pyepo.data.tsp
==============

.. py:module:: pyepo.data.tsp

.. autoapi-nested-parse::

   Synthetic data for traveling salesman problem



Functions
---------

.. autoapisummary::

   pyepo.data.tsp.genData


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

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

   Generate synthetic feature-cost pairs for the traveling salesperson problem.

   Edge costs combine a Euclidean component (node coordinates drawn from a
   mixture of a Gaussian :math:`\mathcal{N}(0, \mathbf{I})` and a uniform
   :math:`\mathbf{U}(-2, 2)` distribution) with a feature-encoded component
   obtained by mapping the standard-Gaussian feature vector through a random
   Bernoulli :math:`\times` uniform matrix :math:`\mathcal{B}` and a polynomial
   of degree ``deg``, scaled by multiplicative noise of half-width ``noise_width``.

   :param num_data: number of data points
   :param num_features: dimension of features
   :param num_nodes: number of nodes
   :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