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Type: Package
Title: 'R' Access to the 'tskit C' API
Version: 0.2.0
Date: 2026-01-27
Description: 'Tskit' enables efficient storage, manipulation, and analysis of ancestral recombination graphs (ARGs) using succinct tree sequence encoding. The tree sequence encoding of an ARG is described in Wong et al. (2024) <doi:10.1093/genetics/iyae100>, while ‘tskit' project is described in Jeffrey et al. (2026) <doi:10.48550/arXiv.2602.09649>. See also https://tskit.dev for project news, documentation, and tutorials. ’Tskit' provides 'Python', 'C', and 'Rust' application programming interfaces (APIs). The 'Python' API can be called from 'R' via the 'reticulate' package to load and analyse tree sequences as described at https://tskit.dev/tutorials/tskitr.html. 'RcppTskit' provides 'R' access to the 'tskit C' API for cases where the 'reticulate' option is not optimal; for example, high-performance or low-level work with tree sequences. Currently, 'RcppTskit' provides a limited set of 'R' functions because the 'Python' API and 'reticulate' already covers most needs.
License: MIT + file LICENSE
URL: https://github.com/HighlanderLab/RcppTskit
BugReports: https://github.com/HighlanderLab/RcppTskit/issues
Depends: R (≥ 4.0.0)
Imports: methods, R6, Rcpp (≥ 1.0.8), reticulate (≥ 1.43.0)
Suggests: covr, knitr, quarto, spelling, testthat (≥ 3.0.0)
LinkingTo: Rcpp (≥ 0.12.10)
VignetteBuilder: quarto
Config/testthat/edition: 3
Encoding: UTF-8
Language: en-GB
RoxygenNote: 7.3.3
NeedsCompilation: yes
Packaged: 2026-02-22 09:34:21 UTC; ggorjanc
Author: Gregor Gorjanc ORCID iD [aut, cre, cph], Tskit Developers [cph] (Authors of included tskit C library)
Maintainer: Gregor Gorjanc <gregor.gorjanc@gmail.com>
Repository: CRAN
Date/Publication: 2026-02-27 16:02:24 UTC

RcppTskit: 'R' Access to the 'tskit C' API

Description

Tskit enables efficient storage, manipulation, and analysis of ancestral recombination graphs (ARGs) using succinct tree sequence encoding. The tree sequence encoding of an ARG is described in Wong et al. (2024) <doi:10.1093/genetics/iyae100>, while tskit project is described in Jeffrey et al. (2026) <doi:10.48550/arXiv.2602.09649>. See also https://tskit.dev for project news, documentation, and tutorials. Tskit provides Python, C, and Rust application programming interfaces (APIs). The Python API can be called from R via the reticulate package to load and analyse tree sequences as described at https://tskit.dev/tutorials/tskitr.html. RcppTskit provides R access to the tskit C API for cases where the reticulate option is not optimal; for example; high-performance or low-level work with tree sequences. Currently, RcppTskit provides a limited set of R functions because the Python API and reticulate already covers most needs.

Author(s)

Maintainer: Gregor Gorjanc gregor.gorjanc@gmail.com (ORCID) [copyright holder]

Other contributors:

See Also

Useful links:

Examples

vignette(package="RcppTskit")

Table collection R6 class (TableCollection)

Description

An R6 class holding an external pointer to a table collection object. As an R6 class, its methods look Pythonic and therefore resemble the tskit Python API. Since the class only holds the pointer, it is lightweight. Currently there is a limited set of R methods for working the tree sequence.

Public fields

pointer

external pointer to the table collection

Methods

Public methods

Method new()

Create a TableCollection from a file or a pointer.

Usage
TableCollection$new(
  file,
  skip_tables = FALSE,
  skip_reference_sequence = FALSE,
  pointer = NULL
)
Arguments
file

a string specifying the full path of the tree sequence file.

skip_tables

logical; if TRUE, load only non-table information.

skip_reference_sequence

logical; if TRUE, skip loading reference sequence information.

pointer

an external pointer (externalptr) to a table collection.

Details

See the corresponding Python function at https://github.com/tskit-dev/tskit/blob/dc394d72d121c99c6dcad88f7a4873880924dd72/python/tskit/tables.py#L3463.

