# Literate NetLogo

This is an example project to demonstrate Literate Programming to create [NetLogo](https://ccl.northwestern.edu/netlogo/) models from ODD+C protocols using [Yarner](https://github.com/mlange-42/yarner).

The document you are currently reading contains the [ODD protocol](#rabies-model-odd-protocol) [(Grimm et al. 2006, 2010)](#references) of a model for Rabies in red foxes. The ODD description is interleaved with code blocks showing the NetLogo code used for the described aspect (ODD+C). Using the Literate Programming tool [Yarner](https://github.com/mlange-42/yarner), these code blocks are extracted from the document and arranged into a working NetLogo model.

* [How to use it](#how-to-use-it)
* [How it works](#how-it-works)
* [Rabies model - ODD protocol](#rabies-model-odd-protocol)
* [References](#references)
* [Appendix](#appendix)

## How to use it

**Read the ODD**

The best way to understand how to use Literate Programming with Yarner to create a NetLogo model from an ODD protocol is to read the [ODD+C of the Rabies model](#rabies-model-odd-protocol), below. It contains the complete code of the model, except the UI elements.

See section [How it works](#how-it-works) for how the model is extracted from this document.

**Run from downloads**

The [Downloads](https://git.ufz.de/oesa/literate-netlogo/-/jobs/artifacts/main/download?job=build) contain a folder `model` with files `Model.nlogo` and `Code.nls`. Open the `.nlogo` file with NetLogo.

**Build from sources**

1. [Install Yarner](https://mlange-42.github.io/yarner/installation.html)
2. Clone the sources of this example:  
   `git clone https://git.ufz.de/oesa/literate-netlogo.git`
3. `cd` into folder `literate-netlogo`
4. Run command `yarner` to extract the model code
5. Open file `model/Model.nlogo` with NetLogo

## How it works

Yarner scans the document for code blocks and puts them together using macros. Each code block has a name, given in its first line and prefixed with `;-`:

```netlogo
;- A code block
let x 0
```

When a code block is referenced by another code block using a macro with `; ==>`, it is placed inside the referencing code block:

```netlogo
;- Outer code block
; ==> A code block.
let y 1
```

The resulting extracted code would look like this:

```netlogo
let x 0
let y 1
```

See the [Yarner documentation](https://mlange-42.github.io/yarner/) for a comprehensive guide and a description of all features.

## Rabies model - ODD protocol

* [Purpose](#purpose)
* [Entities, state variables, and scales](#entities-state-variables-and-scales)
* [Process overview and scheduling](#process-overview-and-scheduling)
* [Design concepts](#design-concepts)
* [Initialization](#initialization)
* [Input data](#input-data)
* [Submodels](#submodels)

### Purpose

The purpose of this model is to demonstrate how NetLogo models can be created from ODD protocols, using Literate Programming with Yarner.

### Entities, state variables, and scales

The model landscape is represented by a grid of 1km x 1km cells, each representing a potential home range of a fox family. The model progresses in discrete ticks of one month each.

The only entity in the model are fox families. Each fox family is represented by a NetLogo patch (i.e. a grid cell).

Each patch (i.e. each potential fox family) has four state variables:

```netlogo
;- State variables
patches-own [
  state
  infected-neighbours
  tick-of-death
  dispersal-tick
]
```

The disease state (`state`) represents the state of the patch. Possible states are `EMPTY`, `S`usceptible, `I`nfected and `R`ecovered:

```netlogo
;- Disease states
globals [
  EMPTY
  S
  I
  R
]
```

Disease states are internally represented by whole numbers 0-3:

```netlogo
;- Setup disease states
set EMPTY 0
set S 1
set I 2
set R 3
```

State variable `infected-neighbours` is a counter for the number of infected neighbouring families. `tick-of-death` is the model step of death for infected families. `dispersal-tick` indicates the month of the year (index [0..11]) of the family's next dispersal event.

### Process overview and scheduling

Processes simulated by the model are [Dispersal](#dispersal), [Infection](#infection) and [Disease course](#disease-course). Processes are executed on every monthly time step in the above order.

After to model processes, the patch colour is updated for [Visualization](#visualization) and the model tick is increased by one.

```netlogo
;- Go
to go
  disperse-offspring
  infect-patches
  age-infection

  update-patches
  tick
end

; ==> Submodels.
```

### Design concepts

Fox families as the only model entities live on a rectangular grid of habitat patches. Patches can be empty or occupied.

Reproduction and juvenile dispersal are subsumed under a single process [Dispersal](#dispersal). Once a year, a certain number of female offspring disperses from each fox family. Time and target location of dispersal are stochastic. Dispersal is restricted by a maximum dispersal radius.

Fox families can become infected with Rabies. Rabies can be transmitted to the 8 immediate neighbouring families. Infection is stochastic and infection probability depends on the number of infected neighbours.

### Initialization

The model is initialized by populating each habitat patch with a `S`usceptible fox family. One randomly selected family is infected.

```netlogo
;- Setup
to setup
  clear-all
  ; ==> Setup disease states.

  ask patches [
    set state S
  ]
  ask one-of patches [
    infect-patch 0
  ]

  update-patches
  reset-ticks
end
```

### Input data

The model uses no input data.

### Submodels

The model is composed of four submodels:

```netlogo
;- Submodels
; ==> Dispersal.
; ==> Infection.
; ==> Disease course.
; ==> Update patches.
```

#### Dispersal

The month of dispersal of each fox family is determined once per year. Actual dispersals are processed at every tick.

```netlogo
;- Dispersal
to disperse-offspring
  if ticks mod 12 = 0 [
    assign-dispersal
  ]
  disperse
end


; ==> Assign dispersal.
; ==> Disperse.
```

At the start of each year, the month of the next dispersal (`dispersal-tick`) is assigned to each fox family (i.e. to each non-empty patch), drawn from a uniform distribution covering the dispersal period. 

```netlogo
;- Assign dispersal
to assign-dispersal
  ask patches with [ state != EMPTY ] [
    set dispersal-tick (ticks + start-dispersal + random length-dispersal)
  ]
end
```

Each fox family disperses in their designated month of dispersal `dispersal-tick` so that all foxes disperse uniformly distributed over the dispersal period. In each step, dispersals are executed in arbitrary order and immediately occupy their target patches. However, the results are independent of that order.

Each female offspring of each family's `num-offspring` tries to occupy an empty patch in radius `dispersal-radius`.  If the number of offspring exceeds the available patches, only as many offspring as there are patches available can disperse.

The target patch of each disperser is set to `S`usceptible. It is assumed that animals infected with Rabies do not disperse.

```netlogo
;- Disperse
to disperse
  ask patches with [ state != EMPTY and dispersal-tick = ticks ] [
    let candidates other patches
                   in-radius dispersal-radius
                   with [ state = EMPTY ]
    let num-candidates num-offspring
    if count candidates < num-candidates [
      set num-candidates count candidates
    ]
    ask n-of num-candidates candidates [
      set state S
    ]
  ]
end
```

#### Infection

Infection depends on the number of infected neighbouring families. For synchronous update, the number of infected neighbours is determined for each patch and stored in state variable `infected-neighbours`.

Then, `S`usceptible patches are infected with a probability calculated from this state variable.

```netlogo
;- Infection
to infect-patches
  ask patches [
    set infected-neighbours 0
  ]
  ask patches with [ state = I ] [
    ask neighbors [
      set infected-neighbours infected-neighbours + 1
    ]
  ]
  ask patches with [ state = S ] [
    if random-float 1 < calc-infection-prob [
      infect-patch ticks
    ]
  ]
end

; ==> Infection probability.
; ==> Infect patch.
```

Infection probability $`P_{inf}`$ per patch is calculated from the number of infected neighbours using the Reed-Frost model [(Abbey 1952)](#references) with parameter `beta`.

```math
P_{inf} = 1 - (1 - \beta)^{I}
```

With $`\beta`$ being the infection probability to be infected by one infected neighbour, and $`I`$ being the number of infected neighbouring patches.

```netlogo
;- Infection probability
to-report calc-infection-prob
  report 1 - (1 - beta) ^ infected-neighbours
end
```

Upon infection of a patch, its `state` is set to `I`nfected. The duration of infection is determined (here, the constant `ticks-infected`), and the model step of death is assigned to the patch state variable `tick-of-death` (see the [Disease course](#disease-course) submodel).

```netlogo
;- Infect patch
to infect-patch [ curr-tick ]
  set state I
  set tick-of-death curr-tick + ticks-infected
end
```

#### Disease course

All Rabies infections are lethal. When the `tick-of-death` of an infected fox family equals the current tick `ticks`, the family is removed from the simulation, leaving an empty patch.

```netlogo
;- Disease course
to age-infection
  ask patches with [ state = I ] [
    if tick-of-death = ticks [
      set state EMPTY
    ]
  ]
end
```

#### Visualization

After each model update, patches are coloured by their disease state: white for empty, blue for susceptible, red for infected and green for recovered patches/families.

```netlogo
;- Update patches
to update-patches   
  ask patches [
    ifelse state = EMPTY [ set pcolor white ]
    [ ifelse state = S [ set pcolor blue ]
    [ ifelse state = I [ set pcolor red ]
    [ set pcolor green ] ] ]
  ]
end
```

## References

Abbey H. 1952: **An examination of the Reed Frost theory of epidemics.** Human Biology, 24:201-233.

Grimm V, Berger U, Bastiansen F, Eliassen S, Ginot V, Giske J, Goss-Custard J, Grand T, Heinz S, Huse G, Huth A, Jepsen JU, Jørgensen C, Mooij WM, Müller B, Pe’er G, Piou C, Railsback SF, Robbins AM, Robbins MM, Rossmanith E, Rüger N, Strand E, Souissi S, Stillman RA, Vabø R, Visser U, DeAngelis DL. 2006. **A standard protocol for describing individual-based and agent-based models**. *Ecological Modelling* 198:115-126.

Grimm V, Berger U, DeAngelis DL, Polhill G, Giske J, Railsback SF. 2010. **The ODD protocol: a review and first update**. *Ecological Modelling* 221: 2760-2768.

## Appendix

### Code entrypoint

This is the entrypoint to this "literate program". The blocks referenced by the macros in the code block below are collected here (recursively), and the result is written to file `model/Code.nls`.

```netlogo
;- file:Code.nls
; ==> Disease states.

; ==> State variables.

; ==> Setup.

; ==> Go.
```

### NetLogo file

In the main `.nlogo` file, we only "include" the `.nls` file to allow for the reverse mode.  

Yarner's reverse mode requires automatically generated comments in the code output to be able to identify the source blocks in this Markdown document. NetLogo, however, supports comments only in the code part, but not in the rest of the content of a `.nlogo` file. 

Moving the actual model code into the separate `.nls` file resolves this limitation. 

The Code tab has this single line of content:

```nlogo
__includes["Code.nls"]
```

Access the file in NetLogo via the `Included files` dropdown in the Code tab.

The file `Model.nlogo` is simply copied from the `nlogo` directory via option `code_files` in the `[paths]` section of the `Yarner.toml`.

This separation of model code (`Code.nls`) and user interface (`Model.nlogo`) also allows to edit the model's UI elements in NetLogo's GUI builder tool, while using Literate Programming for the code.