danieljsharpe

DISCOTRESS

🦜 DISCOTRESS 🦜 is a software package to simulate and analyse the dynamics on arbitrary Markov chains

DISCOTRESS_tutorials

Learn to get started using DISCOTRESS with these tutorials! Then apply to your own Markov chains in ecology 🦜🌴 economics 💸📈 biophysics 🧬🦠 and more!

metadynamics

C++ implementation of metadynamics simulation on a potential energy surface

swendsen_wang_potts

Code for simulation of the Potts spin glass model by the Swendsen-Wang algorithm. The Hoshen-Kopelman algorithm is used for clustering.

cpp_primer

Various pieces of example code for learning features of C++

DISCOTRESS_tools

Various scripts for analysis of the dynamics on Markov chains, and processing DISCOTRESS output

multi_layer_perceptron

Pure Python implementation of a multi-layer perceptron (MLP) neural network

transition_path_theory

Python code for transition path theory (TPT) on a graph (Markov jump process)

bayes_opt

Pure Python code for Bayesian Optimisation (BO) of a continuous objective function

k_distinct_paths

Python code to find the k shortest paths in a kinetic network (Markov chain)

markov_visitation_probabilities

State reduction algorithm to compute visitation probabilities of a state in a finite Markov chain

mlr_mcl

C++ code for multi-level regularised Markov clustering of a kinetic network (Markov chain community detection)

danieljsharpe

danieljsharpe.github.io

data_and_results

A collection of data and results for reference and for sharing

fortran_primer

Various pieces of example code for learning features of Fortran90

fundamental_graph_algorithms

A collection of Python implementations of commonly encountered and fundamental graph algorithms

genetic_algorithm

Genetic algorithm for optimisation of a continuous objective function

girvan-newman

C++ implementation of the Girvan-Newman algorithm for finding community structure in a graph

helpful_scripts

Collection of random useful scripts for my work

hidden_markov_model

Collection of algorithms for analysis of Hidden Markov Models (HMMs)

lattice_protein

Python code for Monte Carlo simulation and ant colony optimisation of a lattice protein model

mini_energy_landscape_explorer

A suite of scripts for analysing and exploring continuous energy functions, demonstrating the use of e.g.: nudged elastic band algorithm, eigenvector-following and BFGS minimisation. A set of model chemical potential energy surfaces are included.

nested_sampling

C++ implementation of the nested sampling algorithm for a potential energy surface

particle_swarm_optimisation

Particle swarm intelligence algorithm for optimisation of a continuous objective function

py_primer

Various pieces of example code for learning features of Python

restricted_boltzmann_machine

Pure Python implementation of a Restricted Boltzmann Machine (RBM)

rosenblatt_perceptron

Pure Python implementation of the simple Rosenblatt perceptron

scikit-learn_examples

Simple example usages of various machine learning methods within Python's scikit-learn package

theoretical_ecology

scripts for simulations of ecosystem dynamics