Returns

A TableCollection object.

Examples
ts_file <- system.file("examples/test.trees", package = "RcppTskit")
tc <- TableCollection$new(file = ts_file)
is(tc)
tc

Method dump()

Write a table collection to a file.

Usage
TableCollection$dump(file)
Arguments
file

a string specifying the full path of the tree sequence file.

Details

See the corresponding Python function at https://tskit.dev/tskit/docs/latest/python-api.html#tskit.TableCollection.dump.

Returns

No return value; called for side effects.

Examples
ts_file <- system.file("examples/test.trees", package = "RcppTskit")
tc <- TableCollection$new(file = ts_file)
dump_file <- tempfile()
tc$dump(dump_file)
tc$write(dump_file) # alias
\dontshow{file.remove(dump_file)}

Method write()

Alias for TableCollection$dump.

Usage
TableCollection$write(file)
Arguments
file

see TableCollection$dump.

Method tree_sequence()

Create a TreeSequence from this table collection.

Usage
TableCollection$tree_sequence()
Details

See the corresponding Python function at https://tskit.dev/tskit/docs/latest/python-api.html#tskit.TableCollection.tree_sequence.

Returns

A TreeSequence object.

Examples
ts_file <- system.file("examples/test.trees", package = "RcppTskit")
tc <- TableCollection$new(file = ts_file)
ts <- tc$tree_sequence()
is(ts)

Method r_to_py()

This function saves a table collection from R to disk and loads it into reticulate Python for use with the tskit Python API.

Usage
TableCollection$r_to_py(tskit_module = get_tskit_py(), cleanup = TRUE)
Arguments
tskit_module

reticulate Python module of tskit. By default, it calls get_tskit_py to obtain the module.

cleanup

logical; delete the temporary file at the end of the function?

Details

See https://tskit.dev/tutorials/tables_and_editing.html#tables-and-editing on what you can do with the tables.

Returns

Table collection in reticulate Python.

Examples
\dontrun{
  ts_file <- system.file("examples/test.trees", package = "RcppTskit")
  tc_r <- tc_load(ts_file)
  is(tc_r)
  tc_r$print()

  # Transfer the table collection to reticulate Python and use tskit Python API
  tskit <- get_tskit_py()
  if (check_tskit_py(tskit)) {
    tc_py <- tc_r$r_to_py()
    is(tc_py)
    tmp <- tc_py$simplify(samples = c(0L, 1L, 2L, 3L))
    tmp
    tc_py$individuals$num_rows # 2
    tc_py$nodes$num_rows # 8
    tc_py$nodes$time # 0.0 ... 5.0093910
  }
}

Method print()

Print a summary of a table collection and its contents.

Usage
TableCollection$print()
Returns

A list with two data.frames; the first contains table collection properties and their values; the second contains the number of rows in each table and the length of their metadata.

Examples
ts_file <- system.file("examples/test.trees", package = "RcppTskit")
tc <- tc_load(file = ts_file)
tc$print()
tc

Method clone()

The objects of this class are cloneable with this method.

Usage
TableCollection$clone(deep = FALSE)
Arguments
deep

Whether to make a deep clone.

See Also

tc_py_to_r, tc_load, and TableCollection$dump.

Examples


## ------------------------------------------------
## Method `TableCollection$new`
## ------------------------------------------------

ts_file <- system.file("examples/test.trees", package = "RcppTskit")
tc <- TableCollection$new(file = ts_file)
is(tc)
tc

## ------------------------------------------------
## Method `TableCollection$dump`
## ------------------------------------------------

ts_file <- system.file("examples/test.trees", package = "RcppTskit")
tc <- TableCollection$new(file = ts_file)
dump_file <- tempfile()
tc$dump(dump_file)
tc$write(dump_file) # alias


## ------------------------------------------------
## Method `TableCollection$tree_sequence`
## ------------------------------------------------

ts_file <- system.file("examples/test.trees", package = "RcppTskit")
tc <- TableCollection$new(file = ts_file)
ts <- tc$tree_sequence()
is(ts)

