### SLiM Initial Population Setup

Source: https://github.com/messerlab/slim/blob/master/QtSLiM/recipes/Recipe 15.13 - Range expansion in a stepping-stone model I.txt

Creates the initial population by adding subpopulations. The first subpopulation is initialized with 100 individuals, while others start empty.

```SLiM
1 early() {
	// create an initial population of 100 individuals, the rest empty
	for (i in seqLen(N))
		sim.addSubpop(i, (i == 0) ? 100 else 0);
}
```

--------------------------------

### SLiM Early Population Setup

Source: https://github.com/messerlab/slim/blob/master/SLiMgui/Recipes/Recipe 9.6.2 - A sweep from standing variation at a predetermined locus.txt

Sets up the initial population size and saves the simulation ID.

```slim
1 early() {
	// save this run's identifier, used to save and restore
	defineConstant("simID", getSeed());
	sim.addSubpop("p1", 500);
}
```

--------------------------------

### Early Stage: Setup and Initial State

Source: https://github.com/messerlab/slim/blob/master/QtSLiM/recipes/Recipe 14.13 - Modeling biallelic loci with a mutation() callback II.txt

Initializes the subpopulation, creates permanent m2 mutation objects, and then removes them to start all individuals in the 'aa' state. It also sets up logging for mutation frequencies.

```slim
1 early() {
	sim.addSubpop("p1", 100);
	
	// create the permanent m2 mutation objects we will use
	target = p1.haplosomes[0];
	target.addNewDrawnMutation(m2, 0:99);
	defineConstant("MUT", target.mutations);
	
	// then remove them; start with "aa" for all individuals
	target.removeMutations();
	
	// log results
	log = community.createLogFile("freq.csv", logInterval=10);
	log.addTick();
	log.addMeanSDColumns("freq", "sim.mutationFrequencies(NULL, MUT);");
}
```

--------------------------------

### SLiM Simulation Initialization and Setup

Source: https://github.com/messerlab/slim/blob/master/QtSLiM/recipes/Recipe 14.16 - Visualizing linkage disequilibrium.txt

Initializes the SLiM simulation environment, including setting the random seed, defining genome length, mutation rates, genomic elements, and recombination rate. This setup is crucial before running any simulation.

```SLiM
initialize()
{
	setSeed(2180149919968428688);
	defineConstant("L", 1e7);
	initializeMutationRate(1e-7);
	initializeMutationType("m1", 0.5, "f", 0.0);
	initializeMutationType("m2", 1.0, "f", 0.1).color="red";  // used for MUT1
	initializeGenomicElementType("g1", m1, 1.0);
	initializeGenomicElement(g1, 0, L-1);
	initializeRecombinationRate(1e-8);
}
1 early()
{
	sim.addSubpop("p1", 1000);
}
5000 late()
{
	// create the MUT1 mutation that we will track over time
	mut1 = sample(p1.haplosomes, 1).addNewDrawnMutation(m2, asInteger(L/2));
	defineGlobal("MUT1", mut1);
}
```

--------------------------------

### Initial Population Setup

Source: https://github.com/messerlab/slim/blob/master/QtSLiM/recipes/Recipe 20.5 - A continuous-space host-parasitoid model.txt

Sets up the initial subpopulations for hosts and parasitoids, including their spatial bounds and initial positions.

```SLiM
ticks all 1 early() {
	host.addSubpop("p1", N0_host);
	p1.setSpatialBounds(c(0, 0, SIDE, SIDE));
	p1.individuals.setSpatialPosition(p1.pointUniform(N0_host));
	
	parasitoid.addSubpop("p2", N0_parasitoid);
	p2.setSpatialBounds(c(0, 0, SIDE, SIDE));
	p2.individuals.setSpatialPosition(p2.pointUniform(N0_parasitoid));
}
```

--------------------------------

### Early Simulation Setup

Source: https://github.com/messerlab/slim/blob/master/QtSLiM/recipes/Recipe 9.2 - Making sweeps conditional on fixation.txt

Initializes the subpopulation and saves the simulation ID at the beginning of the run.

```slim
1 early() {
	// save this run's identifier, used to save and restore
	defineConstant("simID", getSeed());
	
sim.addSubpop("p1", 500);
}
```

--------------------------------

### Early Tick Population Setup

Source: https://github.com/messerlab/slim/blob/master/SLiMgui/Recipes/Recipe 20.3 - A deterministic host-parasitoid model.txt

Sets up the initial subpopulations for host ('p1') and parasitoid ('p2') at the beginning of the simulation (tick 1). This establishes the starting population sizes based on pre-defined constants.

```SLiM
ticks all early() {
	host.addSubpop("p1", N0_host);
	parasitoid.addSubpop("p2", N0_parasitoid);
}
```

--------------------------------

### Initial Population Setup

Source: https://github.com/messerlab/slim/blob/master/QtSLiM/recipes/Recipe 16.2 - Following a pedigree.txt

