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)

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.

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.).

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, 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 and Visualize ---
# 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

# Visually confirm the points have moved
plot(sf::st_geometry(gcps), col = 'grey', pch = 4, cex=0.5,
     main = "Original (Grey) vs. Corrected (Red) Points")
plot(sf::st_geometry(corrected_points), col = 'red', pch = 16, cex=0.5, add = TRUE)