imagine

Provides fast application of image filters to data matrices

This package uses C++ algorithms called 'engines'. More details are shown in vignette.

Installation

Get the development version from github:

# install.packages("devtools")
devtools::install_github("LuisLauM/imagine")

Or install the CRAN version

install.packages("imagine")

Input data

For all functions, the main input data must be a numeric matrix object. Depending on each funtion, user must indicate some extra arguments for the filter.

Examples

Next, we show the utility of quantileFilter, one of the six functions that imagine performs.

# Load imagine
library(imagine)

# Build an example matrix
n <- 1e3
origMatrix <- matrix(seq(n^2), nrow = n)

# Add some NAs
origMatrix_withNA <- origMatrix
origMatrix_withNA[sample(seq(n^2), 0.7*n^2, replace = FALSE)] <- NA

# Apply filter
newMatrix <- quantileFilter(dataMatrix = origMatrix_withNA, radius = 3, x = 0.1, times = 1)

# Plot matrices for compare
cols <- colorRampPalette(c("green3", "red4"))(n)

par(mar = c(0, 2, 0, 0), mfrow = c(3, 1))

image(origMatrix, col = cols, axes = FALSE)
mtext(text = "Original", side = 2, line = 0.5, font = 2)

image(origMatrix_withNA, col = cols, axes = FALSE)
mtext(text = "Original with NAs", side = 2, line = 0.5, font = 2)

image(newMatrix, col = cols, axes = FALSE)
mtext(text = "Filtered", side = 2, line = 0.5, font = 2)