Sets up the initial subpopulation with a specified size and assigns initial tags to individuals.

```SLiM
1 early() {
	sim.addSubpop("p1", 10);
	
	// provide initial tags matching the original model
	p1.individuals.tag = 1:10;
}
```

--------------------------------

### Initial Setup and Logging

Source: https://github.com/messerlab/slim/blob/master/QtSLiM/recipes/Recipe 20.8 - Within-host reproduction in a host-pathogen model.txt

Sets up the initial monkey population, introduces the first infections, and creates a log file to record simulation progress.

```SLiM
ticks all 1 early() {
	monkey.addSubpop("p1", K_MONKEY);
	
	// choose initial hosts carrying the infection
	initial_hosts = p1.sampleIndividuals(5, replace=F);
	pathogen.tag = 3;
	
	for (initial_host in initial_hosts)
	{
		// make a pathogen subpop for the host
		pathogen_subpop = pathogen.addSubpop(pathogen.tag, 1);
		pathogen_subpop.tag = initial_host.pedigreeID;
		pathogen.tag = pathogen.tag + 1;
	}
	
	// log some basic output
	logfile = community.createLogFile("host_pathogen_log.csv", logInterval=1);
	logfile.addTick();
	logfile.addSubpopulationSize(p1);
	logfile.addPopulationSize(pathogen);
	logfile.addCustomColumn("host_count", "pathogen.subpopulations.size();");
	logfile.addMeanSDColumns("monkeyAge", "p1.individuals.age;");
}
```

--------------------------------

### Install SLiMgui Executable

Source: https://github.com/messerlab/slim/blob/master/CMakeLists.txt

Installs the built SLiMgui executable to the 'bin' directory.

```cmake
install(TARGETS ${TARGET_NAME_SLIMGUI} DESTINATION bin)
```

--------------------------------

### SLiM Early Population Setup

Source: https://github.com/messerlab/slim/blob/master/QtSLiM/recipes/Recipe 16.7 - Tracking separate sexes in script, nonWF style.txt

Initializes the subpopulation with a carrying capacity and assigns random sexes to individuals at the start of the simulation.

```SLiM
1 early() {
	sim.addSubpop("p1", K);
	
	// assign random sexes (T = male, F = female)
	p1.individuals.tagL0 = (runif(p1.individualCount) <= 0.5);
}
```

--------------------------------

### Build and Install Arch Linux Package

Source: https://github.com/messerlab/slim/wiki/Arch-Linux-packaging

Builds and installs the SLiM package, running CLI tests beforehand. This process may take a significant amount of time.

```bash
makepkg -si
```

--------------------------------

### Install SLiM using MSYS2

Source: https://github.com/messerlab/slim/blob/master/README.md

Install SLiM and SLiMgui using the pacman package manager on MSYS2. Ensure MSYS2 is updated before installation.

```bash
pacman -S mingw-w64-x86_64-slim-simulator
```

--------------------------------

### Early Stage Simulation Setup

Source: https://github.com/messerlab/slim/blob/master/QtSLiM/recipes/Recipe 11.1 - Assortative mating.txt

Initializes subpopulations and sets migration rates between them. This function runs at the beginning of the simulation.

```slim
1 early() {
	sim.setValue("FST", 0.0);
	sim.addSubpop("p1", 500);
	sim.addSubpop("p2", 500);
	p1.setMigrationRates(p2, 0.1);
	p2.setMigrationRates(p1, 0.1);
}
```

--------------------------------

### Set up Initial Population

Source: https://github.com/messerlab/slim/blob/master/QtSLiM/recipes/Recipe 17.6 - Divergence due to phenotypic competition with an interaction() callback.txt

Creates the initial subpopulation named 'p1' with 500 individuals at the start of the simulation.

```slim
1 late() {
	sim.addSubpop("p1", 500);
}
```

--------------------------------

### CMake Build with GUI Enabled

Source: https://github.com/messerlab/slim/blob/master/CMakeLists.txt

Builds SLiM with its Qt5-based GUI enabled. Requires Qt5 libraries to be installed.

```bash
cd build
cmake -D BUILD_SLIMGUI=ON ../SLiM
make -j10
```

--------------------------------

### Initial Population Setup

Source: https://github.com/messerlab/slim/blob/master/SLiMgui/Recipes/Recipe 16.11 - Life-long monogamous mating.txt

Creates the initial subpopulation with a defined carrying capacity and assigns random ages and an 'unmated' tag to all individuals.

```SLiM
1 first() {
	sim.addSubpop("p1", K);
	p1.individuals.age = rdunif(K, min=0, max=15);		// initial variation in age
	p1.individuals.tag = -1;		// mark all individuals as unmated
}
```

--------------------------------

### Early Stage: Subpopulation and Migration Setup

Source: https://github.com/messerlab/slim/blob/master/QtSLiM/recipes/Recipe 12.3 - Simulating gene drive.txt

Initializes subpopulations and sets migration rates between them. This function runs at the beginning of the simulation (generation 1).

```SLiM
1 early() {
	for (i in 0:5)
		sim.addSubpop(i, 500);
	for (i in 1:5)
		sim.subpopulations[i].setMigrationRates(i-1, 0.001);
	for (i in 0:4)
		sim.subpopulations[i].setMigrationRates(i+1, 0.1);
}
```

