Hello,

I am writing a tool that needs some linear algebra so I am using Eigen for the first time. The tool will do something like the following,

1. import data from a text file
input data will be floating point rows and columns

2. perform PCA on input data and create an eigenvector transformed copy of the input data
The requirement is to convert the input data to a fully orthogonal form.

If it is not convenient to do the PCA with Eigen I can generate the PCA with other tools for now. I found this code for PCA with Eigen,
http://www.di.unipi.it/%7Egulli/coding/pca_eigen.zip
at this blog
http://codingplayground.blogspot.com/20 ... eigen.html
but I haven't had a chance to look at the code very carefully

3. specific data (rows) will be extracted from the PC copy and used to populate a matrix x.
for now, all input rows will be used to create the matrix

4. create matrix x' by transposing x

5. multiply x' by x to create square matrix x'x

6. take the determinant of x'x

I will be sequentially removing rows from x and repeating the procedure to observe the effect on the determinant. I guess the main thing I need to know is which header files I need to include for PCA, transposition, matrix multiplication, and calculating the determinant. It would also help to have the documentation on those functions so I can see what format the data should be stored in, etc. Code samples for anything similar are always useful as well.

Please let me know if you can help and thanks.

LMHmedchem