Configurarea Aplicațiilor Externe¶
The processing framework can be extended using additional applications. Algorithms that rely on external applications are managed by their own algorithm providers. Additional providers can be found as separate plugins, and installed using the QGIS Plugin Manager.
This section will show you how to configure the Processing framework to include these additional applications, and it will explain some particular features of the algorithms based on them. Once you have correctly configured the system, you will be able to execute external algorithms from any component like the toolbox or the graphical modeler, just like you do with any other algorithm.
By default, algorithms that rely on an external application not shipped with QGIS are not enabled. You can enable them in the Processing settings dialog if they are installed on your system.
If you are not an advanced user and you are running QGIS on Windows, you might not be interested in reading the rest of this chapter. Make sure you install QGIS in your system using the standalone installer. That will automatically install SAGA and GRASS in your system and configure them so they can be run from QGIS. All the algorithms from these providers will be ready to be run without needing any further configuration. If installing with the OSGeo4W application, make sure that you also select SAGA and GRASS for installation.
When using external software, opening a file in QGIS does not mean that it can be opened and processed in that other software. In most cases, other software can read what you have opened in QGIS, but in some cases, that might not be true. When using databases or uncommon file formats, whether for raster or vector layers, problems might arise. If that happens, try to use well-known file formats that you are sure are understood by both programs, and check the console output (in the log panel) to find out what is going wrong.
You might for instance get trouble and not be able to complete your work if you call an external algorithm with a GRASS raster layers as input. For this reason, such layers will not appear as available to algorithms.
You should, however, not have problems with vector layers, since QGIS automatically converts from the original file format to one accepted by the external application before passing the layer to it. This adds extra processing time, which might be significant for large layers, so do not be surprised if it takes more time to process a layer from a DB connection than a layer from a Shapefile format dataset of similar size.
Providers not using external applications can process any layer that you can open in QGIS, since they open it for analysis through QGIS.
All raster and vector output formats produced by QGIS can be used as input layers. Some providers do not support certain formats, but all can export to common formats that can later be transformed by QGIS automatically. As for input layers, if a conversion is needed, that might increase the processing time.
External applications may also be made aware of the selections that exist in vector layers within QGIS. However, that requires rewriting all input vector layers, just as if they were originally in a format not supported by the external application. Only when no selection exists, or the Use only selected features option is not enabled in the processing general configuration, can a layer be directly passed to an external application.
In other cases, exporting only selected features is needed, which causes longer execution times.
SAGA algorithms can be run from QGIS if SAGA included in the QGIS installation.
If you are running Windows, both the stand-alone installer and the OSGeo4W installer include SAGA.
Most SAGA algorithms that require several input raster layers require them to have the same grid system. That is, they must cover the same geographic area and have the same cell size, so their corresponding grids match. When calling SAGA algorithms from QGIS, you can use any layer, regardless of its cell size and extent. When multiple raster layers are used as input for a SAGA algorithm, QGIS resamples them to a common grid system and then passes them to SAGA (unless the SAGA algorithm can operate with layers from different grid systems).
Definirea acestui sistem grilă comun este controlată de către utilizator, acest lucru putând făcut din zona grupului SAGA al ferestrei de setare. Există două modalități de stabilire a sistemului grilă țintă:
Setare manuală. Puteți defini extinderea, prin stabilirea valorilor următorilor parametri:
Reeșantionare min X
Reeșantionare max X
Reeșantionare min Y
Reeșantionare max Y
Reeșantionare dimensiune celulă
Rețineți că aplicația QGIS va reeșantiona straturile de intrare la această extindere, chiar dacă acestea nu se suprapun cu ea.
Setare automată din straturile de intrare. Pentru a selecta această opțiune, doar să verificați opțiunea Use min covering grid system for resampling. Toate celelalte setări vor fi ignorate, iar extinderea minimă care acoperă toate straturile de intrare va fi utilizată. Dimensiunea celulei din stratul țintă reprezintă maximul dimensiunilor tuturor celulelor din straturile de intrare.
