Functions

Hill Climbing and Conjugate Gradient module

hill.distance_matrix(coordinate)

calculate the distance among each suggest solution point

hill.calculate_distance(matrix, solution)

returns the distance associated with a solution

hill.neighbors(matrix, solution)

create neighbors of a propose solution

hill.best_solution(coordinate[, …])

finds an optimal solution for the TSP problem using hill climbing algorithm

grad_conj.cgm(A, b, x[, tolerance, iter])

input:

grad_conj.its_simetric(matrix)

ckecks if a matrix is symmetric inputs: matrix: a cuadratic matix outputs: True ir our matrix is simetric, false otherwise

grad_conj.is_pos_def(x)

ckecks if a matrix is define positive input: param x: matrix to check if it is define positive return: True if the matix is define positive and False otherwise output: