23.5. The graphical modeler
The graphical modeler allows you to create complex models using a simple and easy-to-use interface. When working with a GIS, most analysis operations are not isolated, rather part of a chain of operations. Using the graphical modeler, that chain of operations can be wrapped into a single process, making it convenient to execute later with a different set of inputs. No matter how many steps and different algorithms it involves, a model is executed as a single algorithm, saving time and effort.
The graphical modeler can be opened from the Processing menu ().
The modeler has a working canvas where the structure of the model and the workflow it represents are shown. The left part of the window is a section with five panels that can be used to add new elements to the model:
Model Properties: you can specify the name of the model and the group that will contain it
Inputs: all the inputs that will shape your model
Algorithms: the Processing algorithms available
Variables: you can also define variables that will only be available in the Processing Modeler
Undo History: this panel will register everything that happens in the modeler, making it easy to cancel things you did wrong.
Creating a model involves two basic steps:
Definition of necessary inputs. These inputs will be added to the parameters window, so the user can set their values when executing the model. The model itself is an algorithm, so the parameters window is generated automatically as for all algorithms available in the Processing framework.
Definition of the workflow. Using the input data of the model, the workflow is defined by adding algorithms and selecting how they use the defined inputs or the outputs generated by other algorithms in the model.
The first step is to define the inputs for the model. The following elements are found in the Inputs panel on the left side of the modeler window:
Булев - Boolean
Print Layout Item
TIN Creation Layers
Vector Tile Writer Layers
Hovering with the mouse over the inputs will show a tooltip with additional information.
When double-clicking on an element, a dialog is shown that lets you define its characteristics. Depending on the parameter, the dialog will contain at least one element (the description, which is what the user will see when executing the model). For example, when adding a numerical value, as can be seen in the next figure, in addition to the description of the parameter, you have to set a default value and the range of valid values.
You can define your input as mandatory for your model by checking the
Mandatory option and by checking the
checkbox you can set the input to be within the
Advanced section. This is
particularly useful when the model has many parameters and some of them are not
trivial, but you still want to choose them.
Comments tab allows you to tag the input with more information,
to better describe
the parameter. Comments are visible only in the modeler canvas and not in the
final algorithm dialog.
For each added input, a new element is added to the modeler canvas.
You can also add inputs by dragging the input type from the list and dropping it at the position where you want it in the modeler canvas. If you want to change a parameter of an existing input, just double click on it, and the same dialog will pop up.
In the following example we will add two inputs and two algorithms. The aim of
the model is to copy the elevation values from a DEM raster layer to a line layer
Drape algorithm, and then calculate the total ascent of the line
layer using the
Climb Along Line algorithm.
In the Inputs tab, choose the two inputs as
Vector Layer for the line and
Raster Layer for the DEM.
We are now ready to add the algorithms to the workflow.
Algorithms can be found in the Algorithms panel, grouped much in the same way as they are in the Processing toolbox.
To add an algorithm to a model, double-click on its name or drag and
drop it, just like for inputs. As for the inputs you can change the description
of the algorithm and add a comment.
When adding an algorithm, an execution dialog will appear, with a content similar
to the one found in the execution panel that is shown when executing the
algorithm from the toolbox.
The following picture shows both the
Drape (set Z value from raster) and the
Climb along line algorithm dialogs.
As you can see there are some differences.
You have four choices to define the algorithm inputs:
Pre-calculated Value: with this option you can open the Expression Builder and define your own expression to fill the parameter. Model inputs together with some other layer statistics are available as variables and are listed at the top of the Search dialog of the Expression Builder
If a layer generated by the algorithm is only to be used as input to another algorithm, don’t edit that text box.
In the following picture you can see the two input parameters defined as
Model Input and the temporary output layer:
In all cases, you will find an additional parameter named Dependencies that is not available when calling the algorithm from the toolbox. This parameter allows you to define the order in which algorithms are executed, by explicitly defining one algorithm as a parent of the current one. This will force the parent algorithm to be executed before the current one.
When you use the output of a previous algorithm as the input of your algorithm, that implicitly sets the previous algorithm as parent of the current one (and places the corresponding arrow in the modeler canvas). However, in some cases an algorithm might depend on another one even if it does not use any output object from it (for instance, an algorithm that executes a SQL sentence on a PostGIS database and another one that imports a layer into that same database). In that case, just select the previous algorithm in the Dependencies parameter and they will be executed in the correct order.
Once all the parameters have been assigned valid values, click on OK and the algorithm will be added to the canvas. It will be linked to the elements in the canvas (algorithms or inputs) that provide objects that are used as inputs for the algorithm.