--------------------------------

### Single-line comment example

Source: https://github.com/messerlab/slim/blob/master/QtSLiM/help/EidosHelpStatements.html

Illustrates how to use single-line comments starting with '//' in Eidos code.

```Eidos
1 + 1 == 2; // this is true
```

--------------------------------

### SLiM Initialization and Setup

Source: https://github.com/messerlab/slim/blob/master/QtSLiM/recipes/Recipe 9.11 - Effective population size versus census population size.txt

Sets up global parameters, mutation rates, genomic elements, and recombination rates for the SLiM simulation. Initializes SLiM options to keep pedigrees.

```SLiM
initialize() {
	defineGlobal("N", 1000);
	defineGlobal("L", 1e7);
	defineGlobal("MU", 1e-7);
	defineGlobal("R", 1e-8);
	defineGlobal("S", 2.0);
	initializeSLiMOptions(keepPedigrees=T);
	initializeMutationRate(MU);
	initializeMutationType("m1", 0.5, "f", 0.0); 		// neutral
	initializeMutationType("m2", 0.5, "f", S); 		// sweep
	m2.convertToSubstitution = F;
	initializeGenomicElementType("g1", m1, 1.0);
	initializeGenomicElement(g1, 0, L-1);
	initializeRecombinationRate(R);
}
```

--------------------------------

### Initial Setup and Logging

Source: https://github.com/messerlab/slim/blob/master/SLiMgui/Recipes/Recipe 20.8 - Within-host reproduction in a host-pathogen model.txt

Sets up the initial monkey population, selects initial hosts for infection, assigns pathogen subpopulations, and creates a log file to record population sizes and other metrics over time.

```SLiM
ticks all 1 early() {
	monkey.addSubpop("p1", K_MONKEY);
	
	// choose initial hosts carrying the infection
	initial_hosts = p1.sampleIndividuals(5, replace=F);
	pathogen.tag = 3;
	
	for (initial_host in initial_hosts)
	{
		// make a pathogen subpop for the host
		pathogen_subpop = pathogen.addSubpop(pathogen.tag, 1);
		pathogen_subpop.tag = initial_host.pedigreeID;
		pathogen.tag = pathogen.tag + 1;
	}
	
	// log some basic output
	logfile = community.createLogFile("host_pathogen_log.csv", logInterval=1);
	logfile.addTick();
	logfile.addSubpopulationSize(p1);
	logfile.addPopulationSize(pathogen);
	logfile.addCustomColumn("host_count", "pathogen.subpopulations.size();");
	logfile.addMeanSDColumns("monkeyAge", "p1.individuals.age;");
}

```

--------------------------------

### Get Nucleotide Sequence within a Range

Source: https://github.com/messerlab/slim/blob/master/QtSLiM/help/SLiMHelpClasses.html

Returns a portion of the nucleotide sequence for the haplosome, constrained by the specified start and end positions. The format parameter controls the output type.

```SLiM
nucleotides(start=100, end=200, format="string")
```

--------------------------------

### Initial Population Setup and Logging

Source: https://github.com/messerlab/slim/blob/master/QtSLiM/recipes/Recipe 20.6 - A coevolutionary host-parasitoid trait-matching model.txt

Sets up the initial subpopulations for hosts and parasitoids and creates a log file to record population sizes and trait means/SDs over time.

```SLiM
ticks all 1 early() {
	host.addSubpop("p1", N0_host);
	parasitoid.addSubpop("p2", N0_parasitoid);
	
	log = community.createLogFile("host-parasite log.txt", logInterval=1);
	log.addTick();
	log.addPopulationSize(host);
	log.addMeanSDColumns("host", "p1.individuals.tagF;");
	log.addPopulationSize(parasitoid);
	log.addMeanSDColumns("parasitoid", "p2.individuals.tagF;");
}
```

--------------------------------

### SLiM Initialization and Simulation Setup

Source: https://github.com/messerlab/slim/blob/master/SLiMgui/Recipes/Recipe 12.4 - Suppressing hermaphroditic selfing.txt

This snippet shows the basic initialization of SLiM, including mutation rate, genomic elements, and recombination rate, followed by the creation of a subpopulation.

```SLiM
initialize() {
	initializeMutationRate(1e-7);
	initializeMutationType("m1", 0.5, "f", 0.0);
	initializeGenomicElementType("g1", m1, 1.0);
	initializeGenomicElement(g1, 0, 99999);
	initializeRecombinationRate(1e-8);
}
1 early() { sim.addSubpop("p1", 500); }
```

--------------------------------

### SLIM Recipe Initialization and Simulation Setup

Source: https://github.com/messerlab/slim/blob/master/QtSLiM/recipes/Recipe 18.4 - Detecting the dip in diversity (analyzing tree heights in Python) I.txt

