hilbertImage {HilbertVis} | R Documentation |
Calculate a Hilbert curve visualization of a long data vector and return it as a square matrix.
hilbertImage(data, level = 9, mode = "absmax")
data |
A (potentially very long) vector of numerical data. |
level |
The level of the Hilbert curve, determining the size of the returned matrix |
mode |
The binning mode. See shrinkVector for details. |
See the package vignette for an explanation of this visualization technique.
A matrix of dimension 2^level
x 2^level
. Each matrix element corresponds to a bin of consecutive elements
of the data vector, the bins arranged to follow the Hilbert curve of the given level. By default, the value of a
matrix element is either the largest or smallest element in the bin, whichever is larger by absolute value. (See
shrinkVector
for other possible binning modes.)
To display such a matrix graphically, you can use the standard functions image
or levelplot
but the function showHilbertImage
may be more convenient.
For an interactive GUI to explore a Hilbert curve visualisation, use the function
hilbertDisplay
in the HilbertVisGUI
package.
Simon Anders, EMBL-EBI, sanders@fs.tum.de
# Get a vector with example data dataVec <- makeRandomTestData( ) # Plot it in conventional (linear) fashion plotLongVector( dataVec ) # Note how the peaks look quite uniform # Get the Hilbert curve matrix hMat <- hilbertImage( dataVec ) # Plot it with the 'showHilbertImage' function showHilbertImage( hMat ) # Note how you can now see the non-uniformity hidden in the previous plot. # Note also the ugly aliasing when you change the size of the plot window. # Using EBImage allows to display in each matrix element as one pixel: # if( require ( EBImage ) ) # showHilbertImage( hMat, mode="EBImage" )