Package 'artpack' reference manual

Title:	Creates Generative Art Data
Description:	Create data that displays generative art when mapped into a 'ggplot2' plot. Functionality includes specialized data frame creation for geometric shapes, tools that define artistic color palettes, tools for geometrically transforming data, and other miscellaneous tools that are helpful when using 'ggplot2' for generative art.
Authors:	Meghan Harris [aut, cre]
Maintainer:	Meghan Harris <[email protected]>
License:	MIT + file LICENSE
Version:	0.1.0
Built:	2024-11-10 04:30:08 UTC
Source:	https://github.com/meghansaha/artpack

Custom-built artpack Color Palettes

Description

The artpack palette picker. The art_pals function consists of 18 palettes: "arctic", "beach", "bw", "brood", "cosmos", "explorer", "gemstones", "grays", "icecream", "imagination", "majestic", "nature", "neon", "ocean", "plants", "rainbow", "sunnyside", "super"

Usage

art_pals(pal = NULL, n = 5, direction = "regular")
art_pals(pal = NULL, n = 5, direction = "regular")

Arguments

pal

A character string of the desired artpack palette.

The 18 artpack palettes include:

"arctic" - Icy blue and white colors
"beach" - Sand-colored tans and ocean-colored blue colors
"bw" - A gradient of black to white colors
"brood" - A gradient of different shades of dark gray and black colors
"cosmos" - Nebula-inspired blue, purple, and pink colors
"explorer" - Pokemon-type inspired colors
"gemstones" - Birthstone/Mineral-inspired colors
"grays" - A gradient of dark, medium, and light gray colors
"icecream" - A light pastel palette of cream, blue, brown, and pink colors
"imagination" - 90's school supply-inspired colors
"majestic" - Shades of majestic purple colors
"nature" - A mix of tan, brown, green, and red colors
"neon" - A neon spectrum of rainbow colors
"ocean" - A gradient of dark to light blue colors
"plants" - A gradient of dark to light green colors
"rainbow" - A vibrant mix of rainbow colors
"sunnyside" - A retro-inspired mix of pink, orange, and yellow colors
"super" - A marveling mix of heroic colors

n

The numbers of colors desired in the output.

Default is 5. n must be a positive integer with a value greater than 0

direction

The direction of the palette

Default is "regular". Only two options accepted: "regular" or "reverse"

Value

A Character Vector.

Examples



library(ggplot2)
dots <- data.frame(x = c(1:10), y = 2.5)
dots$fills <- art_pals("rainbow", 10)

dots |>
  ggplot(aes(x, y)) +
  theme_void() +
  geom_point(
    shape = 21,
    fill = dots$fills,
    color = "#000000",
    size = 10,
    stroke = 2
  )


dots_rev <- data.frame(x = c(1:10), y = 2.5)
dots_rev$fills <- art_pals("rainbow", 10, "reverse")

dots_rev |>
  ggplot(aes(x, y)) +
  theme_void() +
  geom_point(
    shape = 21,
    fill = dots_rev$fills,
    color = "#000000",
    size = 10,
    stroke = 2
  )

library(ggplot2)
dots <- data.frame(x = c(1:10), y = 2.5)
dots$fills <- art_pals("rainbow", 10)

dots |>
  ggplot(aes(x, y)) +
  theme_void() +
  geom_point(
    shape = 21,
    fill = dots$fills,
    color = "#000000",
    size = 10,
    stroke = 2
  )


dots_rev <- data.frame(x = c(1:10), y = 2.5)
dots_rev$fills <- art_pals("rainbow", 10, "reverse")

dots_rev |>
  ggplot(aes(x, y)) +
  theme_void() +
  geom_point(
    shape = 21,
    fill = dots_rev$fills,
    color = "#000000",
    size = 10,
    stroke = 2
  )

Data Generation for Circles

Description

A tool for creating a data frame of values that create a circle with a specified radius when plotted.

The geom_path and geom_polygon geoms are recommended with this data for use in ggplot2 for generative art.

