28.4. 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

28.4.1. Eingaben

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

28.4.2. Ausgaben

Genau wie die Eingaben müssen alle Ausgaben am Beginn des Skriptes definiert werden:

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.

28.4.3. Syntax Summary for QGIS R scripts

A number of input and output parameter types are offered.

28.4.3.1. Input parameter types

Parameter	Syntax Beispiel	Rückgabeobjekte
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	Datenrahmenumwandlung von csv, voreingestelltes Objekt der `read.csv` Funktion
field	Field = Field Layer	Name des ausgewählten Feldes, z.B. `"Area"`
raster	Layer = raster	RasterBrick Objekt, voreingestelltes Objekt des `raster` Pakets
multiple raster	Layer = multiple raster	RasterBrick Objekt, voreingestelltes Objekt des `raster` Pakets
number	N = number	gewählte Ganzzahl oder Fließkommazahl
string	S = string	in der Box eingefügte Zeichenkette
longstring	LS = longstring	in der Box eingefügte Zeichenkette, kann länger als eine normale Zeichenkette sein
selection	S = selection first;second;third	Zeichenkette des im dropdown-Menü gewählten Objektes
crs	C = crs	Zeichenkette des sich ergebenen KBS im Format: `"EPSG:4326"`
extent	E = extent	Ausdehnungsobjekt des `raster` Pakets, man kann Werte als E@xmin` extrahieren
point	P = point	beim Klicken auf die Karte erhält man die Koordinaten des Punktes
file	F = file	Pfad der gewählten Datei, z.B. „/home/matteo/file.txt“
folder	F = folder	Pfad des gewählten Ordners, z.B „/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

28.4.3.2. Output parameter types

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

Bemerkung

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

28.4.3.3. Skript Hauptteil

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)

28.4.4. Beispiele

28.4.4.1. Beispiel mit Vektorausgabe

Sehen wir uns einen Algorithmus aus der Onlinesammlung an, der zufällige Punkte innerhalb der Ausdehnung eines Eingabelayers erstellt:

##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):

Point pattern analysis ist die Gruppe des Algorithmus
Layer ist der Eingabevektorlayer
Size is a numerical parameter with a default value of 10
Output ist der Vektorlayer der vom Algorithmus erstellt wird
library(sp) loads the sp library
spatpoly = as(Layer, "Spatial") translate to an sp object
Call the spsample function of the sp library and run it using the input defined above (Layer and Size)
Create a SpatialPointsDataFrame object using the SpatialPointsDataFrame function
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.

28.4.4.2. Beispiel mit Rasterausgabe

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.

28.4.4.3. Beispiel mit Tabellenausgabe

Lassen Sie uns den Algorithmus Summary Statistics bearbeiten, so dass als Ausgabe eine Tabelle (csv) erzeugt wird.

Der Hauptteil des Skriptes sieht wie folgt aus:

##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

Die dritte Zeile gibt als Eingabe Vector Field vor. In der vierten Zeile wird die Ausgabe des Algorithmus als Tabelle festgelegt.

In der letzten Zeile wird das im Skript erstellte Objekt Stat in eine csv Tabelle umgewandelt.

28.4.4.4. Beispiel mit Konsolenausgabe

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:

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

28.4.4.5. Beispiel mit 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.