ggpattern Package in R

The ggpattern package in R is a package for creating custom and visually appealing backgrounds for ggplot2 plots. The overall article is going to cover a comprehensive introduction to the ggpattern package in R, including its features and capabilities, installation and setup, and how to use it to create various types of visual patterns and backgrounds for ggplot2 plots. The article will also showcase some examples of how ggpattern can be used by the end of this article, readers should have a good understanding of the ggplot2 package and how to use it to create custom and attractive backgrounds for their plots.

Required Modules

The following modules are required to use the ggpattern package in R:

• ggplot2: The ggplot2 package is a widely used data visualization library in R and is a required dependency for the ggpattern package.
• grid: The grid package is used to create the underlying graphics structure of ggplot2 plots and is also a required dependency for the ggpattern package.
• gridExtra: The gridExtra package is used to combine multiple ggplot2 plots into one figure and is optional but recommended when using the ggpattern package.

R

install.packages("ggpattern")
install.packages("ggplot2")
install.packages("grid")
install.packages("gridExtra")

Note: If you find an error while running the code, make sure you also install some dependencies with the following command on Linux OS:

sudo apt-get install libmagick++-dev
sudo apt install libgdal-dev

What is ggpattern package in R

The ggpattern package is a package for R that provides additional geoms for ggplot2 to display pattern fills in ggplot2 plots. By combining these different concepts, you can create a wide variety of plots with pattern fills in ggplot2 using the ggpattern package. The following are some of the key concepts related to the ggpattern package:

1. Geoms: The ggpattern package provides several new geoms that allow you to add pattern fills to your ggplot2 plots. Some of the geoms provided by the package include geom_pattern(), geom_hex_pattern(), and geom_rect_pattern().
2. Patterns: The ggpattern package provides a variety of patterns that you can use to fill the geoms in your plots. These patterns include dots, diagonal lines, crosshatch, and more.
3. Mapping: The ggpattern package allows you to map variables in your data to different properties of the patterns, such as color, size, and orientation.
4. Aesthetics: The ggpattern package provides several new aesthetics that can be used in conjunction with the new geoms. These aesthetics include fill, color, size, and angle, among others.
5. Statistics: The ggpattern package also provides several new statistical transformations that can be applied to the data before plotting, such as stat_identity and stat_binhex.

Features of ggpattern Package

The ggpattern package in R provides a suite of functions that allow users to add various types of visual patterns and backgrounds to their ggplot2 plots. Some of the key concepts of the ggpattern package include:

1. Patterns: The ggpattern package provides a collection of pre-defined patterns that can be used as backgrounds for ggplot2 plots. These patterns range from simple geometric shapes, such as dots and stripes, to more complex and abstract designs. The package also provides tools for creating custom patterns.
2. Plot annotations: The ggpattern package includes functions for adding annotations, such as titles, captions, and labels, to ggplot2 plots. These annotations can be positioned and formatted to complement the background patterns and create a cohesive and visually appealing overall design.
3. Plot arrangement: The ggpattern package also provides functions for arranging multiple ggplot2 plots in a grid or array, which can be useful for creating complex visualizations or for comparing multiple datasets. The package can also be used to arrange plots with different background patterns to create interesting and informative visual displays.
4. Customization: The ggpattern package provides a range of customization options, such as color, opacity, and size, that can be used to tailor the appearance of the patterns and backgrounds to the needs of the user. The package also includes options for controlling the appearance of the annotations and other elements of the plot.

By utilizing these concepts, the ggpattern package provides a powerful toolset for creating custom and visually appealing backgrounds for ggplot2 plots. The package is easy to use and provides a wide range of options for customizing the appearance of the patterns and backgrounds, making it an ideal tool for data visualization and presentation.

geom_bin2d_pattern Function in R

geom_bin2d_pattern is a geom in the ggpattern package that creates a 2D histogram with a patterned fill. This geom can be useful for visualizing the density of points in a scatter plot. In geom_bin2d_pattern, the fill color of the histogram bins is determined by the density of points in that bin. The patterned fill is added to the histogram using the pattern argument, which can be set to either ‘grid’ or ‘magick’. If the pattern is set to ‘grid’, the patterns are generated using the gridpattern package. If the pattern is set to ‘magick’, the patterns are generated using the magick package. The appearance of the patterns can be controlled using various arguments such as pattern_scale, pattern_fill, bins, fill, color, and size.

