Interactive and standalone regression plotting

regression_plotting.R

# plot_regr_rsq(points) plots points and regression
#
# You can supply the following parameter:
#   points - dataframe of x,y points to plot
plot_regr_rsq <- function(points) {
  if (nrow(points) == 0) {
    plot(NA, xlim=c(-5,50), ylim=c(-5,50), xlab="x", ylab="y")
    return()
  }
  plot(points, xlim=c(-5,50), ylim=c(-5,50), pch=19, cex=2, col="gray")
  if (nrow(points) < 2) return()
  
  regr <- lm(points$y ~ points$x)
  regr_summary <- summary(regr)
  abline(regr, lwd=2, col="cornflowerblue")
  text(1, 50, paste(c("Raw intercept: ", round(regr$coefficients[1], 2)), collapse=" "), cex=0.80)
  text(1, 45, paste(c("Raw slope    : ", round(regr$coefficients[2], 2)), collapse=" "), cex=0.80)
  text(1, 40, paste(c("Correlation  : ", round(cor(points$x, points$y), 2)), collapse=" "), cex=0.80)
  text(1, 35, paste(c("R-squared    : ", round(regr_summary$r.squared, 2)), collapse=" "), cex=0.80)
}

# interactive_regression() runs a regression simulation.
# Click on the plotting area to add points and see a corresponding regression line
#  (hitting ESC will stop the simulation). 
#
# You can supply the following parameter:
#   old_pts - dataframe of x,y points to start interacting with
#
# You will also see three numbers: 
#   intercept – where the regression line intercepts the y-axis
#   regression coefficient – the slope of x on y
#   correlation - correlation of x and y
#   r-squared - R^2 of y
interactive_regression_rsq <- function(points=data.frame()) {
  cat("Click on the plot to create data points; hit [esc] to stop")
  repeat {
    plot_regr_rsq(points)
    click_loc <- locator(1)
    if (is.null(click_loc)) break
    if(nrow(points) == 0 ) {
      points <- data.frame(x=click_loc$x, y=click_loc$y)
    } else {
      points <- rbind(points, c(click_loc$x, click_loc$y))
    }
  }
  
  return(points)
}