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pair: R; Syntax

Appendix D: QGIS R script syntax

Contributed by Matteo Ghetta - funded by Scuola Superiore Sant'Anna

Writing R scripts in Processing is a bit tricky because of the special syntax.

A Processing R script starts with defining its Inputs and Outputs, each preceded with double hash characters (##).

Before the inputs, the group to place the algoritm in can be specified. If the group already exists, the algorithm will be added to it, if not, the group will be created. In the example below, the name of the group is My group:

##My Group=group

Inputs

All input data and parameters have to be specified. There are several types of inputs:

  • vector: ##Layer = vector
  • vector field: ##F = Field Layer (where Layer is the name of an input vector layer the field belongs to)
  • raster: ##r = raster
  • table: ##t = table
  • number: ##Num = number
  • string: ##Str = string
  • boolean: ##Bol = boolean
  • elements in a dropdown menu. The items must be separated with semicolons ;: ##type=selection point;lines;point+lines

Outputs

As for the inputs, each output has to be defined at the beginning of the script:

  • vector: ##output= output vector
  • raster: ##output= output raster
  • table: ##output= output table
  • plots: ##output_plots_to_html (##showplots in earlier versions)
  • To show R output in the Result Viewer, put > in front of the command whose output you would like to show.

pair: R; Syntax summary

Syntax Summary for QGIS R scripts

A number of input and output parameter types are offered.

Input parameter types

Parameter Syntax example Returning objects
vector Layer = vector sf object (or SpatialDataFrame object, if ##load_vector_using_rgdal is specified)
vector point Layer = vector point sf object (or SpatialDataFrame object, if ##load_vector_using_rgdal is specified)
vector line Layer = vector line sf object (or SpatialDataFrame object, if ##load_vector_using_rgdal is specified)
vector polygon Layer = vector polygon sf object (or SpatialPolygonsDataFrame object, if ##load_vector_using_rgdal is used)
multiple vector Layer = multiple vector sf object (or SpatialDataFrame objects if ##load_vector_using_rgdal is specified)
table Layer = table dataframe conversion from csv, default object of read.csv function
field Field = Field Layer name of the Field selected, e.g. "Area"
raster Layer = raster RasterBrick object, default object of raster package
multiple raster Layer = multiple raster RasterBrick objects, default object of raster package
number N = number integer or floating number chosen
string S = string string added in the box
longstring LS = longstring string added in the box, could be longer then the normal string
selection S = selection first;second;third string of the selected item chosen in the dropdown menu
crs C = crs string of the resulting CRS chosen, in the format: "EPSG:4326"
extent E = extent Extent object of the raster package, you can extract values as E@xmin
point P = point when clicked on the map, you have the coordinates of the point
file F = file path of the file chosen, e.g. "/home/matteo/file.txt"
folder F = folder path of the folder chosen, e.g. "/home/matteo/Downloads"

A parameter can be OPTIONAL, meaning that it can be ignored.

In order to set an input as optional, you add the string optional before the input, e.g:

##Layer = vector
##Field1 = Field Layer
##Field2 = optional Field Layer

Output parameter types

Parameter Syntax example
vector Output = output vector
raster Output = output raster
table Output = output table
file Output = output file

Note

You can save plots as png from the Processing Result Viewer, or you can choose to save the plot directly from the algorithm interface.

Script body

The script body follows R syntax and the Log panel can help you if there is something wrong with your script.

