CA S - Correspondence Analysis - Solution

PURPOSE

Execute correspondence analysis (CORAN), or Principal Component Analysis (PCA) of image data the solution is found and eigenimages are calculated.

SEE ALSO

CA SM	[Correspondence Analysis - Show Map & Eigen Values]
CA SR	[Correspondence Analysis - Reconstitute images]
CA SRD	[Correspondence Analysis - Reconstitute Differential images]
CA SRI	[Correspondence Analysis - Reconstitute Importance images]
CA SRP	[Correspondence Analysis - PCA reconstitution]
CA VIS	[Correspondence Analysis - Create VISual map]
SD C	[Save Document - from CA S (_IMC) file]

USAGE

.OPERATION: CA S

.ENTER IMAGE FILE TEMPLATE : SEC***
[Enter a file name template identifying the image series to be analyzed.]

.ENTER FILE NUMBERS OR SELECTION DOC. FILE NAME 1-40,45,50-70
[Enter numbers of image files in the series. If the images are supplied as a 3D stack, then the numbers are interpreted as slice numbers.]

.MASK FILE: MAS002
[Enter the name of the file containing a mask. Only image pixels where mask pixels are greater than 0.5 are analyzed in CORAN or PCA. Enter '*' if no masking is desired.]

.NUMBER OF FACTORS: 20
[Enter the number of factors to be used. Note that eigenvectors and eigenvalues are only computed up to this number. ]

.CORAN OR PCA ANALYSIS (C/P): C
[P: Starts Principal Component Analysis. C: Starts Coran Analysis <br>.]

If CORAN is used the following question appears:

.ADDITIVE CONSTANT: 0.0
[CORAN can not accept images with negative values. If images have negative values this can be corrected by specifying an additive constant that will be added to all (within-mask) pixels of all images].

.OUTPUT FILE PREFIX: coran
[Enter the prefix used for the output files where data are to be stored. 'CA S' creates four files to store the results. Their respective names and meanings are
PREFIX_SEQ Sequential file having image values. This file is used to decrease memory requirements.
PREFIX_IMC Text file with image coordinates
PREFIX_PIX Text file with pixel coordinates
PREFIX_EIG Text file with eigenvectors and eigenvalues

NOTES

1. In general, it is advisable to request a large number of factors (even larger than number of pixels under the mask, the system will automatically limit the number of factors to the permitted number).
   

2. WARNING: for very large problems (the size of covariance matrix in the order of thousands) the methods used are very slow and inaccurate, the system may fail on numerical accuracy.

SUBROUTINES

JPMSK1, SCORAN3, INCOR3, GETCOO, STOCHA, ORDERE, PCA_MAIN, FILELIST

CALLER

UTIL1