Experimental

Computes OD shortest-path costs with impedance perturbations and outputs sensitivity statistics via Monte Carlo sampling.

vector network sensitivity

## Parameters

Name | Description | Required | Default
--- | --- | --- | ---
`input` | Input line network layer. | Required | `network.shp`
`origins` | Origin point layer. | Required | `origins.shp`
`destinations` | Destination point layer. | Required | `destinations.shp`
`edge_cost_field` | Required numeric line field used as an impedance multiplier for perturbation analysis. | Required | `cost`
`impedance_disturbance_range` | Range for cost perturbation as 'min_factor,max_factor' (e.g., '0.8,1.2' for ±20% variation). | Optional | `0.8,1.2`
`monte_carlo_samples` | Number of Monte Carlo samples for perturbation analysis (default 1, max 100). | Optional | `10`
`snap_tolerance` | Optional node snapping tolerance for graph construction. | Optional | —
`max_snap_distance` | Optional max distance from origin/destination points to nearest network node. | Optional | —
`one_way_field` | Optional line field marking one-way digitized edges. | Optional | —
`blocked_field` | Optional line field marking blocked/closed edges. | Optional | —
`parallel_execution` | If true (default), evaluates origin searches in parallel for baseline and perturbed OD runs. | Optional | —
`output` | Output CSV path with OD pairs and sensitivity statistics. | Required | —

## Examples

Computes OD costs with Monte Carlo impedance perturbation sensitivity.

    wbe.od_sensitivity_analysis(destinations='destinations.shp', edge_cost_field='cost', impedance_disturbance_range='0.8,1.2', input='network.shp', monte_carlo_samples=10, origins='origins.shp', output='od_sensitivity.csv')

## Project Links

WbW Homepage User Manual Support WbW