Experimental
Computes OD shortest-path costs with impedance perturbations and outputs sensitivity statistics via Monte Carlo sampling.
vector network sensitivity
| 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 | — |
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')