PRO Production

Workflow-grade Pro analysis with audit-ready outputs.

workflow pro

## Workflow Narrative

Network Readiness and Diagnostics

### Problem It Solves

Is this network structurally and cost-wise ready for reliable routing and service optimization workflows?

### Who It Is For

- Routing analysts, municipal transportation planning teams, and utility network operations.

### Primary User

Municipal/public works GIS teams, utilities, and logistics operations requiring reproducible network QA gates.

### What It Does

- Audits line-based transportation/utility networks for operational routing readiness.
- Detects dead-end concentration and cost-consistency anomalies before routing runs.
- Emits a machine-readable readiness score with pass/fail quality gate and diagnostics outputs.

### How It Works

- Loads a line network and validates geometry is line-based (`LineString`/`MultiLineString`).
- Builds node degree counts from line endpoints to quantify dead-end prevalence.
- Computes per-segment length costs and assesses variance using z-score outlier detection.
- Computes weighted readiness score from connectivity and cost-consistency components.
- Indicative formula: `overall = 0.6 * connectivity_score + 0.4 * cost_consistency_score`.

### Why It Wins

- Replaces manual topology spot-checks with a reproducible score + diagnostics package that is machine-checkable and reportable.

### Typical Buying Trigger

Teams encounter unstable routing outcomes and need an auditable pre-routing network quality gate.

### Typical Presets

- default: balanced scoring for day-to-day network readiness checks.
- pre-routing gate: run before route optimization or service-area generation.
- data onboarding QA: run when ingesting new road/utility centerline deliveries.

## Inputs

Parameter | Optional | Description
--- | --- | ---
network | no | Input line network layer (street, transit, or utility network).
qa_report | no | Output CSV path for detailed QA findings and issue counts.
diagnostics_layer | no | Output GeoJSON/GeoPackage path containing diagnostic geometries.
readiness_score | no | Output JSON path with readiness score, component scores, and pass/fail gate.

## Outputs

Parameter | Type | Description
--- | --- | ---
qa_report | CSV | Tabular QA findings including severity, check type, count, and descriptive diagnostics.
diagnostics_layer | GeoJSON/GeoPackage | Spatial diagnostics layer for issue visualization and spatial triage.
readiness_score | JSON | Machine-readable readiness contract with overall score, component scores, penalties, and pass/fail gate.
html_report | HTML | Human-readable customer-facing report generated from the summary contract for stakeholder review and QA traceability.

## Python Example

    import whitebox_workflows as wbw

    wbe = wbw.WbEnvironment(include_pro=True, tier="pro")

    result = wbe.network_readiness_and_diagnostics_intelligence(
        network="data/street_network.shp",
        qa_report="output/network_readiness_qa.csv",
        diagnostics_layer="output/network_readiness_diagnostics.geojson",
        readiness_score="output/network_readiness_score.json",
    )

    print(result)

## License Notice

Use of this function requires a license for Whitebox Workflows Professional (WbW-Pro). Please visit www.whiteboxgeo.com to purchase a license.

## Project Links

WbW Homepage User Manual Support WbW