Draw visual correlation plots

corplot.R

# Draw visual correlation plots, http://www.indicatrix.org/2014/02/22/visual-correlation-matrices/

# Copyright (C) 2014 Matthew Wigginton Conway.

# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at

#   http://www.apache.org/licenses/LICENSE-2.0

# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

library(ggplot2)
library(scales)

corplot <- function(data, title=NA) {
  # We save two copies because we'll be monkeying with the cors matrix to make the colors
  # right
  cors <- ret <- cor(data)
  
  # Principal diagonal: show white so text is visible
  diag(cors) <- 0
  
  label <- matrix(as.character(round(cors, 2)), nrow(cors), ncol(cors))
  diag(label) <- names(data)
  
  df <- data.frame(x=rep(1:ncol(cors), nrow(cors)), y=-sort(rep(1:nrow(cors), ncol(cors))),
                   r=as.vector(cors), label=as.vector(label))
  
  p <- ggplot(df)
  # default color scheme inspired by color scheme in The Elements of Statistical Learning, by
  # Hastie, Tibshirani and Friedman.
  p <- p + scale_fill_gradient2(lim=c(-1, 1), low=muted('orange'), high=muted('blue')) +
              geom_raster(mapping=aes(x, y, fill=r)) +
              geom_text(mapping=aes(x, y, label=label)) +
              theme(axis.title=element_blank(), axis.text=element_blank(),
                    axis.line=element_blank(), axis.ticks=element_blank(),
                    panel.border=element_blank())
  
  if (!is.na(title)) {
    p <- p + ggtitle(title)
  }
  
  benchplot(p)
  
  return(cors)
}