Quantitative Analysis
Parallel Processing
Numerical Analysis
C++ Multithreading
Python for Excel
Python Utilities

I. Python Object Browser.
II. Python to R Communicator.
1. Why not use RPy?
2. Example of R communication.
3. Under the hood of Python to R Communicator.
4. Installation procedure for Python to R Communicator.
5. Types of data acceptable by R Communicator.
III. Manipulation of piecewise polynomial functions.
IV. Building C++ projects.
Downloads. Index. Contents.

Types of data acceptable by R Communicator.

he R Communicator accepts lists of either 'numeric' or 'character' and matrixes of 'numeric' on R side.

It accepts strings, integers, floatings, lists and numpy.matrixes on the Python side.

To implement custom data marshaling, examine the files channel.py, io.py and make additions to io.py using the existing code as a recipe. The R code needs not to be changed.

Downloads. Index. Contents.

Copyright 2007