This snippet sets up the simulation parameters, including population size, chromosome length, mutation and recombination rates, genomic element types, and initializes the tree sequence output. It is used to configure the simulation environment for diversity analysis.

```SLIM
initialize() {
	defineConstant("N", 10000);  // pop size
	defineConstant("L", 1e8);    // total chromosome length
	defineConstant("L0", 200e3); // between genes
	defineConstant("L1", 1e3);   // gene length
	initializeTreeSeq();
	initializeMutationRate(1e-7);
	initializeRecombinationRate(1e-8, L-1);
	initializeMutationType("m2", 0.5, "g", -(5/N), 1.0);
	initializeGenomicElementType("g2", m2, 1.0);
	
	for (start in seq(from=L0, to=L-(L0+L1), by=(L0+L1)))
		initializeGenomicElement(g2, start, (start+L1)-1);
}
1 early() {
	sim.addSubpop("p1", N);
}
10*N late() {
	sim.treeSeqOutput("./diversity.trees");
}
```

--------------------------------

### SLiM Initialization and Mutation Setup

Source: https://github.com/messerlab/slim/blob/master/QtSLiM/recipes/Recipe 18.3 - Simulation conditional upon fixation of a sweep, preserving ancestry I.txt

Sets up mutation rates, types (including deleterious and beneficial), genomic elements, and recombination rate. This is a prerequisite for running the simulation.

```slim
initialize() {
	initializeMutationRate(1e-7);
	initializeMutationType("m1", 0.5, "f", 0.0);
	initializeMutationType("m2", 0.5, "g", -0.01, 1.0);  // deleterious
	initializeMutationType("m3", 1.0, "f", 0.05);        // introduced
	initializeGenomicElementType("g1", c(m1, m2), c(0.9, 0.1));
	initializeGenomicElement(g1, 0, 99999);
	initializeRecombinationRate(1e-8);
}
```

--------------------------------

### Example Benchmark Runner Output

Source: https://github.com/messerlab/slim/blob/master/simd_benchmarks/README.md

Example output from the SIMD Benchmark Runner script, showing Eidos math function and SLiM simulation benchmark results.

```bash
$ simd_benchmarks/run_benchmarks.sh 
============================================
SIMD Benchmark Runner
============================================
SLiM root: /home/adkern/SLiM
Runs per benchmark: 3

Building with SIMD enabled...
  Done.
Building with SIMD disabled...
  Done.

============================================
Eidos Math Function Benchmarks
============================================

SIMD Build:
  Running Eidos benchmark (SIMD)...
    sqrt():    0.105 sec
    abs():     0.171 sec
    floor():   0.164 sec
    ceil():    0.166 sec
    round():   0.164 sec
    trunc():   0.165 sec
    sum():     0.032 sec
    product(): 0.003 sec (1000 elements, 10000 iters)

Scalar Build:
  Running Eidos benchmark (Scalar)...
    sqrt():    0.108 sec
    abs():     0.166 sec
    floor():   0.231 sec
    ceil():    0.246 sec
    round():   0.473 sec
    trunc():   0.246 sec
    sum():     0.166 sec
    product(): 0.017 sec (1000 elements, 10000 iters)

============================================
SLiM Simulation Benchmark
(N=5000, 5000 generations, selection)
============================================

Running 3 iterations each...

SIMD Build:   12.756s (avg)
Scalar Build: 12.316s (avg)

Speedup: .96x

============================================
Benchmark complete
============================================
```

--------------------------------

### Initialize SLiM Options and Parameters

Source: https://github.com/messerlab/slim/blob/master/QtSLiM/recipes/Recipe 17.10 - A simple biogeographic landscape model.txt

Sets up the simulation environment, including dimensionality, mutation rate, genomic elements, and interaction types for spatial competition and mate choice.

```SLiM
initialize() {
	initializeSLiMOptions(dimensionality="xy");
	initializeMutationRate(1e-7);
	initializeMutationType("m1", 0.5, "f", 0.0);
	initializeGenomicElementType("g1", m1, 1.0);
	initializeGenomicElement(g1, 0, 99999);
	initializeRecombinationRate(1e-8);
	
	// spatial competition
	initializeInteractionType(1, "xy", reciprocal=T, maxDistance=30.0);
	i1.setInteractionFunction("n", 5.0, 10.0);
	
	// spatial mate choice
	initializeInteractionType(2, "xy", reciprocal=T, maxDistance=30.0);
	i2.setInteractionFunction("n", 1.0, 10.0);
}
```

--------------------------------

### Early Simulation Setup and Logging

Source: https://github.com/messerlab/slim/blob/master/QtSLiM/recipes/Recipe 4.2.5 - Basic output, Automatic logging with LogFile.txt

Sets up subpopulations, migration rates, and creates a log file to record simulation data, including a custom FST column.

```SLiM
1 early() {
	sim.addSubpop("p1", 1000);
	sim.addSubpop("p2", 1000);
	p1.setMigrationRates(p2, 0.001);
	p2.setMigrationRates(p1, 0.001);
	log = community.createLogFile("sim_log.txt", logInterval=10);
	log.addCycle();
	log.addCustomColumn("FST", "calcFST(p1.haplosomes, p2.haplosomes);");
}
```

