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add recipe 16.11, life-long monogamous mating
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‎QtSLiM/recipes.qrc‎

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<file>recipes/Recipe 8.3.3 - Haploids with recombination.txt</file>
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<file>recipes/Recipe 8.3.4 - Sex-chromosome evolution and null haplosomes.txt</file>
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<file>recipes/Recipe 8.3.5 - Modeling the full human genome.txt</file>
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<file>recipes/Recipe 8.3.6 - A model of bryophytes with UV sex determination.txt</file>
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<file>recipes/Recipe 8.3.7 - Output from multiple-chromosome models.txt</file>
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<file>recipes/Recipe 9.1 - Introducing adaptive mutations.txt</file>
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<file>recipes/Recipe 9.2 - Making sweeps conditional on fixation.txt</file>
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<file>recipes/Recipe 16.8 - Modeling haplodiploidy with addRecombinant().txt</file>
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<file>recipes/Recipe 16.9 - Complex multi-chromosome inheritance with addMultiRecombinant().txt</file>
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<file>recipes/Recipe 16.10 - Modeling pseudo-autosomal regions (PARs) with addMultiRecombinant().txt</file>
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<file>recipes/Recipe 16.11 - Life-long monogamous mating.txt</file>
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<file>recipes/Recipe 17.1 - A simple 2D continuous-space model.txt</file>
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<file>recipes/Recipe 17.2 - Spatial competition.txt</file>
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<file>recipes/Recipe 17.3 - Boundaries and boundary conditions I (stopping boundaries).txt</file>
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<file>recipes/Recipe 20.6 - A coevolutionary host-parasitoid trait-matching model.txt</file>
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<file>recipes/Recipe 20.7 - A coevolutionary host-parasite matching-allele model.txt</file>
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<file>recipes/Recipe 20.8 - Within-host reproduction in a host-pathogen model.txt</file>
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<file>recipes/Recipe 8.3.6 - A model of bryophytes with UV sex determination.txt</file>
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</qresource>
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</RCC>

‎QtSLiM/recipes/Recipe 16.11 - Life-long monogamous mating.txt‎

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// Keywords: monogamy, monogamous mating, nonWF, non-Wright-Fisher
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initialize() {
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defineConstant("K", 500); // carrying capacity
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defineConstant("R_AGE_M", 3); // minimum age of reproduction (male)
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defineConstant("R_AGE_F", 4); // minimum age of reproduction (female)
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defineConstant("FECUN", 0.2); // mean fecundity per female per tick
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initializeSLiMModelType("nonWF");
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initializeSex();
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}
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1 first() {
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sim.addSubpop("p1", K);
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p1.individuals.age = rdunif(K, min=0, max=15); // initial variation in age
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p1.individuals.tag = -1; // mark all individuals as unmated
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}
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first() {
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// find mated individuals whose mate has died, and mark them as unmated
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mated_individuals = p1.individuals;
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mated_individuals = mated_individuals[mated_individuals.tag >= 0];
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if (size(mated_individuals) > 0)
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{
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tags = mated_individuals.tag;
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tag_counts = tabulate(tags, maxbin=size(mated_individuals)-1);
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tags_to_fix = which(tag_counts == 1);
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unmated_indices = match(tags_to_fix, tags);
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mated_individuals[unmated_indices].tag = -1;
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}
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// find the next tag value to use for new mating pairs
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next_tag = max(p1.individuals.tag) + 1;
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// find unmated individuals that are of reproductive age
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unmated_F = p1.subsetIndividuals(sex="F", tag=-1, minAge=R_AGE_F);
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unmated_M = p1.subsetIndividuals(sex="M", tag=-1, minAge=R_AGE_M);
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// pair individuals randomly; some individuals may be left unpaired
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pair_count = min(size(unmated_F), size(unmated_M));
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unmated_F = sample(unmated_F, pair_count, replace=F);
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unmated_M = sample(unmated_M, pair_count, replace=F);
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for (f in unmated_F, m in unmated_M, tag in seqLen(pair_count) + next_tag)
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{
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f.tag = tag;
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m.tag = tag;
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}
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}
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reproduction() {
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// find the subset of individuals that have a mate
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mated_F = p1.subsetIndividuals(sex="F");
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mated_F = mated_F[mated_F.tag >= 0];
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mated_M = p1.subsetIndividuals(sex="M");
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mated_M = mated_M[mated_M.tag >= 0];
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// look up the male for each female, by tag
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male_indices = match(mated_F.tag, mated_M.tag);
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mated_M = mated_M[male_indices];
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pair_count = size(mated_F);
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// produce offspring from each mated pair
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for (f in mated_F,
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m in mated_M,
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c in rpois(pair_count, FECUN),
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new_tag in seqLen(pair_count))
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{
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// re-tag paired individuals to compact tags down
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f.tag = new_tag;
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m.tag = new_tag;
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offspring = p1.addCrossed(f, m, count=c);
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offspring.tag = -1; // mark offspring as unmated
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}
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self.active = 0; // deactivate for the rest of the tick ("big bang")
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}
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early() {
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// density-dependent population regulation
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p1.fitnessScaling = K / p1.individualCount;
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}
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10000 late() { }

