menobis fit

TL;DR

Use menobis fit to fit grand-canonical multipliers from an observed network and emit the fitted model. Data goes to stdout unless --output is set.

The Python API is the authoritative full model interface. CLI commands expose a convenience subset for the most common grand-canonical routes and may retain command names that do not mirror the model ontology exactly.

Commands

Command	Ensemble	Family	Constraint	Notes
strength-poisson	grand-canonical	ME	strength	default route
strength-geometric	grand-canonical	W	strength	geometric \(M=1\)
strength-negative-binomial	grand-canonical	W	strength	needs --layers
degree-bernoulli	grand-canonical	ME	degree-events	binary degree fit
strength-degree-poisson	grand-canonical	ME	strength-degree	zero-inflated
strength-edges-poisson	grand-canonical	ME	strength-edges	zero-inflated
strength-cost-poisson	grand-canonical	ME	strength-cost	needs coordinates

Examples

menobis fit strength-poisson edges.csv --seed 42
menobis fit strength-negative-binomial edges.csv --layers 4 --json
menobis fit strength-cost-poisson edges.csv --coordinates xy.csv

Options

Option	Meaning
--output, -o	Write the fitted model
--json	Print JSON to stdout
--quiet	Suppress progress
--self-loops/--no-self-loops	Diagonal handling
--layers	B/W layer parameter \(M\) (B/W routes)
--coordinates	Projected XY coordinate CSV (cost routes)

The complete supported matrix is the Python API Supported models.