FormizeR

R package for "Introduction to Programming with R". It easily lets you create visual overviews for point intensities with different shapes.

Installation

For installing the FormizeR package, install the newest of the devtools or remotes package and Rcpp >= 1.0.10. Then go ahead with

devtools/remotes::install_github("KonstiDE/FormizeR", dependencies = T)
library(FormizeR)

library(ggplot2)
library(raster)
library(sf)
library(rayshader)
library(rgl)
library(spatialrisk)

Exemplary Usage

Using the FormizeR plugin is easy, as FormizeR directly provides you with exemplary data to test its potential and get familiar with the styling options. Mandatory are a point layer and a shape layer (both provided inside the package) and the cellsize, determining the size of the form. The standard method with minimal parameters goes as follows:

plot_intensity_standard(
    ger_points,              #provided by FormizeR
    ger_admin,               #provided by FormizeR
    cellsize = 0.3           #size of the form
)

This will plot the bakery-intensity of germany in hexagons, with a default color scale of white to blue. However, to style your plot, FormizeR provides you with a lot of parameters. Mandatory parameters are bold and cursive, not mandatory ones with their default values are bold only:

point_layer sf object: An sf object containing points.
shape_layer sf object: An sf object consisting of a polygon.
cellsize numeric: Size of the hexagons / rectangles.
net logical=TRUE
net.border logical=TRUE
net.border.color character='black'
net.border.width numeric=1
plot logical=TRUE
plot.color vector of characters=c("white", "blue")
plot.scalename character=''
plot.theme ggplot2-theme=theme_bw()
plot.3d logical=FALSE
plot.3d.scale numeric=100
plot.3d.sunangle numeric=360
plot.3d.shadow_intensity numeric=0.75

Anyhow, one thinks that the parameters are not sufficient to create the plot you are aiming for, you simply set plot=FALSE and save the dataframe returned by the plot_intensity_[...] method and plot it yourself via the famous ggplot package. The resulting dataframe consists of a geometry and intensity column containing the polygons and sums of the points for each form respectively. The following snippet shows an example of how to plot the FormizeR result with a custom plot:

df <- plot_intensity_standard(
    ger_points,
    ger_admin,
    cellsize = 0.4,
    plot=FALSE
)

ggplot(data = df$geometry, aes(fill=df$intensity)) + 
    geom_sf(color=NA) + 
    scale_fill_gradientn(colours = c("purple", "orange", "red"))

If you choose to keep many settings provided by us, but still want to plot extra layers, you can just save an abitrary plot_intesity method with also with plot=TRUE and append upon it, like shown below:

p <- plot_intensity_rectengular_fishernet(
  ger_points,
  ger_admin,
  cellsize = 0.7,
  net.border = FALSE,
  plot.colors = c("#ffffd9", "#edf8b1", "#c7e9b4", "#7fcdbb", "#41b6c4", "#1d91c0", "#225ea8", "#0c2c84"),
  plot.theme = theme_dark()
)

p + 
  geom_sf(data = AnotherFancyDataFrame)

A list of all methods can be found below as FormizeR provides:

plot_intensity_standard(...)
plot_intensity_fishernet(...)
plot_intensity_triangular_left(...)
plot_intensity_triangular_right(...)
plot_intensity_rectengular_fishernet(...)
plot_intensity_trakistile(...)
plot_intensity_rhombus(...)
plot_intensity_diamond(...)
plot_intensity_bubbles(...)

______________________________	______________________________	______________________________	______________________________	______________________________	______________________________	______________________________	______________________________	______________________________	______________________________

3D Plots

Creating a 3d plot of your intensity map with FormizeR is easy. Just set the plot and plot.3d both to TRUE. This will result in a rgl window. Position it the way you like it and call rgl.snapshot("snapshot.png") to save you beautiful 3d plot. We depict a minimal example for a 3d plot made with FormizeR in the following snippet:

plot_intensity_standard(
  ger_points,
  ger_admin,
  cellsize = 0.5,
  net.border = FALSE,
  plot.color = c("purple", "orange", "red"),
  plot.3d=TRUE,
)
rgl.snapshot("snapshot.png")

The output then can look somewhat like the following images:

..._standard(plot3d=TRUE)	...fishernet(plot3d=TRUE)

Roadmap

• More geometries and forms
• Basemap integration
• Full ggplot parameter passthrough
• Error handling messages providance