‎SLiMgui/Recipes/Recipe 16.11 - Life-long monogamous mating.txt‎

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// Keywords: monogamy, monogamous mating, nonWF, non-Wright-Fisher
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3+
initialize() {
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defineConstant("K", 500); // carrying capacity
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defineConstant("R_AGE_M", 3); // minimum age of reproduction (male)
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defineConstant("R_AGE_F", 4); // minimum age of reproduction (female)
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defineConstant("FECUN", 0.2); // mean fecundity per female per tick
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initializeSLiMModelType("nonWF");
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initializeSex();
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}
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1 first() {
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sim.addSubpop("p1", K);
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p1.individuals.age = rdunif(K, min=0, max=15); // initial variation in age
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p1.individuals.tag = -1; // mark all individuals as unmated
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}
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first() {
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// find mated individuals whose mate has died, and mark them as unmated
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mated_individuals = p1.individuals;
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mated_individuals = mated_individuals[mated_individuals.tag >= 0];
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if (size(mated_individuals) > 0)
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{
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tags = mated_individuals.tag;
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tag_counts = tabulate(tags, maxbin=size(mated_individuals)-1);
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tags_to_fix = which(tag_counts == 1);
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unmated_indices = match(tags_to_fix, tags);
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mated_individuals[unmated_indices].tag = -1;
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}
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// find the next tag value to use for new mating pairs
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next_tag = max(p1.individuals.tag) + 1;
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// find unmated individuals that are of reproductive age
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unmated_F = p1.subsetIndividuals(sex="F", tag=-1, minAge=R_AGE_F);
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unmated_M = p1.subsetIndividuals(sex="M", tag=-1, minAge=R_AGE_M);
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// pair individuals randomly; some individuals may be left unpaired
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pair_count = min(size(unmated_F), size(unmated_M));
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unmated_F = sample(unmated_F, pair_count, replace=F);
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unmated_M = sample(unmated_M, pair_count, replace=F);
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for (f in unmated_F, m in unmated_M, tag in seqLen(pair_count) + next_tag)
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{
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f.tag = tag;
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m.tag = tag;
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}
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}
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reproduction() {
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// find the subset of individuals that have a mate
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mated_F = p1.subsetIndividuals(sex="F");
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mated_F = mated_F[mated_F.tag >= 0];
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mated_M = p1.subsetIndividuals(sex="M");
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mated_M = mated_M[mated_M.tag >= 0];
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// look up the male for each female, by tag
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male_indices = match(mated_F.tag, mated_M.tag);
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mated_M = mated_M[male_indices];
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pair_count = size(mated_F);
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// produce offspring from each mated pair
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for (f in mated_F,
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m in mated_M,
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c in rpois(pair_count, FECUN),
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new_tag in seqLen(pair_count))
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{
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// re-tag paired individuals to compact tags down
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f.tag = new_tag;
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m.tag = new_tag;
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offspring = p1.addCrossed(f, m, count=c);
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offspring.tag = -1; // mark offspring as unmated
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}
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self.active = 0; // deactivate for the rest of the tick ("big bang")
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}
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early() {
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// density-dependent population regulation
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p1.fitnessScaling = K / p1.individualCount;
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}
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10000 late() { }

‎VERSIONS‎

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development head (in the master branch):
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add recipe 16.11, life-long monogamous mating
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version 5.0 (Eidos version 4.0):

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