For algorithms that do not use multiple raster layers, or for those that do not need a unique input grid system, no resampling is performed before calling SAGA, and those parameters are not used.
Unlike QGIS, SAGA has no support for multi-band layers. If you want to use a multiband layer (such as an RGB or multispectral image), you first have to split it into single-banded images. To do so, you can use the «SAGA/Grid - Tools/Split RGB image» algorithm (which creates three images from an RGB image) or the «SAGA/Grid - Tools/Extract band» algorithm (to extract a single band).
SAGA assumes that raster layers have the same cell size in the X and Y axis. If you are working with a layer with different values for horizontal and vertical cell size, you might get unexpected results. In this case, a warning will be added to the processing log, indicating that an input layer might not be suitable to be processed by SAGA.
When QGIS calls SAGA, it does so using its command-line interface, thus passing a set of commands to perform all the required operations. SAGA shows its progress by writing information to the console, which includes the percentage of processing already done, along with additional content. This output is filtered and used to update the progress bar while the algorithm is running.
Both the commands sent by QGIS and the additional information printed by SAGA can be logged along with other processing log messages, and you might find them useful to track what is going on when QGIS runs a SAGA algorithm. You will find two settings, namely Log console output and Log execution commands, to activate that logging mechanism.
Most other providers that use external applications and call them through the command-line have similar options, so you will find them as well in other places in the processing settings list.
To enable R in Processing you need to install the Processing R Provider plugin and configure R for QGIS.
Configuration is done in Processing tab of .in the
Depending on your operating system, you may have to use R folder to specify where your R binaries are located.
On Windows the R executable file is normally in
a folder (
Specify the folder and NOT the binary!
On Linux you just have to make sure that the R folder is
in the PATH environment variable.
R in a terminal window starts R, then you are ready to go.
After installing the Processing R Provider plugin, you will find some example scripts in the Processing Toolbox:
Scatterplot runs an R function that produces a scatter plot from two numerical fields of the provided vector layer.
test_sf does some operations that depend on the
sfpackage and can be used to check if the R package
sfis installed. If the package is not installed, R will try to install it (and all the packages it depends on) for you, using the Package repository specified in in the Processing options. The default is http://cran.at.r-project.org/. Installing may take some time…
test_sp can be used to check if the R package
spis installed. If the package is not installed, R will try to install it for you.
If you have R configured correctly for QGIS, you should be able to run these scripts.
R integration in QGIS is different from that of SAGA in that there is not a predefined set of algorithms you can run (except for some example script that come with the Processing R Provider plugin).
A set of example R scripts is available in the QGIS Repository. Perform the following steps to load and enable them using the QGIS Resource Sharing plugin.
Add the QGIS Resource Sharing plugin (you may have to enable Show also experimental plugins in the Plugin Manager Settings)
Open it (Plugins-> Resource Sharing-> Resource Sharing)
Choose the Settings tab
Click Reload repositories
Choose the All tab
Select QGIS R script collection in the list and click on the Install button
The collection should now be listed in the Installed tab
Close the plugin
Open the Processing Toolbox, and if everything is OK, the example scripts will be present under R, in various groups (only some of the groups are expanded in the screenshot below).
The scripts at the top are the example scripts from the Processing R Provider plugin.
If, for some reason, the scripts are not available in the Processing Toolbox, you can try to:
Open the Processing settings (tab)
On Ubuntu, set the path to (or, better, include in the path):
On Windows, set the path to (or, better, include in the path):
To edit, double-click. You can then choose to just paste / type the path, or you can navigate to the directory by using the … button and press the Add button in the dialog that opens. It is possible to provide several directories here. They will be separated by a semicolon („;”).
If you would like to get all the R scrips from the QGIS 2 on-line collection, you can select QGIS R script collection (from QGIS 2) instead of QGIS R script collection. You will find probably find that scripts that depend on vector data input or output will not work.
You can write scripts and call R commands, as you would do from R. This section shows you the syntax for using R commands in QGIS, and how to use QGIS objects (layers, tables) in them.
