From bedf0131c692575554869eab146bfab696807a83 Mon Sep 17 00:00:00 2001
From: marwan <>
Date: Mon, 22 Oct 2012 14:18:33 +0000
Subject: [PATCH] bug fix: normalisation of data when data contains Inf
---
crp.m | 22 +++++++++++++++-------
crp2.m | 39 +++++++++++++++++++++++++++------------
crp_big.m | 25 +++++++++++++++++--------
3 files changed, 59 insertions(+), 27 deletions(-)
diff --git a/crp.m b/crp.m
index b7460cd..9ad81bd 100644
--- a/crp.m
+++ b/crp.m
@@ -38,7 +38,7 @@ function xout=crp(varargin)
% minnorm - Minimum norm.
% nrmnorm - Euclidean norm between normalized vectors
% (all vectors have the length one).
-% maxnorm - Maximum norm, fixed recurrence rate.
+% rr - Maximum norm, fixed recurrence rate.
% fan - Fixed amount of nearest neighbours.
% inter - Interdependent neighbours.
% omatrix - Order matrix.
@@ -84,6 +84,9 @@ function xout=crp(varargin)
% $Revision$
%
% $Log$
+% Revision 5.16 2010/06/29 12:46:47 marwan
+% bug in checking the lengths of x and y
+%
% Revision 5.15 2009/03/24 08:31:17 marwan
% copyright address changed
%
@@ -288,22 +291,27 @@ if isnumeric(varargin{1}) % read commandline input
errordlg('The embedding vectors cannot be created. Dimension M and/ or delay T are to big. Please use smaller values.','Dimension/ delay to big')
waitforbuttonpress
end
+ % normalise the data
if size(x,2)>=2
xscale=x(:,1);
if ~isempty(find(diff(xscale)<0)), error('First column of the first vector must be monotonically non-decreasing.'),end
- if nonorm==1, x=(x(:,2)-mean(x(:,2)))/std(x(:,2)); else x=x(:,2); end
+ idx = find(~isinf(x(:,2)));
+ if nonorm==1, x=(x(:,2)-mean(x(idx,2)))/std(x(idx,2)); else x=x(:,2); end
else
- if nonorm==1, x=(x-mean(x))/std(x); end
+ idx = find(~isinf(x));
+ if nonorm==1, x=(x-mean(x(idx)))/std(x(idx)); end
xscale=(1:length(x))';
end
if size(y,2)>=2
yscale=y(:,1);
if ~isempty(find(diff(yscale)<0)), error('First column of the second vector must be monotonically non-decreasing.'),end
- if nonorm==1, y=(y(:,2)-mean(y(:,2)))/std(y(:,2)); else y=y(:,2); end
+ idx = find(~isinf(y(:,2)));
+ if nonorm==1, y=(y(:,2)-mean(y(idx,2)))/std(y(idx,2)); else y=y(:,2); end
else
- if nonorm==1, y=(y-mean(y))/std(y); end
- yscale=(1:length(y))';
+ idx = find(~isinf(y));
+ if nonorm==1, y=(y-mean(y(idx)))/std(y(idx)); end
+ yscale=(1:length(y))';
end
ds=eye(m);
@@ -692,7 +700,7 @@ switch(action)
if check_stop(hCRP,hCtrl,nogui,obj), return, end
set(findobj('Tag','Status','Parent',findobj('Parent',hCRP,'Tag','CRPPlot')'),'String','Building CRP Matrix'),drawnow
- X=(uint8(255*s/max(s(:)))<(255*e/max(s(:))))'; clear s s1 x1 y1 px py
+ X=uint8((s/max(s(:)))<(e/max(s(:))))'; clear s s1 x1 y1 px py
matext=[num2str(round(100*e)/100) unit ' (normalized distance euclidean norm)'];
diff --git a/crp2.m b/crp2.m
index 2fdc261..bb870f4 100644
--- a/crp2.m
+++ b/crp2.m
@@ -37,7 +37,7 @@ function xout=crp2(varargin)
% minnorm - Minimum norm.
% nrmnorm - Euclidean norm between normalized vectors
% (all vectors have the length one).
-% maxnorm - Maximum norm, fixed recurrence rate.
+% rr - Maximum norm, fixed recurrence rate.
% fan - Fixed amount of nearest neighbours.
% omatrix - Order matrix (disabled).
% opattern - Order patterns recurrence plot.
@@ -86,6 +86,9 @@ function xout=crp2(varargin)
% $Revision$
%
% $Log$
+% Revision 5.18 2010/06/29 12:47:30 marwan
+% some minor bugs in output and test of time series lengths (of x and y)
+%
% Revision 5.17 2009/03/24 08:31:17 marwan
% copyright address changed
%
@@ -295,19 +298,31 @@ if isnumeric(varargin{1}) % read commandline input
'Either too much NaN or the number of columns in the vectors do not match.'])
