Add select_by_index method to Feature class

[nicolaloi]

Type

• Bug fix (non-breaking change which fixes an issue): Fixes #
• New feature (non-breaking change which adds functionality). Resolves "select_by_index" to work with the class "open3d.pipelines.registration.Feature" #7004
• Breaking change (fix or feature that would cause existing functionality to not work as expected) Resolves #

Motivation and Context

Allow the creation of a new Feature instance with selected features from the current Feature instance, similar to PointCloud::SelectByIndex.

Checklist:

• I have run python util/check_style.py --apply to apply Open3D code style
  to my code.
• This PR changes Open3D behavior or adds new functionality.
  • Both C++ (Doxygen) and Python (Sphinx / Google style) documentation is
    updated accordingly.
  • I have added or updated C++ and / or Python unit tests OR included test
    results (e.g. screenshots or numbers) here.
• I will follow up and update the code if CI fails.
• For fork PRs, I have selected Allow edits from maintainers.

Description

Add a select_by_index method to the Feature class, similar to PointCloud::SelectByIndex and TriangleMesh::SelectByIndex.

No modifications for the tensor module, since it doesn't have a Feature class (functions like ComputeFPFHFeatures are working directly with core::Tensors).

Testing

I have added a unit test.
The following is an extra script for local testing:

import open3d as o3d
import numpy as np

ply_point_cloud = o3d.data.DemoCropPointCloud()
pcd = o3d.io.read_point_cloud(ply_point_cloud.point_cloud_path)

fpfh_features = o3d.pipelines.registration.compute_fpfh_feature(
    pcd, o3d.geometry.KDTreeSearchParamHybrid(radius=0.25, max_nn=20))

n_select = 100
selected_indexes = np.random.choice(fpfh_features.num(), n_select, replace=False)
selected_fpfh_features = fpfh_features.select_by_index(selected_indexes)

assert selected_fpfh_features.num() == n_select

np_fpfh_features = np.asarray(fpfh_features.data)

# assert that the selected features are indeed the same as the ones we selected with numpy
assert np.allclose(np_fpfh_features[:, sorted(selected_indexes)], np.asarray(selected_fpfh_features.data))