add recipe 22.7 back in

QtSLiM/recipes.qrc

@@ -202,5 +202,6 @@
         <file>recipes/Recipe 19.6 - A coevolutionary host-parasitoid trait-matching model.txt</file>
         <file>recipes/Recipe 19.7 - A coevolutionary host-parasite matching-allele model.txt</file>
         <file>recipes/Recipe 19.8 - Within-host reproduction in a host-pathogen model.txt</file>
+        <file>recipes/Recipe 22.7 - Parallelizing nonWF reproduction and spatial interactions.txt</file>
     </qresource>
 </RCC>

QtSLiM/recipes/Recipe 22.7 - Parallelizing nonWF reproduction and spatial interactions.txt

@@ -0,0 +1,62 @@
+initialize() {
+	initializeSLiMModelType("nonWF");
+	initializeSLiMOptions(dimensionality="xy");
+	defineConstant("K", 100000);  // carrying-capacity density
+	defineConstant("S", 0.005);   // sigma_S, the spatial interaction width
+	defineConstant("M", 0.025);   // sigma_M, the spatial mating width
+
+	initializeMutationType("m1", 0.5, "f", 0.0);
+	m1.convertToSubstitution = T;
+
+	initializeGenomicElementType("g1", m1, 1.0);
+	initializeGenomicElement(g1, 0, 1e8 - 1);
+	initializeMutationRate(1e-7);
+	initializeRecombinationRate(1e-8);
+
+	// competition kernel
+	initializeInteractionType(1, "xy", reciprocal=T, maxDistance=S * 2);
+	i1.setInteractionFunction("n", 1.0, S);
+
+	// mating kernel
+	initializeInteractionType(2, "xy", reciprocal=T, maxDistance=M * 2);
+	i1.setInteractionFunction("n", 1.0, M);
+}
+2: first() {
+	i2.evaluate(p1);
+}
+reproduction() {
+	inds = p1.individuals;
+	mates = i2.drawByStrength(inds, 1, returnDict=T);
+	order = mates.compactIndices();
+	inds = inds[order];
+	num = rpois(size(inds), 5);
+	nonzero_indices = which(num > 0);
+
+	for (i in nonzero_indices)
+	{
+		ind = inds[i];
+		offspring = p1.addCrossed(ind, mates.getValue(i), count=num[i], defer=T);
+		offspring.setSpatialPosition(ind.spatialPosition);
+	}
+
+	self.active = 0;
+}
+1 early() {
+	sim.addSubpop("p1", K);
+	p1.individuals.setSpatialPosition(p1.pointUniform(K));
+}
+early() {
+	// deviate offspring from their maternal positions
+	newborns = p1.subsetIndividuals(maxAge=0);
+	old_pos = newborns.spatialPosition;
+	new_pos = p1.pointReflected(old_pos + rnorm(size(old_pos), 0, 0.02));
+	newborns.setSpatialPosition(new_pos);
+}
+early() {
+	// spatial competition
+	i1.evaluate(p1);
+	inds = p1.individuals;
+	competition = i1.localPopulationDensity(inds);
+	inds.fitnessScaling = K / competition;
+}
+100 late() { }

SLiMgui/Recipes/Recipe 22.7 - Parallelizing nonWF reproduction and spatial interactions.txt

@@ -0,0 +1,62 @@
+initialize() {
+	initializeSLiMModelType("nonWF");
+	initializeSLiMOptions(dimensionality="xy");
+	defineConstant("K", 100000);  // carrying-capacity density
+	defineConstant("S", 0.005);   // sigma_S, the spatial interaction width
+	defineConstant("M", 0.025);   // sigma_M, the spatial mating width
+
+	initializeMutationType("m1", 0.5, "f", 0.0);
+	m1.convertToSubstitution = T;
+
+	initializeGenomicElementType("g1", m1, 1.0);
+	initializeGenomicElement(g1, 0, 1e8 - 1);
+	initializeMutationRate(1e-7);
+	initializeRecombinationRate(1e-8);
+
+	// competition kernel
+	initializeInteractionType(1, "xy", reciprocal=T, maxDistance=S * 2);
+	i1.setInteractionFunction("n", 1.0, S);
+
+	// mating kernel
+	initializeInteractionType(2, "xy", reciprocal=T, maxDistance=M * 2);
+	i1.setInteractionFunction("n", 1.0, M);
+}
+2: first() {
+	i2.evaluate(p1);
+}
+reproduction() {
+	inds = p1.individuals;
+	mates = i2.drawByStrength(inds, 1, returnDict=T);
+	order = mates.compactIndices();
+	inds = inds[order];
+	num = rpois(size(inds), 5);
+	nonzero_indices = which(num > 0);
+
+	for (i in nonzero_indices)
+	{
+		ind = inds[i];
+		offspring = p1.addCrossed(ind, mates.getValue(i), count=num[i], defer=T);
+		offspring.setSpatialPosition(ind.spatialPosition);
+	}
+
+	self.active = 0;
+}
+1 early() {
+	sim.addSubpop("p1", K);
+	p1.individuals.setSpatialPosition(p1.pointUniform(K));
+}
+early() {
+	// deviate offspring from their maternal positions
+	newborns = p1.subsetIndividuals(maxAge=0);
+	old_pos = newborns.spatialPosition;
+	new_pos = p1.pointReflected(old_pos + rnorm(size(old_pos), 0, 0.02));
+	newborns.setSpatialPosition(new_pos);
+}
+early() {
+	// spatial competition
+	i1.evaluate(p1);
+	inds = p1.individuals;
+	competition = i1.localPopulationDensity(inds);
+	inds.fitnessScaling = K / competition;
+}
+100 late() { }