To add an algorithm that calls an R function (or a more complex R script that you have developed and you would like to have available from QGIS), you have to create a script file that performs the R commands.
R script files have the extension
.rsx, and creating them is
pretty easy if you just have a basic knowledge of R syntax and R
They should be stored in the R scripts folder.
You can specify the folder (R scripts folder) in the
R settings group in Processing settings dialog).
Let’s have a look at a very simple script file, which calls the R
spsample to create a random grid within the boundary of the
polygons in a given polygon layer.
This method belongs to the
Since almost all the algorithms that you might like to incorporate
into QGIS will use or generate spatial data, knowledge of spatial
sf, is very useful.
##Random points within layer extent=name ##Point pattern analysis=group ##Vector_layer=vector ##Number_of_points=number 10 ##Output=output vector library(sp) spatpoly = as(Vector_layer, "Spatial") pts=spsample(spatpoly,Number_of_points,type="random") spdf=SpatialPointsDataFrame(pts, as.data.frame(pts)) Output=st_as_sf(spdf)
The first lines, which start with a double Python comment sign
##), define the display name and group of the script, and
tell QGIS about its inputs and outputs.
When you declare an input parameter, QGIS uses that information for two things: creating the user interface to ask the user for the value of that parameter, and creating a corresponding R variable that can be used as R function input.
In the above example, we have declared an input of type
When executing the algorithm, QGIS will open the layer selected
by the user and store it in a variable named
So, the name of a parameter is the name of the variable that you
use in R for accessing the value of that parameter (you should
therefore avoid using reserved R words as parameter names).
Spatial parameters such as vector and raster layers are read using
commands (you do not have to worry about adding those commands to
your description file – QGIS will do it), and they are stored as
Table fields are stored as strings containing the name of the selected field.
Vector files can be read using the
readOGR() command instead
st_read() by specifying
This will produce a
Spatial*DataFrame object instead of an
Raster files can be read using the
readGDAL() command instead
brick() by specifying
If you are an advanced user and do not want QGIS to create the
object for the layer, you can use
##pass_filenames to indicate
that you prefer a string with the filename.
In this case, it is up to you to open the file before performing
any operation on the data it contains.
With the above information, it is possible to understand the first lines of the R script (the first line not starting with a Python comment character).
library(sp) spatpoly = as(Vector_layer, "Spatial") pts=spsample(polyg,numpoints,type="random")
spsample function is provided by the sp library, so
the first thing we do is to load that library.
Vector_layer contains an
Since we are going to use a function (
spsample) from the sp
library, we must convert the
sf object to a
SpatialPolygonsDataFrame object using the
Then we calling the
spsample function, with this object and
numpoints input parameter (which specifies the number of
points to generate).
Since we have declared a vector output named
Output, we have to
create a variable named
Output containing an
We do this in two steps.
First we create a
SpatialPolygonsDataFrame object from the
result of the function, using the SpatialPointsDataFrame function,
and then we convert that object to an
sf object using the
st_as_sf function (of the sf library).
You can use whatever names you like for your intermediate
Just make sure that the variable storing your final result has
the defined name (in this case
Output), and that it contains
a suitable value (an
sf object for vector layer output).
In this case, the result obtained from the
spsample method had
to be converted explicitly into an
sf object via a
SpatialPointsDataFrame object, since it is itself an object of
ppp, which can not be returned to QGIS.
If your algorithm generates raster layers, the way they are saved
will depend on whether or not you have used the
If you have used it, layers are saved using the
If not, the
writeRaster() method from the
will be used.
If you have used the
##pass_filenames option, outputs are
generated using the
raster package (with
If your algorithm does not generate a layer, but a text result in
the console instead, you have to indicate that you want the
console to be shown once the execution is finished.
To do so, just start the command lines that produce the results
you want to print with the
> («greater than») sign.
Only output from lines prefixed with
> are shown.