## ------------------------------------------------
## Method `TableCollection$r_to_py`
## ------------------------------------------------

## Not run: 
  ts_file <- system.file("examples/test.trees", package = "RcppTskit")
  tc_r <- tc_load(ts_file)
  is(tc_r)
  tc_r$print()

  # Transfer the table collection to reticulate Python and use tskit Python API
  tskit <- get_tskit_py()
  if (check_tskit_py(tskit)) {
    tc_py <- tc_r$r_to_py()
    is(tc_py)
    tmp <- tc_py$simplify(samples = c(0L, 1L, 2L, 3L))
    tmp
    tc_py$individuals$num_rows # 2
    tc_py$nodes$num_rows # 8
    tc_py$nodes$time # 0.0 ... 5.0093910
  }

## End(Not run)

## ------------------------------------------------
## Method `TableCollection$print`
## ------------------------------------------------

ts_file <- system.file("examples/test.trees", package = "RcppTskit")
tc <- tc_load(file = ts_file)
tc$print()
tc

Succinct tree sequence R6 class (TreeSequence)

Description

An R6 class holding an external pointer to a tree sequence object. As an R6 class, its methods look Pythonic and therefore resemble the tskit Python API. Since the class only holds the pointer, it is lightweight. Currently there is a limited set of R methods for working with the tree sequence.

Public fields

pointer

external pointer to the tree sequence

Methods

Public methods

Method new()

Create a TreeSequence from a file or a pointer. See ts_load for details and examples.

Usage
TreeSequence$new(
  file,
  skip_tables = FALSE,
  skip_reference_sequence = FALSE,
  pointer = NULL
)
Arguments
file

a string specifying the full path of the tree sequence file.

skip_tables

logical; if TRUE, load only non-table information.

skip_reference_sequence

logical; if TRUE, skip loading reference sequence information.

pointer

an external pointer (externalptr) to a tree sequence.

Details

See the corresponding Python function at https://tskit.dev/tskit/docs/latest/python-api.html#tskit.load.

Returns

A TreeSequence object.

Examples
ts_file <- system.file("examples/test.trees", package = "RcppTskit")
ts <- TreeSequence$new(file = ts_file)
is(ts)
ts
ts$num_nodes()
# Also
ts <- ts_load(ts_file)
is(ts)

Method dump()

Write a tree sequence to a file.

Usage
TreeSequence$dump(file)
Arguments
file

a string specifying the full path of the tree sequence file.

Details

See the corresponding Python function at https://tskit.dev/tskit/docs/latest/python-api.html#tskit.TreeSequence.dump.

Returns

No return value; called for side effects.

Examples
ts_file <- system.file("examples/test.trees", package = "RcppTskit")
ts <- ts_load(ts_file)
dump_file <- tempfile()
ts$dump(dump_file)
ts$write(dump_file) # alias
\dontshow{file.remove(dump_file)}

Method write()

Alias for TreeSequence$dump.

Usage
TreeSequence$write(file)
Arguments
file

see TreeSequence$dump.

Method dump_tables()

Copy the tables into a TableCollection.

Usage
TreeSequence$dump_tables()
Details

See the corresponding Python function at https://tskit.dev/tskit/docs/latest/python-api.html#tskit.TreeSequence.dump_tables.

Returns

A TableCollection object.

Examples
ts_file <- system.file("examples/test.trees", package = "RcppTskit")
ts <- ts_load(ts_file)
tc <- ts$dump_tables()
is(tc)

Method print()

Print a summary of a tree sequence and its contents.

Usage
TreeSequence$print()
Returns

A list with two data.frames; the first contains tree sequence properties and their values; the second contains the number of rows in each table and the length of their metadata.

Examples
ts_file <- system.file("examples/test.trees", package = "RcppTskit")
ts <- ts_load(ts_file)
ts$print()
ts

Method r_to_py()

This function saves a tree sequence from R to disk and loads it into reticulate Python for use with the tskit Python API.

Usage
TreeSequence$r_to_py(tskit_module = get_tskit_py(), cleanup = TRUE)
Arguments
tskit_module

reticulate Python module of tskit. By default, it calls get_tskit_py to obtain the module.

cleanup

logical; delete the temporary file at the end of the function?