Example

This code creates a plot using the ggplot2 package, and adds a patterned background to the plot using the geom_bin2d_pattern function from the ggpattern package. The pattern_type argument is used to specify the type of pattern, which is based on the density of the data. The pattern argument is set to “magick” to specify that the patterns are generated using the magick package. The pattern_scale argument is used to control the size of the patterns, and the pattern_fill argument is used to specify the color of the patterns. The bins argument is used to specify the number of bins in the 2D histogram. The fill argument is used to specify the fill color of the histogram, and the colour argument is used to specify the color of the bin boundaries. The size argument is used to control the size of the bins. Finally, the scale_pattern_type_continuous function is used to specify the range of intensity values for the patterns, and the labs function is used to add a title and subtitle to the plot.

R

# Load the necessary packages
library(ggplot2)
library(ggpattern)

# Check if magick package is available
if (require("magick")) {

  # Create a scatter plot using ggplot2
  # and diamonds data
  p <- ggplot(diamonds, aes(x, y)) +
    # Set x and y axis limits
    xlim(4, 10) + ylim(4, 10) +
    # Add a pattern background to the plot
    # using geom_bin2d_pattern
    geom_bin2d_pattern(
      # Specify the pattern type based on
      # the density of the data
      aes(pattern_type = ..density..),
      # Specify that the patterns are generated
      # using the magick package
      pattern       = 'magick',
      # Control the size of the patterns
      pattern_scale = 3,
      # Specify the color of the patterns
      pattern_fill  = 'black',
      # Specify the number of bins in the 2D histogram
      bins          = 6,
      # Specify the fill color of the histogram
      fill          = 'white',
      # Specify the color of the bin boundaries
      colour        = 'black',
      # Control the size of the bins
      size          = 0.5
    ) +
    # Set the theme of the plot
    theme_bw(18) +
    # Remove the legend
    theme(legend.position = 'none') +
    # Specify the range of intensity values for the patterns
    scale_pattern_type_continuous(choices =
                 gridpattern::names_magick_intensity[15:21]) +
    # Add a title and subtitle to the plot
    labs(
      title = "ggpattern::geom_bin2d_pattern()",
      subtitle = "pattern = 'magick'"
    )

  # Display the plot
  p

}

Output:

geom_crossbar_pattern() Function in R

The geom_crossbar_pattern() is a geom in the ggpattern package that is used to create crossbar plots with color fills from an image pattern. The geom creates a bar plot with horizontal bars that extend from a lower to an upper limit. The color fill of the bars is determined by an image pattern that can be selected from a number of predefined patterns, or a custom pattern can be specified. The geom_crossbar_pattern() geom is created by specifying the ymin and ymax aesthetics to determine the lower and upper limits of the bars. The pattern_fill aesthetic is used to specify the pattern that should be used to fill the bars. The image pattern can be selected from a number of predefined patterns (e.g. “plasma”) or a custom image file can be specified. The width aesthetic can be used to specify the width of the bars. 
In addition to the aesthetics, the geom_crossbar_pattern() geom also has a number of arguments that can be used to control the appearance of the plot. For example, the pattern argument can be used to specify the type of pattern to use, the width argument can be used to specify the width of the bars, and the theme argument can be used to specify the appearance of the plot.

Example

The code above creates a plot using the ggplot2 library and the ggpattern library. To use the ggpattern library, it first checks if the magick library is installed by using the require() function. If magick is installed, it proceeds to create a plot. The data used in the plot is stored in a data frame called df. The plot is created using the ggplot function, with trt and resp as the x and y variables, respectively. The plot is created using the geom_crossbar_pattern function, which is a geom provided by the ggpattern library. This function is used to create a crossbar pattern plot, where the bars are filled with a pattern rather than a solid color. The aes argument inside the geom_crossbar_pattern function specifies the aesthetic mapping of the data, such as the lower and upper limits of the bars (ymin and ymax), and the pattern fill (pattern_fill). The pattern argument is set to ‘plasma’, which specifies the type of pattern to use for the bar fills. The width argument specifies the width of the bars. The plot is further customized using the theme_bw and labs functions, which set the overall plot theme and label the plot title and subtitle, respectively. The coord_fixed function is used to set the aspect ratio of the plot.