Usage

circle_data(
  x,
  y,
  radius,
  color = NULL,
  fill = NULL,
  n_points = 100,
  group_var = FALSE,
  group_prefix = "circle_"
)
circle_data(
  x,
  y,
  radius,
  color = NULL,
  fill = NULL,
  n_points = 100,
  group_var = FALSE,
  group_prefix = "circle_"
)

Arguments

`x`	Numeric value of length 1 - The center `x` coordinate value of the circle.
`y`	Numeric value of length 1 - The center `y` coordinate value of the circle.
`radius`	Numeric value of length 1 that must be greater than 0 - The radius of the circle.
`color`	Character value of length 1 - The color of the square's border. A valid `R` color from `colors()` or a standard 6 digit hexadecimal webcolor like "#000000"
`fill`	Character value of length 1 - The color of the square. A valid `R` color from `colors()` or a standard 6 digit hexadecimal webcolor like "#000000"
`n_points`	Numeric value. Default is 100. This determines how many points the square will have. This option can come in handy when using jitter options or other texture/illusion methods. Must be of length 1 and at least a value of 100.
`group_var`	Logical. Default is `FALSE`. If `TRUE`, a `group` variable will be added to the dataframe. Useful in iterative data generation.
`group_prefix`	Character string of length 1 - The prefix used for the `group` variable. Default is "square_"

Value

A Tibble

Examples



# Creating one circle

library(ggplot2)
one_circle <- circle_data(x = 0, y = 0, radius = 5)

# Plot The Data
one_circle |>
  ggplot(aes(x, y)) +
  geom_path(color = "green") +
  coord_equal()

# To create multiple circles, use your preferred method of iteration:
# Creating two circles

library(purrr)
library(dplyr)

# Make your specs
x_vals <- c(0, 10)
y_vals <- c(0, 0)
radi <- c(1, 3)
fills <- c("purple", "yellow")
circle_n <- 1:2

# Prep for your iteration
lst_circle_specs <-
  list(
    x_vals,
    y_vals,
    radi,
    fills,
    circle_n
  )

# Use `circle_data()` in your preferred iteration methods
two_circles <- pmap(lst_circle_specs, ~ circle_data(
  x = ..1,
  y = ..2,
  radi = ..3,
  fill = ..4,
  color = "#000000",
  group_var = TRUE
) |>
  # circle_data adds a `group` variable if `group_var` = TRUE.
  # For multiple circles, a unique identifier should be added/pasted in.
  mutate(group = paste0(group, ..5))) |>
  list_rbind()

# Plot the data

two_circles |>
  ggplot(aes(x, y, group = group)) +
  theme(legend.position = "none") +
  geom_polygon(
    color = two_circles$color,
    fill = two_circles$fill
  ) +
  coord_equal() #Always use coord_equal() or coord_fixed for circles!

# Creating one circle

library(ggplot2)
one_circle <- circle_data(x = 0, y = 0, radius = 5)

# Plot The Data
one_circle |>
  ggplot(aes(x, y)) +
  geom_path(color = "green") +
  coord_equal()

# To create multiple circles, use your preferred method of iteration:
# Creating two circles

library(purrr)
library(dplyr)

# Make your specs
x_vals <- c(0, 10)
y_vals <- c(0, 0)
radi <- c(1, 3)
fills <- c("purple", "yellow")
circle_n <- 1:2

# Prep for your iteration
lst_circle_specs <-
  list(
    x_vals,
    y_vals,
    radi,
    fills,
    circle_n
  )

# Use `circle_data()` in your preferred iteration methods
two_circles <- pmap(lst_circle_specs, ~ circle_data(
  x = ..1,
  y = ..2,
  radi = ..3,
  fill = ..4,
  color = "#000000",
  group_var = TRUE
) |>
  # circle_data adds a `group` variable if `group_var` = TRUE.
  # For multiple circles, a unique identifier should be added/pasted in.
  mutate(group = paste0(group, ..5))) |>
  list_rbind()

# Plot the data

two_circles |>
  ggplot(aes(x, y, group = group)) +
  theme(legend.position = "none") +
  geom_polygon(
    color = two_circles$color,
    fill = two_circles$fill
  ) +
  coord_equal() #Always use coord_equal() or coord_fixed for circles!

Data Generation for A Custom-built Square Grid

Description

Creates a dataframe of x and y points to visualize a square grid based on given x and y limits. Providing a color palette and fill style are optional.

Usage

grid_maker(
  xlim,
  ylim,
  size,
  fill_pal = NULL,
  fill_style = "range",
  color_pal = NULL,
  color_style = "range"
)
grid_maker(
  xlim,
  ylim,
  size,
  fill_pal = NULL,
  fill_style = "range",
  color_pal = NULL,
  color_style = "range"
)

Arguments

`xlim`	A numeric vector with two X limits. A minimum and maximum limit for the X axis. Must be a length of 2.
`ylim`	A numeric vector with two Y limits. A minimum and maximum limit for the Y axis. Must be a length of 2.
`size`	A numeric input. The size of the grid. How many shapes will appear in a single row or column. Must be a length of 1, greater than 0, and less than or equal to the max `xlim` and max `ylim`.
`fill_pal`	Optional. A character vector of 6 digit hexadecimal webcolor code, or `R` `colors()` color strings to be applied to fill the grid.
`fill_style`	Optional. A character input. "range" or "random". Determines how the fill color palette is mapped.
`color_pal`	Optional. A character vector of 6 digit hexadecimal webcolor code, or `R` `colors()` color strings to be applied to borders of the grid.
`color_style`	Optional. A character input. "range" or "random". Determines how the border color palette is mapped.

Value

A Tibble

Examples



# Creating data for a grid:

library(ggplot2)
grid_data <- grid_maker(
  xlim = c(0, 50),
  ylim = c(0, 50),
  size = 10,
  fill_pal = c("turquoise", "black", "purple"),
  color_pal = c("black", "limegreen")
)

ggplot() +
  geom_polygon(
    data = grid_data,
    aes(x, y, group = group),
    fill = grid_data$fill,
    color = grid_data$color
  ) +
  coord_equal()

# Creating data for a grid:

library(ggplot2)
grid_data <- grid_maker(
  xlim = c(0, 50),
  ylim = c(0, 50),
  size = 10,
  fill_pal = c("turquoise", "black", "purple"),
  color_pal = c("black", "limegreen")
)

ggplot() +
  geom_polygon(
    data = grid_data,
    aes(x, y, group = group),
    fill = grid_data$fill,
    color = grid_data$color
  ) +
  coord_equal()

Convert Numbers into Padded Strings for Easier Group Numbering

Description

Convert Numbers into Padded Strings for Easier Group Numbering

Usage

group_numbers(numbers)
group_numbers(numbers)

Arguments

numbers

A numeric vector with a length of at least 1.

Value

A Character Vector

Examples

# Useful for easier group numbering so groups are ordered as intended
# Expects a numeric vector of numbers to convert to padded numbers
regular_numbers <- 1:19
padded_numbers <- group_numbers(regular_numbers)

# The padding matters when creating labels for groupings
# as numbers will be converted to characters if attached to strings.
# Sorts as expected:
sort(regular_numbers)

# Does not as a character:
sort(paste0("group_", regular_numbers))

# Will sort as expected when padded:
sort(paste0("group_", padded_numbers))
# Useful for easier group numbering so groups are ordered as intended
# Expects a numeric vector of numbers to convert to padded numbers
regular_numbers <- 1:19
padded_numbers <- group_numbers(regular_numbers)

# The padding matters when creating labels for groupings
# as numbers will be converted to characters if attached to strings.
# Sorts as expected:
sort(regular_numbers)

# Does not as a character:
sort(paste0("group_", regular_numbers))

# Will sort as expected when padded:
sort(paste0("group_", padded_numbers))

Data Generation for Circle Packing

Description

A tool for creating a data frame of values that create a circle packing design when plotted. When the default circle_type "whole" is used, the output should mapped with geom_polygon in a ggplot. When "swirl" is used, the output should be mapped with geom_path for the best results.

Usage

packer(
  n,
  min_x = 0,
  max_x = 100,
  min_y = 0,
  max_y = 100,
  big_r = 5,
  med_r = 3,
  small_r = 1,
  color_pal = NULL,
  color_type = "regular",
  circle_type = "whole"
)
packer(
  n,
  min_x = 0,
  max_x = 100,
  min_y = 0,
  max_y = 100,
  big_r = 5,
  med_r = 3,
  small_r = 1,
  color_pal = NULL,
  color_type = "regular",
  circle_type = "whole"
)

Arguments

`n`	The total number of circles you would like the function to attempt to create. A single numeric value with a minimum value of 10.
`min_x`	The minimum limit of the x-axis - the left 'border' of the canvas A single numeric value.
`max_x`	The maximum limit of the x-axis - the right 'border' of the canvas A single numeric value.
`min_y`	The minimum limit of the y-axis - the bottom 'border' of the canvas A single numeric value.
`max_y`	The maximum limit of the y-axis - the top 'border' of the canvas A single numeric value.
`big_r`	The radius used for your 'big' sized circles A single numeric value.
`med_r`	The radius used for your 'medium' sized circles. A single numeric value.
`small_r`	The radius used for your 'small' sized circles. A single numeric value.
`color_pal`	A vector of hex color codes that will be mapped to the data.
`color_type`	Default is "regular" - The colors will be mapped in order from big circles to small circles. "reverse" - The colors will be mapped in reversed order from small to big circles. "random" - The colors will be mapped randomly to any sized circle.
`circle_type`	Default is "whole" - Regular circles. "swirl" - circles are replaced with spirals. Spirals should be mapped with `geom_path` in a ggplot for the best results.

Value

A Tibble

Examples




library(ggplot2)
set.seed(0310)
packed_circles <- packer(
  n = 50, big_r = 5, med_r = 3, small_r = 1,
  min_x = 0, max_x = 100, min_y = 0, max_y = 100
)
packed_circles

packed_circles |>
  ggplot(aes(x, y, group = group)) +
  theme_void() +
  theme(plot.background = element_rect(fill = "black")) +
  geom_polygon(fill = "white", color = "red") +
  coord_equal()

library(ggplot2)
set.seed(0310)
packed_circles <- packer(
  n = 50, big_r = 5, med_r = 3, small_r = 1,
  min_x = 0, max_x = 100, min_y = 0, max_y = 100
)
packed_circles

packed_circles |>
  ggplot(aes(x, y, group = group)) +
  theme_void() +
  theme(plot.background = element_rect(fill = "black")) +
  geom_polygon(fill = "white", color = "red") +
  coord_equal()

Rotate Points in a Data Frame Based on an Anchor Point

Description

Rotates the x and y points in a given data frame by a given angle based on a designated anchor point.

Usage

rotator(data, x, y, angle = 5, anchor = "center", drop = FALSE)
rotator(data, x, y, angle = 5, anchor = "center", drop = FALSE)

Arguments

`data`	A data frame or tibble with at least `x` and `y` variables
`x`	A numeric variable in `data`. The variable intended to be plotted on the x axis in a `ggplot`.
`y`	A numeric variable in `data`. The variable intended to be plotted on the y axis in a `ggplot`.
`angle`	The angle (in degrees) the points in `data` will be rotated around it's anchor
`anchor`	The anchor point for the rotation. Default is "center". Options include:"center", "bottom", "top", "left", and "right"
`drop`	Logical `TRUE` or `FALSE` that determines if all other variables that are not being rotated are removed from the final output. Default is `FALSE`.

Value

A data frame

Examples



library(ggplot2)
original_square <- data.frame(
  x = c(0, 3, 3, 0, 0),
  y = c(0, 0, 3, 3, 0)
)
rotated_square <- rotator(data = original_square,
                          x = x,
                          y = y,
                          angle = 45,
                          anchor = "center")

ggplot()+
  geom_path(data = original_square,
                     aes(x,y),
                     color = "red")+
  geom_polygon(data = rotated_square,
                        aes(x,y),
                        fill = "purple")+
  coord_equal()


library(ggplot2)
original_square <- data.frame(
  x = c(0, 3, 3, 0, 0),
  y = c(0, 0, 3, 3, 0)
)
rotated_square <- rotator(data = original_square,
                          x = x,
                          y = y,
                          angle = 45,
                          anchor = "center")

ggplot()+
  geom_path(data = original_square,
                     aes(x,y),
                     color = "red")+
  geom_polygon(data = rotated_square,
                        aes(x,y),
                        fill = "purple")+
  coord_equal()

Data Generation for Squares

Description

A tool for creating a data frame of values that create a square with a specified size when plotted.

The geom_path and geom_polygon geoms are recommended with this data for use in ggplot2 for generative art.

Usage

square_data(
  x,
  y,
  size,
  color = NULL,
  fill = NULL,
  n_points = 100,
  group_var = FALSE,
  group_prefix = "square_"
)
square_data(
  x,
  y,
  size,
  color = NULL,
  fill = NULL,
  n_points = 100,
  group_var = FALSE,
  group_prefix = "square_"
)

Arguments

`x`	Numeric value of length 1 - The bottom left `x` value of the square.
`y`	Numeric value of length 1 - The bottom left `y` value of the square.
`size`	Numeric value of length 1 that must be greater than 0 - The size of the square.
`color`	Character value of length 1 - The color of the square's border. A valid `R` color from `colors()` or a standard 6 digit hexadecimal webcolor like "#000000"
`fill`	Character value of length 1 - The color of the square. A valid `R` color from `colors()` or a standard 6 digit hexadecimal webcolor like "#000000"
`n_points`	Numeric value. Default is 100. This determines how many points the square will have. This option can come in handy when using jitter options or other texture/illusion methods. Must be of length 1 and at least a value of 4.
`group_var`	Logical. Default is `FALSE`. If `TRUE`, a `group` variable will be added to the dataframe. Useful in iterative data generation.
`group_prefix`	Character string of length 1 - The prefix used for the `group` variable. Default is "square_"

Value

A Tibble

Examples



# Creating one square
library(ggplot2)
one_square <- square_data(x = 0, y = 0, size = 5)

# Plot The Data
one_square |>
  ggplot(aes(x,y))+
  geom_path(color = "green")+
  coord_equal()

# To create multiple squares, use your preferred method of iteration:
# Creating two squares

library(purrr)
library(dplyr)

# Make your specs
x_vals <- c(0,4)
y_vals <- c(0,0)
sizes <- c(1,3)
fills <- c("purple", "yellow")
square_n <- 1:2

# Prep for your iteration
lst_square_specs <-
  list(
    x_vals,
    y_vals,
    sizes,
    fills,
    square_n
  )

# Use `square_data()` in your preferred iteration methods
two_squares <- pmap(lst_square_specs, ~square_data(
  x = ..1,
  y = ..2,
  size = ..3,
  fill = ..4,
  color = "#000000",
  group_var = TRUE
) |>
  # square_data adds a `group` variable if `group_var` = TRUE.
  # For multiple squares, a unique identifier should be added/pasted in.
  mutate(group = paste0(group,..5))
) |>
  list_rbind()

# Plot the data

two_squares |>
  ggplot(aes(x, y, group = group))+
  theme(legend.position = "none")+
  geom_polygon(color = two_squares$color,
               fill = two_squares$fill) +
  coord_equal()


# Creating one square
library(ggplot2)
one_square <- square_data(x = 0, y = 0, size = 5)

# Plot The Data
one_square |>
  ggplot(aes(x,y))+
  geom_path(color = "green")+
  coord_equal()

# To create multiple squares, use your preferred method of iteration:
# Creating two squares

library(purrr)
library(dplyr)

# Make your specs
x_vals <- c(0,4)
y_vals <- c(0,0)
sizes <- c(1,3)
fills <- c("purple", "yellow")
square_n <- 1:2

# Prep for your iteration
lst_square_specs <-
  list(
    x_vals,
    y_vals,
    sizes,
    fills,
    square_n
  )

# Use `square_data()` in your preferred iteration methods
two_squares <- pmap(lst_square_specs, ~square_data(
  x = ..1,
  y = ..2,
  size = ..3,
  fill = ..4,
  color = "#000000",
  group_var = TRUE
) |>
  # square_data adds a `group` variable if `group_var` = TRUE.
  # For multiple squares, a unique identifier should be added/pasted in.
  mutate(group = paste0(group,..5))
) |>
  list_rbind()

# Plot the data

two_squares |>
  ggplot(aes(x, y, group = group))+
  theme(legend.position = "none")+
  geom_polygon(color = two_squares$color,
               fill = two_squares$fill) +
  coord_equal()

Data Generation for 2D Sine and Cosine Waves

Description

A tool for making data frames filled with data that displays sine or cosine waves when graphed.

