Programming Assignments for the Stochastic Simulation course in the Master Computational Science at the UvA
In this assignment, we first explored the mandelbrot set and made some pictures of the never ending fractals. Then, we investigated the convergence of the area with different monte carlo integration methods.
Can be made with running python mandelbrot_plots.py
All the integration files can be found in the integrations folder, and there all six different types of integrations can be performed by runing the right files. The data can then be found in the data/ folder.
The plots are made with the python scripts that can be found in the results/ folder, and the corresponding figures can then be found in the figures/
The assignment is divided into four experiments: the 'normal' M/M/n queue, the M/M/n queue with priority scheduling (shortest jobs first), an M/D/n queue with a deterministic job-lenght of 1 and an M/LT/n queue with a job-lenght distribution of 75% percent around 1 and 25% around 5.
Bash scripts were written to perform all the simulations and can be found in the first folder. The data it produces can be found in the data/ folder.
The plots, that can be found in the figures/ folder, can be produced by (for example) running python plots.py inside the results/ folder.
Results include average waiting times for different workloads for all experiments.
In this assignment, we searched for the global optima of particles in a confined space using a simulated annealing algorithm.
Bash scripts were written to perform all the simulations. There are different bash scripts for each cooling scheme.
The code to calculate the forces is included in the forces/ folder.
All results can be found results/ folder. Configurations look like this:
