This function creates a legend to accompany a map describing a linear sequence of distributions.
legend_timeline( palette, specificity = TRUE, time_labels = NULL, label_i = "Maximum\nintensity", label_l = "Layer", label_s = c("Low specificity", "Moderate specificity", "High specificity"), axis_i = c("low", "high"), return_df = FALSE )
palette | data frame containing a color palette generated by palette_timeline. |
---|---|
specificity | logical indicating whether to visualize intensity and layer information for three specificity values (i.e., 0, 50, 100) or for a single specificity value (i.e., 100). Typically, a single specificity value is appropriate for map_multiples visualizations. |
time_labels | character vector with two elements to be used as labels for the start and end points of the time axis (i.e. x-axis) in the legend. |
label_i | character vector with a single element describing the meaning of intensity values. |
label_l | character vector with a single element describing the meaning of layer values. |
label_s | character vector with three elements describing differences in the meaning of specificity across three legend wheels. |
axis_i | character vector with two elements describing the meaning of low and high intensity values. |
return_df | logical indicating whether to return the legend as a
|
A ggplot2
plot object of the legend. Alternatively,
return_df = TRUE
will return a data frame containing a data frame
containing the data needed to build the legend. The data frame columns are:
specificity
: the degree to which intensity values are unevenly
distributed across layers; mapped to chroma.
layer_id
: integer identifying the layer containing the maximum
intensity value; mapped to hue.
color
: the hexadecimal color associated with the given layer and
specificity values.
intensity
: maximum cell value across layers divided by the maximum
value across all layers and cells; mapped to alpha level.
legend_timecycle for cyclical sequences of distributions and legend_set for distributions of distinct groups.
Other legend:
legend_set()
,
legend_timecycle()
# load fisher data data(fisher_ud) # generate hcl palette pal <- palette_timeline(fisher_ud) # create legend for palette legend_timeline(pal)