Draw horizon chart along the spiral

Source: R/graphics.R

Draw horizon chart along the spiral

spiral_horizon(
  x,
  y,
  y_max = max(abs(y)),
  n_slices = 4,
  slice_size,
  pos_fill = "#D73027",
  neg_fill = "#313695",
  use_bars = FALSE,
  bar_width = min(diff(x)),
  negative_from_top = FALSE,
  track_index = current_track_index()
)

Arguments

x

X-locations of the data points.

y

Y-locations of the data points.

y_max

Maximal absolute value on y-axis.

n_slices

Number of slices.

slice_size

Size of the slices. The final number of sizes is ceiling(max(abs(y))/slice_size).

pos_fill

Colors for positive values.

neg_fill

Colors for negative values.

use_bars

Whether to use bars?

bar_width

Width of bars.

negative_from_top

Should negative distribution be drawn from the top?

track_index

Index of the track.

Value

A list of the following objects:

  • a color mapping function for colors.

  • a vector of intervals that split the data.

Details

Since the track height is very small in the spiral, horizon chart visualization is an efficient way to visualize distribution-like graphics.

See also

horizon_legend() for generating the legend.

Examples

# \donttest{
df = readRDS(system.file("extdata", "global_temperature.rds", package = "spiralize"))
df = df[df$Source == "GCAG", ]
spiral_initialize_by_time(xlim = range(df$Date), unit_on_axis = "months", period = "year",
    period_per_loop = 20, polar_lines_by = 360/20)
spiral_track()
spiral_horizon(df$Date, df$Mean, use_bar = TRUE)


# with legend
require(ComplexHeatmap)
#> Loading required package: ComplexHeatmap
#> ========================================
#> ComplexHeatmap version 2.18.0
#> Bioconductor page: http://bioconductor.org/packages/ComplexHeatmap/
#> Github page: https://github.com/jokergoo/ComplexHeatmap
#> Documentation: http://jokergoo.github.io/ComplexHeatmap-reference
#> 
#> If you use it in published research, please cite either one:
#> - Gu, Z. Complex Heatmap Visualization. iMeta 2022.
#> - Gu, Z. Complex heatmaps reveal patterns and correlations in multidimensional 
#>     genomic data. Bioinformatics 2016.
#> 
#> 
#> The new InteractiveComplexHeatmap package can directly export static 
#> complex heatmaps into an interactive Shiny app with zero effort. Have a try!
#> 
#> This message can be suppressed by:
#>   suppressPackageStartupMessages(library(ComplexHeatmap))
#> ========================================
spiral_initialize_by_time(xlim = range(df$Date), unit_on_axis = "months", period = "year",
    period_per_loop = 20, polar_lines_by = 360/20, 
    vp_param = list(x = unit(0, "npc"), just = "left"))
spiral_track()
lt = spiral_horizon(df$Date, df$Mean, use_bar = TRUE)
lgd = horizon_legend(lt, title = "Temperature difference")
draw(lgd, x = unit(1, "npc") + unit(2, "mm"), just = "left")

# }