--------------------------------

### MutationEffect Callback Example

Source: https://github.com/messerlab/slim/blob/master/QtSLiM/help/SLiMHelpCallbacks.html

A mutationEffect callback example that sets a neutral relative fitness (1.0) for mutations of type m2 in subpopulation p3 between ticks 1000 and 2000. This demonstrates spatial heterogeneity in selection.

```Eidos
1000:2000 mutationEffect(m2, p3) { 1.0; }
```

--------------------------------

### Setup for Live Plotting

Source: https://github.com/messerlab/slim/blob/master/QtSLiM/recipes/Recipe 14.7 - Live plotting with R using system().txt

Initializes a subpopulation and sets up a temporary file path for saving plot images. If running in SLiMgui, it opens the plot document.

```SLiM
1 early() {
	sim.addSubpop("p1", 5000);
	sim.setValue("fixed", NULL);
	
defineConstant("pngPath", writeTempFile("plot_", ".png", ""));
	
	// If we're running in SLiM GUI, open a plot window
	if (exists("slimgui"))
		s slimgui.openDocument(pngPath);
}
```

--------------------------------

### Subpopulation First Male Index Property

Source: https://github.com/messerlab/slim/blob/master/QtSLiM/help/SLiMHelpClasses.html

Gets the index of the first male in the subpopulation.

```SLiM
firstMaleIndex => (integer$)
```

--------------------------------

### Initialize SLiM Simulation Parameters

Source: https://github.com/messerlab/slim/blob/master/QtSLiM/recipes/Recipe 17.11 - Local adaptation on a heterogeneous landscape map.txt

Sets up the simulation environment, including dimensionality, mutation types, genomic elements, and interaction parameters for competition and mate choice.

```SLiM
initialize() {
	defineConstant("SIGMA_C", 0.1);
	defineConstant("SIGMA_K", 0.5);
	defineConstant("SIGMA_M", 0.1);
	defineConstant("N", 500);
	
	initializeSLiMOptions(dimensionality="xyz");
	initializeMutationRate(1e-6);
	initializeMutationType("m1", 0.5, "f", 0.0);        // neutral
	initializeMutationType("m2", 0.5, "n", 0.0, 1.0);   // QTL
	m2.convertToSubstitution = F;
	
	initializeGenomicElementType("g1", c(m1, m2), c(1, 0.1));
	initializeGenomicElement(g1, 0, 1e5 - 1);
	initializeRecombinationRate(1e-8);
	
	// competition
	initializeInteractionType(1, "xyz", reciprocal=T, maxDistance=SIGMA_C * 3);
	i1.setInteractionFunction("n", 1.0, SIGMA_C);
	
	// mate choice
	initializeInteractionType(2, "xyz", reciprocal=T, maxDistance=SIGMA_M * 3);
	i2.setInteractionFunction("n", 1.0, SIGMA_M);
}
mutationEffect(m2) { return 1.0; }
```

--------------------------------

### Get Maximum Available Threads

Source: https://github.com/messerlab/slim/blob/master/QtSLiM/help/EidosHelpFunctions.html

Returns the maximum number of threads that can be utilized by the system.

```C++
parallelGetMaxThreads()
```

--------------------------------

### Initialize SLiM Simulation Options

Source: https://github.com/messerlab/slim/blob/master/QtSLiM/recipes/Recipe 17.3 - Boundaries and boundary conditions IV (reprising boundaries).txt

Sets up the simulation environment for a 2D spatial model and defines mutation parameters.

```SLiM
initialize() {
	initializeSLiMOptions(dimensionality="xy");
	initializeMutationRate(1e-7);
	initializeMutationType("m1", 0.5, "f", 0.0);
	initializeGenomicElementType("g1", m1, 1.0);
	initializeGenomicElement(g1, 0, 99999);
	initializeRecombinationRate(1e-8);
	
	initializeInteractionType(1, "xy", reciprocal=T, maxDistance=0.3);  // competition
	i1.setInteractionFunction("n", 3.0, 0.1);
}
```

--------------------------------

### Get Length of a Value

Source: https://github.com/messerlab/slim/blob/master/QtSLiM/help/EidosHelpFunctions.html

Returns the length of a given value (e.g., a vector or list).

```Eidos
length(x)
```

--------------------------------

### Initialize Subpopulations and Logging

Source: https://github.com/messerlab/slim/blob/master/QtSLiM/recipes/Recipe 20.7 - A coevolutionary host-parasite matching-allele model.txt

Sets up the initial subpopulations for host and parasite, creates a log file, and adds custom columns to track nucleotide frequencies.

```SLiM
ticks all 1 early() {
	host.addSubpop("p0", 1000);
	parasite.addSubpop("p1", 1000);
	
	log = community.createLogFile("host-parasite log.txt", logInterval=1);
	log.addTick();
	log.addCustomColumn("hA", "nucleotideFreq(host, 'A');");
	log.addCustomColumn("hC", "nucleotideFreq(host, 'C');");
	log.addCustomColumn("hG", "nucleotideFreq(host, 'G');");
	log.addCustomColumn("hT", "nucleotideFreq(host, 'T');");
	log.addCustomColumn("pA", "nucleotideFreq(parasite, 'A');");
	log.addCustomColumn("pC", "nucleotideFreq(parasite, 'C');");
	log.addCustomColumn("pG", "nucleotideFreq(parasite, 'G');");
	log.addCustomColumn("pT", "nucleotideFreq(parasite, 'T');");
}
```

--------------------------------

### Initialize Population

Source: https://github.com/messerlab/slim/blob/master/QtSLiM/recipes/Recipe 13.4 - A quantitative genetics model with heritability.txt

Adds a subpopulation named 'p1' with 1000 individuals at the start of the simulation.

```slim
1 late() {
	sim.addSubpop("p1", 1000);
}
```

--------------------------------

### Early Stage: Setup and Initial Population

Source: https://github.com/messerlab/slim/blob/master/QtSLiM/recipes/Recipe 14.13 - Modeling biallelic loci with a mutation() callback I.txt

Creates the initial population, defines canonical mutation objects for 'm2' and 'm3', and sets the population to be homozygous for the 'm3' allele at all positions. Sets up logging for mutation frequencies.

```slim
1 early() {
	sim.addSubpop("p1", 100);
	
	// create the canonical mutation objects
	target = p1.haplosomes[0];
	target.addNewDrawnMutation(m2, 0:99);
	defineConstant("MUT2", target.mutations);
	target.removeMutations();
	target.addNewDrawnMutation(m3, 0:99);
	defineConstant("MUT3", target.mutations);
	target.removeMutations();
	
	// start homozygous "aa" at every position
	p1.haplosomes.addMutations(MUT3);
	
	// log results
	log = community.createLogFile("freq.csv", logInterval=10);
	log.addTick();
	log.addMeanSDColumns("freq", "sim.mutationFrequencies(NULL, MUT2);");
}
```

--------------------------------

### Build SLiMgui Option

Source: https://github.com/messerlab/slim/blob/master/CMakeLists.txt

Option to build the Qt-based GUI for SLiM. This requires Qt to be installed.

```cmake
option(BUILD_SLIMGUI "Build the Qt-based GUI for SLiM" OFF)
```

--------------------------------

### Mutation Callback Example (No Restriction)

Source: https://github.com/messerlab/slim/blob/master/QtSLiM/help/SLiMHelpCallbacks.html

A basic mutation callback that is called for every auto-generated mutation.

```SLiM
mutation() { ... }
```

--------------------------------

### Initial Population Setup

Source: https://github.com/messerlab/slim/blob/master/QtSLiM/recipes/Recipe 16.8 - Modeling haplodiploidy with addRecombinant().txt

Creates the initial subpopulations for males (haploid) and females (diploid) and migrates males into the female subpopulation. It also removes the now-empty male subpopulation.

```SLiM
1 early() {
	// make an initial population with the right genetics
	mCount = asInteger(K * P_OFFSPRING_MALE);
	fCount = K - mCount;
	sim.addSubpop("p1", mCount, sexRatio=1.0, haploid=T); // males
	sim.addSubpop("p2", fCount, sexRatio=0.0, haploid=F); // females
	p1.takeMigrants(p2.individuals);
	p2.removeSubpopulation();
}
```

--------------------------------

### Add Subpopulation

Source: https://github.com/messerlab/slim/blob/master/SLiMgui/Recipes/Recipe 14.2 - Mortality-based fitness I.txt

Adds an initial subpopulation named 'p1' with 500 individuals at the start of the simulation.

```SLiM
sim.addSubpop("p1", 500);
```

--------------------------------

### Set Up Early Population Structure

Source: https://github.com/messerlab/slim/blob/master/QtSLiM/recipes/Recipe 9.7 - Adaptive introgression.txt

Defines the number of subpopulations and migration rates between them at the start of the simulation.

```SLiM
1 early() {
	subpopCount = 10;
	for (i in 1:subpopCount)
		sim.addSubpop(i, 500);
	for (i in 2:subpopCount)
		sim.subpopulations[i-1].setMigrationRates(i-1, 0.01);
	for (i in 1:(subpopCount-1))
		sim.subpopulations[i-1].setMigrationRates(i+1, 0.2);
}
```

--------------------------------

### Initialize Simulation Environment

Source: https://github.com/messerlab/slim/blob/master/SLiMgui/Recipes/Recipe 6.4 - Genomic structure, Part IV (Custom display colors in SLiMgui).txt

Sets up the initial simulation environment by clearing chromosome color substitutions and adding a subpopulation. This is typically done at the beginning of a simulation.

```SLiM
1 early() {
	sim.chromosomes.colorSubstitution = "";
	sim.addSubpop("p1", 5000);
}
```

--------------------------------

### Initialize Population

Source: https://github.com/messerlab/slim/blob/master/QtSLiM/recipes/Recipe 9.5.1 - A soft sweep from recurrent de novo mutations in a large population.txt

