For a reason I haven't quite figured out, the results of PCOMP and the
ENVI results differ by a factor of the square root of the eigenvalue
for the corresponding band.
This works for me:
x = [2.5, 0.5, 2.2, 1.9, 3.1, 2.3, 2.0, 1.0, 1.5, 1.1]
y = [2.4, 0.7, 2.9, 2.2, 3.0, 2.7, 1.6, 1.1, 1.6, 0.9]
;xmean = x - Mean(x)
;ymean = y - Mean(y)
Window, XSIZE=600, YSIZE=800
!P.MULTI=[0,1,2]
Plot, xmean, ymean, PSYM=7
;dataAdjust = Transpose([ [xmean], [ymean] ])
dataAdjust = Transpose([ [x], [y] ])
covArray = Correlate(dataAdjust, /COVARIANCE, /DOUBLE)
eigenvalues = EIGENQL(covArray, EIGENVECTORS=eigenvectors, /DOUBLE)
Print, 'EIGENVALUES: ', eigenvalues
Print, 'EIGENVECTORS: '
Print, eigenvectors
rowFeatureVector = eigenvectors[0,*] ; Take first principle component.
;rowFeatureVector = eigenvectors
finalData = Transpose(rowFeatureVector) ## Transpose(dataAdjust)
Plot, finaldata+Mean(x), finaldata+mean(y), PSYM=7
!P.MULTI=0
; Method using PCOMP in IDL library.
data = Transpose([[x],[y]])
;r = PCOMP(data, /COVARIANCE, NVARIABLES=1, EIGENVALUES=ev, /
STANDARDIZE)
r = PCOMP(data, /COVARIANCE, EIGENVALUES=ev)
Print, 'IDL EIGENVALUES: ', ev
; Compare methods.
Window, 1
;PLOT, r
PLOT, r[0,*] / sqrt(ev[0])
OPLOT, finalData, LINESTYLE=2
Window, 2
PLOT, r[0,*] / sqrt(ev[0]) + Mean(x), r[0,*] / sqrt(ev[0]) + Mean(y),
PSYM=2
;PLOT, r + Mean(x), r + Mean(y), PSYM=2
OPLOT, finalData + Mean(x), finalData + Mean(y), PSYM=7
END
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