pyepo.data.shortestpath
=======================

.. py:module:: pyepo.data.shortestpath

.. autoapi-nested-parse::

   Synthetic data for shortest path problem



Functions
---------

.. autoapisummary::

   pyepo.data.shortestpath.genData


Module Contents
---------------

.. py:function:: genData(num_data: int, num_features: int, grid: tuple[int, int], deg: int = 1, noise_width: float = 0, seed: int = 135) -> tuple[numpy.ndarray, numpy.ndarray]

   Generate synthetic feature-cost pairs for the shortest path problem.

   Features are sampled from a standard multivariate Gaussian
   :math:`\mathcal{N}(0, \mathbf{I})`. A random Bernoulli(0.5) matrix
   :math:`\mathcal{B}` maps each feature vector into the edge-cost
   coefficients via a polynomial of degree ``deg``, scaled by multiplicative
   uniform noise of half-width ``noise_width``.

   :param num_data: number of data points
   :param num_features: dimension of features
   :param grid: size of grid network
   :param deg: polynomial degree of the feature-to-cost mapping
   :param noise_width: half-width of the multiplicative uniform noise
   :param seed: random seed (default 135 for reproducibility)

   :returns: data features (np.ndarray), costs (np.ndarray)
   :rtype: tuple