For instance, here is the description file of an algorithm that
performs a normality test on a given field (column) of the
attributes of a vector layer:
##layer=vector ##field=field layer ##nortest=group library(nortest) >lillie.test(layer[[field]])
The output of the last line is printed, but the output of the first is not (and neither are the outputs from other command lines added automatically by QGIS).
If your algorithm creates any kind of graphics (using the
method), add the following line (
output_plots_to_html used to be
This will cause QGIS to redirect all R graphical outputs to a temporary file, which will be opened once R execution has finished.
Both graphics and console results will be available through the processing results manager.
For more information, please check the R scripts in the official QGIS collection (you download and install them using the QGIS Resource Sharing plugin, as explained elsewhere). Most of them are rather simple and will greatly help you understand how to create your own scripts.
raster libraries are loaded by default,
so you do not have to add the corresponding
However, other additional libraries that you might need have to be
explicitly loaded by typing:
library(ggplot2) (to load the
If the package is not already installed on your machine, Processing
will try to download and install it.
In this way the package will also become available in R Standalone.
Be aware that if the package has to be downloaded, the script
may take a long time to run the first time.
The R script
sp_test tries to load the R packages
The R script sf_test tries to load
If these two packages are not installed, R may try to load and install
them (and all the libraries that they depend on).
The following R libraries end up in
sf_test has been run from the Processing Toolbox on Ubuntu with
version 2.0 of the Processing R Provider plugin and a fresh install of
R 3.4.4 (apt package
abind, askpass, assertthat, backports, base64enc, BH, bit, bit64,
blob, brew, callr, classInt, cli, colorspace, covr, crayon, crosstalk,
curl, DBI, deldir, desc, dichromat, digest, dplyr, e1071, ellipsis,
evaluate, fansi, farver, fastmap, gdtools, ggplot2, glue, goftest,
gridExtra, gtable, highr, hms, htmltools, htmlwidgets, httpuv, httr,
jsonlite, knitr, labeling, later, lazyeval, leafem, leaflet,
leaflet.providers, leafpop, leafsync, lifecycle, lwgeom, magrittr, maps,
mapview, markdown, memoise, microbenchmark, mime, munsell, odbc, openssl,
pillar, pkgbuild, pkgconfig, pkgload, plogr, plyr, png, polyclip, praise,
prettyunits, processx, promises, ps, purrr, R6, raster, RColorBrewer,
Rcpp, reshape2, rex, rgeos, rlang, rmarkdown, RPostgres, RPostgreSQL,
rprojroot, RSQLite, rstudioapi, satellite, scales, sf, shiny,
sourcetools, sp, spatstat, spatstat.data, spatstat.utils, stars, stringi,
stringr, svglite, sys, systemfonts, tensor, testthat, tibble, tidyselect,
tinytex, units, utf8, uuid, vctrs, viridis, viridisLite, webshot, withr,
xfun, XML, xtable
Configuring GRASS is not much different from configuring SAGA. First, the path to the GRASS folder has to be defined, but only if you are running Windows.
By default, the Processing framework tries to configure its GRASS connector to use the GRASS distribution that ships along with QGIS. This should work without problems for most systems, but if you experience problems, you might have to configure the GRASS connector manually. Also, if you want to use a different GRASS installation, you can change the setting to point to the folder where the other version is installed. GRASS 7 is needed for algorithms to work correctly.
If you are running Linux, you just have to make sure that GRASS is correctly installed, and that it can be run without problem from a terminal window.
GRASS algorithms use a region for calculations. This region can be defined manually using values similar to the ones found in the SAGA configuration, or automatically, taking the minimum extent that covers all the input layers used to execute the algorithm each time. If the latter approach is the behavior you prefer, just check the Use min covering region option in the GRASS configuration parameters.
To use LAStools in QGIS, you need to download and install LAStools on your computer and install the LAStools plugin (available from the official repository) in QGIS.
On Linux platforms, you will need Wine to be able to run some of the tools.
LAStools is activated and configured in the Processing options
), where you can specify the
location of LAStools (LAStools folder) and Wine
On Ubuntu, the default Wine folder is