## -----------------------------------------------------------------------------
library(unifiedml)

## -----------------------------------------------------------------------------
# Example 1: lm with matrix interface (including factors)
demo_lm_matrix <- function() {
  cat("\n=== Example 1: lm with matrix interface ===\n")
  
  lm_matrix <- unifiedml::formula_to_matrix(stats::lm)  # Uses generic predict()
  
  # Create data with factor and numeric columns
  X <- data.frame(
    wt = mtcars$wt,
    hp = mtcars$hp,
    cyl = factor(mtcars$cyl)
  )
  y <- mtcars$mpg
  weights <- rep(1, nrow(X))
  
  model <- lm_matrix$fit(X, y, weights = weights)
  preds <- lm_matrix$predict(model, X[1:5, ])
  
  cat("Predictions:\n")
  print(preds)
  cat("\nCoefficients:\n")
  print(coef(model))
}

# Example 2: glmnet with formula interface (with factors)
demo_glmnet_formula <- function() {
  cat("\n=== Example 2: glmnet with formula interface ===\n")
  
  if (!requireNamespace("glmnet", quietly = TRUE)) {
    cat("glmnet package not installed, skipping example\n")
    return(invisible(NULL))
  }
  
  glmnet_formula <- unifiedml::matrix_to_formula(
    fit_func = glmnet::glmnet,
    predict_func = function(model, newX, ...) {
      # Wrapper to provide default s parameter
      glmnet::predict.glmnet(model, newx = newX, s = 0.01, ...)
    }
  )
  
  # Formula with factor - model.matrix will auto-create dummies
  model <- glmnet_formula$fit(mpg ~ wt + hp + factor(cyl), data = mtcars)
  preds <- glmnet_formula$predict(model, newdata = mtcars[1:5, ])
  
  cat("Predictions:\n")
  print(preds)
}

# Example 3: Special characters in column names
demo_special_names <- function() {
  cat("\n=== Example 3: Column names with special characters ===\n")
  
  lm_matrix <- unifiedml::formula_to_matrix(lm)
  
  # Create problematic column names
  X <- data.frame(
    `x-1` = mtcars$wt,      # Dash
    `a:b` = mtcars$hp,       # Colon
    `log(x)` = log(mtcars$disp),  # Parentheses
    check.names = FALSE
  )
  y <- mtcars$mpg
  
  model <- lm_matrix$fit(X, y)
  preds <- lm_matrix$predict(model, X[1:3, ])
  
  cat("Predictions:\n")
  print(preds)
  cat("\nModel handled special column names correctly!\n")
}

# Run examples (uncomment to test)
demo_lm_matrix()
demo_glmnet_formula()
demo_special_names()