R

#Load required packages
library(ggplot2)
library(ggpattern)
# Check if the magick package is installed, if not install it
if (require("magick")) {

  # Create a sample data frame
  df <- data.frame(
    trt = factor(c(1, 1, 2, 2)),
    resp = c(1, 5, 3, 4),
    group = factor(c(1, 2, 1, 2)),
    upper = c(1.1, 5.3, 3.3, 4.2),
    lower = c(0.8, 4.6, 2.4, 3.6)
  )

  # Plot the data using ggplot2
  p <- ggplot(df, aes(trt, resp)) +
    # Add the geom_crossbar_pattern layer using the ggpattern package
    geom_crossbar_pattern(
      aes(
        ymin          = lower,
        ymax          = upper,
        pattern_fill  = interaction(trt, group),
      ),
      pattern = 'plasma',
      width   = 0.2,
    ) +
    # Add a black and white theme to the plot
    theme_bw(18) +
    # Add plot labels
    labs(
      title = "ggpattern::geom_crossbar_pattern()",
      subtitle = "pattern = 'plasma'"
    ) +
    # Adjust the size of the legend key
    theme(legend.key.size = unit(1.5, 'cm')) +
    # Fix the aspect ratio of the plot
    coord_fixed(ratio = 1/3)

  # Display the plot
  p

}

Output:

geom_rect_pattern() Function in R

geom_rect_pattern() is a function in the R package ggplot2, which is used to create a rectangular pattern plot. It creates a grid of rectangles with colors or patterns to display the data. This function takes several arguments, including:

• mapping: a named list that maps variables in the data to visual properties of the plot.
• data: the data to be plotted.
• stat: a string indicating the statistical transformation to be applied to the data before plotting
• position: a string indicating the position adjustment to be applied to the layers
• width: the width of the rectangles
• height: the height of the rectangles
• hjust: the horizontal justification of the rectangles
• vjust: the vertical justification of the rectangles
• angle: the angle of the rectangles
• fill: the fill color of the rectangles
• color: the color of the rectangles
  The geom_rect_pattern() function can be used to create a variety of different plot types, such as heatmaps, mosaic plots, and trellis plots.

Example

The code starts by loading the ggplot2 and ggpattern libraries and then checking if the magick library is installed and loaded. Next, a data frame called plot_df is created, which contains the data to be plotted. The data frame has columns for the minimum and maximum values of the x and y axis, the type, the color, the orientation, and other properties of the rectangles to be plotted. After creating the data frame, a ggplot object is created and the geom_rect_pattern function from the ggpattern library is used to add rectangles to the plot. In this function, the aes argument is used to specify the x and y minimum and maximum values for each rectangle and the color, second color, and orientation of the pattern. The plot is then customized using theme_bw to set a black and white theme, labs to add a title and subtitle, and theme to increase the size of the legend key. Finally, the plot is displayed using the p object. Overall, this code creates a plot of rectangles with gradient patterns, and the rectangles are specified using the data in the plot_df data frame.

R

# Load the ggplot2 and ggpattern libraries
library(ggplot2)
library(ggpattern)

# Check if the magick library is installed and loaded
if (require("magick")) {

  # Create a data frame with the values to be plotted
  plot_df <- data.frame(
    xmin    = c(0, 10, 3),
    xmax    = c(8, 18, 4),
    ymin    = c(0, 10, 8),
    ymax    = c(5, 19, 15),
    type    = c('a', 'b', 'c'),
    colour1 = c('red', 'black', 'blue'),
    colour2 = c('black', NA, 'yellow'),
    orient  = c('horizontal', 'radial', 'vertical'),
    stringsAsFactors = FALSE
  )

  # Create a ggplot object and add the rectangles using the geom_rect_pattern function
  p <- ggplot(plot_df) +
    geom_rect_pattern(
      aes(
        xmin=xmin, ymin=ymin, xmax=xmax, ymax=ymax,
        # Specify the fill color using the pattern_fill argument
        pattern_fill  = I(colour1),
        # Specify the second fill color using the pattern_fill2 argument
        pattern_fill2 = I(colour2),
        # Specify the orientation of the pattern using the pattern_orientation argument
        pattern_orientation = I(orient)
      ),
      # Specify the pattern type using the pattern argument
      pattern         = 'gradient',
      # Specify the border color using the color argument
      colour          = 'black',
      # Specify the density of the pattern using the pattern_density argument
      pattern_density = 0.3,
      # Remove the solid fill color
      fill = NA
    ) +
    # Set the theme to a black and white theme
    theme_bw(18) +
    # Add a title and subtitle to the plot
    labs(
      title = "ggpattern::geom_rect_pattern()",
      subtitle = "pattern = 'gradient'"
    ) +
    # Increase the size of the legend key
    theme(legend.key.size = unit(1.5, 'cm'))

  # Display the plot
  p
}

Output: