NASSA
Reference evapotranspiration (FAO-56)
Calculate a daily value of reference evapotranspiration, useful for vegetation (incl. crop) models. The module code is based on FAO-56 Penman-Monteith method.
Get fertility rates (females, 5-year cohort)
This NetLogo code snippet provides fertility estimates of females for use in demographic simulations. The figures used are based on two different sources, and will be assigned per 5-year age cohort.
Network structures
A draft model with some useful code for creating different network structures using the Netlogo NW extension: small-world, preferential attachment, circular, star, wheel, lattice, random, nearest neighbours.
Importing a Roman Transport network
Use open Roman datasets via and import them into a NetLogo model, using the ORBIS dataset (http://orbis.stanford.edu/) to create a set of Roman settlements and major routes between them.
Out of Africa - Conditional isotropic diffusion
A reimplementation of the classical study by Young and Bettinger (1992) investigating the possible drivers behind the Out of Africa dispersal of modern humans.
Pedestrian random walk in NetLogo (ch2.1)
A collection of methods for random walk in NetLogo, including various movement restrictions, biases, and algorithm alternatives.
Place them on the map
Multiple agent placement in specific geographical location. Set up an input number of agents (turtles) at an input location (cell or patch) in an grid holding the input spatial data (map).
Epidemic Network
Experimental environment for testing of large array of theoretical conditions for development epidemic event within various quantitative, spatial and connectedness (network structure) aspects.
Preferential Attachment Network
This NetLogo algorithm simulates network formation using preferential attachment. New nodes are more likely to connect to existing nodes with higher degrees, reflecting a "lottery" system where popular nodes attract more links.
Angle-and-step random walk
An Python implementation of random walk in 2D space based on agent angle orientation and step distance. It defines an agent class `Walker` capable of random walk movement based on random angle and movement step distance in a continuous 2D space.
Random walk in data frames
Collection of methods for producing random walks in two-dimensional space outputting position coordinates in data frames, including alternatives for grid and non-grid space. In R, it uses tidyverse "tibble" to construct the data frames that store trajectories.
Resource exploitation procedure
This module takes an agent and lets it decide which resources to target and exploit. The agent moves to the patch to be harvested, takes the resources and returns home