end
- Nx=size(x,1); Ny=size(y,1);
- NX=Nx-t*(m0-1);NY=Ny-t*(m0-1);
- x0=zeros(Nx,m);y0=zeros(Ny,m);
- x0(1:size(x,1),1:size(x,2))=x;
- y0(1:size(y,1),1:size(y,2))=y;
-
- if nonorm==1,
- x=(x0-repmat(mean(x0),Nx,1))./repmat(std(x0),Nx,1);
- y=(y0-repmat(mean(y0),Ny,1))./repmat(std(y0),Ny,1);
- end
+ Nx=size(x,1); Ny=size(y,1);
+ NX=Nx-t*(m0-1);NY=Ny-t*(m0-1);
+ x0=zeros(Nx,m);y0=zeros(Ny,m);
+ x0(1:size(x,1),1:size(x,2))=x;
+ y0(1:size(y,1),1:size(y,2))=y;
+
+ % normalise the data
+ if nonorm == 1,
+ for k = 1:size(x0,2)
+ idx = find(~isinf(x0(:,k)));
+ stdx = std(x0(idx,k));
+ meanx = mean(x0(idx,k));
+ x(:,k) = (x0(:,k) - meanx) / stdx;
+ end
+ for k = 1:size(y0,2)
+ idy = find(~isinf(x0(:,k)));
+ stdy = std(y0(idy,k));
+ meany = mean(y0(idy,k));
+ y(:,k) = (y0(:,k) - meany) / stdy;
+ end
+ end
if ~isempty(find(isnan(x))), for k=1:size(x,2), x(find(isnan(x(:,k))),:)=[]; end, end
if ~isempty(find(isnan(y))), for k=1:size(y,2), y(find(isnan(y(:,k))),:)=[]; end, end
+
if size(x,1) < t*(m0-1)+1 | size(y,1) < t*(m0-1)+1
error(['Too less data',10,...
'Either too much NaN or the number of columns in the vectors do not match.'])
@@ -1118,7 +1133,7 @@ switch(action)
if check_stop(hCRP,hCtrl,nogui,obj), return, end
set(findobj('Tag','Status','Parent',findobj('Parent',hCRP,'Tag','CRPPlot')),'String','Building CRP Matrix'),drawnow
- X=reshape(uint8(255*s/max(s))<(255*e/max(s)),Ny,Nx); clear s x1 y1
+ X=uint8(reshape((s/max(s))<(e/max(s)),Ny,Nx)); clear s x1 y1
matext=[num2str(round(100*e)/100) unit ' (normalized distance euclidean norm)'];
diff --git a/crp_big.m b/crp_big.m
index cb7643a..095e947 100644
--- a/crp_big.m
+++ b/crp_big.m
@@ -40,7 +40,7 @@ function xout=crp_big(varargin)
% minnorm - Minimum norm.
% nrmnorm - Euclidean norm between normalized vectors
% (all vectors have the length one).
-% maxnorm - Maximum norm, fixed recurrence rate.
+% rr - Maximum norm, fixed recurrence rate.
% fan - Fixed amount of nearest neighbours.
% inter - Interdependent neighbours.
% omatrix - Order matrix.
@@ -82,6 +82,9 @@ function xout=crp_big(varargin)
% $Revision$
%
% $Log$
+% Revision 5.14 2010/06/29 12:48:16 marwan
+% bug in checking the lengths of x and y
+%
% Revision 5.13 2009/03/24 08:31:17 marwan
% copyright address changed
%
@@ -278,21 +281,27 @@ if isnumeric(varargin{1})==1 % read commandline input
errordlg('The embedding vectors cannot be created. Dimension M and/ or delay T are to big. Please use smaller values.','Dimension/ delay to big')
waitforbuttonpress
end
+ % normalise the data
if size(x,2)>=2
xscale=x(:,1);
if ~isempty(find(diff(xscale)<0)), error('First column of the first vector must be monotonically non-decreasing.'),end
- if nonorm==1, x=(x(:,2)-mean(x(:,2)))/std(x(:,2)); else x=x(:,2); end
+ idx = find(~isinf(x(:,2)));
+ if nonorm==1, x=(x(:,2)-mean(x(idx,2)))/std(x(idx,2)); else x=x(:,2); end
else
- if nonorm==1, x=(x-mean(x))/std(x); end
+ idx = find(~isinf(x));
+ if nonorm==1, x=(x-mean(x(idx)))/std(x(idx)); end
xscale=(1:length(x))';
end
+
if size(y,2)>=2
yscale=y(:,1);
if ~isempty(find(diff(yscale)<0)), error('First column of the second vector must be monotonically non-decreasing.'),end
- if nonorm==1, y=(y(:,2)-mean(y(:,2)))/std(y(:,2)); else y=y(:,2); end
+ idx = find(~isinf(y(:,2)));
+ if nonorm==1, y=(y(:,2)-mean(y(idx,2)))/std(y(idx,2)); else y=y(:,2); end
else
- if nonorm==1, y=(y-mean(y))/std(y); end
- yscale=(1:length(y))';
+ idx = find(~isinf(y));
+ if nonorm==1, y=(y-mean(y(idx)))/std(y(idx)); end
+ yscale=(1:length(y))';
end
ds=eye(m);
@@ -704,7 +713,7 @@ switch(action)
matext=[num2str(round(100*e)/100) unit ' (fixed distance minimum norm)'];
end
- X1=255*s/max(s(:))<(255*e/max(s(:)));
+ X1=s/max(s(:))<(e/max(s(:)));
X0=(uint8(X1))'; clear s s1 x1 y1 px py X1
X(1+Ny2*(j-1):Ny2+Ny2*(j-1),1+Nx2*(i-1):Nx2+Nx2*(i-1))=X0;
X(NY0+1:end,:)=[];
@@ -731,7 +740,7 @@ switch(action)
s1 = px(:,ones(1,NY),:) - py(ones(1,NX),:,:);
s = sqrt(sum(s1.^2, 3));
- X0=(uint8(255*s/max(s(:)))<(255*e/max(s(:))))'; clear s s1 x1 y1 px py
+ X0=uint8((s/max(s(:)))<(e/max(s(:))))'; clear s s1 x1 y1 px py
X(1+Ny2*(j-1):Ny2+Ny2*(j-1),1+Nx2*(i-1):Nx2+Nx2*(i-1))=X0;
X(NY0+1:end,:)=[];
--
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