Creates the primary subpopulation 'p1' with a size of 100,000 individuals at the start of the simulation.

```SLiM
sim.addSubpop("p1", 100000);
```

--------------------------------

### SLiM Early Stage Population Setup

Source: https://github.com/messerlab/slim/blob/master/QtSLiM/recipes/Recipe 18.3 - Simulation conditional upon fixation of a sweep, preserving ancestry I.txt

Initializes the simulation ID using the random seed and sets up the initial population size. This runs at the beginning of the simulation.

```slim
1 early() {
	defineConstant("simID", getSeed());
	sim.addSubpop("p1", 500);
}
```

--------------------------------

### Initialize SLiM Simulation Parameters

Source: https://github.com/messerlab/slim/blob/master/QtSLiM/recipes/Recipe 19.14 - Modeling identity by state (IBS) (uniquing mutations with a mutation() callback).txt

Sets up the simulation environment, including nucleotide-based operations, ancestral nucleotides, mutation types, genomic elements, and recombination rates.

```slim
initialize() {
	initializeSLiMOptions(nucleotideBased=T);
	initializeAncestralNucleotides(randomNucleotides(100));
	initializeMutationTypeNuc("m1", 0.5, "f", 0.0);
	initializeGenomicElementType("g1", m1, 1.0, mmJukesCantor(1e-4 / 3));
	initializeGenomicElement(g1, 0, 99);
	initializeRecombinationRate(1e-3);
}
```

--------------------------------

### Mutation Callback Example (Specific Subpopulation)

Source: https://github.com/messerlab/slim/blob/master/QtSLiM/help/SLiMHelpCallbacks.html

A mutation callback restricted to mutations originating from a specific subpopulation.

```SLiM
mutation(, p1) { ... }
```

--------------------------------

### Mutation Callback Example (Specific Mutation Type)

Source: https://github.com/messerlab/slim/blob/master/QtSLiM/help/SLiMHelpCallbacks.html

A mutation callback restricted to a specific mutation type.

```SLiM
mutation(m1) { ... }
```

--------------------------------

### Initialize SLiM Options and Parameters

Source: https://github.com/messerlab/slim/blob/master/QtSLiM/recipes/Recipe 17.3 - Boundaries and boundary conditions I (stopping boundaries).txt

Sets up the simulation environment, including dimensionality, mutation rate, genomic elements, and recombination rate. It also defines interaction types and their spatial functions.

```SLiM
initializeSLiMOptions(dimensionality="xy");
initializeMutationRate(1e-7);
initializeMutationType("m1", 0.5, "f", 0.0);
initializeGenomicElementType("g1", m1, 1.0);
initializeGenomicElement(g1, 0, 99999);
initializeRecombinationRate(1e-8);

initializeInteractionType(1, "xy", reciprocal=T, maxDistance=0.3);  // competition
i1.setInteractionFunction("n", 3.0, 0.1);
```

--------------------------------

### Return statement example in SLiM context

Source: https://github.com/messerlab/slim/blob/master/QtSLiM/help/EidosHelpStatements.html

Demonstrates the use of the return statement to break out of nested loops.

```Eidos
return 5;
```

--------------------------------

### Initial Population Setup

Source: https://github.com/messerlab/slim/blob/master/QtSLiM/recipes/Recipe 16.3 - Modeling clonal haploid bacteria with horizontal gene transfer.txt

Sets up the initial population with two individuals and introduces distinct beneficial mutations at specific genomic locations. This is part of the early simulation phase.

```SLiM
1 early() {
	// start from two bacteria with different beneficial mutations
	sim.addSubpop("p1", 2);
	
	h = p1.individuals.haplosomes;
	h[0].addNewDrawnMutation(m2, asInteger(L * 0.25));
	h[1].addNewDrawnMutation(m2, asInteger(L * 0.75));
}
```

--------------------------------

### Add Subpopulation and Start Simulation

Source: https://github.com/messerlab/slim/blob/master/SLiMgui/Recipes/Recipe 8.1.2 - Reproduction, Sex ratios I.txt

Adds an initial subpopulation to the simulation and defines the point at which the simulation should end.

```SLiM
1 early() { sim.addSubpop("p1", 500, 0.6); }
10000 early() { sim.simulationFinished(); }
```

--------------------------------

### Initialize Population and Simulation End

Source: https://github.com/messerlab/slim/blob/master/QtSLiM/recipes/Recipe 6.4 - Genomic structure, Part IV (Custom display colors in SLiMgui).txt

Sets up the initial population for the simulation and defines the condition for the simulation to finish. The color substitution for chromosomes is cleared to ensure default display behavior.

```SLiM
1 early() {
	sim.chromosomes.colorSubstitution = "";
	sim.addSubpop("p1", 5000);
}
10000 early() { sim.simulationFinished(); }
```

--------------------------------

### Initialize SLiM Model Parameters

Source: https://github.com/messerlab/slim/blob/master/QtSLiM/recipes/Recipe 13.4 - A quantitative genetics model with heritability.txt

