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Principal Component Analysis of Data Cube - Example 2.

( PCA on a reduced cube.)

     Load cube

          Make plot of spectra with entire cube: Data Cube / plot / sum spect for whole cube

          Select peaks as separate layers

               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 of original cube (less blank images).

               Show all the score images separately:

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