On 11/2/24 08:14, Dr. Jürgen Sauermann
wrote:
Hi Hendrik,
I am wondering if it may make sense to make those functions
built-ins?
As of today only QR-factorization is built-in but I always felt
that that
may be too little (at least if compared to packages like e.g.
LApack),
with f being a function selector or a function name like in ⎕FX
and ⎕CR.
Best Regards,
Jürgen
All these functions could be accessed as either ⌹[f]B or as A[f]B
On 10/30/24 15:58, Henrik Moller
wrote:
Earlier this year, I put a native function
package, catted "mtx," on GitHub. I've no idea if anyone is
using it, but I just put up a new release. The biggest change
is that the new version uses the GNU gsl library rather than
an ad-hoc eigensystems package I used in the first release, so
the new version is easier to install.
A new feature is some massaging of the covariance and
eigensystems code to allow principal component analysis of
statistical data*--see the README for an example. That's in
addition to the existing capabilities:
- Matrix determinants
- Matrix eigenvalues and eigenvectors
- Identity matrices
- Vector cross products
- Vector interior angles
- Vector or scalar rotation matrices
- Gaussian complex random values
- Vector/matrix normalisation
- Homogeneous matrices
- Covariance
Anyway, it's at github.com/ChrisMoller/mtx
* One of my sons is a medical physicist and one the newer
things in that is using PCA to use sampled radiomic data to
model the shapes of cancerous regions. He asked me for the
capability, but I have no idea how useful it will be for
anyone else.