Elements can be dragged to a different position on the canvas. This is useful to make the structure of the model more clear and intuitive. You can also resize elements. This is particularly useful if the description of the input or algorithm is long.
Links between elements are updated automatically and you can see a plus button at the top and at the bottom of each algorithm. Clicking the button will list all the inputs and outputs of the algorithm so you can have a quick overview.
You can zoom in and out by using the mouse wheel.
You can run your algorithm any time by clicking on the button. In order to use the algorithm from the toolbox, it has to be saved and the modeler dialog closed, to allow the toolbox to refresh its contents.
Undo History panel together with the and buttons are
extremely useful to quickly rollback to a previous situation. The
panel lists everything you have done when creating the workflow.
You can move or resize many elements at the same time by first selecting them, dragging the mouse.
If you want to snap the elements while moving them in the canvas you can choose.
Themenu contains some very useful options to interact with your model elements:
Snap Selected Components to Grid: snap and align the elements into a grid
Add Group Box: add a draggable box to the canvas. This feature is very useful in big models to group elements in the modeler canvas and to keep the workflow clean. For example we might group together all the inputs of the example:
You can change the name and the color of the boxes. Group boxes are very useful when used together with. This allows you to zoom to a specific part of the model.
You might want to change the order of the inputs and how they are listed in the
main model dialog. At the bottom of the
Input panel you will find the
Reorder Model Inputs... button and by clicking on it a new dialog pops up
allowing you to change the order of the inputs:
Use the Save model button to save the current model and the
Open Model button to open a previously saved model.
Models are saved with the
If the model has already been saved from the modeler window,
you will not be prompted for a filename.
Since there is already a file associated with the model, that file
will be used for subsequent saves.
Before saving a model, you have to enter a name and a group for it in the text boxes in the upper part of the window.
Models saved in the
models folder (the default folder when you
are prompted for a filename to save the model) will appear in the
toolbox in the corresponding branch.
When the toolbox is invoked, it searches the
models folder for
files with the
.model3 extension and loads the models they
Since a model is itself an algorithm, it can be added to the toolbox
just like any other algorithm.
Models can also be saved within the project file using the
Save model in project button.
Models saved using this method won’t be written as
on the disk but will be embedded in the project file.
The models folder can be set from the Processing configuration dialog, under the Modeler group.
Models loaded from the
models folder appear not only in the
toolbox, but also in the algorithms tree in the Algorithms
tab of the modeler window.
That means that you can incorporate a model as a part of a bigger model,
just like other algorithms.
Models will show up in the Browser panel and can be run from there.
You can edit the model you are currently creating, redefining the workflow and the relationships between the algorithms and inputs that define the model.
If you right-click on an algorithm in the canvas, you will see a context menu like the one shown next:
Selecting the Remove option will cause the selected algorithm to be removed. An algorithm can be removed only if there are no other algorithms depending on it. That is, if no output from the algorithm is used in a different one as input. If you try to remove an algorithm that has others depending on it, a warning message like the one you can see below will be shown:
Selecting the Edit… option will show the parameter dialog of the algorithm, so you can change the inputs and parameter values. Not all input elements available in the model will appear as available inputs. Layers or values generated at a more advanced step in the workflow defined by the model will not be available if they cause circular dependencies.
Select the new values and click on the OK button as usual. The connections between the model elements will change in the modeler canvas accordingly.
The Add comment… allows you to add a comment to the algorithm to better describe the behavior.
A model can be run partially by deactivating some of its algorithms. To do it, select the Deactivate option in the context menu that appears when right-clicking on an algorithm element. The selected algorithm, and all the ones in the model that depend on it will be displayed in grey and will not be executed as part of the model.
When right-clicking on an algorithm that is not active, you will see a Activate menu option that you can use to reactivate it.
On the right-hand side, you will see a simple HTML page, created using the description of the input parameters and outputs of the algorithm, along with some additional items like a general description of the model or its author. The first time you open the help editor, all these descriptions are empty, but you can edit them using the elements on the left-hand side of the dialog. Select an element on the upper part and then write its description in the text box below.
Model help is saved as part of the model itself.
As we will see in a later chapter, Processing algorithms can be called from the QGIS Python console, and new Processing algorithms can be created using Python. A quick way to create such a Python script is to create a model and then export it as a Python file.
You might notice that some algorithms that can be executed from the toolbox do not appear in the list of available algorithms when you are designing a model. To be included in a model, an algorithm must have the correct semantic. If an algorithm does not have such a well-defined semantic (for instance, if the number of output layers cannot be known in advance), then it is not possible to use it within a model, and it will not appear in the list of algorithms that you can find in the modeler dialog.