GUI for Multivariate Image Analysis of Multispectral Images: Cont=Contingency(Mem1,Mem2) - File Exchange

Code covered by the BSD License

Highlights from
GUI for Multivariate Image Analysis of Multispectral Images

histogram(varargin) GUI for Plotting historgam and equalizing image arrays
image_mva(varargin) GUI for Multivariate Analysis of images
profiles(varargin) GUI for plotting profiles for image arrays
threshold(varargin) GUI for thresholding images
Cont=Contingency(Mem1,Mem2) CONTINGENCY Form contigency matrix for two vectors
DCAgg(Distance, Method, k) DCAGG Performs agglomerative clustering
LogFactorial(n) LOGFACTORIAL Calculates the Natural log of the factorial of n
MakeGaussData(NCentres,NDims,... MAKEGAUSSDATA - Creates spherical data clouds
MaxMax(x) MAXMAX Maximum of all elements in an n-dimension array
MeanMean(x) MEANMEAN Mean of all elements in an n-dimension array
MinMin(x) MINMIN Minimum of all elements in an n-dimension array
PCAGraph(X,dims,labels) PCAGRAPH Plots data projected onto its first 2 principal components
SumSum(x) SUMSUM Sums all elements in an n-dimension array
[AR,RI,MI,HI]=RandIndex(c1,c2... RANDINDEX - calculates Rand Indices to compare two partitions
[C,perm]=ChooseInitialCentres... CHOOSEINITIALCENTRES Randomly picks sample points
[Classes,Centres,FinalDistanc... DCKMEANS Performs k-means clustering
[RITrue,RISelf,EstIndex]=DoCl... DOCLUSTERING Performs cluster analysis of specified data using specified
[mix, class,likelihood]=dcEMG... DCEMGMM - estimates Gaussian Mixture Model using the EM algorithm
[purspec,purint,purity_spec]=... function [purspec,purint,purity_spec]=simplisma(data,varlist,offset,n,data2);
array_subset=array_downsizing... function array_subset=array_downsizing(array, N);
c=PlotColour(index,lineflag) PLOTCOLOUR Returns colour and marker string for PLOT
class=im_class_MLE(im,plot); function class=im_class_MLE(im,plot);
data_der=invder(data) data_der=invder(data)
dcFuzzy(X,c,m,InitCentres) DCFUZZY Performs fuzzy c-means clustering
im=vms_im_read(filename,plot)... im=vms_im_read(filename,plot);
threshold_grayscale_image(ori... 431-400 Year Long Project
Contents.m
DcDemo.m
uigetfiles.m
View all files

from GUI for Multivariate Image Analysis of Multispectral Images by Kateryna Artyushkova
A GUI for MIA of multispectral image data sets (PCA, Simplisma, MCR, classification).

Cont=Contingency(Mem1,Mem2)

function Cont=Contingency(Mem1,Mem2)
%CONTINGENCY Form contigency matrix for two vectors
% C=Contingency(Mem1,Mem2) returns contingency matrix for two
% column vectors Mem1, Mem2. These define which cluster each entity 
% has been assigned to.
%
% See also RANDINDEX.
%

%(C) David Corney (2000)   		D.Corney@cs.ucl.ac.uk

if nargin < 2 | min(size(Mem1)) > 1 | min(size(Mem2)) > 1
   error('Contingency: Requires two vector arguments')
   return
end

Cont=zeros(max(Mem1),max(Mem2));

for i = 1:length(Mem1);
   Cont(Mem1(i),Mem2(i))=Cont(Mem1(i),Mem2(i))+1;
end

Highlights from GUI for Multivariate Image Analysis of Multispectral Images

Highlights from
GUI for Multivariate Image Analysis of Multispectral Images