Returns

Tree sequence in reticulate Python.

Examples
\dontrun{
  ts_file <- system.file("examples/test.trees", package = "RcppTskit")
  ts_r <- ts_load(ts_file)
  is(ts_r)
  ts_r$num_individuals() # 8

  # Transfer the tree sequence to reticulate Python and use tskit Python API
  tskit <- get_tskit_py()
  if (check_tskit_py(tskit)) {
    ts_py <- ts_r$r_to_py()
    is(ts_py)
    ts_py$num_individuals # 8
    ts2_py <- ts_py$simplify(samples = c(0L, 1L, 2L, 3L))
    ts_py$num_individuals # 8
    ts2_py$num_individuals # 2
    ts2_py$num_nodes # 8
    ts2_py$tables$nodes$time # 0.0 ... 5.0093910
  }
}

Method num_provenances()

Get the number of provenances in a tree sequence.

Usage
TreeSequence$num_provenances()
Examples
ts_file <- system.file("examples/test.trees", package = "RcppTskit")
ts <- ts_load(ts_file)
ts$num_provenances()

Method num_populations()

Get the number of populations in a tree sequence.

Usage
TreeSequence$num_populations()
Examples
ts_file <- system.file("examples/test.trees", package = "RcppTskit")
ts <- ts_load(ts_file)
ts$num_populations()

Method num_migrations()

Get the number of migrations in a tree sequence.

Usage
TreeSequence$num_migrations()
Examples
ts_file <- system.file("examples/test.trees", package = "RcppTskit")
ts <- ts_load(ts_file)
ts$num_migrations()

Method num_individuals()

Get the number of individuals in a tree sequence.

Usage
TreeSequence$num_individuals()
Examples
ts_file <- system.file("examples/test.trees", package = "RcppTskit")
ts <- ts_load(ts_file)
ts$num_individuals()

Method num_samples()

Get the number of samples (of nodes) in a tree sequence.

Usage
TreeSequence$num_samples()
Examples
ts_file <- system.file("examples/test.trees", package = "RcppTskit")
ts <- ts_load(ts_file)
ts$num_samples()

Method num_nodes()

Get the number of nodes in a tree sequence.

Usage
TreeSequence$num_nodes()
Examples
ts_file <- system.file("examples/test.trees", package = "RcppTskit")
ts <- ts_load(ts_file)
ts$num_nodes()

Method num_edges()

Get the number of edges in a tree sequence.

Usage
TreeSequence$num_edges()
Examples
ts_file <- system.file("examples/test.trees", package = "RcppTskit")
ts <- ts_load(ts_file)
ts$num_edges()

Method num_trees()

Get the number of trees in a tree sequence.

Usage
TreeSequence$num_trees()
Examples
ts_file <- system.file("examples/test.trees", package = "RcppTskit")
ts <- ts_load(ts_file)
ts$num_trees()

Method num_sites()

Get the number of sites in a tree sequence.

Usage
TreeSequence$num_sites()
Examples
ts_file <- system.file("examples/test.trees", package = "RcppTskit")
ts <- ts_load(ts_file)
ts$num_sites()

Method num_mutations()

Get the number of mutations in a tree sequence.

Usage
TreeSequence$num_mutations()
Examples
ts_file <- system.file("examples/test.trees", package = "RcppTskit")
ts <- ts_load(ts_file)
ts$num_mutations()

Method sequence_length()

Get the sequence length.

Usage
TreeSequence$sequence_length()
Examples
ts_file <- system.file("examples/test.trees", package = "RcppTskit")
ts <- ts_load(ts_file)
ts$sequence_length()

Method time_units()

Get the time units string.

Usage
TreeSequence$time_units()
Examples
ts_file <- system.file("examples/test.trees", package = "RcppTskit")
ts <- ts_load(ts_file)
ts$time_units()

Method min_time()

Get the min time in node table and mutation table.

Usage
TreeSequence$min_time()
Examples
ts_file <- system.file("examples/test.trees", package = "RcppTskit")
ts <- ts_load(ts_file)
ts$min_time()

Method max_time()

Get the max time in node table and mutation table.

