type: string, default:
Technique for optimizing the layout.
- For neato, if
neatouses stress majorization.
neatouses a version of the gradient descent method.
KKis sometimes appreciably faster for small (number of nodes < 100) graphs. A significant disadvantage is that
neatouses a version of the stochastic gradient descent method.
sgd’s advantage is faster and more reliable convergence than both the previous methods, while
sgd’s disadvantage is that it runs in a fixed number of iterations and may require larger values of
maxiterin some graphs.
There are two experimental modes in
mode="hier", which adds a top-down directionality similar to the layout used in
mode="ipsep", which allows the graph to specify minimum vertical and horizontal distances between nodes. (See the sep attribute.)
sfdp, the default is
mode="spring", which corresponds to using a
spring-electrical model. Setting
mode="maxent" causes a similar model
to be run but one that also takes into account edge lengths specified by the