The geom_path and geom_polygon geoms are recommended with this data for use in ggplot2 for generative art.

Usage

wave_data(
  start,
  end,
  size = 1,
  type = "sin",
  orientation = "horizontal",
  freq = 3,
  n_points = 500,
  color = NULL,
  fill = NULL,
  group_var = FALSE,
  dampen = NULL,
  amplify = NULL
)
wave_data(
  start,
  end,
  size = 1,
  type = "sin",
  orientation = "horizontal",
  freq = 3,
  n_points = 500,
  color = NULL,
  fill = NULL,
  group_var = FALSE,
  dampen = NULL,
  amplify = NULL
)

Arguments

`start`	Numeric value. The starting point of the wave on the coordinate system. By default refers to the x-axis. Will refer to the y-axis if `orientation` is set to `vertical`. Must be of length 1.
`end`	Numeric value. The ending point of the wave on the coordinate system. By default refers to the x-axis. Will refer to the y-axis if `orientation` is set to `vertical` Must be of length 1.
`size`	Numeric value. The height or width of the wave. Orientation is set to `horizontal` by default, thus size will affect height by default. When orientation is set to `vertical`, size controls the width of the wave. Must be a positive numeric value. Must be of length 1.
`type`	String value. "sin" or "cos" for sine or cosine waves. `sin` is default. Must be of length 1.
`orientation`	String value. Default is `horizontal` which will draw the wave from left to right (x-axis) on the coordinate system. `vertical` will draw the wave from bottom to top (y-axis) on the coordinate system. Must be of length 1.
`freq`	Numeric value. Default is 3 cycles per second. This affects how many "peaks" are created in the wave. Must be a positive numeric value. Must be of length 1.
`n_points`	Numeric value. Default is 500. This determines how many points each half of the wave will have. This option can come in handy when using jitter options or other texture/illusion methods. Must be of length 1.
`color`	Optional String Value. A 6 digit hexadecimal webcolor code, or `R` `colors()` color string for the border color of the wave. Must be of length 1.
`fill`	Optional String Value. A 6 digit hexadecimal webcolor code, or `R` `colors()` color string for the fill color of the wave. Must be of length 1.
`group_var`	Logic value. `TRUE` or `FALSE`. Default is `FALSE`. If `TRUE`, Adds a group variable to the data frame. Useful for iterative work to make multiple waves in a single data frame.
`dampen`	Optional. A factor in which to dampen the wave (make "flatter"). Must be of length 1.
`amplify`	Optional. A factor in which to amplify the wave (make "sharper"). Must be of length 1.

Value

A Tibble

Examples



library(ggplot2)
wave_df <- wave_data(
  start = 0, end = 10,
  fill = "purple",
  color = "green"
)

wave_df |>
  ggplot(aes(x, y)) +
  theme_void() +
  geom_polygon(
    fill = wave_df$fill,
    color = wave_df$color,
    linewidth = 3
  ) +
  coord_equal()

library(ggplot2)
wave_df <- wave_data(
  start = 0, end = 10,
  fill = "purple",
  color = "green"
)

wave_df |>
  ggplot(aes(x, y)) +
  theme_void() +
  geom_polygon(
    fill = wave_df$fill,
    color = wave_df$color,
    linewidth = 3
  ) +
  coord_equal()

Package 'artpack'

Help Index

Custom-built artpack Color Palettes

Description

Usage

Arguments

Value

Examples

Data Generation for Circles

Description

Usage

Arguments

Value

Examples

Data Generation for A Custom-built Square Grid

Description

Usage

Arguments

Value

Examples

Convert Numbers into Padded Strings for Easier Group Numbering

Description

Usage

Arguments

Value

Examples

Data Generation for Circle Packing

Description

Usage

Arguments

Value

Examples

Rotate Points in a Data Frame Based on an Anchor Point

Description

Usage

Arguments

Value

Examples

Data Generation for Squares

Description

Usage

Arguments

Value

Examples

Data Generation for 2D Sine and Cosine Waves

Description

Usage

Arguments

Value

Examples