Usage
TreeSequence$max_time()
Examples
ts_file <- system.file("examples/test.trees", package = "RcppTskit")
ts <- ts_load(ts_file)
ts$max_time()

Method metadata_length()

Get the length of metadata in a tree sequence and its tables.

Usage
TreeSequence$metadata_length()
Returns

A named list with the length of metadata.

Examples
ts_file <- system.file("examples/test.trees", package = "RcppTskit")
ts <- ts_load(ts_file)
ts$metadata_length()

Method clone()

The objects of this class are cloneable with this method.

Usage
TreeSequence$clone(deep = FALSE)
Arguments
deep

Whether to make a deep clone.

See Also

ts_load

ts_py_to_r, ts_load, and TreeSequence$dump.

Examples


## ------------------------------------------------
## Method `TreeSequence$new`
## ------------------------------------------------

ts_file <- system.file("examples/test.trees", package = "RcppTskit")
ts <- TreeSequence$new(file = ts_file)
is(ts)
ts
ts$num_nodes()
# Also
ts <- ts_load(ts_file)
is(ts)

## ------------------------------------------------
## Method `TreeSequence$dump`
## ------------------------------------------------

ts_file <- system.file("examples/test.trees", package = "RcppTskit")
ts <- ts_load(ts_file)
dump_file <- tempfile()
ts$dump(dump_file)
ts$write(dump_file) # alias


## ------------------------------------------------
## Method `TreeSequence$dump_tables`
## ------------------------------------------------

ts_file <- system.file("examples/test.trees", package = "RcppTskit")
ts <- ts_load(ts_file)
tc <- ts$dump_tables()
is(tc)

## ------------------------------------------------
## Method `TreeSequence$print`
## ------------------------------------------------

ts_file <- system.file("examples/test.trees", package = "RcppTskit")
ts <- ts_load(ts_file)
ts$print()
ts

## ------------------------------------------------
## Method `TreeSequence$r_to_py`
## ------------------------------------------------

## Not run: 
  ts_file <- system.file("examples/test.trees", package = "RcppTskit")
  ts_r <- ts_load(ts_file)
  is(ts_r)
  ts_r$num_individuals() # 8

  # Transfer the tree sequence to reticulate Python and use tskit Python API
  tskit <- get_tskit_py()
  if (check_tskit_py(tskit)) {
    ts_py <- ts_r$r_to_py()
    is(ts_py)
    ts_py$num_individuals # 8
    ts2_py <- ts_py$simplify(samples = c(0L, 1L, 2L, 3L))
    ts_py$num_individuals # 8
    ts2_py$num_individuals # 2
    ts2_py$num_nodes # 8
    ts2_py$tables$nodes$time # 0.0 ... 5.0093910
  }

## End(Not run)

## ------------------------------------------------
## Method `TreeSequence$num_provenances`
## ------------------------------------------------

ts_file <- system.file("examples/test.trees", package = "RcppTskit")
ts <- ts_load(ts_file)
ts$num_provenances()

## ------------------------------------------------
## Method `TreeSequence$num_populations`
## ------------------------------------------------

ts_file <- system.file("examples/test.trees", package = "RcppTskit")
ts <- ts_load(ts_file)
ts$num_populations()

## ------------------------------------------------
## Method `TreeSequence$num_migrations`
## ------------------------------------------------

ts_file <- system.file("examples/test.trees", package = "RcppTskit")
ts <- ts_load(ts_file)
ts$num_migrations()

## ------------------------------------------------
## Method `TreeSequence$num_individuals`
## ------------------------------------------------

ts_file <- system.file("examples/test.trees", package = "RcppTskit")
ts <- ts_load(ts_file)
ts$num_individuals()

## ------------------------------------------------
## Method `TreeSequence$num_samples`
## ------------------------------------------------

ts_file <- system.file("examples/test.trees", package = "RcppTskit")
ts <- ts_load(ts_file)
ts$num_samples()

## ------------------------------------------------
## Method `TreeSequence$num_nodes`
## ------------------------------------------------

ts_file <- system.file("examples/test.trees", package = "RcppTskit")
ts <- ts_load(ts_file)
ts$num_nodes()

