Apply a Trained PAI Model to Correct a Vector Map

Applies a trained pai_model object to an sf vector map, correcting the position of all its vertices based on the learned transformation.

Usage

apply_pai_model(pai_model, map, aoi = NULL)

Arguments

pai_model

An object of class pai_model returned by train_pai_model().

map

An sf object representing the vector map to be corrected.

aoi

An optional sf polygon object representing the Area of Interest. If provided, the transformation is only applied within this area.

Value

A new sf object with the corrected geometry.

Details

This function is the final step in the PAI workflow, applying the learned spatial correction to a target map. It uses a robust feature-by-feature iteration that correctly handles all standard simple and multi-part geometry types (POINT, LINESTRING, POLYGON, etc.).

If an Area of Interest (aoi) is provided, the transformation is only applied to the parts of the map features that fall within the aoi polygon. The features outside the aoi are kept in their original, untransformed state.

Examples

# This example demonstrates a full workflow with POINT geometry.

# --- 1. Load Data and Train Model ---
data(gcps) # gcps is an sf object with POINT geometry
gam_model <- train_pai_model(gcps, pai_method = "gam")
#> Training 'gam' model...

# --- 2. Apply the Model to Correct the Points ---
corrected_points <- apply_pai_model(gam_model, gcps)
#> Applying PAI model to map features...
#> Correction complete.

# --- 3. Inspect  ---
# The coordinates of the corrected points should be different.
head(sf::st_coordinates(gcps))
#>             X       Y
#> [1,] 268828.1 4488391
#> [2,] 268684.7 4488627
#> [3,] 268710.3 4488347
#> [4,] 268509.3 4488540
#> [5,] 268516.0 4488406
#> [6,] 268840.4 4488505
head(sf::st_coordinates(corrected_points))
#>             X       Y
#> [1,] 268828.3 4488391
#> [2,] 268684.9 4488627
#> [3,] 268710.2 4488347
#> [4,] 268509.6 4488540
#> [5,] 268515.7 4488405
#> [6,] 268840.7 4488505