code: def draw_matheron_paths(
      model: GP,
      sample_shape: Size,
      prior_sampler: TPathwisePriorSampler = draw_kernel_feature_paths,
      update_strategy: TPathwiseUpdate = gaussian_update,
      **kwargs: Any,
  ) -> MatheronPath:
      r"""Generates function draws from (an approximate) Gaussian process prior.
  
      When evaluted, sample paths produced by this method return Tensors with dimensions
      `sample_dims x batch_dims x [joint_dim]`, where `joint_dim` denotes the penultimate
      dimension of the input tensor. For multioutput models, outputs are returned as the
      final batch dimension.
  
      Args:
          model: Gaussian process whose posterior is to be sampled.
          sample_shape: Sizes of sample dimensions.
          prior_sample: A callable that takes a model and a sample shape and returns
              a set of sample paths representing the prior.
          update_strategy: A callable that takes a model and a tensor of prior process
              values and returns a set of sample paths representing the data.
      """
  
      return DrawMatheronPaths(
          model,
          sample_shape=sample_shape,
          prior_sampler=prior_sampler,
          update_strategy=update_strategy,
          **kwargs,
      )
  
file_path: botorch/botorch/sampling/pathwise/posterior_samplers.py
imports: from __future__ import annotations
  from typing import Any, Optional, Union
  from botorch.models.approximate_gp import ApproximateGPyTorchModel
  from botorch.models.model_list_gp_regression import ModelListGP
  from botorch.sampling.pathwise.paths import PathDict, PathList, SamplePath
  from botorch.sampling.pathwise.prior_samplers import draw_kernel_feature_paths, TPathwisePriorSampler
  from botorch.sampling.pathwise.update_strategies import gaussian_update, TPathwiseUpdate
  from botorch.sampling.pathwise.utils import get_output_transform, get_train_inputs, get_train_targets, TInputTransform, TOutputTransform
  from botorch.utils.context_managers import delattr_ctx
  from botorch.utils.dispatcher import Dispatcher
  from gpytorch.models import ApproximateGP, ExactGP, GP
  from torch import Size
label_desc: Use image node_id 1 for calling a global function with example usage: draw_matheron_paths(model, sample_shape, prior_sampler, update_strategy) and returns: DrawMatheronPaths