on $u$. Conversely, the term acts as a sum of repulsive forces if $q$ is larger than zero. The Gansner [*et al.*]{}algorithm typically needs several iterations to converge. In this process the entropy weighting factor $\alpha$ has a strong influence in the maxent-stress model: a high value will cause the vertices to expand into space indefinitely while a low value will cause no entropy influence. The maxent-stress algorithm therefore starts with $\alpha = 1$ and gradually reduces this value to $\alpha = 0.008$ with a rate of $0.3$. For each value of $\alpha$, a maximum of 50 linear system solves are performed and Gansner [*et al.*]{}set $q$ to $0$ except when the graph has more than 30% degree-1 vertices (then $q \gets 0.8$). Note that in this entropy context they assume $\Vert x \Vert^0 = \ln \Vert x \Vert$. If the relative difference $\lVert x' - x \rVert / \lVert x \rVert$ between two successive solutions $x$ and $x'$ is below $0.001$, the algorithm is terminated.

More implementation details ([*e.g.,* ]{}the approximation of the entropy term in case of $|S| \in {\mathcal{O}(n)}$) can be found in Section \[sec:impl\].

New Algorithm and its Implementation {#sec:algo-impl}
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Now we describe the adaptations 