Exercise 1: Particle class
This first exercise is meant to get comfortable with pybind11’s syntax.
Define a class Particle with the following attributes:
name(const std::string)x,y,zcoordinates (double)px,py,pzmomentum (double)massin GeV (double) For this class write the necessary constructors, getters and setters, as well as two methods returning the particle’s energy and invariant mass.
Also define a function that returns the distance between two particles.
Finally bind all the code in a Python module and test it in Python.
Exercise 2: Convolutional kernels
In this context a convolutional kernel is a scalar function of the distance between two points.
Define an abstract class Kernel, and two derived classes GaussianKernel and
ExponentialKernel. Each class should define an apply method, that applies the
respective function to the point distance.
On the Python side, define a class StepKernel, whose application
returns a value if the distance is below a certain threshold, and zero otherwise.
Exercise 3: Matrix
Define a class Matrix, with the getters for the sizes and the data pointer, as well as
the two overloads of the operator[]. Then overload all the main arithmetic operators:
- addition and subtraction of two matrices
- in-place addition and subtraction
- multiplication of a matrix by a scalar (both commutations)
- division of a matrix by a scalar
- in-place multiplication and division by a scalar
- matrix-matrix multiplication
Then bind the class, defining all the arithmetic operators, the __len__ and __str__
variables and the __getitem__ and __setitem__ methods.
Part 2
Expose the class as a Python buffer.