Function reference • slendr

Compiling and running population genetic models

slim(): Run a slendr model in SLiM

msprime(): Run a slendr model in msprime

compile_model(): Compile a slendr demographic model

read_model(): Read a previously serialized model configuration

schedule_sampling(): Define sampling events for a given set of populations

Installation and configuration of Python dependencies

setup_env(): Setup a dedicated Python virtual environment for slendr

init_env(): Activate slendr's own dedicated Python environment

check_env(): Check that the active Python environment is setup for slendr

clear_env(): Remove the automatically created slendr Python environment

Model components

population(): Define a population

world(): Define a world map for all spatial operations

Spatial population dynamics

move(): Move the population to a new location in a given amount of time

expand_range(): Expand the population range

shrink_range(): Shrink the population range

set_range(): Update the population range

set_dispersal(): Change dispersal parameters

Non-spatial population dynamics

gene_flow(): Define a gene-flow event between two populations

resize(): Change the population size

Manipulation of spatial objects

region(): Define a geographic region

join(): Merge two spatial slendr objects into one

overlap(): Generate the overlap of two slendr objects

subtract(): Generate the difference between two slendr objects

reproject(): Reproject coordinates between coordinate systems

distance(): Calculate the distance between a pair of spatial boundaries

area(): Calculate the area covered by the given slendr object

Model visualization and diagnostics

plot_map(): Plot slendr geographic features on a map

plot_model(): Plot demographic history encoded in a slendr model

animate_model(): Animate the simulated population dynamics

explore_model(): Open an interactive browser of the spatial model

print(<slendr_pop>) print(<slendr_region>) print(<slendr_map>) print(<slendr_model>) print(<slendr_nodes>): Print a short summary of a slendr object

print(<slendr_ts>): Print tskit's summary table of the Python tree-sequence object

Tree sequence loading and processing

ts_load(): Load a tree sequence file produced by a given model

ts_save(): Save a tree sequence to a file

ts_recapitate(): Recapitate the tree sequence

ts_simplify(): Simplify the tree sequence down to a given set of individuals

ts_mutate(): Add mutations to the given tree sequence

ts_coalesced(): Check that all trees in the tree sequence are fully coalesced

ts_samples(): Extract names and times of individuals of interest in the current tree sequence (either all sampled individuals or those that the user simplified to)

Tree sequence format conversion

ts_genotypes(): Extract genotype table from the tree sequence

ts_eigenstrat(): Convert genotypes to the EIGENSTRAT file format

ts_vcf(): Save genotypes from the tree sequence as a VCF file

Accessing tree sequence components

ts_nodes(): Extract combined annotated table of individuals and nodes

ts_edges(): Extract spatio-temporal edge annotation table from a given tree or tree sequence

ts_table(): Get the table of individuals/nodes/edges/mutations from the tree sequence

ts_phylo(): Convert a tree in the tree sequence to an object of the class phylo

ts_tree(): Get a tree from a given tree sequence

ts_draw(): Plot a graphical representation of a single tree

ts_metadata(): Extract list with tree sequence metadata saved by SLiM

ts_ancestors(): Extract (spatio-)temporal ancestral history for given nodes/individuals

ts_descendants(): Extract all descendants of a given tree-sequence node

Tree sequence statistics

ts_f2() ts_f3() ts_f4() ts_f4ratio(): Calculate the f2, f3, f4, and f4-ratio statistics

ts_afs(): Compute the allele frequency spectrum (AFS)

ts_divergence(): Calculate pairwise divergence between sets of individuals

ts_diversity(): Calculate diversity in given sets of individuals

ts_fst(): Calculate pairwise statistics between sets of individuals

ts_tajima(): Calculate Tajima's D for given sets of individuals

ts_segregating(): Calculate the density of segregating sites for the given sets of individuals

ts_ibd(): Collect Identity-by-Descent (IBD) segments