Popsom7

Fixed a fatal bug in `map_build` in the Python release.

This release reintroduced our fast, vectorized training algorithm for SOM with substantial improvements. In R it is about an order of magnitude faster than the canonical, stochastic C implementation of the training algorithm.

In the Python version worked on the quality of the generated map.

What's Changed
* Vsom algorithm integration by lutzhamel in https://github.com/lutzhamel/popsom7/pull/25
* Merging 7.1.0 changes into main by lutzhamel in https://github.com/lutzhamel/popsom7/pull/26


**Full Changelog**: https://github.com/lutzhamel/popsom7/compare/v7.0.0...v7.1.0

What's Changed
* Popsom7 by lutzhamel in https://github.com/lutzhamel/popsom7/pull/20
* edits by lutzhamel in https://github.com/lutzhamel/popsom7/pull/21


**Full Changelog**: https://github.com/lutzhamel/popsom7/compare/v6.0...v7.0.0

- Renamed the functions in the interface to avoid collisions with S3 functions within the R environment. We know that this is another renaming of the POPSOM interface and we apologize for any inconvenience. We expect that the interface is now stable for the foreseeable future.
- New features:
* The `map.minimal` object. This is an object that only contains the trained neurons and nothing else. This is an appropriate model when POPSOM is used as a preprocessing step and no other model information is needed. Note that `map.minimal` objects cannot be processed by any of the other functions in the POPSOM interface.
* The `map.convergence` function provides details about the underlying convergence characteristics.
- Bugfixes
* Most importantly the artificial limit of a minimum of 50 instances in the training
data has been removed.

Reworked the description of the package in order to reflect the capabilities of the package better.

* Something got rattled with the S3 interface in R 4.x. It no longer works the way it did in release 3.x. Therefore, I took the S3 interface out because I want the package to work with both 3.x and 4.x installations. Furthermore, the advantages of the S3 interface are incremental at best and I don't feel like debugging R internals.

* Implemented a 'summary' function for map objects.