refactor: move optional arguments of motifs-graphlets functions behind the ellipsis

[krlmlr]

Part of the repo-wide ellipsis migration coordinated in #2757 —
see that PR for the full rationale (CONTRIBUTING.md, Argument Order and the Ellipsis).
Based directly on main (the registry split landed via #2779); a single topic commit.

What this does

Inserts ... between the defining arguments (head) and the optional
modifiers (tail) of 6 exported motifs-graphlets functions.
Arguments after ... become keyword-only.

• Legacy positional or abbreviated calls are recovered by the generated
  ARG_HANDLE block and emit a single lifecycle::deprecate_soft("3.0.0", …) —
  behavior is unchanged.
• No defaults change, no arguments are renamed, deprecated functions untouched.
• Registry: tools/migrations/motifs-graphlets.R; blocks regenerated via
  Rscript tools/generate-migrations.R (idempotent, CI-checked).
• Rd usage/arguments updated mechanically (see note below).

New signatures

function	head (positional)	keyword-only tail
graphlet_basis()	graph	weights
graphlet_proj()	graph	weights, cliques, niter, Mu
graphlets()	graph	weights, niter
count_motifs()	graph, size	cut.prob
motifs()	graph, size	cut.prob, callback
sample_motifs()	graph, size	cut.prob, sample.size, sample

Notes for review

• The environment used to prepare this PR cannot install igraph.r2cdocs
  (GitHub API unreachable), so man/*.Rd files were updated mechanically
  (usage + ... argument item) instead of via devtools::document().
  R CMD check's usage↔formals validation passes; a follow-up
  devtools::document() run may reflow whitespace but should produce no
  semantic diff.
• Package tests that called these functions positionally were updated to
  named arguments (they are the same soft-deprecation user code will see).

[github-actions]

This is how benchmark results would change (along with a 95% confidence interval in relative change) if f38d2e2 is merged into main:

• ✔️as_adjacency_matrix: 819ms -> 822ms [-0.93%, +1.68%]
• ✔️as_biadjacency_matrix: 863ms -> 874ms [-2.26%, +4.66%]
• ✔️as_data_frame_both: 1.57ms -> 1.57ms [-2.26%, +2.48%]
• ✔️as_long_data_frame: 4.08ms -> 4.05ms [-3.18%, +1.71%]
• 🚀es_attr_filter: 3.11ms -> 3.02ms [-4.86%, -0.43%]
• ✔️graph_from_adjacency_matrix: 149ms -> 151ms [-2.33%, +5.19%]
• ✔️graph_from_data_frame: 3.64ms -> 3.65ms [-1.27%, +1.72%]
• ✔️vs_attr_filter: 1.77ms -> 1.77ms [-1.26%, +2.01%]
• ✔️vs_by_name: 1.16ms -> 1.17ms [-0.54%, +2.44%]
  Further explanation regarding interpretation and methodology can be found in the documentation.

[github-actions]

This is how benchmark results would change (along with a 95% confidence interval in relative change) if afe604e is merged into main:

• ✔️as_adjacency_matrix: 887ms -> 884ms [-1.86%, +1.04%]
• ✔️as_biadjacency_matrix: 851ms -> 855ms [-0.88%, +1.8%]
• ✔️as_data_frame_both: 1.63ms -> 1.64ms [-1.86%, +3.1%]
• ✔️as_long_data_frame: 4.09ms -> 4.07ms [-2.34%, +1.47%]
• ✔️es_attr_filter: 2.89ms -> 2.89ms [-2.22%, +2.33%]
• ✔️graph_from_adjacency_matrix: 166ms -> 166ms [-1.55%, +1.1%]
• ✔️graph_from_data_frame: 3.57ms -> 3.53ms [-2.86%, +0.34%]
• ✔️vs_attr_filter: 1.7ms -> 1.69ms [-3.32%, +2.01%]
• ✔️vs_by_name: 1.1ms -> 1.09ms [-4.45%, +3.85%]
  Further explanation regarding interpretation and methodology can be found in the documentation.