## ./

# cnb_pca.pro

## Routines

`cnb_pca, data, eval, evec [, mean=mean]`

This procedure calculates the principal components of a dataset.

`test`

## Routine details

## topcnb_pca

`cnb_pca, data, eval, evec [, mean=mean]`

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.

### Parameters

- data in required
An n_dim x n_data array of data points

- eval
- evec

### Keywords

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

## toptest

`test`

## File attributes

Modifcation date: | Fri Jun 11 18:41:28 2010 |

Lines: | 134 |