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CNB_PCA

CNB_PCA

Purpose


  This procedure calculates the principal components of a
  dataset. Many IDL routines do this, but I don't really
  understand their idiosyncrasies. In particular, the builtin PCOMP
  has weird outputs, and chokes whin n_dim >> 1, n_dim << n_data.
  This procedure efficiently handles that case.
  This procedure is the driver for the PRICOM object class. That
  class has methods for projecting new data on to principal
  components, etc.

Inputs


  data: An n_dim x n_data array of data points
 

Outputs


  eval: The eigenvalues associated with each principal component. The
  eigenvalues are proportional to the scatter of the data projected
  onto the principal component.
  evec: The principal components.
 

Keyword Parameters


  mean: The routine subtracts off the mean data vector before
        performing the analysis. This keyword holds that mean

Modification History


  June 11 2010: Written by Chris Beaumont



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