Quickstart

Each wrapped R package has its own submodule. Import the one you need and call the wrapper class like the corresponding R function; arguments are converted to R, and the fitted R object’s components become Python attributes (with . replaced by _).

import numpy as np
from rbartpackages import BART3

x_train = np.random.randn(100, 5)
y_train = x_train[:, 0] + 0.1 * np.random.randn(100)

bart = BART3.gbart(x_train=x_train, y_train=y_train, ndpost=200)
y_pred = bart.predict(x_train)  # shape (ndpost, n)

Argument names use Python underscores in place of R dots: pass x_train for the R argument x.train. The same pattern works for the other wrappers, e.g. rbartpackages.BART, rbartpackages.dbarts, rbartpackages.bartMachine, and rbartpackages.missBART.

Data frames

R dataframes are converted to/from pandas dataframes on the Python side. If polars[pyarrow] is installed, dataframes are returned as polars dataframes, and both pandas and polars dataframes are accepted as input.

R documentation

The original R documentation of each function is appended to the corresponding wrapper class docstring, so help(BART3.gbart) shows the upstream reference.