square {rearrr} | R Documentation |
Create x-coordinates so the points form a square
Description
Create the x-coordinates for a vector
of y-coordinates such that
they form a rotated square.
This will likely look most like a square when the y-coordinates are somewhat equally distributed, e.g. a uniform distribution.
Usage
square(
data,
y_col = NULL,
.min = NULL,
.max = NULL,
offset_x = 0,
keep_original = TRUE,
x_col_name = ".square_x",
edge_col_name = ".edge",
overwrite = FALSE
)
Arguments
data |
|
y_col |
Name of column in |
.min |
Minimum y-coordinate. If |
.max |
Maximum y-coordinate. If |
offset_x |
Value to offset the x-coordinates by. |
keep_original |
Whether to keep the original columns. (Logical) Some columns may have been overwritten, in which case only the newest versions are returned. |
x_col_name |
Name of new column with the x-coordinates. |
edge_col_name |
Name of new column with the edge identifiers. If Numbering is clockwise and starts at the upper-right edge. |
overwrite |
Whether to allow overwriting of existing columns. (Logical) |
Value
data.frame
(tibble
) with the added x-coordinates and an identifier
for the edge the data point is a part of.
Author(s)
Ludvig Renbo Olsen, r-pkgs@ludvigolsen.dk
See Also
Other forming functions:
circularize()
,
hexagonalize()
,
triangularize()
Examples
# Attach packages
library(rearrr)
library(dplyr)
library(purrr)
has_ggplot <- require(ggplot2) # Attach if installed
# Set seed
set.seed(1)
# Create a data frame
df <- data.frame(
"y" = runif(200),
"g" = factor(rep(1:5, each = 40))
)
# Square 'y'
df_sq <- square(df, y_col = "y")
df_sq
# Plot square
if (has_ggplot){
df_sq %>%
ggplot(aes(x = .square_x, y = y, color = .edge)) +
geom_point() +
theme_minimal()
}
#
# Grouped squaring
#
# Square 'y' for each group
# First cluster the groups a bit to move the
# squares away from each other
df_sq <- df %>%
cluster_groups(
cols = "y",
group_cols = "g",
suffix = "",
overwrite = TRUE
) %>%
dplyr::group_by(g) %>%
square(
y_col = "y",
overwrite = TRUE
)
# Plot squares
if (has_ggplot){
df_sq %>%
ggplot(aes(x = .square_x, y = y, color = g)) +
geom_point() +
theme_minimal()
}
#
# Specifying minimum value
#
# Specify minimum value manually
df_sq <- square(df, y_col = "y", .min = -2)
df_sq
# Plot square
if (has_ggplot){
df_sq %>%
ggplot(aes(x = .square_x, y = y, color = .edge)) +
geom_point() +
theme_minimal()
}
#
# Multiple squares by contraction
#
# Start by squaring 'y'
df_sq <- square(df, y_col = "y")
# Contract '.square_x' and 'y' towards the centroid
# To contract with multiple multipliers at once,
# we wrap the call in purrr::map_dfr
df_expanded <- purrr::map_dfr(
.x = c(1, 0.75, 0.5, 0.25, 0.125),
.f = function(mult) {
expand_distances(
data = df_sq,
cols = c(".square_x", "y"),
multiplier = mult,
origin_fn = centroid,
overwrite = TRUE
)
}
)
df_expanded
if (has_ggplot){
df_expanded %>%
ggplot(aes(
x = .square_x_expanded, y = y_expanded,
color = .edge, alpha = .multiplier
)) +
geom_point() +
theme_minimal()
}