
end
L(find(isnan(L)))=0;
RR(find(isnan(RR)))=0;
DET(find(isnan(DET)))=0;
if ~nargout
switch flag
case 1
subplot(2,2,2), hold on, plot([-w:w],RR,'r','linew',.7), hold off, set(gca,'YLimMode','Auto')
subplot(2,2,3), hold on, plot([-w:w],DET,'r','linew',.7), hold off, hold off, set(gca,'YLimMode','Auto')
subplot(2,2,4), hold on, plot([-w:w],L,'r','linew',.7), hold off, hold off, set(gca,'YLimMode','Auto')
case 2
subplot(2,2,2), hold on, plot([-w:w],smooth(RR,5,5),'r','linew',.7), hold off, hold off, set(gca,'YLimMode','Auto')
subplot(2,2,3), hold on, plot([-w:w],smooth(DET,5,5),'r','linew',.7), hold off, hold off, set(gca,'YLimMode','Auto')
subplot(2,2,4), hold on, plot([-w:w],smooth(L,5,5),'r','linew',.7), hold off, hold off, set(gca,'YLimMode','Auto')
end
else
out.RRm=RR;
out.DETm=DET;
out.Lm=L;
end
warning on