This document summarizes experiments with the Jupyter Kernel for C++. It covers creating a simple C++ program in Jupyter, invoking C++ help, using Xwidgets with observer functions, and invoking the Armadillo linear algebra library for tasks like principal component analysis. The goal is to demonstrate how Jupyter can provide an intuitive interface for C++ similar to languages like Python and R. Setup instructions are provided to replicate the environment.

1. C++ Jupyter Kernel
Kasturi Murthy, PhD

2. Introduction
●
C++ is a very powerful language but lacks intutive character
that programming languages like R and Python offer in the
backdrop of Jupyter Kernel
●
This a short presentation on my experiments with Jupyter
Kernel for C++ (Ubuntu 18.04) covering the following:
– Simple C++ example
– How to Invoke C++ help as and when required
– Xwidgets in conjuction with Observer function
– Invoking Armadillo Linear Algebra Libraries, Random Number Generation and
dimensionality reduction techniques like PCA
●
Set up your programming environment –
Follow Github Instructions

3. Introduction
●
C++ is a very powerful language but lacks intutive character
that programming languages like R and Python in the
backdrop of Jupyter Kernel
●
This a short presentation on my experiments with Jupyter
Kernel for C++ (Ubuntu 18.04) covering the following:
– Simple C++ example
– How to Invoke C++ help as and when required
– Xwidgets in conjuction with Observer function
– Invoking Armadillo Linear Algebra Libraries, Random Number Generation and PCA
●
Set up your programming environment –
Follow Github Instructions

4. C++ Program
● Now, you see on top right side the
[1] The usual C++ stuff
[2] Nothing new initializing a variable ‘x’
[3] What is in the variable ‘x’ - the intutiveness aspect

5. C++ Program
xwidgets

6. C++ Program
C++11 Lambda
Function!

7. Principal Component Analysis (PCA)
➔ Armadillo uses BLAS and LPACK for Matrix
Operations
➔ OpenBLAS used in this example is an
implementation of BLAS (Basic Linear
Algebra Subprograms)

8. Conclusions
● Looked at how to bring Jupyter Kernel Capability to C++
using Xeus-cling
● Looked at:
– Simple C++ example
– How to Invoke C++ help as and when required – inline with code
– Xwidgets in conjuction with Observer Pattern/function
– Invoking Armadillo Linear Algebra Libraries, Random Number Generation and PCA

9. Thanks!