## ------------------------------------------------
## Method `TreeSequence$num_edges`
## ------------------------------------------------

ts_file <- system.file("examples/test.trees", package = "RcppTskit")
ts <- ts_load(ts_file)
ts$num_edges()

## ------------------------------------------------
## Method `TreeSequence$num_trees`
## ------------------------------------------------

ts_file <- system.file("examples/test.trees", package = "RcppTskit")
ts <- ts_load(ts_file)
ts$num_trees()

## ------------------------------------------------
## Method `TreeSequence$num_sites`
## ------------------------------------------------

ts_file <- system.file("examples/test.trees", package = "RcppTskit")
ts <- ts_load(ts_file)
ts$num_sites()

## ------------------------------------------------
## Method `TreeSequence$num_mutations`
## ------------------------------------------------

ts_file <- system.file("examples/test.trees", package = "RcppTskit")
ts <- ts_load(ts_file)
ts$num_mutations()

## ------------------------------------------------
## Method `TreeSequence$sequence_length`
## ------------------------------------------------

ts_file <- system.file("examples/test.trees", package = "RcppTskit")
ts <- ts_load(ts_file)
ts$sequence_length()

## ------------------------------------------------
## Method `TreeSequence$time_units`
## ------------------------------------------------

ts_file <- system.file("examples/test.trees", package = "RcppTskit")
ts <- ts_load(ts_file)
ts$time_units()

## ------------------------------------------------
## Method `TreeSequence$min_time`
## ------------------------------------------------

ts_file <- system.file("examples/test.trees", package = "RcppTskit")
ts <- ts_load(ts_file)
ts$min_time()

## ------------------------------------------------
## Method `TreeSequence$max_time`
## ------------------------------------------------

ts_file <- system.file("examples/test.trees", package = "RcppTskit")
ts <- ts_load(ts_file)
ts$max_time()

## ------------------------------------------------
## Method `TreeSequence$metadata_length`
## ------------------------------------------------

ts_file <- system.file("examples/test.trees", package = "RcppTskit")
ts <- ts_load(ts_file)
ts$metadata_length()

Get the reticulate tskit Python module

Description

This function imports the reticulate Python tskit module. If it is not yet installed, it attempts to install it first.

Usage

get_tskit_py(object_name = "tskit", force = FALSE)

check_tskit_py(object, stop = FALSE)

Arguments

object_name

character name of the object holding the reticulate tskit module. If this object exists in the global R environment and is a reticulate Python module, it is returned. Otherwise, the function attempts to install and import tskit before returning it.

force

logical; force installation and/or import before returning the reticulate Python module.

object

reticulate Python module.

stop

logical; whether to throw an error in check_tskit_py.

Details

This function is meant for users running tskit <- get_tskit_py() or similar code, and for other functions in this package that need the tskit reticulate Python module. The point of get_tskit_py is to avoid importing the module repeatedly; if it has been imported already, we reuse that instance. This process can be sensitive to the reticulate Python setup, module availability, and internet access.

Value

get_tskit_py returns the reticulate Python module tskit if successful. Otherwise it throws an error (when object_name exists but is not a reticulate Python module) or returns simpleError (when installation or import failed). check_tskit_py returns TRUE if object is a reticulate Python module or FALSE otherwise.

Functions

Examples

## Not run: 
  tskit <- get_tskit_py()
  is(tskit)
  if (check_tskit_py(tskit)) {
    tskit$ALLELES_01
  }

## End(Not run)

Report the version of installed kastore C API

Description

Report the version of installed kastore C API

Usage

kastore_version()

Details

The version is stored in the installed header kastore.h.

Value

A named vector with three elements major, minor, and patch.

Examples

kastore_version()

Load a table collection from a file

Description

Load a table collection from a file

Usage

tc_load(file, skip_tables = FALSE, skip_reference_sequence = FALSE)

tc_read(file, skip_tables = FALSE, skip_reference_sequence = FALSE)

Arguments

file

a string specifying the full path to a tree sequence file.

skip_tables

logical; if TRUE, load only non-table information.

skip_reference_sequence

logical; if TRUE, skip loading reference sequence information.

