Source code for arviz.wrappers.wrap_pymc

# pylint: disable=arguments-differ
"""Base class for PyMC interface wrappers."""
from .base import SamplingWrapper

# pylint: disable=abstract-method
[docs] class PyMCSamplingWrapper(SamplingWrapper): """PyMC (4.0+) sampling wrapper base class. See the documentation on :class:`~arviz.SamplingWrapper` for a more detailed description. An example of ``PyMCSamplingWrapper`` usage can be found in the :ref:`pymc_refitting` notebook. Warnings -------- Sampling wrappers are an experimental feature in a very early stage. Please use them with caution. """
[docs] def sample(self, modified_observed_data): """Update data and sample model on modified_observed_data.""" import pymc # pylint: disable=import-error with self.model: pymc.set_data(modified_observed_data) idata = pymc.sample( **self.sample_kwargs, ) return idata
[docs] def get_inference_data(self, fitted_model): """Return sampling result without modifying. PyMC sampling already returns and InferenceData object. """ return fitted_model