Path Analysis¶

Path Analysis represents graph-style connectivity between mission assets. It is intended for multi-hop network reasoning, route availability, and optimal strand evaluation.

Current Scope¶

The current asset model stores path configuration and exposes helper accessors for reporting and plotting. The full computation service is still an evolving capability.

Engineering Questions¶

Is there a valid path between a source and target asset?
Which intermediate assets form the path?
How many hops are required?
Which path minimizes range or hop count?
When are one or more strands active?

Path Model¶

flowchart LR
    S["Source Asset"] --> A["Connection"]
    A --> B["Intermediate Asset"]
    B --> C["Connection"]
    C --> T["Target Asset"]

Main Configuration Parameters¶

Field	Meaning
`source_asset_guid`	Start node for the path search.
`target_asset_guid`	Final node for the path search.
`max_hops`	Maximum number of allowed hops.
`connections`	Directed edges from one asset to another.
`optimal_strand.optimize_total_range`	Prefer shortest total range.
`optimal_strand.optimize_num_hops`	Prefer fewer hops.
`interval.use_asset_interval`	Use asset-derived validity interval.
`interval.specify_interval`	Use custom interval.
`interval.step_size_s`	Sampling step for interval analysis.

Result Concepts¶

Concept	Meaning
Strand	A candidate path through one or more directed connections.
Active strand	A strand available at a given time.
Hop count	Number of links in the strand.
Optimal strand	Strand selected by range, hop count, or future criteria.

Reporting Helpers¶

The current model includes timeline-style helper methods:

Helper	Meaning
`has_any_valid_strand(t)`	Returns 1 if at least one strand is active.
`num_active_strands(t)`	Counts active strands.
`min_hops_active(t)`	Minimum hop count among active strands.
`max_hops_active(t)`	Maximum hop count among active strands.
`mean_hops_active(t)`	Average hop count among active strands.