Remember that you have to load all additional libraries in the script:

library(sp)

pair: R scripts; Examples

Examples

Example with vector output

Let's take an algorithm from the online collection that creates random points from the extent of an input layer:

##Point pattern analysis=group
##Layer=vector polygon
##Size=number 10
##Output=output vector
library(sp)
spatpoly = as(Layer, "Spatial")
pts=spsample(spatpoly,Size,type="random")
spdf=SpatialPointsDataFrame(pts, as.data.frame(pts))
Output=st_as_sf(spdf)

Explanation (per line in the script):

  1. Point pattern analysis is the group of the algorithm
  2. Layer is the input vector layer
  3. Size is a numerical parameter with a default value of 10
  4. Output is the vector layer that will be created by the algorithm
  5. library(sp) loads the sp library
  6. spatpoly = as(Layer, "Spatial") translate to an sp object
  7. Call the spsample function of the sp library and run it using the input defined above (Layer and Size)
  8. Create a SpatialPointsDataFrame object using the SpatialPointsDataFrame function
  9. Create the output vector layer using the st_as_sf function

That's it! Just run the algorithm with a vector layer you have in the QGIS Legend, choose the number of random point. The resulting layer will be added to your map.

Example with raster output

The following script will perform basic ordinary kriging to create a raster map of interpolated values from a specified field of the input point vector layer by using the autoKrige function of the automap R package. It will first calculate the kriging model and then create a raster. The raster is created with the raster function of the raster R package:

##Basic statistics=group
##Layer=vector point
##Field=Field Layer
##Output=output raster
##load_vector_using_rgdal
require("automap")
require("sp")
require("raster")
table=as.data.frame(Layer)
coordinates(table)= ~coords.x1+coords.x2
c = Layer[[Field]]
kriging_result = autoKrige(c~1, table)
prediction = raster(kriging_result$krige_output)
Output<-prediction

By using ##load_vector_using_rgdal, the input vector layer will be made available as a SpatialDataFrame objects, so we avoid having to translate it from an sf object.

Example with table output

Let's edit the Summary Statistics algorithm so that the output is a table file (csv).

The script body is the following:

##Basic statistics=group
##Layer=vector
##Field=Field Layer
##Stat=Output table
Summary_statistics<-data.frame(rbind(
    sum(Layer[[Field]]),
    length(Layer[[Field]]),
    length(unique(Layer[[Field]])),
    min(Layer[[Field]]),
    max(Layer[[Field]]),
    max(Layer[[Field]])-min(Layer[[Field]]),
    mean(Layer[[Field]]),
    median(Layer[[Field]]),
    sd(Layer[[Field]])),
  row.names=c("Sum:","Count:","Unique values:","Minimum value:","Maximum value:","Range:","Mean value:","Median value:","Standard deviation:"))
colnames(Summary_statistics)<-c(Field)
Stat<-Summary_statistics

The third line specifies the Vector Field in input and the fourth line tells the algorithm that the output should be a table.

The last line will take the Stat object created in the script and convert it into a csv table.

Example with console output

We can use the previous example and instead of creating a table, print the result in the Result Viewer:

##Basic statistics=group
##Layer=vector
##Field=Field Layer
Summary_statistics<-data.frame(rbind(
sum(Layer[[Field]]),
length(Layer[[Field]]),
length(unique(Layer[[Field]])),
min(Layer[[Field]]),
max(Layer[[Field]]),
max(Layer[[Field]])-min(Layer[[Field]]),
mean(Layer[[Field]]),
median(Layer[[Field]]),
sd(Layer[[Field]])),row.names=c("Sum:","Count:","Unique values:","Minimum value:","Maximum value:","Range:","Mean value:","Median value:","Standard deviation:"))
colnames(Summary_statistics)<-c(Field)
>Summary_statistics

The script is exactly the same as the one above except for two edits:

  1. no output specified (the fourth line has been removed)
  2. the last line begins with >, telling Processing to make the object available through the result viewer

Example with plot

To create plots, you have to use the ##output_plots_to_html parameter as in the following script:

##Basic statistics=group
##Layer=vector
##Field=Field Layer
##output_plots_to_html
####output_plots_to_html
qqnorm(Layer[[Field]])
qqline(Layer[[Field]])

The script uses a field (Field) of a vector layer (Layer) as input, and creates a QQ Plot (to test the normality of the distribution).

The plot is automatically added to the Processing Result Viewer.