PCA |.  PCA demo 1

PCA Tutorial 2

• Load cube
• Tools / import / i/o / import from file
• Select demo-images / date-cubes / Enk / 128-96-100.raw.
• (credit)
• If a .rpl file is there, the parameters in the import window do not need to be initialized.
• resize
• See cube image window - appears black. Slide the slider - see different slices.
• Make plot of spectra with entire cube:
• Select / rectangle - select all. (see yellow rectangle in cube window).
• Data Cube / plot / of spect w/in rectangle
• 
• Select peaks as separate layers
• data cube / slider / layers
• Select 7 layers, adjust sliders to enclose peaks.
• 
• Make new cube with summed layers. 'cube / from layers. Note that this cube has only 7 slices, rather than 101. However none of the 'counts' are lost - but summed. Note that the cube as read in uses 2 bytes, but that 'info / size and limits' shows that none of the pixels is over 1 byte. A new cube taking half of the memory could be made using ' cube / clip to byte', without loosing any data.
• 
• Do principal component analysis of the summed cube:   PCA / 1 Eigenvalues
• 

Note - a blank cube image (a mean centered copy of the original cube) is made. It can be used in place of the original, or closed. To see slices, make a slider: 'slider / view slice'.

• Show all the score images separately:
• 'image / slices to windows', take default (0 6) of all images.
• See 7 images being made.
• shift / resize.
• Click on score image 6, 5, ... 0. Temporarily reduce size of large background window. Tile.
• 

I didn't clean up the background before taking this last screen snapshot.

• Scatter diagrams, color overlays can be made with these score images.