dDensityPlot: Display density on 2D plot

View source: R/dDensityPlot.R

dDensityPlotR Documentation

Display density on 2D plot

Description

Function to show density for a set of observations on a field created by two variables. The plot is constructed primarily for displaying density of 2D-stochastic neighbour embedding fields, but can be used for any sets of two known for the same observations. As the number of datapoints is often very high, the files would, if saved as pdf of another vector based file type become big. For this reason, the plots are saved as jpeg and no axes or anything alike are added, to simplify usage in publications.

Usage

dDensityPlot(
  xYData,
  colorScale = "default",
  plotName = "All_density",
  idsVector,
  densContour = TRUE,
  title = FALSE,
  plotDir = "default",
  bandColor = "black",
  dotSize = 500/sqrt(nrow(xYData)),
  createOutput = TRUE
)

Arguments

xYData

A dataframe or matrix with two columns. Each row contains information about the x and y positition in the field for that observation.

colorScale

This gives the specific color for the densest part of the plot(s). It has three possible values:

A specific color, e.g. 'red' or '#FF0000'

If no idsVector provided

A color scale from dColorVector

If idsVector provided. See dColorVector for alternatives.

"default"

"One color (blue) if no idsVector is provided, and otherwise the viridis color scale.

plotName

A name that is common to all density plots created. It can be the groups name, e.g. 'Malaria patients' or 'Clusters'. If only one plot is created, the name is still taken from here.

idsVector

Optional. Vector with the same length as xYData containing information about the id of each observation. If provided, density plots for each individual id and all ids together are produced.

densContour

If density contours should be created for the plot(s) or not. Defaults to TRUE. If a density object, as generated by dContours, is included, this will be used for the internal scaling of the plot, allowing for density distribution checks of different subcompartments of the data with the same scaling.

title

If there should be a title displayed on the plotting field. As the plotting field is saved as a png, this title cannot be removed as an object afterwards, as it is saved as coloured pixels. To simplify usage for publication, the default is FALSE, as the files are still named, eventhough no title appears on the plot.

plotDir

If different from the current directory. If not "." and non-existent, the function creates it. Default is "." if idsVector is not specified and otherwise paste0("Density plots for ", plotName, "s").

bandColor

The color of the contour bands. Defaults to black.

dotSize

Simply the size of the dots. The default makes the dots smaller the more observations that are included.

createOutput

For testing purposes. Defaults to TRUE. If FALSE, no output is generated.

Value

Plots showing the densities of the specific xYData (subset) displayed as color on the field created by the same xYData (subset).

See Also

dColorPlot, dResidualPlot, dWilcox, dColorVector

Examples


# Load some data
data(testData)
## Not run: 
# Load or create the dimensions that you want to plot the result over. 
# uwot::umap recommended due to speed, but tSNE or other method would
# work as fine. 
data(testDataSNE)

# Plot all data together
dDensityPlot(xYData = testDataSNE$Y)

# Now each depeche cluster is plotted separately and together.

# Run the clustering function. For more rapid example execution,
# a depeche clustering of the data is included
# testDataDepeche <- depeche(testData[,2:15])
data(testDataDepeche)

dDensityPlot(
    xYData = testDataSNE$Y,
    idsVector = testDataDepeche$clusterVector,
    plotName = "cluster"
)

## End(Not run)

Theorell/DepecheR documentation built on July 27, 2023, 8:13 p.m.