Set a default color for continuous values — set_default_color

Generates a gradient color palette based on input to colors param. Sets a default gradient if NULL is passed. midpoint param only supplied when using color scale with 3 colors.

Supports colors setting at four levels:

type specific defaults - defaults for a specific feature or type of plot can be passed through data_default param
global options (general session setting with blanket color palette type effects)
- options('giotto.color_cd_pal) - default continuous divergent palette is blue, white, red, for sequential ('giotto.color_cs_pal), it is 'viridis'
- options('giotto.color_c_rev) - whether colors should be reversed
giotto instructions (gobject specific and effects specific types of plots)
- run showColorInstructions() for details on options/params to set in the giottoInstructions object
function specific (directly pass desired colors to plotting function)

Usage

set_default_color_continuous(
  colors = NULL,
  midpoint = NULL,
  style = c("divergent", "sequential"),
  ...,
  instr_pal,
  instr_rev,
  data_default = NULL,
  type = c("fill", "color")
)

set_default_color_continuous_cell(
  colors = NULL,
  instrs,
  midpoint = NULL,
  style = "divergent",
  ...,
  data_default = NULL
)

set_default_color_continuous_poly(
  colors = NULL,
  instrs,
  midpoint = NULL,
  style = "divergent",
  ...
)

set_default_color_continuous_heatmap(
  colors = NULL,
  instrs,
  midpoint = NULL,
  style = "divergent",
  ...
)

set_default_color_continuous_CCcom_heatmap(
  colors = NULL,
  instrs,
  midpoint = NULL,
  style = "divergent",
  ...
)

set_default_color_continuous_CCcom_dotplot(
  colors = NULL,
  instrs,
  midpoint = NULL,
  style = "divergent",
  ...,
  type = c("fill", "color"),
  data_default = list(pal = c("darkblue", "blue", "white", "red", "darkred"))
)

Arguments

colors: character or NULL. 2 to n number of hex color codes or 1 single name of a palette to use can be passed
midpoint: numeric. midpoint value of color gradient
style: scale color scale around midpoint (divergent) or starting from minimum value (sequential)
...: additional params to pass to respective ggplot fill_gradient functions
instr_pal, instr_rev: used by upstream function to pass specific giottoInstructions params
data_default: data type (e.g. cells, polys, heatmap) specific default colors to use
type: whether setting is for ggplot2 'fill' or 'color' type function
instrs: giottoInstructions object (output of instructions(gobject))

Value

continuous color palette

Functions

set_default_color_continuous(): Framework function. Direct use should be minimal. Specific wrapper functions should be used for each item that needs defaults setting (plots or types of features).

Examples

g <- GiottoData::loadGiottoMini("vizgen")
#> 1. read Giotto object
#> 2. read Giotto feature information
#> /home/runner/work/_temp/Library/GiottoData/Mini_datasets/Vizgen/VizgenObject/Features/rna_feature_spatVector.shp
#> rna
#> 3. read Giotto spatial information
#> 3.1 read Giotto spatial shape information
#> aggregate_spatInfo_spatVector.shp z0_spatInfo_spatVector.shp
#>  z1_spatInfo_spatVector.shp
#> aggregate
#> z0
#> z1
#> 
#> 3.2 read Giotto spatial centroid information
#> aggregate
#> z0
#> z1
#> 
#> 3.3 read Giotto spatial overlap information
#> rna_aggregate_spatInfo_spatVectorOverlaps.shp
#>  rna_z0_spatInfo_spatVectorOverlaps.shp rna_z1_spatInfo_spatVectorOverlaps.shp
#> poly_ID feat_ID feat_ID_uniq stack
#> aggregate and rna
#> poly_ID feat_ID feat_ID_uniq
#> z0 and rna
#> poly_ID feat_ID feat_ID_uniq
#> z1 and rna
#> 
#> 4. read Giotto image information
#> 
#> no external python path or giotto
#>  environment was specified, will check if a
#>  default python path is available
#> 
#> A default python path was found: /usr/bin/python3 and will be used
#>  If this is not the correct python path, either
#> 
#> 1. use installGiottoEnvironment() to install
#>  a local miniconda python environment along with required modules
#> 
#> 2. provide an existing python path to
#>  python_path to use your own python path which has all modules
#>  installed
#> Set options("giotto.use_conda" = FALSE) if
#>  python functionalities are not needed

nr_feat_polys <- function(...) {
    spatInSituPlotPoints(g,
        polygon_fill = "nr_feats",
        polygon_fill_as_factor = FALSE,
        polygon_feat_type = "aggregate",
        polygon_line_size = 0.1,
        polygon_alpha = 1,
        ...
    )
}

# default
nr_feat_polys()
#> Warning: You need to select features (feats) and modify feature
#>  types (feat_type) if you want to show individual features
#>  (e.g. transcripts)
#>  This warning is shown once per session
#> plot polygon layer done


# set global option level: viridis
options("giotto.color_c_pal" = "v")
nr_feat_polys()
#> plot polygon layer done


# set instructions level: magma
GiottoClass::instructions(g, "poly_color_c_pal") <- "magma"
nr_feat_polys()
#> plot polygon layer done


GiottoClass::instructions(g, "poly_color_c_rev") <- TRUE
nr_feat_polys()
#> plot polygon layer done

nr_feat_polys(polygon_fill_gradient_style = "s")
#> plot polygon layer done



# set function level: mako
GiottoClass::instructions(g, "poly_color_c_rev") <- FALSE
nr_feat_polys(polygon_fill_gradient = "mako")
#> plot polygon layer done


# set function level: color vector (2 to n colors)
nr_feat_polys(
    polygon_fill_gradient = c("green", "purple"),
    polygon_fill_gradient_style = "s"
)
#> plot polygon layer done


nr_feat_polys(
    polygon_fill_gradient = c("blue", "yellow", "red"),
    polygon_fill_gradient_style = "s"
)
#> plot polygon layer done


nr_feat_polys(
    polygon_fill_gradient = c(
        "darkgrey", "darkblue", "purple", "violet", "cyan"
    ),
    polygon_fill_gradient_style = "s"
)
#> plot polygon layer done