Sets up the simulation environment, including heritability, mutation rates, mutation types (neutral and QTL), genomic elements, and recombination rate.

```slim
initialize() {
	defineConstant("h2", 0.1);     // target heritability

	initializeMutationRate(1e-6);
	
	initializeMutationType("m1", 0.5, "f", 0.0);       // neutral
	initializeMutationType("m2", 0.5, "n", 0.0, 1.0);  // QTL
	m2.convertToSubstitution = F;
	
	initializeGenomicElementType("g1", c(m1, m2), c(1, 0.01));
	initializeGenomicElement(g1, 0, 1e5 - 1);
	initializeRecombinationRate(1e-8);
}
```

--------------------------------

### Initialize SLiM Model and Constants

Source: https://github.com/messerlab/slim/blob/master/QtSLiM/recipes/Recipe 15.8 - Evolutionary rescue after environmental change.txt

Sets up the simulation environment, defines constants for population size, environmental optima, and change time, and initializes mutation types, genomic elements, and basic evolutionary parameters.

```SLiM
initialize() {
	initializeSLiMModelType("nonWF");
	defineConstant("K", 500);
	defineConstant("opt1", 0.0);
	defineConstant("opt2", 10.0);
	defineConstant("Tdelta", 10000);
	
	initializeMutationType("m1", 0.5, "n", 0.0, 1.0);  // QTL
	initializeGenomicElementType("g1", m1, 1.0);
	initializeGenomicElement(g1, 0, 99999);
	initializeMutationRate(1e-7);
	initializeRecombinationRate(1e-8);
}
```

--------------------------------

### Mutation Callback Example (Specific Type and Subpopulation)

Source: https://github.com/messerlab/slim/blob/master/QtSLiM/help/SLiMHelpCallbacks.html

A mutation callback restricted to a specific mutation type and subpopulation.

```SLiM
mutation(m1, p1) { ... }
```

--------------------------------

### Initialization and Spatial Setup

Source: https://github.com/messerlab/slim/blob/master/SLiMgui/Recipes/Recipe 17.3 - Boundaries and boundary conditions I (stopping boundaries).txt

Initializes SLiM options, mutation, genomic elements, recombination, and interaction types for a 2D spatial simulation. Sets up the initial population with random spatial positions.

```slim
initialize() {
	initializeSLiMOptions(dimensionality="xy");
	initializeMutationRate(1e-7);
	initializeMutationType("m1", 0.5, "f", 0.0);
	initializeGenomicElementType("g1", m1, 1.0);
	initializeGenomicElement(g1, 0, 99999);
	initializeRecombinationRate(1e-8);
	
	initializeInteractionType(1, "xy", reciprocal=T, maxDistance=0.3);  // competition
	i1.setInteractionFunction("n", 3.0, 0.1);
}
1 late() {
	sim.addSubpop("p1", 500);
	
	// Initial positions are random within spatialBounds
	p1.individuals.setSpatialPosition(p1.pointUniform(500));
}
1: late() {
	i1.evaluate(p1);
}
```

--------------------------------

### Block comment example

Source: https://github.com/messerlab/slim/blob/master/QtSLiM/help/EidosHelpStatements.html

Shows how to use block comments delimited by '/*' and '*/' for multi-line comments or code disabling.

```Eidos
/*

  This computes the factorial x!, which is

  the product of all values from 1 to x, for

  any positive integer x.

*/
x_factorial = product(1:x);
```

--------------------------------

### For Loop for Calculating Squares

Source: https://github.com/messerlab/slim/blob/master/QtSLiM/help/EidosHelpStatements.html

Iterates through a sequence of numbers and prints the square of each element. This is an example of a 'for each' style loop.

```Eidos
> my_sequence = 1:4;
for (element in my_sequence)
  print("The square of " + element + " is " + element^2);
```

--------------------------------

### SLiM Logging Setup

Source: https://github.com/messerlab/slim/blob/master/QtSLiM/recipes/Recipe 15.13 - Range expansion in a stepping-stone model I.txt

Configures a log file to record simulation progress. It logs cycle number, population size, mean and standard deviation of population size, and migrant counts.

```SLiM
1 late() {
	// set up a log file
	log = community.createLogFile("sim_log.txt", sep="\t", logInterval=10);
	log.addCycle();
	log.addPopulationSize();
	log.addMeanSDColumns("size", "sim.subpopulations.individualCount;");
	log.addCustomColumn("pop_migrants", "sum(sim.subpopulations.individuals.migrant);");
	log.addMeanSDColumns("migrants",
		"sapply(sim.subpopulations, 'sum(applyValue.individuals.migrant);');");
}
```

--------------------------------

### Eidos if Statement Example

Source: https://github.com/messerlab/slim/blob/master/QtSLiM/help/EidosHelpStatements.html

Demonstrates a simple if statement with a condition that evaluates to true. The condition must be a scalar value.

```Eidos
if (2^2^2^2^2 > 10000) "exponentiation is da bomb!"
```