Add network statistics workflow step

[networmix]

Summary

• implement NetworkStats workflow step to compute base capacity and degree stats
• document new workflow step in DSL and API docs
• update CLI docs with new output key
• export NetworkStats from workflow package
• add unit test for new step

Testing

• make format
• make check

[Copilot]

Pull Request Overview

Adds a new NetworkStats workflow step that computes basic capacity and degree statistics for network links and nodes, along with tests and documentation updates.

• Implemented and registered the NetworkStats step in the workflow package.
• Added a unit test to verify link and per-node statistics.
• Updated DSL, CLI, and API reference docs to include the new step.

Reviewed Changes

Copilot reviewed 7 out of 7 changed files in this pull request and generated 1 comment.

Show a summary per file

File	Description
ngraph/workflow/network_stats.py	Implements the NetworkStats step and registers it.
ngraph/workflow/init.py	Exports NetworkStats in the workflow package.
tests/workflow/test_network_stats.py	Adds unit test for the new workflow step.
docs/reference/dsl.md	Documents NetworkStats in the DSL reference.
docs/reference/cli.md	Adds NetworkStats to CLI output documentation.
docs/reference/api.md	Includes NetworkStats in the API reference list.
docs/reference/api-full.md	Provides full API docs for NetworkStats.

Comments suppressed due to low confidence (2)

tests/workflow/test_network_stats.py:52

• This test validates link and per-node stats but does not assert on node_capacity and node_degree distributions. Consider adding assertions for those keys to ensure full coverage of the new workflow step.

    assert set(per_node.keys()) == {"A", "B", "C"}

docs/reference/api.md:201

• The NetworkStats entry appears to be commented out; remove the leading # so it renders properly in the list of available workflow steps.

# - NetworkStats: Computes basic capacity and degree statistics

[Copilot]

The logic for building distribution stats is duplicated for links, node capacities, and node degrees. Consider extracting this into a helper function to reduce repetition and improve readability.

Suggested change

	link_caps_sorted = sorted(link_caps)
	link_stats = {
	"values": link_caps_sorted,
	"min": min(link_caps_sorted) if link_caps_sorted else 0.0,
	"max": max(link_caps_sorted) if link_caps_sorted else 0.0,
	"mean": mean(link_caps_sorted) if link_caps_sorted else 0.0,
	"median": median(link_caps_sorted) if link_caps_sorted else 0.0,
	}
	link_stats = self.compute_distribution_stats(link_caps)