Details

See the corresponding Python function at https://github.com/tskit-dev/tskit/blob/dc394d72d121c99c6dcad88f7a4873880924dd72/python/tskit/tables.py#L3463.

Value

A TableCollection object.

Functions

See Also

TableCollection$new

Examples

ts_file <- system.file("examples/test.trees", package = "RcppTskit")
tc <- tc_load(ts_file)
is(tc)
tc

Transfer a table collection from reticulate Python to R

Description

This function saves a table collection from reticulate Python to disk and reads it into R for use with RcppTskit.

Usage

tc_py_to_r(tc, cleanup = TRUE)

Arguments

tc

table collection in reticulate Python.

cleanup

logical; delete the temporary file at the end of the function?

Value

A TableCollection object.

See Also

TableCollection$r_to_py tc_load, and TableCollection$dump.

Examples

## Not run: 
  ts_file <- system.file("examples/test.trees", package = "RcppTskit")

  # Use the tskit Python API to work with a table collection (via reticulate)
  tskit <- get_tskit_py()
  if (check_tskit_py(tskit)) {
    tc_py <- tskit$TableCollection$load(ts_file)
    is(tc_py)
    tc_py$individuals$num_rows # 8
    tmp <- tc_py$simplify(samples = c(0L, 1L, 2L, 3L))
    tmp
    tc_py$individuals$num_rows # 2
    tc_py$nodes$num_rows # 8
    tc_py$nodes$time # 0.0 ... 5.0093910

    # Transfer the table collection to R and use RcppTskit
    tc_r <- tc_py_to_r(tc_py)
    is(tc_r)
   tc_r$print()
  }

## End(Not run)

Load a tree sequence from a file

Description

Load a tree sequence from a file

Usage

ts_load(file, skip_tables = FALSE, skip_reference_sequence = FALSE)

ts_read(file, skip_tables = FALSE, skip_reference_sequence = FALSE)

Arguments

file

a string specifying the full path to a tree sequence file.

skip_tables

logical; if TRUE, load only non-table information.

skip_reference_sequence

logical; if TRUE, skip loading reference sequence information.

Details

See the corresponding Python function at https://tskit.dev/tskit/docs/latest/python-api.html#tskit.load.

Value

A TreeSequence object.

Functions

See Also

TreeSequence$new

Examples

ts_file <- system.file("examples/test.trees", package = "RcppTskit")
ts <- ts_load(ts_file)
is(ts)
ts
ts$num_nodes()
# Also
ts <- TreeSequence$new(file = ts_file)
is(ts)

Transfer a tree sequence from reticulate Python to R

Description

This function saves a tree sequence from reticulate Python to disk and reads it into R for use with RcppTskit.

Usage

ts_py_to_r(ts, cleanup = TRUE)

Arguments

ts

tree sequence in reticulate Python.

cleanup

logical; delete the temporary file at the end of the function?

Value

A TreeSequence object.

See Also

TreeSequence$r_to_py ts_load, and TreeSequence$dump.

Examples

## Not run: 
  ts_file <- system.file("examples/test.trees", package = "RcppTskit")

  # Use the tskit Python API to work with a tree sequence (via reticulate)
  tskit <- get_tskit_py()
  if (check_tskit_py(tskit)) {
    ts_py <- tskit$load(ts_file)
    is(ts_py)
    ts_py$num_individuals # 8
    ts2_py <- ts_py$simplify(samples = c(0L, 1L, 2L, 3L))
    ts_py$num_individuals # 8
    ts2_py$num_individuals # 2
    ts2_py$num_nodes # 8
    ts2_py$tables$nodes$time # 0.0 ... 5.0093910

    # Transfer the tree sequence to R and use RcppTskit
    ts2_r <- ts_py_to_r(ts2_py)
    is(ts2_r)
    ts2_r$num_individuals() # 2
  }

## End(Not run)

Report the version of installed tskit C API

Description

Report the version of installed tskit C API

Usage

tskit_version()

Details

The version is defined in the installed header tskit/core.h.

Value

A named vector with three elements major, minor, and patch.

Examples

tskit_version()

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They may not be fully stable and should be used with caution. We make no claims about them.
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