Release v0.8.6

Added

• Wrapped two gradient-free optimizers from scipy: Nelder-Mead and Powell. They are available as jax_fdm.optimizers.NelderMead and jax_fdm.optimizers.Powell, respectively.
• Linked two evolutionary optimizers from scipy They are available as jax_fdm.optimizers.DualAnnealing and jax_fdm.optimizers.DifferentialEvolution.
• Added support for kwargs in LossPlotter.plot(). The kwargs control the parameters of the equilibrium model used to plot the loss history.
• Added VertexSupportParameter.index(). This change might appear redundant, but it was necessary to deal with the method resolution order of the parent classes of VertexSupportParameter.
• Added VertexGroupSupportParameter.index() for similar reasons as the listed above.

Changed

• Changed datastructure.print_stats() to report positive and negative forces separately.
• Turned off display in TruncatedNewton.
• Fixed bug in OptimizationRecorder. The recorder did not know how to record optimization history without an explictly initialized optimizer.
• Deprecated jax_fdm.optimization.optimizers.scipy in favor of jax_fdm.optimization.optimizers.gradient_based.
• Fixed bug. Return early in NetworkArtist.edge_width() if the artist edges list is empty.
• Fixed bug in EdgesForceEqualGoal.prediction(): the normalization mean of compressive edge forces was a negative number. This led to negative normalized variance values, which was plainly incorrect.
• VertexGroupSupportParameter inherits from VertexGroupParameter instead of NodeGroupParameter. This was a bug.

Removed