Types of changes

This PR aims to add the Linear Circular OT distance (with uniform measure on the circle as reference measure) introduced in LCOT: Linear Circular Optimal Transport
and its sliced counterpart introduced in Linear Spherical Sliced Optimal Transport: A Fast Metric for Comparing Spherical Data
.

Changes:

• Added the ot.solver_1d.linear_circular_embedding and ot.solver_1d.linear_circular_ot functions to compute the Linear Circular OT distance.
• Added the ot.sliced.linear_sliced_wasserstein_sphere function to compute its sliced counterpart.
• Refactored the code for the spherical sliced distances, adding the functions ot.sliced.get_projections_sphere and ot.sliced.projection_sphere_to_circle.
• Added tests for these functions in test/test_1d_solver and test/test_sliced.
• Added the Linear Circular OT distance in the example plot_compute_wasserstein_circle.py
• Modified the default behavior of ot.wasserstein_circle to always use ot.solver_1d.binary_search_circle for any p, which seems to give better results even for p=1 (as discussed in Issue Wasserstein Circle distance doesn't seem correct? #738).
• Improved the visualization of the sphere in the example plot_ssw_unif_torch.py.

Motivation and context / Related issue

The Linear Circular OT distance with uniform measure on the circle is very fast to compute, as the OT maps can be computed in closed-forms. It is thus faster to compute than the true wasserstein distance on the circle.

How has this been tested (if it applies)

I added tests of these functions in test/test_1d_solver and test/test_sliced.

PR checklist

• I have read the CONTRIBUTING document.
• The documentation is up-to-date with the changes I made (check build artifacts).
• All tests passed, and additional code has been covered with new tests.
• I have added the PR and Issue fix to the RELEASES.md file.