Add cost distribution analysis

[networmix]

No description provided.

[Copilot]

Pull Request Overview

This PR adds cost distribution analysis to the max flow computation system. Cost distribution tracks how flow volume is distributed across paths of different total costs, providing insights for latency span analysis and performance characterization of network paths.

Key Changes:

• Extended FlowSummary dataclass with a cost_distribution field mapping path costs to flow volumes
• Enhanced max flow algorithms to track cost distribution during sequential path augmentation
• Added comprehensive test coverage for cost distribution functionality across various network scenarios

Reviewed Changes

Copilot reviewed 9 out of 9 changed files in this pull request and generated no comments.

Show a summary per file

File	Description
ngraph/lib/algorithms/types.py	Added cost_distribution field to FlowSummary dataclass with documentation
ngraph/lib/algorithms/max_flow.py	Enhanced calc_max_flow to track cost distribution during path augmentation iterations
ngraph/network.py	Updated all FlowSummary instantiations to include empty cost_distribution field
tests/lib/algorithms/test_types.py	Updated FlowSummary tests to include cost_distribution field
tests/lib/algorithms/test_max_flow.py	Added comprehensive test class TestMaxFlowCostDistribution with 9 test scenarios
tests/test_network_enhanced_max_flow.py	Added integration test verifying cost distribution exposure through Network API
docs/reference/api.md	Added cost distribution documentation with example usage for latency analysis
docs/reference/api-full.md	Updated auto-generated API documentation timestamp and added cost_distribution field
docs/examples/basic.md	Added detailed cost distribution analysis examples with latency span analysis functions

Comments suppressed due to low confidence (2)

ngraph/lib/algorithms/max_flow.py:228

• [nitpick] The variable name costs is ambiguous in this context. Since this represents node costs from the source in shortest path computation, consider renaming to node_costs or distances for clarity.

    costs, pred = spf(

ngraph/lib/algorithms/max_flow.py:266

• [nitpick] The variable name costs is ambiguous in this context. Since this represents node costs from the source in shortest path computation, consider renaming to node_costs or distances for clarity.

        costs, pred = spf(