---
jupytext:
  text_representation:
    extension: .md
    format_name: myst
    format_version: 0.12
    jupytext_version: 1.9.1
kernelspec:
  display_name: Python 3
  language: python
  name: python3
---

:::{currentmodule} tsdate
:::

(sec_python_api)=

# Python API

This page provides formal documentation for the _tsdate_ Python API.


## Running tsdate

```{eval-rst}
.. autofunction:: tsdate.date
.. autodata:: tsdate.core.estimation_methods
   :no-value:
.. autofunction:: tsdate.variational_gamma
.. autofunction:: tsdate.inside_outside
.. autofunction:: tsdate.maximization
```

## Underlying fit objects

Instances of the classes below are returned by setting `return_fit=True`
when dating. The fits can be inspected to obtain more detailed results than
may be present in the returned tree sequence and its metadata. The classes
are not intended to be instantiated directly.

```{eval-rst}
.. autoclass:: tsdate.discrete.BeliefPropagation()
   :members:

.. autoclass:: tsdate.variational.ExpectationPropagation()
   :members:
```

## Prior and Time Discretisation Options

```{eval-rst}
.. autofunction:: tsdate.build_prior_grid
.. autofunction:: tsdate.build_parameter_grid
.. autoclass:: tsdate.node_time_class.NodeTimeValues
.. autodata:: tsdate.prior.DEFAULT_APPROX_PRIOR_SIZE
```

## Variable population sizes

```{eval-rst}
.. autoclass:: tsdate.demography.PopulationSizeHistory
```

## Preprocessing Tree Sequences

```{eval-rst}
.. autofunction:: tsdate.preprocess_ts
.. autofunction:: tsdate.util.split_disjoint_nodes
```

# Functions for Inferring Tree Sequences with Historical Samples

```{eval-rst}
.. autofunction:: tsdate.sites_time_from_ts
.. autofunction:: tsdate.add_sampledata_times
```

# Constants

```{eval-rst}
.. automodule:: tsdate
   :members:
```